Podcasts about New Relic

Today we are talking about Drush, Core Contributions, and Drupal's Past with guest Moshe Weitzman. We'll also cover Cache Metrics as our module of the week. For show notes visit: https://www.talkingDrupal.com/556 Topics Moshe Updates and Clients Maintaining Drush Long Term Locale Performance Overhaul CLI in Core Initiative Which Commands Make the Cut Roadmap Contrib Commands Moving Commands Technical Hurdles How to Help From AI Initiative DDEV Add-ons for Local CI MySQL Toolkit Database Images Testing With Real Databases Devel Module Status Organic Groups Origins Where Ideas Come From Finding Drupal Early Days Release Cadence And Backward Compatibility Avoiding Maintainer Burnout Maintaining With AI And Xdebug Resources Drush's Final Act Drupal cli issue DDEV addons https://github.com/ddev/ddev-drupal-contrib https://github.com/weitzman/ddev-mtk https://www.drupal.org/project/dtt Guests Moshe Weitzman - weitzman.github.io moshe-weitzman Hosts Nic Laflin - nLighteneddevelopment.com nicxvan John Picozzi - epam.com johnpicozzi Scott Falconer - managing-ai.com scott-falconer MOTW Correspondent Martin Anderson-Clutz - mandclu.com mandclu Brief description: Have you ever wanted insights into how cache is working on your Drupal site? There's a module for that. Module name/project name: Cache Metrics Brief history How old: created in Oct 2019 by Moshe Weitzman (moshe weitzman), today's guest, a consistent core contributor, a member of the security team, and one of the rare few with a two-digit user id on drupal.org Versions available: 2.0.3, 2.1.0, and 2.2.0, the last of which works with Drupal 8.7.7, 9, 10, and 11 Maintainership Actively maintained Security and test coverage Documentation - in depth README Number of open issues: 2 open issues, 1 of which is a bug, but is marked fixed Usage stats: 37 sites Module features and usage With this module enabled, your Drupal site will log all cache tag invalidations Additionally, cache tag invalidations will be sent to New Relic as custom events, where you can use the rich reporting tools available to mine for further insights. Many Drupal hosting options include New Relic out-of-the-box, and there's a free tier you can use if you're self-hosting, so this a reporting tool lots of Drupal sites can use Cache hits and misses are also sent to New Relic, so you can investigate things like cache misses as a percentage by cache bin Finally, the aforementioned README also includes information about how to use a different analytics provider, in case New Relic doesn't meet your specific needs Drupal sites probably don't need this kind of visibility on a regular basis, but if you're troubleshooting any kind of cache-related issue, this could be really useful

Observability emerged from the need to understand complex software systems, and involves tracking metrics, logs, and traces so engineers can detect and diagnose problems before they affect users. However, modern applications often encompass hundreds of services, containers, and dependencies, generating more observability data than dashboards and alerts alone can effectively surface. New Relic is a The post New Relic and Agentic DevOps with Nic Benders appeared first on Software Engineering Daily.

Observability emerged from the need to understand complex software systems, and involves tracking metrics, logs, and traces so engineers can detect and diagnose problems before they affect users. However, modern applications often encompass hundreds of services, containers, and dependencies, generating more observability data than dashboards and alerts alone can effectively surface. New Relic is a The post New Relic and Agentic DevOps with Nic Benders appeared first on Software Engineering Daily.

Jeff Collins, CEO of WanAware The last time the channel faced a shift this fundamental was the rise of the hypervisor. That transition reshaped everything, but it happened inside the four walls of the data center. What’s different about the current moment, argues WanAware CEO Jeff Collins, is that AI workloads, inference nodes, IoT, and SCADA infrastructure are being bolted onto customer environments without the kind of formal network redesign that virtualization demanded. The result is a growing visibility gap that most MSPs don’t realize they have. Collins points to a striking finding from a WanAware survey conducted in late 2025: when business leaders were asked about their visibility gap, they rated it extremely high. When IT was asked the same question, they rated it low. Both were technically right. IT was measuring visibility against the machines in their purview – Active Directory, database servers, web front ends. The business was measuring it against everything else: Kubernetes workloads, cloud functions, agentic AI processes, and infrastructure that might not exist tomorrow. That disconnect is why MSPs can show perfect MTTR and SLA performance while the customer is saying you’re failing. The conversation covers where traditional monitoring breaks down, why 30% false positive rates persist even after major platform investments, and how ephemeral workloads designed to disappear create alerts that will never resolve. Collins makes a compelling case that MSPs need to push visibility up the OSI stack, from layers one through three into the application and business logic layers where margin is significantly higher. He shares a practical framework for how to start, using vertical industry knowledge – particularly in sectors like Canadian oil and gas, where SCADA networks and AWS IoT Core infrastructure represent opportunities to grow a $1,000-a-month customer into a $30,000-a-month engagement. Read Full Transcript Robert Dutt: Hello and welcome to the ChannelBuzz.ca podcast, bringing news and information to the Canadian IT channel for the last 16 years. I’m Robert Dutt, editor of ChannelBuzz.ca and still your host for the show. Today we’re talking about a problem a lot of MSPs and channel partners are starting to feel, even if they don’t always have a name for it yet, and that’s visibility. As AI workloads, hybrid architectures and distributed endpoints become the norm, network traffic is changing faster than the tools that many partners rely on to understand what’s actually happening inside their customers’ environments. My guest today is Jeff Collins, CEO of WanAware. Jeff spends a lot of time with service providers and enterprise teams dealing with this shift, where accountability for performance, security and uptime is increasing, even as environments become harder to see and harder to diagnose when something goes wrong. WanAware operates in the network and infrastructure visibility space, but this conversation isn’t about the tools, the dashboards. It’s about how blind spots form in modern networks, why they’re easy to miss until there’s an outage, a security issue, or an SLA failure, and what partners need to understand as AI-driven infrastructure quietly reshapes traffic patterns and dependencies. In this discussion, we’re going to explore where traditional monitoring starts to fall apart, how partners can rethink what good visibility really means today, and why the ability to see what’s happening across distributed environments is quickly becoming both a risk issue and a business opportunity for MSPs. If you’re responsible for customer outcomes, but you don’t always feel confident you can see everything that matters, this conversation is for you. [MUSIC] Robert Dutt: Jeff, thanks for taking the time. I appreciate it. Jeff Collins: Thanks, Rob. Thanks for having me on. Robert Dutt: You’ve been advising partners, MSPs, VARs, these types of folks through a lot of change over time. Why does this moment with the rise of AI workloads and the continuing trend of hybrid networks feel like a real inflection point rather than sort of just the next evolution of the way things look? Jeff Collins: I think one of the biggest reasons why is because it’s so transformational to what MSPs and resellers and VARs and distributors have dealt with for, let’s say, the last 25 years. If we think about the last major inflection point that they dealt with was really kind of the realm of the hypervisor, this ecosystem where no longer did we have to have a server running an operating system, and that created kind of the whole ecosystem we deal with today. It created cloud, it created containers, all those things were built off this concept of a hypervisor. That was really the last major transformational thing that has happened. Now we fast forward to today and we’ve got this era of AI. We’ve got this era where we’re now taking agentic approaches, generative approaches, to things that our customers deal with every day. When I talk about our customers, those are the customers of the MSP, those are the customers of the reseller, the distributor. Not only are they dealing with that, they’re dealing with this massive evolution in the customer base, but they’re also having to do that same evolution in their own environments. If you’re an MSP and you’re focused on infrastructure, or you’re an MSP and you look more like an MSSP where you’re focused on security, now you’re starting to have to deal with, “Okay, I’ve got these tools, I’ve got these people, I’ve got these agents, I’ve got all these entities inside of my business that are doing something for my customer.” But now I have to think about how am I going to do that faster? How am I going to do that better? How am I going to do that more effectively? Because our customers are getting much more advanced. That’s really one of the biggest things that I see that we’re seeing a lot of, that “Where do I start?” from the channel partner community. When we think about the channel, we know all this stuff is going on, but it seems like such a Herculean lift that I think sometimes it’s hard to know where we make that first step. Robert Dutt: That makes sense. A lot of this, a lot of AI especially, and to a degree sort of the hybridization of the network, that complexity has come on without kind of a formal network redesign. Like you mentioned the transition to hypervisors and that necessitated rethinking how things were done because it was a physical change. Whereas a lot of, especially with AI, it’s kind of being bolted in, added on as you go. Why does that make the environment today harder to understand than maybe it was for past transitions when you’re sitting there watching it as an MSP or other partner? Jeff Collins: Well, I think one of the biggest reasons why this era is so much more difficult than the last transition is because we’re not bound by the four walls of our proverbial house. If we think about when we dealt with the last transition, every customer, their physical server sat inside of something they control. So we’ll refer to it as their house because that’s the easiest kind of comparison we can do. In today’s world, there’s certainly a lot that exists in our customers’ houses and in the houses that the MSP or the reseller or the channel partner or whomever it is are engaged in. But so much of that’s going outside of those walls. And when we think about AI, AI is certainly outside of those walls. I mean, we might be dealing with Anthropic, we might be dealing with ChatGPT or Gemini or the thousand other agentic or generative approaches that are out there. Those are all over the place. And now we’re asking these entities to take oftentimes a process-driven approach that they’ve had for 20, 25 years. And how do you change that process-driven approach when you don’t really know where those workloads, where those assets, where that data is going to reside either today or tomorrow, or even if that data that we’re looking at is even going to exist tomorrow. That’s this whole realm. I mean, we’ve been talking about ephemeral workloads for, you know, let’s call it 14 years, 15 years since really the rise of AWS. But now we’re starting to deal with these ephemeral workloads, not just in the realm of infrastructure, but also in data, in generative concepts, in agents. You know, historically, we had Bob Smith, who might have worked in the NOC. Well, tomorrow, Bob Smith is an agent. What does that look like? It’s AI. What did Bob Smith do yesterday? Did Bob Smith, the new agentic version of Bob Smith, did that person do the right thing, the wrong thing, the incorrect thing? How do we manage that? How do we deal with that? How do we process that? Those are all the things that are across the board, just happening at massive rapid scale. And so, you know, it’s a really difficult time right now to be an MSP or a channel partner, but it’s also an amazing time to be an MSP or channel partner. You know, our world, our capabilities are advancing so fast. You think about one of the simplest use cases that’s out there that all of us think is simple, that MSPs deal with every day, is a circuit outage. You know, a telecom circuit goes down and it’s connected to SD-WAN or it’s connected to a router or it’s connected to some type of device that’s out at the prem. And historically, every MSP on the planet’s dealt with it kind of in a similar way. We get an alert from a monitoring system that feeds a ticketing system. It pops up on a tier one agent’s dashboard. The tier one agent looks at it, they verify power, they verify if the router’s operational, and then they open a ticket with a carrier. And then they, and that’s the hurry up and wait type of world. Well, now in the era of AI, that changes that quite a bit, because every one of those things are very process driven. We don’t need people for that anymore. So now we can have a system take that process flow on, do that. Now, historically, we could use a system to do that. We could write automation and a lot of MSPs did that historically, but the problem with automation is automation is static. When we leverage AI, we can leverage enrichment that helps influence that agentic approach. And so now if there’s a nuance going on, let’s say an example is there’s a global power outage. So let’s say there’s a power outage in the entire Vancouver area. We know that. Well, historically, if we’re looking at that, we see all these customers that are down, we might through a tier one agent approach, a person-based approach that following a process, or even an automated approach, not really correlate that. Because if the MSP is in, let’s say, Montreal, they might not realize there’s a large scale power outage in Vancouver, which is thousands of kilometers away. And so when we think about that, that’s really where these things can change a lot from an agentic perspective. And then the MSP gets the joy of being able to repurpose that person to be much more valuable to their organization, that tier one person can become tier two, and that can really start changing that dynamic a lot. Robert Dutt: Most MSPs would have historically said we have good visibility across what our customers are doing. And probably I would say most believe they have good visibility today. Where does that confidence most often turn out to be misplaced or to start to break down as the model shifts? Jeff Collins: Yeah, so I would 100% agree that most MSPs, when workloads are static, have great visibility. The problem is that in today’s world, so many workloads are becoming dynamic. And we see that change happening consistently. You know, customers, you know, historically MSPs had problems monitoring services inside of a cloud provider. You have ephemeral workloads, you have workloads that aren’t necessarily a server, they’re much more like a service. So you have things that might be a Kubernetes instance, they might be a Kubernetes runtime instance, they might be a function. Those are all things that are crucial to the operation of a customer. They’ve taken those workloads that historically operated on a machine. And they’ve taken those workloads and now they’re in some type of small form factor instance that exists for a very short period of time. That’s been very difficult for MSPs to deal with across the board. But now we take that same concept and that same concept goes outside of the cloud providers. We now have that moving into inference nodes. We now have that moving into IoT and IIoT and OT, where we’re starting to deal with these ecosystems where these workloads are very ephemeral by nature. They might exist for a short period or components of those might exist for a short period, or the way that those are correlated and analyzed might exist. But if you think about inside of a customer from a business risk perspective, those actually carry the highest business risk. An individual Windows 2012 server has some level of business risk. If it’s running SAP, probably a higher level of business risk. But if it’s one Active Directory node and the customer has 100 machines in Active Directory, it doesn’t really matter in the scheme of the world. And so those are the realities of what happens as we kind of think through this stuff. And so for MSPs, this really drives that visibility gap. You know, we did a survey earlier this year, or actually late last year, sorry, in 2025. We did a survey across the board asking business leaders really what the visibility gap was and what they believed. And we asked business leaders and we also asked IT. It was really interesting to see kind of the dichotomy. When you ask the business what the visibility gap was, it was extremely high. When you ask technology what the visibility gap is, it was really low. Now they were both technically right. And here’s why. So IT was thinking about the visibility gap of the machines that they understand, the machines in their purview. So those might be, you know, an Active Directory server, a database server, maybe you have a web front end. Those are all there. And those are 100% being monitored to that IT team or to that MSP. The problem is, is the business itself is operating on a whole bunch of additional workloads that IT doesn’t necessarily have purview to. And so because of that, we start ending up with this difference of visibility. And that’s why oftentimes when you’ll go and you’ll talk to a customer or you’ll go and you’ll talk to the business itself. And the business is saying, why do we have this MSP who works for us? This MSP isn’t doing anything. And the MSP is coming back with these great reports that are showing MTTR is consistently dropping. You know, initial response time, triage time is consistently dropping. We’re blowing out every single metric that we provided you in an SLA or an SLO. And the business is coming back and saying, but you’re failing. And the MSP is saying, I don’t understand. We are not. And here’s all the metrics. And it’s because of this difference in resources that exist, that is what is happening. And so I think that’s one of the big areas that we always have to think through is, you know, as we’re looking at things and as MSPs look at things, they have to continue to be pushing upward inside of the business to understand all those areas that the business is driving that IT, who they’ve historically sold to, may not know about those resources, especially in a lot of these other spaces, AI, IoT, IIoT, OT, ephemeral workloads, cloud workloads, those types of things that are often outside of that scope. Robert Dutt: Yeah. I guess when you’re looking at sort of your visibility stopping basically at the edge of the organization, you’ve got all of this out there, pretty significant impacts on real world issues like latency, like security exposure, like the ability to meet those SLAs that you signed up for, those kinds of things. Jeff Collins: Yeah. Yeah. 100% agreed. And, you know, when you think about the core components that an MSP does, you know, MSPs generally deal with availability and they deal with performance. When you add in the MSSP, now we add in the security component. And some MSPs and MSSPs are more hybrid-based approaches. They may deal with all three. But as you kind of look at those, those core tenant areas have become much more difficult, especially in the last 10 years, certainly in the last year. I mean, the last year has been so disruptive for all that we do. And it’s because those pieces have become much less simple. You know, if I go back 25 years or even 20 years, customers by and large used MPLS networks, rather simple to monitor. You have guaranteed jitter, you have guaranteed latency, you have, you know, all these things that are very easily assumed by an MSP. So if latency exceeds 74 milliseconds between these two individual locations, that breaks the SLA that the provider provides and it’s an easy conversation. You need to go fix this. This is not okay. Well, in today’s world, most of our customers don’t have MPLS networks. Most of them have, you know, sometimes now it’s satellite. They might have Starlink for LEO. They might have 4G or 5G, depending on what portion of the world they’re in. They might have some type of broadband service, fiber broadband, or copper broadband, or some other type of realm. Well, those don’t necessarily have SLAs for that in any way, shape, or form. We may luck out and they have an availability SLA. Maybe it’s three nines or two nines, or maybe not even two nines, depending on what type of service that is. And then when we start moving inside of the network, outside of the service provider, outside of the circuit provider itself, we start moving into other arenas that look like this. You know, historically we had a Dell server, an HP server that had a mean time before failure. Well, that’s pretty easy to understand. If I have a server and it’s going to run for 25,000 hours, it’s easy to understand that life. But when now we’re starting to get services that have an expected failure, and that expected failure is generally measured in less than a year, because the assumption is that the software, the application, resolves that issue. If you’re an MSP and you’re not monitoring the application and you don’t understand the application, you’re now chasing outages that don’t matter. And that’s one of the other things that’s really hard. And we see this all the time. You know, I’ll talk to MSPs and they’re like, “Jeff,” and it goes back to that same conversation we had before of not knowing the business. “Jeff, we get, today we have 30% of our tickets that become false positives. What do we do about that? We’ve gone out and we’ve bought the newest monitoring platform. We’ve implemented AI. We’ve implemented all this automation. We spent $20 million doing that.” These are all real things that I have in conversations with MSPs. And at the end of the day, they still have 30% false positives that they’re working. And the reality is, is because it’s certainly an outage. There was 100% an outage that happened. But the reality is that outage was never going to get restored because the outage was designed. You know, that workload disappeared. A DevOps team or a DevSecOps team deployed a new environment and that workload is now gone. And there’s a brand new workload that you’re not monitoring right now. You know nothing about it. And those are the things that we all collectively have to continually evolve to. It’s that driving up the stack. You know, one of the things that I often see is, you know, we have this proverbial thing that we’ve all dealt with, the OSI model. You know, there’s seven layers to that OSI model. So often in MSPs, we focus on four of them. The problem is, and most MSPs only focus on the first three. They don’t even focus on the fourth one. The issue is, is there’s three more. And those three more are what get driven by the business. And so the more that we can focus on visibility within those three, understanding that, bringing that into our tools, that drives additional value. It also drives significantly larger margin. You know, if we think about margin contribution at monitoring a telecom circuit, that’s a pretty low margin at this point in time. There’s a lot of automation around that. Monitoring a server – that world used to be high-margin, but it’s compressing. Customers are increasingly doing more of this themselves. They’re doing automation directly into their CI/CD pipeline. So it becomes this knife fight. And there’s more and more MSPs that are out there that are also fighting for that same share of market. And so the key is, the more that MSPs can go up market, they can understand, you know, I hate to use this term digital transformation because it literally gets overused every day by every marketing team on the planet. But the reality is, is that if we go behind this marketing abomination of this term, and we actually look at what happens, there’s a ton of value that we can go after. And if we go after that value, and we go after what people are trying to do, we align with that, we can now take those same products, those same processes that we’ve historically had as MSPs, and we can really start evolving that. Moving upward, driving in significant value, taking our tool sets that we may have today, maybe those can evolve with us, maybe we have to make new changes in our tool sets. But the reality is we’re driving that margin upward. So we’re going from maybe our contribution margin to our business today is 30%, let’s say, we can start moving back up into 60, 70, 80% contribution margin from a managed services perspective, which is where we all want to be. We don’t want to be fighting knife fights for 30%. It’s just hard, it’s difficult. Our customer acquisition costs are still generally high. We have salespeople, we have marketing efforts, we have all those things that we’re burning through every day. And we need more and more market share, we need more and more assets that we’re monitoring. And as a result of that, we need better ways that can contribute higher margin and create stickier customers that we’re not in those knife fights with. Robert Dutt: The situation seems to be putting MSPs in a situation where they’re increasingly accountable for outcomes that they can’t fully see the contributing factors of. Before you move on, I just wanted to double click on that just a little bit and just ask, how does that change kind of the risk profile for an MSP when you’re accountable for those things that you don’t completely understand or have complete control over? Jeff Collins: Yeah, I would say a lot of that. And one of the things that MSPs have to think through is a lot of that starts at the sales cycle. If you don’t ask the right questions at the sales cycle stage, oftentimes you get pushed into that ecosystem. When you’re looking at the core functional plumbing behind what a customer is trying to do, and that’s the only thing you’re looking at, you often get siloed into that ecosystem. You’re looking at a server, you’re not looking at SAP. One server going down in SAP doesn’t necessarily mean SAP has a problem. But if that one server is the only HANA server in SAP, that’s catastrophic. You know, it’s this realm of contextual knowledge. Historically MSPs have that contextual knowledge, but it’s all the way at tier three and tier four. That contextual knowledge has to move to tier one. If MSPs want to get to the arena where that is no longer a problem, the contextual pieces have to move downward. You have to go from a hero-based MSP to a process-driven MSP. So many MSPs are built on heroes. It’s really hard to build a scalable business off heroes. You have to have heroes. Heroes are the people that when everything breaks and the world is on fire, they’re the ones who carry you through. And those heroes we want to have, we want to empower them, but they can’t be doing the stuff that should be done at tier one. So if we take that exact same question that you had, Rob, that question is, you know, how do we make, at the end of the day, how do we make MSPs more relevant to their clients and much more aligned with what the client’s trying to do? And that’s by taking the contextual knowledge of what the customer is trying to do, aligning that with the tactical approaches that the MSP is trying to do, and having a very crystal clear playbook of how this tactical component makes up this strategic initiative inside of the business. So we’ll take that, we’ll take that simple example. I shouldn’t say simple. SAP is far from simple. But the reality is, is that SAP is something that customers rely on. And when they rely on that, if SAP goes down the business goes down. And if you have an MSP that’s monitoring that, and at the same second of the same day, the MSP gets 36 tickets. We’ll just pick a random 36 number. 36 severity one tickets come in at that point in time. One of those severity one tickets is for SAP HANA. And the customer only has one instance of that. And that is taking down a large company. So that’s the first ticket. The next 35 tickets are for ephemeral workloads that the customer migrated off of, you got the alert, they migrated to a brand new ephemeral workload. And the 35 don’t matter. They’re false positives. But the one fully matters. In every single MSP on the planet, those 36 tickets are eligible for the same response interval. That’s a pretty tough average to be able to. Are you going to luck out and get the one? Or are you going to luck out, or not luck out, for lack of a better term, and work 35 false positives before you get to the one that matters? Now, most MSPs are going to tell me and they’re going to tell us that, well, we have more than one tier one path. That’s great. But the reality is you need to be responding to that one ticket right now. And you need to understand that that one ticket matters. And the only way you can do that is by starting at the beginning, starting with the sales cycle, understanding what customers are doing. If you’ve already gone down the path and the customer’s embedded, use your customer support teams. Understand what your customers are doing, start layering in that context, start enriching that data, knowing what that actually feeds, and understanding the dependencies and interdependencies inside of that. So if that server goes down, certainly you could by virtue say a database server going down is a SEV-1, but it may not be. If they have four database servers, they’re running in a high availability group, who cares? If one goes down, not the end of the world, go fix it tomorrow. That’s where context, that’s where understanding those dependencies is so crucial. And I mentioned at the beginning of this is how do you take that first step forward? We always take this first step forward and how I instruct MSPs is start doing things like this, take this step forward, break this down into simple programmatic approaches. And when we think about AI, it’s the exact same idea. We move steps forward, we have agentic, we have generative. Pick one, pick an area you want to focus on with your customers, understand the business outcome they’re trying to do. And if you have an inference engine, that’s going to be really crucially important here. So let’s understand that. Let’s monitor that. Let’s understand the intricacies related to how that customer is leveraging it, why it’s important. Are there latency constraints? Are there packet loss constraints? Those types of things. Let’s monitor to that and let’s understand how that happens. And if a customer has an application on the back end, you know, maybe they have New Relic or they have AppDynamics or they have some type of APM toolset, great. Let’s start bringing those into our monitoring. Let’s start bringing that intelligence in, understanding application flows, understanding dependencies, building that to be part of our story. And now we create so much more opportunity for us as an MSP driving that contribution margin northbound. Robert Dutt: So it sounds like we’re kind of defining good visibility in a modern environment and kind of setting up for looking forward as understanding what actually matters to the customer and understanding what kind of flows into it, what all results in that thing that’s important to the customer still being up, still being running, still being functional, and kind of work backwards from there as opposed to the more “this machine is working, this machine is not” kind of approach. Jeff Collins: Yep. Yeah. You want to go from tactical to transformational. That’s really the idea. Robert Dutt: And you shared kind of the idea of the first step to do towards that. I guess as you’re moving towards that first step, you know, is there any one question or kind of mindset that you find works for MSPs to have in mind or asking customers to surface those blind spots and really start to understand what that context is that they have to have? Jeff Collins: Yeah, that’s a really good question, Rob. And, you know, there’s some things that I do tell MSPs to start with before you ever ask that first question. One of them is kind of some of the simple, let’s call it research that you can do before you ever reach out to your customer. One of the easiest things you can do is start by what industry are they in. You know, in Canada, Canada has a lot of oil and gas, lots and lots of oil and gas companies exist in Canada. And so if you have an oil and gas company, we can start right off the bat with a lot of the things that oil and gas companies live and die with. And we’ll just pick on this one as an example. So oil and gas companies have SCADA networks. They have industrial IoT devices that are out there. They’re processing massive amounts of data. That data may be going into the cloud. It may be going into a data center. It may be going into some type of vault or something like that, depending on what they have. But each one of those are things that, as an MSP, you can start out before you ever ask your customer anything. You know that those are the things that exist in their environment. And you can quickly look and see, well, am I monitoring any of those? Well, no, I’m only monitoring Active Directory. Okay, Active Directory is probably important to the oil and gas company. But if it goes down, do they quit producing oil? The answer is probably no. And so if your answer is ever no, you know right off the bat that you’re not monitoring something that’s strategic to your customer. And so the first thing that you should always think about is, okay, if we have this industry, we should be monitoring the things that are strategic. Well, how do we do that? Well, we start with that one step forward. The first thing we talk to them about is just like when we went out and we sold that initial monitoring of Active Directory, they did it because they didn’t have time for it. There’s no oil and gas company on the planet that has time to be monitoring their SCADA networks. They just don’t. They may tell you that they do, but they don’t. So leverage your relationships, leverage your engagement with them and go after those pieces. Understand, you know, if they’re in AWS IoT Core, understand what that looks like. Understand who’s monitoring that. Understand how DevOps is working within that space. Maybe it’s DevSecOps inside of that environment. Understand that convergence of the teams and then start building a story around, you know, let’s take that on for you. Let’s start changing that. Let’s use the same paradigm that we’ve done, driving MTTR down, driving availability up, driving resolution times down, all those types of things. Let’s bring that into the era of SCADA networks, IoT, our core infrastructure. That’s where we start changing the value inside of our customer engagements. And that’s really where I see a huge opportunity for MSPs across Canada, where you can take that environment, you can take those opportunities you already have, and you can grow them from, you know, maybe you bill that customer $1,000 a month. You can grow it to billing them $20,000 or $30,000 a month, but it’s the most crucial $30,000 they spend. Because, you know, if that offshore environment or that, you know, oil sands environment or whatever it might be within the oil and gas space or in the energy sector, whatever it might be, those things are crucial to their business. And so the more that MSPs can kind of make that step forward, and then also start incorporating AI, every single one of those entities is incorporating AI. They’re incorporating it directly into their pipelines. They’re incorporating it directly into their data pipelines, not just the oil and gas pipelines, but each one of those, the more you can incorporate that, the more you can monitor, the more you can show value of everything that you do amazing as an MSP, that’s really where you start creating that intrinsic strategic value and you get out of that tactical approach. Robert Dutt: And the good news is for a lot of these folks in the MSP space, presumably they have some of these pieces already in place, just not necessarily connected up to the technical side, i.e. sales and marketing have been focused on a vertical. And even if they haven’t, because they have customers in this space, they’ve built some of that muscle memory, some of that knowledge of what really matters. Now it’s just a matter, hopefully, of connecting it into the services that they’re offering. Jeff Collins: Yep, totally agreed. Robert Dutt: All right. Well, it’s been a really interesting look at sort of where visibility is at. And I think a real interesting opportunity that you’ve surfaced in terms of how it can be turned into a value conversation. I appreciate your taking the time. Jeff Collins: Sounds great. Thanks so much for having me on, Rob. Robert Dutt: There you have it, my chat with Jeff Collins from WanAware. I’d like to thank Jeff for sharing his insights. The thing that stuck with me from this conversation is how much of what’s changed in the modern network hasn’t been designed in, it’s been bolted on. AI workloads, hybrid architectures, IoT, SCADA, all of it layered into environments without the kind of formal rethinking that happened when we moved to virtualization. And Jeff made a really compelling case that for MSPs, closing that visibility gap isn’t just a risk management play, it’s a revenue opportunity, and potentially a significant one, especially in verticals like energy and critical infrastructure where visibility is tied directly to uptime, safety, and compliance. We’ll be back on Monday with In Case You Missed It, your weekly news roundup. Thanks for listening. I’m Robert Dutt for ChannelBuzz.ca, and I’ll see you in the channel.

Observability is no longer just about dashboards. It is about systems that can act. I caught up with Brian Emerson, Chief Product Officer at New Relic, at Advance 2026, and one thing was clear. Brian shared a bold view of where software is headed. More applications will be built in the next five years than in the last fifty. That creates a scale problem no team can solve manually. His answer is intelligence and automation, led by what New Relic calls the S agent. What stood out to me is how this shifts incident response. Instead of pulling people into late night war rooms, the idea is a digital war room where agents constantly watch behavior, surface issues, and even help resolve them. For customers, the starting point is simple. Turn it on and let it begin optimizing alerts and recommendations.We also talked about trust, which is the real conversation right now. Application health is no longer just uptime. It is behavior, outcomes, and user experience. AI systems can fail quietly, with wrong answers or poor decisions. That is why New Relic is pushing toward agentic monitoring, so teams can see not just the infrastructure but the actual experience their users are getting.One insight Brian shared surprised me. New Relic chose to lean into fast-improving general models instead of building niche ones, because the pace of change makes specialization short lived. That says a lot about how quickly this space is moving.His message for leaders was simple. The shift is from recommendations to action. The real opportunity now is letting agents handle the last mile of operations and moving closer to self-healing systems.#Data #AI #NewRelic #Observability #AI #SRE #AgenticAI #TheRavitShow

At New Relic Advance 2026 in San Francisco, one theme was impossible to miss. Observability is no longer just about seeing problems. It's about fixing them. I caught up with Ashan Willy, CEO of New Relic, to talk about what this shift really means for customers.The biggest highlight was the launch of their SRE Agent and the broader move toward an agentic platform. What stood out in our conversation was not just the technology, but the reason behind it.Customers are overwhelmed by signals, alerts, and dashboards. They don't need more data. They need faster action.That is exactly what New Relic is aiming to solve. Closing the gap between insight and execution so engineers spend less time diagnosing and more time delivering.Compared to last year, this feels like a real strategic inflection point. The conversation is no longer about adding AI features. It is about redesigning workflows around AI-native operations.The big question now is not whether agents will assist engineers. It is how much responsibility they will take on as trust grows. If this launch works, by next year we should see fewer alerts, faster resolutions, and teams spending more time building instead of firefighting.#Data #AI #NewRelic #Observability #AI #SRE #AgenticAI #TheRavitShow

Recent analysis from Goldman Sachs indicates that $700 billion in AI investment during 2025 resulted in no measurable U.S. GDP growth, with most AI equipment imports negating domestic benefits and 80% of surveyed firms reporting no productivity or employment improvements. This pattern suggests that AI-related spending has primarily shifted margins from enterprise IT budgets to a small number of infrastructure vendors rather than delivering distributed value. Internal concerns are rising, with 90% of IT leaders questioning AI's return on investment, and 80% citing fragmented data as a primary challenge to measuring outcomes. Further context reveals that agentic AI initiatives face operational headwinds: Gartner expects 40% of such projects to be cancelled by 2027, and S&P Global found nearly half are abandoned before production, most often due to inadequate planning and data foundations. Margin erosion is widespread, attributed to AI implementation costs, and attempts to scale AI agents into production remain limited by inference costs and insufficient infrastructure. Despite increased adoption efforts, sustainable value delivery from AI platforms remains elusive for most organizations. Enterprise AI access is becoming increasingly concentrated. OpenAI's partnership with consulting firms such as BCG, McKinsey, Accenture, and Capgemini consolidates control of the enterprise distribution layer, narrowing competitive opportunities for smaller providers. Meanwhile, Amazon's 13-hour AWS outage, linked to the misconfiguration of an internal AI tool, underscores the liability ambiguity in agentic systems—where vendors may attribute autonomous actions to user error, complicating risk assignment. Additional updates from vendors such as Anthropic, Cloudflare, and New Relic address incremental technical capabilities, with a distinct focus on cost, operational governance, and policy enforcement. The prevailing themes for MSPs and IT leaders are increased scrutiny of AI value, heightened exposure to cost and accountability risk, and the emergence of managed service opportunities around data governance, cost instrumentation, and liability management. With enterprise market channels consolidating and risk shifting toward service providers, integrating robust contractual definitions for autonomy, incident attribution, and financial boundaries is essential to limit harm and clarify responsibility before incidents occur. Four things to know today 00:00 Goldman: $700B AI Spend Delivered Near-Zero U.S. GDP Growth in 2025 03:49 OpenAI Enlists BCG, McKinsey, Accenture to Distribute Enterprise AI Agents 06:44 Report: Amazon's Own Engineers Prefer Claude Over Its Mandated Internal Tools 08:56 AI Inference Costs Are Falling — But Governance Gaps Are Growing This is the Business of Tech.    Supported by: CometBackup  Small Biz Thoughts Community   

As AI systems move rapidly from experimentation into production, organizations are discovering that adoption alone is not the hard part, understanding, governing, and trusting AI in live environments is. In this episode of the Tech Transformed, Shubhangi Dua speaks with Camden Swita, Head of AI, New Relic, about why AI observability has become a critical requirement for modern enterprises, particularly as agentic AI and AI-driven operations take on increasingly autonomous roles.The discussion explores how traditional observability models fall short when applied to probabilistic systems, why many AI ops initiatives stall at proof-of-concept, and what security and IT leaders must prioritize to safely scale AI in production.Be the first to see how intelligent observability takes you beyond dashboards to agentic AI with business impact at New Relic Advance, February 24, 2026.Why AI Adoption Is Outpacing Operational ReadinessWhile AI adoption is accelerating rapidly, most organizations still lack visibility into what their AI systems are actually doing once deployed. Generative AI is already widely used for natural language querying, coding assistants, customer support bots, and increasingly within IT operations and SRE workflows. As these systems move into production, new challenges emerge around cost control, governance, performance quality, and trust. Leaders recognize AI's potential value, but without deep observability, they struggle to determine whether AI-enabled systems are delivering consistent outcomes or introducing hidden operational and security risks.How Observability Must Evolve for Agentic AI and AI OpsThe episode then examines how observability itself must evolve to support agentic and autonomous AI systems. While core observability principles still apply, AI introduces a new layer of complexity that requires visibility into model behavior, agent decision-making, and multi-step workflows. Modern AI observability extends traditional application performance monitoring by capturing telemetry from LLM interactions, agent orchestration layers, and automated evaluations of output quality against intended use cases. Without this visibility, teams are effectively operating blind, unable to diagnose failures, validate compliance, or confidently deploy AI at scale. At the same time, AI is increasingly being embedded into observability platforms to reduce noise, accelerate root cause analysis, and improve incident response.Making Agentic AI Work in PracticeSuccessful adoption starts with low-risk, high-friction tasks such as incident triage, dashboard interpretation, and runbook summarization, rather than fully autonomous remediation. These use cases deliver immediate productivity gains while preserving human oversight. Over time, stronger feedback loops, better context management, and human-in-the-loop learning allow agents to become more reliable and useful. Looking ahead, Camden predicts that 2026 will be a turning point for agentic AI in production, driven by maturing AI observability platforms, richer semantic data, and knowledge graphs that connect technical telemetry to real business outcomes.Listen to Are “Vibe-Coded” Systems the Next Big Risk to Enterprise Stability?When Vibe Code Breaks OpsAI-generated code is pushing prototypes into production faster than ops can cope. How observability becomes the...

This week we're joined by Dana Lawson, CTO at Netlify. We talk about her journey from the US Army to leading engineering teams at companies like GitHub, New Relic, and now Netlify. We discuss Netlify's evolution from JAMstack to AI-powered developer tools, including Agent Runners and their MCP server. We also explore the concept of "Agent Experience" (AX) as a new paradigm alongside UX and DX, and how hiring practices are evolving in the age of AI.Netlify: https://www.netlify.com/Agent Experience Hub: https://www.netlify.com/agent-experience/agentexperience.ax: https://agentexperience.ax/Agent Runners: https://www.netlify.com/platform/agent-runners/Netlify MCP Server: https://docs.netlify.com/build/build-with-ai/netlify-mcp-server/Dana on LinkedIn: https://www.linkedin.com/in/dglawson/Dana's LeadDev Profile: https://leaddev.com/community/dana-lawsonDana's UXDX Profile: https://uxdx.com/profile/dana-lawson/

Developers are not just writing code anymore. They are starting to run a virtual team. At AWS re:Invent, I had a conversation with Jemiah Sius, VP, Market Strategy and Developer Relations, from New Relic about how AI is changing the day-to-day life of developers. This was one of those chats that makes you pause and rethink how software will be built very soon.Here is what stood out-- Agentic AI is becoming real for developers Teams are excited about agents that behave like a digital team or a virtual SRE, taking care of reliability and performance while developers focus on building features-- Developers are becoming orchestrators Over the next 6 to 8 months, the role of the developer is shifting. Less time writing every line of code, more time directing agents and tools. This shift is already driving a big jump in productivity-- Observability matters more than ever As agents start working across multiple LLM servers and interacting with other agents, visibility becomes critical. Without observability across the full agent layer, things can quickly create more work instead of less-- New Relic and AWS coming together We talked about the New Relic integration with AWS Q, which brings observability data directly into AWS DevOps workflows, and the new security agent that surfaces real production data on vulnerabilitiesIt was great catching up with Jemiah again and hearing how New Relic is thinking about the future of developers and reliability.#Data #AI #AWSRecipes #NewRelic #AgenticAI #Security #MCP #reinvent #NewRelic #TheRavitShow

Fantastic catching up with Camden Swita, Head of AI at New Relic at AWS re:Invent last week to discuss the biggest changes in the world of Agentic AI over the last year! We talked about how New Relic is connecting the dots at AWS re:Invent with major announcements including:- The Security RX agent, an AI agent that automates the process of finding and remediating security vulnerabilities in runtime, saving engineers a huge amount of time- Integrating the Model Context Protocol (MCP) server with AWS DevOps agents to ensure agents can access live context and make informed decisions from production- Camden also shared advice for leaders entering the agent tech space: don't treat observability as a secondary concern, as end-to-end tracing will be "fundamentally essential" for compliance and performanceWatch the video to learn more!#Data #AI #AWSRecipes #NewRelic #AgenticAI #Security #MCP #reinvent #NewRelic #TheRavitShow

Podcast: Tech Transformed PodcastGuest: Manesh Tailor, EMEA Field CTO, New Relic Host: Shubhangi Dua, B2B Tech Journalist, EM360TechAI-driven development has become obsessive recently, with vibe-coding becoming more common and accelerating innovation at an unprecedented rate. This, however, is also leading to a substantial increase in costly outages. Many organisations do not fully grasp the repercussions until their customers are affected.In this episode of the Tech Transformed Podcast, EM360Tech's Podcast Producer and B2B Tech Journalist, Shubhangi Dua, spoke with Manesh Tailor, EMEA Field CTO at New Relic, about why AI-generated code, also called vibe-coding, rapid prototyping, and a focus on speed create dangerous gaps. They also talked about why full-stack observability is now crucial for operational resilience in 2026 and beyond.AI Vibe Code Prioritising Speed over StabilityAI has changed how software is built. Problems are solved faster, prototypes are created in hours, and proofs-of-concept (POC) swiftly reach production. But this speed comes with drawbacks.“These prototypes, these POCs, make it to production very readily,” Tailor explained. “Because they work—and they work very quickly.”In the past, the time needed to design and implement a solution served as a natural filter. However, the barrier has now disappeared.Tailor tells Dua: “The problem occurs, the solution is quick, and these things get out into production super, super fast. Now you've got something that wasn't necessarily designed well.”The outcome is that the new systems work but do not scale. They lack operational resilience and greatly increase the cognitive load on engineering teams.New Relic's research indicates that in EMEA alone:The annual median cost of high-impact IT outages for EMEA businesses is $102 million per yearDowntime costs EMEA businesses an average of $2 million per hourMore than a third (37%) of EMEA businesses experience high-impact outages weekly or more often.Essentially, AI-driven development heightens risks and increases blind spots. “There are unrealised problems that take longer to solve—and they occur more often,” Tailor noted. This is because many AI-generated solutions overlook operability, scaling, or long-term maintenance.Modern architectures were already complex before AI came along. Microservices, SaaS dependencies, and distributed systems scatter visibility across the stack.“We've got more solutions, more technology, more unknowns, all moving faster,” he tells Dua. “That's generated more data, more noise—and more blind spots.”Traditional...

Czy zdarzyło Ci się, że strona „muliła”, a standardowe narzędzia jak PageSpeed Insights czy Query Monitor nie dawały jasnej odpowiedzi? W tym odcinku wchodzimy głębiej - na poziom serwera i interpretera PHP. Dowiesz się, czym są narzędzia APM i dlaczego New Relic to „czarna skrzynka”, którą warto mieć w swoim projekcie. Pokazuję, jak dane z APM zmieniają Twoją pozycję w rozmowie z klientem - z wykonawcy zgadującego przyczynę błędu, stajesz się inżynierem operującym na twardych dowodach.

Ari Zilka, founder of MyDecisive.ai and former Hortonworks CPO, argues that most observability vendors now offer essentially identical, reactive dashboards that highlight problems only after systems are already broken. After speaking with all 23 observability vendors at KubeCon + CloudNativeCon North America 2025, Zilka said these tools fail to meaningfully reduce mean time to resolution (MTTR), a long-standing demand he heard repeatedly from thousands of CIOs during his time at New Relic.Zilka believes observability must shift from reactive monitoring to proactive operations, where systems automatically respond to telemetry in real time. MyDecisive.ai is his attempt to solve this, acting as a “bump in the wire” that intercepts telemetry and uses AI-driven logic to trigger actions like rolling back faulty releases.He also criticized the rising cost and complexity of OpenTelemetry adoption, noting that many companies now require large, specialized teams just to maintain OTel stacks. MyDecisive aims to turn OpenTelemetry into an enterprise-ready service that reduces human intervention and operational overhead.Learn more from The New Stack about OpenTelemetry:Observability Is Stuck in the Past. Your Users Aren't. Setting Up OpenTelemetry on the Frontend Because I Hate MyselfHow to Make OpenTelemetry Better in the BrowserJoin our community of newsletter subscribers to stay on top of the news and at the top of your game.  Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Straight from re:Invent 2025, technology leaders from C3 AI, nCino, New Relic and Vercel reveal learnings, best practices and predictions for the future of Agentic AI.Topics Include:Four technology executives introduce their companies' AI innovations in fintech, cloud, enterprise software, and observability.Vercel built agents for code reviews, infrastructure optimization, and across finance, sales, and support functions.C3.ai deploys enterprise AI applications from scratch to production in six months for Fortune 500s.New Relic provides observability for AI systems and built agents that resolve infrastructure issues in real-time.Vercel's agents improve code quality by incorporating security and framework best practices into AI-generated output.C3.ai partnered with Department of Defense to autonomously produce mission-critical intelligence assessment reports from data.Industry shifted from copilots everywhere to agents that actually own outcomes and land the plane.New Relic moved beyond natural language translation to agents that execute actions and resolve issues autonomously.Panel debates whether Model Context Protocol or broader ecosystem approaches better enable agent interoperability and communication.Autonomy requires accountability: agent decisions must be explainable with traceable steps and replay capabilities built-in.Governance and security should be prerequisites for acceleration, not impediments—a critical mental model shift needed.Many enterprises struggle with process bottlenecks preventing them from harnessing high-quality agents despite having technology.Financial services must carefully balance where human discretion remains essential versus where agent autonomy justified.Will Jung envisions deeply continuous context enabling banks to deliver truly personalized insights without appearing creepy.Suraj Krishnan predicts agents will own outcomes by 2026, coordinating tools and other agents to achieve goals.Participants:Panelist: Merel Witteveen, SVP of Operations, C3.aiPanelist: Will Jung, Chief Technology Officer, nCinoPanelist: Suraj Krishnan, GVP of Engineering, New RelicPanelist: Aparna Sinha, Senior Vice President, Product, VercelModerator: Olawale Oladehin, Managing Director, NAMER Technology Segments (Enterprise, ISV, DNB, and Model Providers), Amazon Web ServicesSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Jyoti Bansal is the co-founder and CEO of Harness, the software delivery platform used by thousands of engineering teams, and previously founded AppDynamics, which he led from inception to a multibillion-dollar acquisition by Cisco. In this episode, Jyoti unpacks what it really takes to move from mid-market to enterprise, why he thinks in terms of “product-market-sales fit,” and how he structures Harness as a collection of “startups within a startup” to launch multiple “best-of-breed” products. In today's episode, we discuss: Why companies get stuck in the mid-market and struggle to move up into enterprise Why Jyoti deliberately lost Netflix as their customer The difference between product-market-sales fit, and product-market-fit How to build a scalable, capacity-driven go-to-market machine (instead of chasing deals) Diagnosing whether you have a product problem or a distribution problem How to hire and evaluate your first head of sales and top sales leaders Why Jyoti sold AppDynamics three days before IPO The “binary differentiator” rule for launching new products into crowded markets Why Harness runs 16 product lines under one roof Where to find Jyoti: LinkedIn: https://www.linkedin.com/in/jyotibansal/ Twitter/X: https://x.com/jyotibansalsf Where to find Brett: LinkedIn: https://www.linkedin.com/in/brett-berson-9986094/ Twitter/X: https://twitter.com/brettberson Where to find First Round Capital: Website: https://firstround.com/ First Round Review: https://review.firstround.com/ Twitter/X: https://twitter.com/firstround YouTube: https://www.youtube.com/@FirstRoundCapital This podcast on all platforms: https://review.firstround.com/podcast References: Amazon: https://www.amazon.com/ AppDynamics: https://www.appdynamics.com/ Barclays: https://home.barclays/ BIG Labs: https://www.biglabs.com/ Carlos Delatorre: https://www.linkedin.com/in/cadelatorre/ Charles Schwab: https://www.schwab.com/ Cisco: https://www.cisco.com/ Citi: https://www.citi.com/ Cloudability: https://www.apptio.com/products/cloudability/ Datadog: https://www.datadoghq.com/ Dynatrace: https://www.dynatrace.com/ Harness: https://www.harness.io/ Jeff Bezos: https://x.com/JeffBezos Microsoft: https://www.microsoft.com/ Nasdaq: https://www.nasdaq.com/ Netflix: https://www.netflix.com/ New Relic: https://newrelic.com/ Salesforce: https://www.salesforce.com/ Splunk: https://www.splunk.com/ Traceable: https://www.traceable.ai/ Unusual Ventures: https://www.unusual.vc/ VMware: https://www.vmware.com/ Timestamps: (01:48) Why do companies get stuck in the mid-market? (05:09) Designing a product for enterprise and mid-market (07:19) Why Jyoti lost Netflix as a customer - on purpose (10:18) Becoming a scalable GTM organization (12:32) The real signs of product-market fit (14:04) Have you delivered the value? (15:46) How to hire your first sales team (19:59) The four signs of excellent sales leaders (23:16) How to interview a sales leader (27:51) Where Jyoti developed his commercial taste (29:37) Why early founders need to learn sales (32:02) How AppDynamics began (36:36) Why Jyoti sold three days pre-IPO (41:55) What does a healthy board look like? (44:23) How Jyoti perceives competition (46:18) Why you need a binary differentiator (49:53) How to launch multiple products (52:00) “We need to be best of breed” (57:38) Why PMs are like mini-entrepreneurs (1:00:20) The startup within a startup (1:02:45) A culture of continuous improvement

Check out the podcast on Macslist here: (https://www.macslist.org/?post_type=podcasts&p=16430&preview=true) On Sept. 11, we hosted our third quarterly event of 2025 in partnership with Willamette University's Atkinson School of Management. Almost 100 people gathered for networking and a panel discussion, “The Leadership Skills You Need to Succeed in Oregon's Tough Job Market.”  Together, the panelists shared their experiences from higher education, tech recruiting, and executive coaching, offering practical advice for job seekers navigating Oregon's challenging job market. Attendees also had the opportunity to connect with representatives from eight tabling organizations, including educators, professional associations, and career coaches. About Our Guest Leah Straley, dean of Graduate Admissions for Willamette University.  Panelists Ashley Nixon, Ph.D., dean for academic affairs and professor of human resources and organizational behavior, Willamette University Tim Butler, principal sourcer, global talent sourcing, New Relic, Inc. Dr. Carol Parker Walsh, JD, PhD, ACC, executive coach & leadership consultant, Carol Parker Walsh Consulting Group Learn more about your ad choices. Visit megaphone.fm/adchoicesSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Check out the podcast on Macslist here: (https://www.macslist.org/?post_type=podcasts&p=16430&preview=true) On Sept. 11, we hosted our third quarterly event of 2025 in partnership with Willamette University's Atkinson School of Management. Almost 100 people gathered for networking and a panel discussion, “The Leadership Skills You Need to Succeed in Oregon's Tough Job Market.”  Together, the panelists shared their experiences from higher education, tech recruiting, and executive coaching, offering practical advice for job seekers navigating Oregon's challenging job market. Attendees also had the opportunity to connect with representatives from eight tabling organizations, including educators, professional associations, and career coaches. About Our Guest Leah Straley, dean of Graduate Admissions for Willamette University.  Panelists Ashley Nixon, Ph.D., dean for academic affairs and professor of human resources and organizational behavior, Willamette University Tim Butler, principal sourcer, global talent sourcing, New Relic, Inc. Dr. Carol Parker Walsh, JD, PhD, ACC, executive coach & leadership consultant, Carol Parker Walsh Consulting Group Learn more about your ad choices. Visit megaphone.fm/adchoices

How do you monitor distributed systems that span dozens of microservices, multiple languages, and different databases? The old approach of gathering logs from different machines and recompiling apps with profiling flags doesn't scale when you're running thousands of servers. You need a unified strategy that works everywhere, on every component, in every language—and that means tackling the problem from the kernel level up.Mohammed Aboullaite is a backend engineer at Spotify, and he joins us to explore the latest in continuous profiling and observability using eBPF. We dive into how eBPF lets you programmatically peek into the Linux kernel without recompiling it, why companies like Google and Meta run profiling across their entire infrastructure, and how to manage the massive data volumes that continuous profiling generates. Mohammed walks through specific tools like Pyroscope, Pixie, and Parca, explains the security model of loading code into the kernel, and shares practical advice on overhead thresholds, storage strategies, and getting organizational buy-in for continuous profiling.Whether you're debugging performance issues, optimizing for scale, or just want to see what your code is really doing in production, this episode covers everything from packet filters to cultural changes in service of getting a clear view of your software when it hits production.---Support Developer Voices on Patreon: https://patreon.com/DeveloperVoicesSupport Developer Voices on YouTube: https://www.youtube.com/@DeveloperVoices/joineBPF: https://ebpf.io/Google-Wide Profiling Paper (2010): https://research.google.com/pubs/archive/36575.pdfGoogle pprof: https://github.com/google/pprofContinuous Profiling Tools:Pyroscope (Grafana): https://grafana.com/oss/pyroscope/Pixie (CNCF): https://px.dev/Parca: https://www.parca.dev/Datadog Continuous Profiler: https://www.datadoghq.com/product/code-profiling/Supporting Technologies:OpenTelemetry: https://opentelemetry.io/Grafana: https://grafana.com/New Relic: https://newrelic.com/Envoy Proxy: https://www.envoyproxy.io/Spring Cloud Sleuth: https://spring.io/projects/spring-cloud-sleuthMohammed Aboullaite:LinkedIn: https://www.linkedin.com/in/aboullaite/GitHub: https://github.com/aboullaiteWebsite: http://aboullaite.meTwitter/X: https://twitter.com/laytounKris on Bluesky: https://bsky.app/profile/krisajenkins.bsky.socialKris on Mastodon: http://mastodon.social/@krisajenkinsKris on LinkedIn: https://www.linkedin.com/in/krisjenkins/

Episode 146: In this episode of Critical Thinking - Bug Bounty Podcast Justin, Joseph, and Brandyn all sit down to celebrate the spooky season by swapping their scariest bug stories. From frightening fails and firings to hacks with chilling and critical consequences. Grab your flashlight and a blanket for this one!Follow us on twitter at: https://x.com/ctbbpodcastGot any ideas and suggestions? Feel free to send us any feedback here: info@criticalthinkingpodcast.ioShoutout to YTCracker for the awesome intro music!====== Links ======Follow your hosts Rhynorater, rez0 and gr3pme on X: https://x.com/Rhynoraterhttps://x.com/rez0__https://x.com/gr3pme====== Ways to Support CTBBPodcast ======Hop on the CTBB Discord at https://ctbb.show/discord!We also do Discord subs at $25, $10, and $5 - premium subscribers get access to private masterclasses, exploits, tools, scripts, un-redacted bug reports, etc.You can also find some hacker swag at https://ctbb.show/merch!Today's Sponsor: ThreatLocker. Check out ThreatLocker Network Controlhttps://www.criticalthinkingpodcast.io/tl-nc====== This Week in Bug Bounty ======Methodology tips from top Bug Bounty huntersYesWeHack marks first year of partnership with Singapore's GovernmentHackerOne Hacker-Powered Security Report====== Resources ======Critical Research LabHacking the World Poker Tour: Inside ClubWPT Gold's Back OfficeFile Creation via SQLite Injection====== Timestamps ======(00:00:00) Introduction(00:10:11) Crit Research Lab News(00:21:31) Hacking the World Poker Tour & File Creation via SQLite Injection(00:30:40) Brandyn's Spooky Bug(00:38:02) Joseph's Spooky Bug(00:44:18) Justin's Spooky Bug(00:54:44) Banking Bugs, LHE Scares, and Workday weirdness.(01:14:52) Firings and failures(01:22:49) Bank Bug Redux(01:35:55) Wedding planning/registry app & Amazon Rufus bugs(01:40:52) New Relic bug

"The tools we make are observability tools today. But it can never be the goal of our business to provide observability. The goal of our business as a vendor and as a partner with our customers is to give them understandability,” stated Nic Benders, the Chief Technical Strategist at New Relic.In this episode of the Don't Panic It's Just Data podcast, host Christina Stathopoulos, the Founder of Dare to Data, speaks with Benders about where observability is headed in IT systems. They discuss how AI is transforming observability into a more comprehensive understanding of complex systems, moving beyond traditional monitoring to achieve true understandability. Benders explained the importance of merging various data types to provide a complete picture of system performance and user experience. He believes AI can bridge the gap between mere observation of systems and a deeper understanding of their functionality. This could ultimately lead to enhanced incident response and operational efficiency. With maturing technology, complexity is expected to grow, too. The straightforward act of “observing” those complexities is like watching a green light on a machine. This is not enough. The major challenge is to “understand” the inside operations of the machine. This is the difference between simply seeing the data and knowing the "why."Observability to UnderstandabilityAs per Benders, the term observability "leaves a lot to be desired." While it's the industry's common label, it only describes seeing a system. The real goal, he argues, is to understand it.Alluding to an analogy, the technical strategist asks Stathopoulos to imagine a nuclear power plant full of a million blinking lights and screens. “You can have all the observability available, but if you're not an expert, you won't grasp what's actually happening,” says Benders. Typically, software has been developed by a single person who knows every inch of it. However, today, technology has become more perplexing. AI, alongside teamwork and collaboration, provides the tools to solve this problem. An engineer might manage code they didn't write, making a dashboard full of charts unhelpful. Understandability means moving beyond raw data to give context and meaning.Ultimately, Benders advises IT leaders to embrace change. The tech industry is constantly changing and advancing. Instead of fearing new tools, organizations should focus on what they need to grasp the unknown. As he puts it, "a lot of unknown is coming over the next few decades."TakeawaysObservability is not enough; understanding is crucial.AI can enhance the understanding of complex systems.The shift from observing to understanding is essential for modern IT.AI presents both challenges and opportunities in software development.New interfaces powered by AI can improve user interaction with data.AI can help reduce incident response times significantly.Collaboration with AI is becoming the norm in software development.Real-world applications show measurable benefits of AI in observability.IT decision-makers must prepare for ongoing changes in technology.Understanding the unknown is key to navigating future challenges.Chapters00:00 Introduction to Observability and Understandability05:00...

My guest this week is Brian Kotlyar, Head of Marketing & Growth at Hightouch, the leading composable CDP that helps companies activate their data warehouses to drive personalized marketing and business operations. With 20-plus years of experience at Intercom, Sprinklr, and New Relic, Brian knows how to cut through the martech noise and build teams that turn data into real growth. 

En esta tertulia de alto nivel sobre startups, inteligencia artificial y transformación empresarial, los Jordi, Bernat, Marcel y David abordan temas clave como la compraventa de empresas tecnológicas, el mercado laboral en el sector IT, el auge del trabajo remoto, y el cambio en la relación entre empleados y empleadores. Se profundiza en los desafíos de crear una startup, cómo atraer talento senior, y la necesidad de transparencia salarial.Además, se analiza el impacto real de la IA en sectores como el desarrollo de software, el marketing y la agricultura, y se cuestionan valoraciones multimillonarias como la de LoveFrom por parte de OpenAI. También se comparan las estrategias tecnológicas de Google y Microsoft, se discuten modelos de negocio sostenibles frente al hype, y se reflexiona sobre la viabilidad financiera de startups de IA como Perplexity.Finalmente, se presentan casos de éxito como Dertack, una innovadora plataforma de generación de leads a partir de ofertas de empleo, y Névoda Farms, una startup agroindustrial que aplica tecnología para escalar su producción vegetal con eficiencia.

Reinvention beats repetition every time. In a crowded market, it's reimagination that sets you apart.That's the real lesson behind The New Look, a drama that follows Christian Dior as he rebuilds a whole new vision of fashion. In this episode, we're taking inspiration from that spirit of transformation with the help of our special guest, Hrishi Kulkarni, Director of Customer Advocacy & Executive Programs at dbt Labs.Together, we explore what B2B marketers can learn from narrative-driven branding, thoughtful reinvention, and the power of showing up with both creativity and compassion.About our guest, Hrishi KulkarniHrishi Kulkarni leads customer advocacy and executive programs at dbt Labs. Previously, Hrishi served as Head of Customer Marketing & Executive Programs at New Relic. He has also worked at Salesforce in Customer Engagement and Marketing and QStream in Customer Success and Professional Services. Hrishi brings with him over 16 years of experience in customer engagement. He is also an equality champion, SF LGBT Center board member and founder of LGBTQ+ ERGs in India and Asia.What B2B Companies Can Learn From The New Look:Storytelling is your superpower. In The New Look, Christian Dior tells stories through his fashion. His work is infused with personal meaning, from tributes to his sister to inspiration from his mother. Hrishi says, “Marketing is all about storytelling. I joined marketing because I love storytelling… it emotionally connects your product and your services to your audience.” In B2B, storytelling isn't fluff, it's how you make people care. It's how you stand out. Don't just tell your audience what your product does, tell them why it matters.Innovation only works when it's authentic. Dior's most memorable move wasn't a massive runway spectacle; it was an intimate, unexpected fashion show that broke every rule. Hrishi explains, “He's not going to have a huge fashion show… He's going to create it in a very small space, a very personalized experience. Which never before any designer had done.” That decision wasn't flashy for the sake of it. It was deeply intentional. For B2B marketers, it's a reminder that innovation doesn't mean gimmicks. It means staying true to your values and finding fresh, genuine ways to express them.Repetition kills good content. Dior didn't copy what worked, he created what was next. Hrishi says, “As a customer marketer… we have to be creative in identifying and securing the right stories and then finding innovative ways to amplify those stories. If you keep amplifying different stories also in similar ways, at some point it is going to fall flat.” B2B marketers often default to the same formats: another case study, another quote, another video. But to keep your audience engaged, you have to rethink how you tell your stories, not just what stories you tell.Quotes*“ I love storytelling. It's because, if you think about it, storytelling truly impacts people's hearts and minds. It emotionally connects your product and your services to your audience. And that's exactly what Dior has done with his fashion. Like the perfume story you shared earlier, right? It's inspired by his sister. Like a lot of his design of his costumes, of his art, his all comes inspired from his mother. So he truly shows us how storytelling can drive the fashion industry. He started his fashion through the art of storytelling. Also thinking outside the box. If you saw the show, he's constantly innovating. He's constantly thinking outside the box. And as a customer marketer, you have to be constantly creative in identifying and securing the right stories and then finding innovative ways to amplify those stories. If you keep amplifying different stories also in similar ways, at some point it is going to fall flat. So it's always “how can I be innovative with these stories?” And then of course thought leadership, right? It's storytelling or thinking outside the box, being creative to showcase the thought leadership of your customers, their brand.”*“ In terms of B2B, customers love to hear how other customers are doing, how they're using your platform. .And I always say that what makes a kickass story is it has to be data driven and there has to be some human element to it. And now that's your recipe of a powerful story. ”*“ In a B2B world, we create all these customer stories, but what's our end goal? Our end goal is how are my sales teams, my how are my account executives going to leverage this story with other prospects, with other customers. So truly thinking that buyer journey, how are your different stories going to influence every stage in that buyer journey?”*“ Being authentic is so important in marketing. That is something we learned from The New Look. Be authentic in what you do. The passion comes across genuinely. It comes across easily. It's very evident. Be innovative. Don't be afraid to take risks.”Time Stamps[0:55] Meet Hrishi Kulkarni, Customer Advocacy & Executive Programs Lead at dbt Labs[01:10] Why The New Look?[04:19] Customer Advocacy & Executive Programs at dbt Labs[06:54] Origins of The New Look[11:54] B2B Marketing Takeaways from The New Look[24:57] Building a Strong Content Strategy[27:53] Measuring ROI in Customer Marketing[32:08] dbt Labs Executive Sponsorship Program[34:12] Advice for Marketing LeadersLinksConnect with Hrishi on LinkedInLearn more about dbt LabsAbout Remarkable!Remarkable! is created by the team at Caspian Studios, the premier B2B Podcast-as-a-Service company. Caspian creates both nonfiction and fiction series for B2B companies. If you want a fiction series check out our new offering - The Business Thriller - Hollywood style storytelling for B2B. Learn more at CaspianStudios.com. In today's episode, you heard from Ian Faison (CEO of Caspian Studios) and Meredith Gooderham (Head of Production). Remarkable was produced this week by Jess Avellino, mixed by Scott Goodrich, and our theme song is “Solomon” by FALAK. Create something remarkable. Rise above the noise.

"Having the insight and being able to stitch together your technical resources and business decisions together, is the prime place where observability can add value to you,” stated Manesh Tailor, EMEA Field CTO at New Relic.In this episode of the Tech Transformed podcast, Kevin Petrie, Vice President of Research at BARC, speaks with Manesh Tailor about the intersection of artificial intelligence (AI) and observability, and how this is positively changing business operations.Tailor emphasises how intelligent observability has changed beyond simple monitoring to provide real-time insights into customer experience and the entire technology stack. This enables informed decisions across engineering, operations, and business domains, directly linking technical performance to strategic business outcomes.He also discusses the different stages observability has been through and where it's leading to now. The current wave, Observability 3.0, takes advantage of AI to predict issues and even enable self-healing systems. New Relic has embraced this two-way street, using AI within its platform. This was in an ambition to help users and "AI monitoring" to track the performance of language models alongside traditional metrics. Such a platform provides a holistic view of system health and the cost implications of AI deployments.Alluding to the management of AI-powered applications, Tailor says collaboration is key between application and data science teams. Not only does it provide real time data but as a result leads to efficient decision making.Futuristically, the speedy proliferation of AI agents has both pros and cons for observability. This is where New Relic comes in. It addresses the challenges by constructing a platform-centric "AI orchestrator" with a growing library of AI-native agents. In essence, as AI-powered applications become increasingly integral to business operations, intelligent observability is no longer optional. TakeawaysObservability is crucial for understanding unknowns in systems.AI enhances observability by providing predictive insights.The evolution of observability includes intelligent monitoring.Collaboration between technical and business teams is essential.Cost efficiency is a key focus in modern observability.Real-time data is vital for effective decision-making.Self-healing systems represent the future of observability.AI and observability must work in tandem for success.The complexity of systems is increasing, requiring better tools.Observability is applicable across all organizational levels.Chapters00:00 Introduction to AI and Observability03:10 Defining Observability and Its Evolution05:49 The Role of AI in Observability08:46 Navigating AI-Driven Applications11:52 Target Users and Community for Observability14:57 Collaboration Across Teams17:55 Challenges and Opportunities in Observability20:47 The Future of Observability and AI23:54 Key Takeaways for CIOs and IT LeadersAbout New RelicThe New Relic Intelligent Observability Platform empowers businesses to proactively eliminate disruptions in their digital experiences. As the only AI-enhanced platform that unifies and correlates telemetry data, New...

New Relic's Head of AI and ML Innovation, Camden Swita discusses their four-cornered AI strategy and envisions a future of "agentic orchestration" with specialized agents.Topics Include:Introduction of Camden Swita, Head of AI at New Relic.New Relic invented the observability space for monitoring applications.Started with Java workloads monitoring and APM.Evolved into full-stack observability with infrastructure and browser monitoring.Uses advanced query language (NRQL) with time series database.AI strategy focuses on AI ops for automation.First cornerstone: Intelligent detection capabilities with machine learning.Second cornerstone: Incident response with generative AI assistance.Third cornerstone: Problem management with root cause analysis.Fourth cornerstone: Knowledge management to improve future detection.Initially overwhelmed by "ocean of possibilities" with LLMs.Needed narrow scope and guardrails for measurable progress.Natural language to NRQL translation proved immensely complex.Selecting from thousands of possible events caused accuracy issues.Shifted from "one tool" approach to many specialized tools.Created routing layer to select right tool for each job.Evaluation of NRQL is challenging even when syntactically correct.Implemented multi-stage validation with user confirmation step.AWS partnership involves fine-tuning models for NRQL translation.Using Bedrock to select appropriate models for different tasks.Initially advised prototyping on biggest, best available models.Now recommends considering specialized, targeted models from start.Agent development platforms have improved significantly since beginning.Future focus: "Agentic orchestration" with specialized agents.Envisions agents communicating through APIs without human prompts.Integration with AWS tools like Amazon Q.Industry possibly plateauing in large language model improvements.Increasing focus on inference-time compute in newer models.Context and quality prompts remain crucial despite model advances.Potential pros and cons to inference-time compute approach.Participants:Camden Swita – Head of AI & ML Innovation, Product Management, New RelicSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

This week on That Tech Pod, Laura and Kevin sit down with tech veteran and AI thought leader Ken Gavranovic, CEO of Product Genius, for a lively and insightful conversation that spans AI, ethics, innovation and pop culture. Ken opens up about his challenging childhood, sharing how it sparked a passion for technology and a desire to build tools that could truly make a difference, much like the kid in the movie War Games. From early fumbles in fax software that made others millions but netted him nothing to working with tech giants like Disney and 7-Eleven, Ken walks us through his evolution into the AI space and why he believes AI will have the most substantial impact on humanity. We talk about ethical AI and data privacy, especially when it comes to children and younger audiences, how to leverage AI insights without drowning in data and the key contrasts in AI adoption between big corporations and smaller businesses. Laura and Ken geek out about functional health, from UV-cap water bottles to proactive blood testing to the very real fears (ahem, Laura) about robot uprisings from a tangent on the movie Smart House, the series Cassandra and The Terminator movies. Plus, we discuss recycled toilet paper and sustainability with a shoutout to Who Gives a Crap, and wrap things up with a peek into Ken's Amazon best-seller, Business Breakthrough 3.0, a must-read for any leader navigating digital transformation. Tune in for an episode that's smart, human, and just the right amount of tech-weird.Ken Gavranovic is a global keynote speaker, a seasoned technology executive, and the CEO of Product Genius, where he leads the development of AI-powered tools that transform real-time data into actionable customer insights, driving service improvements and operational efficiency. With over two decades of experience, Ken has helped businesses—from startups to global brands like Disney World and 7-Eleven—leverage cutting-edge tech to achieve measurable results. He has led 18 successful exits, 35 mergers and acquisitions, and an IPO, and has held key executive roles at New Relic and Cox Automotive. A global keynote speaker and member of Thinkers50 and the Forbes Council, Ken is also a co-author of the Amazon best-seller Business Breakthrough 3.0, a practical guide for leaders navigating digital transformation and scaling operations.

In this week's episode of The Venue Rx Podcast, host Jonathan Aymin sits down with Ken Gavranovic, CEO of Product Genius, to explore how AI is shaking up the wedding venue industry. Ken shares eye-opening insights on how AI is changing the way couples discover venues—especially through search engines like Google—and how it's helping businesses create more meaningful, personalized customer experiences.From streamlining day-to-day operations to gathering real-time feedback, Ken breaks down how venue owners can harness AI to boost efficiency and improve service. He also dives into practical strategies for using AI to stay competitive, manage online reviews, and build stronger client relationships. About Our Guest: Ken Gavranovic is a hands-on tech leader, global keynote speaker, and member of both Thinkers50 and the Forbes Council. With over 20 years of experience, he's helped traditional businesses harness the power of AI and emerging tech to get fast, real-world results. Ken has partnered with top venture firms, led 18+ successful exits, 35 mergers and acquisitions, and even taken a company public. He's also brought innovation to major brands like Disney World and 7-Eleven, using technology to boost customer experience and streamline operations.As CEO of Product Genius, Ken is building AI tools that turn real-time data into personalized customer interactions—helping businesses improve service, efficiency, and stay ahead of the competition. He previously founded Interland (now Web.com), growing it from zero to $200 million in just three years and guiding it through an IPO. He's also held executive roles at New Relic and Cox Automotive, where he led digital transformations that made a big impact on both customers and teams.Ken has spoken at 50+ events around the world, sharing practical insights on AI, scaling, and driving growth. He's also co-author of the Amazon bestseller Business Breakthrough 3.0, which lays out a clear five-step roadmap for leaders to drive change, align teams, and grow with purposeFind Him Here: Email: ken@kengavranovic.comWebsite: https://kengavranovic.com/Linkedin: https://www.linkedin.com/in/gavranovic/Instagram: https://www.instagram.com/kengavranovic/X: https://twitter.com/kgavranovic

New Relic's Chief Customer Officer Arnaldo (Arnie) Lopez details how their observability platform helps 70,000+ customers monitor cloud performance through AWS infrastructure while introducing AI capabilities that simplify operations.Topics Include:Arnie Lopez is SVP, Chief Customer Officer at New Relic.Oversees pre-sales, post-sales, technical support, and enablement teams.New Relic University offers customer certifications.Founded in 2008, pioneered application performance monitoring (APM).Now offers "Observability 3.0" for full-stack visibility.Prevents interruptions during cloud migration and operations.Serves 70,000+ customers across various industries.16,000 enterprise-level paying customers.Platform consolidates multiple monitoring tools into one solution.Helps detect issues before customers experience performance problems.Market challenge: customers using disparate observability solutions.Reduces TCO by eliminating multiple monitoring tools.Targets VPs, CTOs, CIOs, and sometimes CEOs.Decade-long partnership with AWS.Platform built on largest unified telemetry data cloud.Uses AWS Graviton instances and Amazon EKS.AWS partnership enables innovation and customer trust.Three AI approaches: user assistance, LLM monitoring, faster insights.New Relic AI helps write query language (NURCLs).Monitors LLMs in customer environments.Uses AI to accelerate incident resolution.Lesson learned: should have started AI implementation sooner.Many customers still cautiously adopting AI technologies.Goal: continue growth with AWS partnership.Offers compute-based pricing model.Customers only pay for what they use.Announced one-step AWS monitoring for enterprise scale.Amazon Q Business and New Relic AI integration.Agent-to-agent AI eliminates data silos.Embeds performance insights into business application workflows.Participants:Arnie Lopez – SVP Chief Customer Officer, New RelicSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

Ishan Mukherjee is the Co-Founder/CEO of Rox, a Sequoia-backed AI-powered sales productivity platform. Before Rox, he was the Chief Growth Officer at New Relic where he scaled the self-serve business from $0-$100M in ARR. Prior to New Relic, Ishan founded Pixie Labs (acq by New Relic). Before that he led product at Siri Knowledge Graph at Apple, Lattice Data (acquired by Apple), Premise Data, and Amazon Robotics. Ishan was also an early engineer in Kiva (acquired by Amazon) where he joined after graduating from MIT. In Today's Episode We Discuss: 04:50 Biggest Lessons Scaling New Relic's PLG to $100M in ARR 05:59 How to Do PLG and Enterprise at the Same Time 07:00 How to do Content in a PLG World 08:50 Performance Marketing or Organic Content: What Works for PLG 10:27 Why You Should Stop Marketing at Events 11:47 Why SEM is a Cartel 14:15 Why Unpaid Design Partners are BS 17:17 How AI Changes the World of Enterprise Sales: Commit-Based vs. Usage-Based  20:49 How to do Sales Compensation Plans 24:44 How to Ramp New Sales Reps 25:03 The Impact of AI on Sales Research 29:18 How to do Deep Customer Research in an AI World 35:56 Changing Spending Patterns in SaaS 41:41 Retention and Churn in Enterprise AI 43:31 The Future of Sales Teams with AI 44:45 Hiring and Scaling Sales Teams 54:28 Quickfire    

Join Bhavin Shah and Ryan Wallner as they speak with Jemiah Sius, Senior Director of Developer Relations at New Relic to talk about how to get started with learning about Kubernetes. They hosts and Jemiah explore how this has changed within the last 10 years as well as explore what are some good resources for learning and diving in. Links https://www.linkedin.com/in/jemiahsius/ https://newrelic.com/ https://newrelic.com/events/new-relic-now/roadshow https://www.udemy.com/topic/kubernetes/

Today on the Invest In Her podcast, host Catherine Gray speaks with Mariane Bekker, a seasoned tech executive with over a decade of experience leading high-performing engineering teams at top startups like New Relic and Mindbody. Currently, she is the Managing Partner at Founders Bay, a premier venture studio dedicated to AI startups in the Bay Area, where she connects a thriving community of 30,000 founders and investors through events, virtual workshops, and fundraising resources. Additionally, Mariane is the force behind Women Founders Bay, one of the largest networks for female tech entrepreneurs, providing invaluable mentorship, resources, and networking opportunities to empower women in the industry. In this episode, Mariane dives into the evolving landscape of AI-driven startups, sharing insights on how entrepreneurs can successfully navigate the tech world. She discusses the importance of community-building, the challenges women founders face, and the role of venture studios in accelerating innovation. Catherine and Mariane also explore strategies for fundraising, scaling businesses, and fostering a more inclusive startup ecosystem. This conversation is packed with actionable advice for aspiring and established entrepreneurs alike! https://www.foundersbay.com/ https://www.womenfoundersbay.com/ www.sheangelinvestors.com    Follow Us On Social Facebook @sheangelinvestors Twitter (X) @sheangelsinvest Instagram @sheangelinvestors & @catherinegray_investinher LinkedIn @catherinelgray & @sheangels

In this episode of "ThinkFuture," host Chris Kalaboukis sits down with tech veteran Ken, who shares his fascinating journey from the early days of web hosting to leading-edge AI applications. Ken recounts his entrepreneurial beginnings with a successful web hosting company and his transition into enterprise tech consulting. He discusses his pivotal role at New Relic, where he saw firsthand how AI could revolutionize troubleshooting in software development. Ken then delves into his work with Blameless, where he helped foster a culture where AI aids in incident response without finger-pointing. His most recent endeavor, Product Genius, aims to deploy AI assistants in physical spaces to enhance customer interactions and operational efficiency. The conversation wraps up with Ken's vision for AI's role in reshaping industries, emphasizing augmentation over replacement of human roles.---Connect with Ken here: https://kengavranovic.comThe First Future Planner: Record First, Action Later: https://foremark.usBe A Better YOU with AI: Join The Community: ⁠https://10xyou.us⁠Get AIDAILY every weekday. ⁠https://aidaily.us⁠My blog: ⁠https://thinkfuture.com

Episode SummaryIn this episode of OnBase, host Chris Moody sits down with Kelly Flowers to discuss the power of systems-based strategy in driving predictable outcomes in sales development. Kelly shares her unique journey into sales, the lessons she learned from transitioning industries, and how she developed a structured approach to pipeline generation, OKRs, and sales efficiency. She also highlights the biggest challenges in sales today, the role of AI in streamlining sales processes, and the myths that hold sales teams back. With practical insights and actionable strategies, this conversation is a must-listen for revenue leaders looking to optimize their go-to-market strategies and drive consistent results. About the Guest Kelly Flowers serves as the AVP, of Global Sales Development at SentinelOne and previously held positions including Head of Sales and Business Development at 1Password, Director of AMER Sales Development at Databricks, and Senior Manager of Customer Success, Enterprise Renewals at New Relic, Inc.  Additionally, Kelly has experience as a Manager of Sales Development and as an SDR Manager at Wizeline, as well as serving as the San Francisco Community Chair for Women in Sales Everywhere (WISE). Kelly holds a degree in Global Studies & Spanish, International Relations from Sonoma State University and has also studied Spanish Language at Tecnológico de Monterrey. Connect with Kelly Key Takeaways- Systems Thinking vs. Goal Setting: Goals help you achieve one-time success, but systems-based strategies ensure sustainable, repeatable success. - Pipeline Predictability Comes from Process: Breaking down the sales cycle into measurable inputs and outputs helps reps consistently hit quota. - Behavior Matters as Much as Performance: Being a "quota crusher" isn't enough—collaboration, integrity, and consistency are key to long-term success. - AI as a Sales Multiplier, Not a Replacement: Sales professionals must leverage AI tools for research, prioritization, and process automation—but human connection remains essential. Quotes "Revenue intelligence makes arguments about 'who said what' obsolete by providing unfiltered, real-time data everyone can trust." Recommended Resources Books:- Setting the Table by Danny Meyer Newsletter: - Endurance by Katie Ceccarini Podcast: - Grit with Joubin Mirzadegan Connect with Kelly⁠ ⁠⁠⁠| ⁠⁠⁠⁠⁠⁠⁠Follow us on LinkedIn ⁠⁠⁠⁠⁠⁠⁠| ⁠⁠⁠⁠⁠⁠⁠Website

Melton Littlepage is a seasoned marketing executive with over two decades of experience driving innovation, creating new categories, and accelerating growth in the technology sector. Currently the Chief Marketing Officer at 1Password, Melton previously held the same role at Outreach, where he led comprehensive global marketing teams to enhance brand presence and revenue generation. His prior leadership roles include transformative contributions at Tenable in cybersecurity, New Relic in software analytics, Schoology in edtech, and Concur, a multi-billion dollar global B2B SaaS leader. His expertise spans strategic communications, brand management, demand generation, and customer engagement across diverse domains.1Password is a secure password management tool that helps individuals and businesses store, manage, and use passwords and sensitive information safely. It features strong password generation, secure storage, encrypted data protection, and cross-platform accessibility. Ideal for personal and enterprise use, 1Password supports secure credential sharing, password hygiene monitoring, and integration with business tools, offering a user-friendly solution for enhancing digital security.On today's show, Alan and Melton discuss 1Password and its role in the cybersecurity space, exploring how Melton differentiates the brand. They explore 1Password's strategic move into the golf industry through the Presidents Cup and the potential power of sports marketing. Melton shares his approach to crafting marketing strategies for both B2B and B2C audiences. They end by examining how trends like Formula 1's resurgence and the popularity of longform podcasts are shifting the way we should think about marketing.In this episode, you'll learn:The strategy behind a bold marketing move Insight on how to successfully pitch a new strategyHow Formula 1 and longform podcasts are reshaping the way we approach marketingKey Highlights:[01:11] Personal story: Fear of heights[04:05] Career path to 1Password[11:42] What is going on in the cybersecurity industry[13:56] How 1Password is approaching security[16:33] Differentiating within industry[19:19] Recent sports marketing move with golf [24:12] The pitch [27:04] An experience from your past that defines you[29:08] Advice to your younger self[30:32] A topic that marketers need to learn more about: Mapping your buyers journey[33:04] Trends or subcultures others should follow: Formula 1 movement[36:00] Largest opportunity or threat to marketers today: Longform podcastLooking for more?Visit our website for the full show notes, links to resources mentioned in this episode, and ways to connect with the guest! Become a member today and listen ad-free, visit https://plus.acast.com/s/marketingtoday. Hosted on Acast. See acast.com/privacy for more information.

In today's episode, Matt interviews Ed Diller, Sales Leader at New Relic. They explore effective coaching practices and myths in sales leadership. They discuss the importance of strategic communication, creating win-win scenarios, and maintaining work-life balance in a post-COVID world. Ed shares valuable lessons from his extensive career, emphasizing the need for risk-taking, clear communication, and the benefits of focusing on strengths. He also highlights the role of coaching in career progression and how leaders can foster engagement and avoid burnout in hybrid work environments. Takeaways:Ensure clear and concise communication, especially when working remotely. Utilize tools to mitigate grammatical errors and enhance the professionalism of communications.Use virtual face-to-face meetings (via Zoom or similar platforms) to maintain human connection and engagement within the team. Promote informal interactions to build camaraderie.Focus on being invited to higher-level discussions rather than bypassing immediate contacts. Build rapport and trust with initial points of contact before aiming for discussions with their superiors.Address the need for work-life balance in a remote work environment to prevent burnout among team members.Recommend that aspiring sales leaders read beyond typical sales books, exploring works that provide broader insights into leadership, strategy, and empathy.Focus on modeling the behaviors and strategies you want to see in your team. Provide constructive feedback aligned with their career aspirations, not just their current roles.Quote of the Show:“Great salespeople don't just want a bigger paycheck for selling more. They want to take on more, they want to do more.” - Ed DillerLinks:LinkedIn: https://www.linkedin.com/in/edwardmdiller/ Website: https://newrelic.com/ Ways to Tune In:Spotify: https://open.spotify.com/show/0Yb1wPzUxyrfR0Dx35ym1A Apple Podcasts: https://podcasts.apple.com/us/podcast/coach2scale-how-modern-leaders-build-a-coaching-culture/id1699901434 Google Podcasts: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy50cmFuc2lzdG9yLmZtL2NvYWNoMnNjYWxlLWhvdy1tb2Rlcm4tbGVhZGVycy1idWlsZC1hLWNvYWNoaW5nLWN1bHR1cmU Amazon Music: https://music.amazon.com/podcasts/fd188af6-7c17-4b2e-a0b2-196ecd6fdf77 Podchaser: https://www.podchaser.com/podcasts/coach2scale-how-modern-leaders-5419703 YouTube: https://www.youtube.com/@Coach2Scale CoachEm™ is the first Coaching Execution Platform that integrates deep learning technology to proactively analyze patterns, highlight the "why" behind the data with root causes, and identify the actions that will ultimately improve business results going forward.  These practical coaching recommendations for managers will help their teams drive more deals, bigger deals, faster deals and loyal customers. Built with decades of go-to-market experience, world-renowned data scientists and advanced causal AI/ML technology, CoachEm™ leverages your existing tech stack to increase rep productivity, increase retention, and replicate best practices across your team.Learn more at coachem.io

Send us a textEn este episodio de Life on Mars, Àlex entrevista a Diego Mariño, fundador de Ducksboard, la startup que vendió a New Relic en 2014. A través de una conversación sincera y sin filtros, Diego nos lleva más allá del éxito inicial de la venta para desvelar el lado menos conocido del proceso post-acquisition. Desde el periodo de earn-out y los retos de permanecer en una compañía adquirida, hasta los cambios de responsabilidad, el burnout y el dilema de encontrar una nueva motivación después de haber alcanzado una meta importante.Diego comparte con Àlex cómo vivió la transición tras la venta de su empresa, las lecciones que aprendió a posteriori y cómo, con el tiempo, encontró un balance entre sus responsabilidades y su bienestar personal. También exploran la importancia de estar preparado para el “tour of duty” que suele acompañar una adquisición, y Diego nos ofrece consejos clave para otros emprendedores sobre cláusulas y condiciones que todos deberían considerar antes de vender.Este episodio es una inmersión en el lado más humano del M&A, ideal para quienes están pensando en vender su empresa, quienes están en pleno proceso, o quienes simplemente quieren conocer los desafíos que vienen después del éxito.Y, si vais a vender la empresa, pues hablad con ellos primero, que algo parece que saben. Por lo menos, os invitarán a comer pulpo

Andrew Tunall is a product engineering leader focused on pushing the boundaries of reliability with a current focus on mobile observability. Using his experience from AWS and New Relic, he's vocal about the need for a more user-focused observability, especially in mobile, where traditional practices fall short. * Career Journey and Current Role: Andrew Tunall, now at Embrace, a mobile observability startup in Portland, Oregon, started his journey at AWS before moving to New Relic. He shifted to a smaller, Series B company to learn beyond what corporate America offered.* Specialization in Mobile Observability: At Embrace, Andrew and his colleagues build tools for consumer mobile apps, helping engineers, SREs, and DevOps teams integrate observability directly into their workflows.* Gap in Mobile Observability: Observability for mobile apps is still developing, with early tools like Crashlytics only covering basic crash reporting. Andrew highlights that more nuanced data on app performance, crucial to user experience, is often missed.* Motivation for User-Centric Tools: Leaving “big observability” to focus on mobile, Andrew prioritizes tools that directly enhance user experience rather than backend metrics, aiming to be closer to end-users.* Mobile's Role as a Brand Touchpoint: He emphasizes that for many brands, the primary consumer interaction happens on mobile. Observability needs to account for this by focusing on user experience in the app, not just backend performance.* Challenges in Measuring Mobile Reliability: Traditional observability emphasizes backend uptime, but Andrew sees a gap in capturing issues that affect user experience on mobile, underscoring the need for end-to-end observability.* Observability Over-Focused on Backend Systems: Andrew points out that “big observability” has largely catered to backend engineers due to the immense complexity of backend systems with microservices and Kubernetes. Despite mobile being a primary interface for apps like Facebook and Instagram, observability tools for mobile lag behind backend-focused solutions.* Lack of Mobile Engineering Leadership in Observability: Reflecting on a former Meta product manager's observations, Andrew highlights the lack of VPs from mobile backgrounds, which has left a gap in observability practices for mobile-specific challenges. This gap stems partly from frontend engineers often seeing themselves as creators rather than operators, unlike backend teams.* OpenTelemetry's Limitations in Mobile: While OpenTelemetry provides basic instrumentation, it falls short in mobile due to limited SDK support for languages like Kotlin and frameworks like Unity, React Native, and Flutter. Andrew emphasizes the challenges of adapting OpenTelemetry to mobile, where app-specific factors like memory consumption don't align with traditional time-based observability.* SREs as Connective Tissue: Andrew views Site Reliability Engineers (SREs) as essential in bridging backend observability practices with frontend user experience needs. Whether through service level objectives (SLOs) or similar metrics, SREs help ensure that backend metrics translate into positive end-user experiences—a critical factor in retaining app users.* Amazon's Operational Readiness Review: Drawing from his experience at AWS, Andrew values Amazon's practice of operational readiness reviews before launching new services. These reviews encourage teams to anticipate possible failures or user experience issues, weighing risks carefully to maintain reliability while allowing innovation.* Shifting Focus to “Answerability” in Observability: For Andrew, the goal of observability should evolve toward “answerability,” where systems provide engineers with actionable answers rather than mere data. He envisions a future where automation or AI could handle repetitive tasks, allowing engineers to focus on enhancing user experiences instead of troubleshooting. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit read.srepath.com

Today's episode explores observability within the software delivery lifecycle, particularly test-related events. Joining us is Rodrigo Martin, a principal software engineer and test architect at New Relic with an impressive two decades of experience in software testing. Rodrigo sheds light on the often overlooked aspects of observability in testing environments, discussing how tracking test-related events can significantly enhance debugging capabilities, performance monitoring, and overall test suite reliability. He shares actionable insights on getting started with event tracking, the key metrics you need to focus on, and the common challenges you might face. Whether you're dealing with flaky tests, trying to improve pipeline performance, or simply wanting to understand your testing processes' inner workings better, Rodrigo's expert advice has got you covered. Don't miss this episode if you want to take your DevOps observability efforts to the next level. Grab your headphones and join us on this journey to make your CI/CD pipelines more efficient and your developer experience richer. Listen up!

Subscribe: Apple Podcasts | Spotify | Stitcher | Overcast Support the Show. Get the AudioBook! AudioBook: Audible| Kobo| Authors Direct | Google Play | Apple Introduction In the world of startups, founders are often laser-focused on product development, leaving crucial back-office tasks like accounting as an afterthought. Yet, ignoring this foundational piece of the puzzle can lead to disastrous consequences when it's time to scale or raise funding. Without proper systems in place, businesses risk losing investor trust, facing compliance issues, or simply running into operational chaos. But how can entrepreneurs find a balance between driving their product forward and keeping their financial house in order? In this episode of The Entrepreneur Ethos, Jarie Bolander chats with the co-founders of KBA Partners—Kasia Rzepnikowska, Angel Zhao, and Barbara Legnitto Hansson—who turned their decades of experience in high-growth companies like New Relic into a boutique firm that helps startups navigate the complex world of finance and accounting. Drawing on their unique backgrounds in taking companies from fledgling startups to billion-dollar valuations, they offer actionable advice on building a financial infrastructure that's not just about staying compliant but enabling growth. This conversation dives deep into how early-stage companies can avoid the common pitfalls of financial mismanagement, why accounting should be seen as an asset rather than a burden, and how having the right systems in place early can provide the peace of mind needed to focus on what really matters—growing your business. From setting up basic bookkeeping to managing the complexities of scaling, these experts share practical, real-world insights that every entrepreneur needs to hear. If you're a founder who wants to sleep better at night knowing your financials are rock solid or an entrepreneur navigating the tricky waters of startup growth, you won't want to miss this episode. Hit play and learn how to lay the groundwork for long-term success with guidance from industry veterans who've been there and done it. Tune in now and start securing your startup's future! Links Barbara Legnitto Hansson LinkedIn Angel Zhao LinkedIn Kasia Rzepnikowska on LinkedIn Keep In Touch Book or Blog or Twitter or LinkedIn or Get Story-Driven Learn more about your ad choices. Visit podcastchoices.com/adchoices

It turns out, you don't need to step outside to observe the clouds. On this episode, we're joined by Chronosphere Field CTO Ian Smith. He and Corey delve into the innovative solutions Chronosphere offers, share insights from Ian's experience in the industry, and discuss the future of cloud-native technologies. Whether you're a seasoned cloud professional or new to the field, this conversation with Ian Smith is packed with valuable perspectives and actionable takeaways.Show Highlights:(0:00) Intro(0:42) Chronosphere sponsor read(1:53) The role of Chief of Staff at Chronosphere(2:45) Getting recognized in the Gartner Magic Quadrant(4:42) Talking about the buying process(8:26) The importance of observability(10:18) Guiding customers as a vendor(12:19)  Chronosphere sponsor read(12:46) What should you do as an observability buyer(16:01) Helping orgs understand observability(19:56) Avoiding toxicly positive endorsements(24:15) Being transparent as a vendor(27:43) The myth of "winner take all"(30:02) Short term fixes vs. long term solutions(33:54) Where you can find more from Ian and ChronosphereAbout Ian SmithIan Smith is Field CTO at Chronosphere where he works across sales, marketing, engineering and product to deliver better insights and outcomes to observability teams supporting high-scale cloud-native environments. Previously, he worked with observability teams across the software industry in pre-sales roles at New Relic, Wavefront, PagerDuty and Lightstep.LinksChronosphere: https://chronosphere.io/?utm_source=duckbill-group&utm_medium=podcastIan's Twitter: https://x.com/datasmithingIan's LinkedIn: https://www.linkedin.com/in/ismith314159/SponsorChronosphere: https://chronosphere.io/?utm_source=duckbill-group&utm_medium=podcast

(0:00) Intro.(1:03) About the podcast sponsor: The American College of Governance Counsel.(1:50) Start of interview. *Reference to E137 with Coco Brown (CEO of Athena Alliance).(2:47) Yvonne's origin story.(5:49) Her executive career starting with Accenture, and later with VMware, New Relic, and CEO of Airware and Puppet.(9:03) On her board journey. Distinctions between private and public company service. Plus non-profits.(17:43) Explaining board composition and dynamics in VC-backed companies.(23:23) Explaining board composition and dynamics in PE-backed companies. "It's much more straightforward, structured, and contained."(27:39) On the 'Stay Private vs Go Public' debate and other considerations on private markets.(34:29) On the AI boom and how to think about it from a board's perspective: "how do you experiment and lean in without committing?"(39:06) On the increasing relevance of cybersecurity in the age of digitization. "Cyber attacks are like earthquakes in California. They're going to happen."(42:33) On geopolitics and the boardroom. "How you think about it really depends on what type of company you're in, how big it is, and what you're trying to achieve."(45:40) How to think about the ESG landscape.(49:56) Podcasts that she regularly listens to: Boardroom Governance with Evan Epstein :)The Economist PodcastsGrit Podcast with Joubin MirzadeganAcquired Podcast(52:03) Her mentors and sponsors. Carl Eschenbach John Chambers(54:44) Quotes that she thinks of often or lives her life by: "Be the change you want to see in the world" by Mahatma Gandhi,(55:15) An unusual habit or absurd thing that she loves: misting plants.(56:35) The living person she most admires: MacKenzie Scott.Yvonne Wassenaar is a seasoned Silicon Valley C-level executive and board member with experience across public, private equity-backed, and venture-backed companies. She currently serves on the boards of Forrester, Rubrik, Arista Networks, JFrog, Alation, Braze, and InfoBlox. She also serves on the boards of Harvey Mudd College and UCLA Anderson's Easton Technology Management Center. You can follow Evan on social media at:Twitter: @evanepsteinLinkedIn: https://www.linkedin.com/in/epsteinevan/ Substack: https://evanepstein.substack.com/__You can join as a Patron of the Boardroom Governance Podcast at:Patreon: patreon.com/BoardroomGovernancePod__Music/Soundtrack (found via Free Music Archive): Seeing The Future by Dexter Britain is licensed under a Attribution-Noncommercial-Share Alike 3.0 United States License

What are effective remote communication strategies for product teams? In this episode of Product Talk hosted by Workleap Director of Product Barbara Bermes, New Relic Fmr VP of Engineering Jade Rubick speaks on effective strategies for managing communication in remote and asynchronous work environments. He covers the challenges of async communication, such as over-specification vs. under-specification, and strategies to address them. Jade also shares best practices for using tools like Slack to enhance productivity and collaboration, including using threaded replies, managing notifications, and replying with documentation. Tune in for insights on fostering a healthy remote communication culture.

New Relic's all-in-one observability platform makes it simple to optimize your performance by giving you a single source of truth to analyze your apps, infrastructure, and all of your Azure services. Glenn Thomas from New Relic joins Scott Hanselman to talk about Azure's Native New Relic Service in Azure. Glenn demos how easy it is to get started with New Relic and manage Azure resources directly in the Azure portal. In addition, he provides an overview of how New Relic can help quickly identify and troubleshoot performance issues, including a look at Ask AI in New Relic Observability. Chapters 00:00 - Introduction 00:53 - Getting started from Azure Marketplace 02:27 - Exploring a new service 03:10 - Installing New Relic extension in a VM 04:05 - Accessing your New Relic service with SSO 04:47 - Troubleshooting scenario walkthrough with AI analysis 11:23 - Ask AI in New Relic 14:00 - Wrap-up Recommended resources New Relic's Azure Native Solution on the Azure Marketplace Azure Native New Relic Service Introduction New Relic AI New Relic Errors Inbox New Relic Distributed Tracing Azure Native New Relic Service: Full stack observability in minutes Create a Pay-as-You-Go account (Azure) Create a free account (Azure) Connect Scott Hanselman | Twitter/X: @SHanselman Azure Friday | Twitter/X: @AzureFriday New Relic | Twitter/X: @NewRelic Azure Support | Twitter/X: @AzureSupport

New Relic's all-in-one observability platform makes it simple to optimize your performance by giving you a single source of truth to analyze your apps, infrastructure, and all of your Azure services. Glenn Thomas from New Relic joins Scott Hanselman to talk about Azure's Native New Relic Service in Azure. Glenn demos how easy it is to get started with New Relic and manage Azure resources directly in the Azure portal. In addition, he provides an overview of how New Relic can help quickly identify and troubleshoot performance issues, including a look at Ask AI in New Relic Observability. Chapters 00:00 - Introduction 00:53 - Getting started from Azure Marketplace 02:27 - Exploring a new service 03:10 - Installing New Relic extension in a VM 04:05 - Accessing your New Relic service with SSO 04:47 - Troubleshooting scenario walkthrough with AI analysis 11:23 - Ask AI in New Relic 14:00 - Wrap-up Recommended resources New Relic's Azure Native Solution on the Azure Marketplace Azure Native New Relic Service Introduction New Relic AI New Relic Errors Inbox New Relic Distributed Tracing Azure Native New Relic Service: Full stack observability in minutes Create a Pay-as-You-Go account (Azure) Create a free account (Azure) Connect Scott Hanselman | Twitter/X: @SHanselman Azure Friday | Twitter/X: @AzureFriday New Relic | Twitter/X: @NewRelic Azure Support | Twitter/X: @AzureSupport

New Relic's all-in-one observability platform makes it simple to optimize your performance by giving you a single source of truth to analyze your apps, infrastructure, and all of your Azure services. Glenn Thomas from New Relic joins Scott Hanselman to talk about Azure's Native New Relic Service in Azure. Glenn demos how easy it is to get started with New Relic and manage Azure resources directly in the Azure portal. In addition, he provides an overview of how New Relic can help quickly identify and troubleshoot performance issues, including a look at Ask AI in New Relic Observability. Chapters 00:00 - Introduction 00:53 - Getting started from Azure Marketplace 02:27 - Exploring a new service 03:10 - Installing New Relic extension in a VM 04:05 - Accessing your New Relic service with SSO 04:47 - Troubleshooting scenario walkthrough with AI analysis 11:23 - Ask AI in New Relic 14:00 - Wrap-up Recommended resources New Relic's Azure Native Solution on the Azure Marketplace Azure Native New Relic Service Introduction New Relic AI New Relic Errors Inbox New Relic Distributed Tracing Azure Native New Relic Service: Full stack observability in minutes Create a Pay-as-You-Go account (Azure) Create a free account (Azure) Connect Scott Hanselman | Twitter/X: @SHanselman Azure Friday | Twitter/X: @AzureFriday New Relic | Twitter/X: @NewRelic Azure Support | Twitter/X: @AzureSupport

New Relic's all-in-one observability platform makes it simple to optimize your performance by giving you a single source of truth to analyze your apps, infrastructure, and all of your Azure services. Glenn Thomas from New Relic joins Scott Hanselman to talk about Azure's Native New Relic Service in Azure. Glenn demos how easy it is to get started with New Relic and manage Azure resources directly in the Azure portal. In addition, he provides an overview of how New Relic can help quickly identify and troubleshoot performance issues, including a look at Ask AI in New Relic Observability. Chapters 00:00 - Introduction 00:53 - Getting started from Azure Marketplace 02:27 - Exploring a new service 03:10 - Installing New Relic extension in a VM 04:05 - Accessing your New Relic service with SSO 04:47 - Troubleshooting scenario walkthrough with AI analysis 11:23 - Ask AI in New Relic 14:00 - Wrap-up Recommended resources New Relic's Azure Native Solution on the Azure Marketplace Azure Native New Relic Service Introduction New Relic AI New Relic Errors Inbox New Relic Distributed Tracing Azure Native New Relic Service: Full stack observability in minutes Create a Pay-as-You-Go account (Azure) Create a free account (Azure) Connect Scott Hanselman | Twitter/X: @SHanselman Azure Friday | Twitter/X: @AzureFriday New Relic | Twitter/X: @NewRelic Azure Support | Twitter/X: @AzureSupport

Tanguy Crusson is the product lead for Jira Product Discovery at Atlassian. In his more than 10 years at the company, he has been instrumental in taking several new products from zero to one, including HipChat, Statuspage, and Jira Product Discovery. In this episode, we dive deep into the struggles of innovating and building new products inside a large company. Tanguy shares candid stories about what worked, what didn't, and his many hard-won lessons learned about how to successfully build 0 to 1. We cover:• Why large companies with so many advantages still fail at creating new products• Lessons learned from building HipChat• How to avoid common pitfalls like competitive myopia and premature scaling• Lessons learned from the acquisition and integration of Statuspage• Insights from the success of Jira Product Discovery• Tactics for protecting your “ugly babies”• The power of “lighthouse users”• The importance of having a “why now”• Much more—Brought to you by:• Vanta—Automate compliance. Simplify security• WorkOS—Modern identity platform for B2B SaaS, free up to 1 million MAUs• Coda—The all-in-one collaborative workspace—Find the transcript at: https://www.lennysnewsletter.com/p/building-0-to-1-inside-atlassian-tanguy-crusson—Where to find Tanguy Crusson:• X: https://x.com/tanguycrusson• LinkedIn: https://www.linkedin.com/in/tanguy-crusson-99832a—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Tanguy's background(02:30) Tanguy's journey at Atlassian(07:03) The challenges of innovating in large companies(10:42) Atlassian's high bar for excellence (12:58) The HipChat story: successes, failures, and lessons learned(20:47) Lessons learned from building HipChat(33:49) Statuspage: a journey of perseverance(39:48) Acquisition challenges and lessons(47:22) Strategic decisions: build, buy, or partner?(48:17) Learning to articulate "why now"(54:08) A quick summary of lessons in this episode(55:40) The success and pain of launching Jira Product Discovery (58:10) Incubating new products: the Point A program(01:00:13) Failure is the most likely outcome(01:04:15) Atlassian's four-phase approach to launching new products(01:09:20) Breaking rules without breaking trust(01:16:16) Early success and team autonomy(01:17:22) Innovating without disrupting existing customers(01:23:17) The Lighthouse Users program(01:30:00) Protecting and nurturing new ideas(01:36:14) Balancing innovation with personal well-being(01:38:17) A reminder to look after yourself(01:42:06) Lightning round—Referenced:• Atlassian: https://www.atlassian.com/• HipChat: https://community.atlassian.com/t5/Hipchat/ct-p/hipchat• Stride: https://community.atlassian.com/t5/Stride/ct-p/stride• Statuspage: https://www.atlassian.com/software/statuspage• Opsgenie: https://www.atlassian.com/software/opsgenie• Jira Product Discovery: https://www.atlassian.com/software/jira/product-discovery• HipChat billboard: https://x.com/HubSpot/status/654696998126272512• Announcing our new partnership with Slack: https://www.atlassian.com/blog/announcements/new-atlassian-slack-partnership• Slack shows it's worried about Microsoft Teams with a full-page newspaper ad: https://www.theverge.com/2016/11/2/13497766/slack-microsoft-teams-new-york-times-ad• What Is ‘Dogfooding'?: https://www.nytimes.com/2022/11/14/business/dogfooding.html• Jira: https://www.atlassian.com/software/jira• Confluence: https://www.atlassian.com/software/confluence• PagerDuty: https://www.pagerduty.com/• New Relic: https://newrelic.com/• BigPanda: https://www.bigpanda.io/• Transparent Uptime: http://www.transparentuptime.com/• Vision, conviction, and hype: How to build 0 to 1 inside a company | Mihika Kapoor (Product at Figma): https://www.lennysnewsletter.com/p/vision-conviction-hype-mihika-kapoor• Figma: https://www.figma.com/• Lessons from Atlassian: Launching new products, getting buy-in, and staying ahead of the competition | Megan Cook (head of product, Jira): https://www.lennysnewsletter.com/p/lessons-from-atlassian-launching• Noah Weiss on LinkedIn: https://www.linkedin.com/in/noahw/• Tanguy's LinkedIn post about “lighthouse users”: https://www.linkedin.com/posts/tanguy-crusson-99832a_lighthouse-users-one-of-the-pm-techniques-activity-7176654510801502210-hWNi/• Pixar Chief: Protect Your ‘Ugly Babies' (Your Unsightly Ideas): https://www.forbes.com/sites/andyboynton/2014/03/17/pixar-chief-protect-your-ugly-babies-your-unsightly-ideas/• Atlas: https://www.atlassian.com/software/atlas• Point A: https://www.atlassian.com/point-a• Scott Farquhar on LinkedIn: https://www.linkedin.com/in/scottfarquhar• Who: A Method for Hiring: https://www.amazon.com/Who-Method-Hiring-HC-2008/dp/B004C79SRS/• Hakim's Odyssey: Book 1: From Syria to Turkey: https://www.amazon.com/Hakims-Odyssey-Book-Syria-Turkey/dp/1637790007• Living with the Earth, Volume 1: Permaculture, Ecoculture: Inspired by Nature: https://www.amazon.com/Living-Earth-Gardeners-Permaculture-Ecoculture/dp/1856232603/• INRIA: https://en.wikipedia.org/wiki/French_Institute_for_Research_in_Computer_Science_and_Automation• How a Hydrofoil Works: https://web.mit.edu/2.972/www/reports/hydrofoil/hydrofoil.html• What Is Kitefoil or Foilboarding?: https://www.whenitswindy.com/wp/?page_id=534• Freediving: https://en.wikipedia.org/wiki/Freediving• Tanguy's freediving stats: https://www.aidainternational.org/Athletes/Profile-00000000-0000-0000-0000-000000000a45• Perplexity: https://www.perplexity.com/—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. Get full access to Lenny's Newsletter at www.lennysnewsletter.com/subscribe

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