 From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. The rapid awareness and adoption of AI has increased concerns around security governance, compliance, and business risk. The digital business imperative to improve customer experience, combined with a vastly more complex technology environment, comprising multiple clouds. You now have IoT in there, containers, application integration, and the popularity of open source software are driving the need for better observability across technology stacks. But fragmented IT environments, lack of talent and a spate of existing installed monitoring tools are preventing organizations from achieving their full stack observability aspirations. Hello and welcome to this week's theCUBE Research Insights powered by ETR. In this Breaking Analysis, we dig deeper into the trends and observability based on a recent custom study from our partners at Enterprise Technology Research. And as always, we're going to provide our perspective on the market, the trends, players, with a view toward things to watch in 2024. Let's start with a look at what is full stack observability and why the heck did they call it Ali-O11Y? We'll explain. Full stack observability is the capability to discover the real time status of each technology stack component within a distributed IT environment. It involves holistically viewing cloud hosted applications, services, infrastructure on-prem IT, Kubernetes or K8s, there's your hint on Ali. Ali uses telemetry data like metrics, logs, traces, other information from the entire IT environment to provide complete end-to-end visibility to understand the connection and dependencies between all these IT components. Now, full stack observability is more than just monitoring and reporting. It uses reasoning and often machine intelligence to draw conclusions about an environment to either recommend or even change and take action, recommend change or take action on behalf of humans. And oh yeah, Ali-O11Y, whatever you wanna call it. Look, observability has an O, it's got 11 letters in between the O and the Y, hence Ali, like K8s, our industry. Anyway, FSO or Ali has been a hot topic in the press and analyst community. That's why we're so excited to share the results of a recent study from ETR. ETR is an amazing custom research capability that we're privileged to share with you. This particular study was done in partnership with New Relic who we promise has zero influence on the commentary and conclusions of this breaking analysis or the ETR analysis. This particular study had 1,700 respondents and unlike most of the work that we share had a global respondent base when U.S. customers only accounting for about a quarter of the survey. Normally, it's well over 60%. The companies spanned multiple industries, all organizational sizes, 80% or more or more. 80% of the respondents had more than 5,000 employees and it was mostly technology practitioners but a really healthy mix of management and executive management. Now, like security, observability is a crowded market. It's grown out of the world application performance monitoring, APM, network monitoring, log analytics, AI ops is in there, database performance management and monitoring, dashboarding, error tracking, literally dozens of legacy and fragmented market segments that are coming together with this new term, relatively new term of full stack observability. There are literally dozens and dozens and dozens of vendors in this space. Now, here's a sample. We're using network monitoring as the sector of choice in this space. Other is the leading vendor which underscores how crowded the market is but the likes of Splunk, Grafana, Dynatrace, Elastic, AppDynamics, which is owned by Cisco, open source tools like OpenTelemetry, Prometheus and the ElkStack. Of course, you've got New Relic in there, SumoLogic and many more play in this specific market. Now, on the right hand side of this chart, you can see the sectors that ETR tracked in the studies around 18, I think I counted, including distributed tracing, serverless monitoring, mobile monitoring where other is by far the dominant vendor, ML ops and so forth. So selecting each one in the pull downs, it shuffles the deck of the players. Splunk leads in most, but as a leader, everybody wants to attack them and get a piece of their market pie. That's why Cisco paid $28 billion for Splunk because Splunk, that is, has the largest footprint. But there are many, many others. For example, in application performance monitoring, Datadog, Dynatrace, AppD, which again is Cisco and New Relic, they join Splunk at the top of the list. In something like in the sector of synthetic monitoring, Dynatrace and Datadog pop up as the most popular, along with Splunk. In distributed tracing, Grafana, Dynatrace, the open source Prometheus and open telemetry are cited more often than Splunk. And others always prominent in this survey. So you get the point, FSO, it involves a lot of different capabilities and many, many vendors playing in the market. And for example, I'll give you some names in the other category that you may or may not be familiar with Lucidworks, Exabeam, Sentry, Moogsoft, Honeycomb. Chaos search, you could argue, was in there. Greylog, ScienceLogic, Cribble, Monte Carlo, Observe, InfluxData, dozens more than I could name. It's very crowded. Now, because the market is so fragmented and the budget pressures of 2022 and 2023, they've caused a lot of consolidation. This chart shows the number of observability tools installed in 2023 at the top as compared to 2022 at the bottom of this chart. And you can see the reduction in the percent of customers with five, six, seven and eight tools that's highlighted in the red. And then the shift up and the shift toward and over to one, two and three tools. So you shift up, you see the bars drop in those five, six, seven, eight and you look left and you see the increase in the number of one, two and three tools installed shown by those red arrows. But it's clear that the movement in the past year is just scratching the surface as around 60% of customers cite that they still have four or more tools. So a lot more work has to be done to accommodate greater consolidation. Now, because said that around 30% of customers in the survey lean toward having multiple tools as a means of tapping best of breed capabilities. So like security in a smaller, maybe less crowded market, the quest for excellence often results in fragmentation. Now when asked which vendor platforms customers prefer to consolidate on, around 13% say they don't want to consolidate but Splunk, Dynatrace and Datadog are most commonly cited. Once again, other is in the mix pretty prominently with Elastic, AppD and New Relic also showing. Now some interesting things change when you filter the data, for example, executive management prefers to consolidate on Dynatrace and surprisingly a somewhat higher percentage, 16%, say they don't want to consolidate, that's executive management. For what it's worth, the small percentage of females in the survey, they were about 17% of the total 1700 were females. They want to consolidate on AppDynamics, a company Cisco acquired in 2017. Services and consultancies prefer to consolidate on Datadog. So again, this just underscores the complexity and varied preferences in the market. Now another notable finding in the survey is the degree to which manual labor is still a dominant force. Despite all the AI hype, less than 10% of customers say their incident detection and remediation workflows in the future, so I think this chart looks at 24 months ahead, will be mostly AI led, but a huge percentage, having said that around 75% as shown in this chart, expect to have some type of AI led automation in their identification and remediation workflows. Now automation is a two-edged sword. It's one of those alluring concepts, but there's real caution around trusting machines to judge what action should and shouldn't be taken and when. So given the sensitive nature of change management, we would expect this trend to continue to lean toward AI led automation, but it's going to take some time before humans are mostly out of the loop. Moreover, while many vendors claim to have AI, there's a wide spectrum of capabilities and customers should be very cautious about vendor claims in this regard. Now, not surprisingly, the regulated industries of financial services, healthcare and government, when you do the filtering on those industries, you see a much lower tendency to be mostly AI led in this context over the next year. Well under 5% say mostly AI led in that previous chart, whereas industries like energy and high tech are much more likely to aggressively adopt AI in this space. Now, notably the data shows that senior managements are more likely to push for AI adoption, whereas the practitioners who literally have their jobs on the line, i.e. machines replacing humans, doing the work of humans until you lose your job or getting fired for implementing rogue automation. Those practitioners are much less likely to say that they are going to be mostly AI led. So what does full stack observability do for your business? Well, according to more than 1500 practitioners in this survey who answered this portion of the question, there are many benefits. Better uptime, approved efficiency, more secure environment, better customer experience. It helps developers be more productive because they're doing less troubleshooting, et cetera. And this ostensibly is going to lead to greater business agility as cited and more revenue as is also cited. Only one half of 1% cited no benefit from their observability stacks. This is across all rules, all geos, all industries by the way, but there are challenges to adopting full stack observability, including the siloed nature of data and IT, tools creep, lack of talent, but the number one pressure is lack of budget, i.e. perceived as too expensive. So the industry has to do a better job. It has an opportunity to better sell the benefits. Maybe perhaps retiring goofy terms like Oli would help. Okay, let's wrap with some things to watch for 2024. Security remains the number one priority in the ETR survey data it has for several years now. And that requires better visibility. So we don't expect full stack observability to be a fad that fades in 2024, just the opposite actually. As digital businesses fight for customers and access to real time, that access to real time data becomes more critical and full stack observabilities only grow, is only going to grow in prominence in our view. The latest ETR survey data on the spending macro, which we're going to unveil later on next month, is showing some positive momentum for 2024, but really toward the latter half, certainly not in Q1, maybe in Q2, but definitely more optimistic toward the latter part of the year. Adam Salipsky said it best when he shared at re-invented, we've seen better times, we've seen worse times, but we've never seen such uncertain times. True words of wisdom from the CEO of AWS. Look, everybody's AI crazed, including us, but your practitioners are cautious and probably skeptical that they have job security. So part of your challenge is to convince the doers in your business that AI will bring new opportunities and relieve them of mundane and tedious tasks. There are many examples and proof points of this, take RPA for example. And you'll have to also put in processes to make sure that automation doesn't create Bobo's, because with cloud and distributed computing, mistakes can travel very fast. A last point here is clearly the market generally in full stack observability, specifically is moving toward platforms, but the siloed nature of tech stacks, technical debt and sunk cost is going to mean a continued fragmented market that said those leaders with full stack capabilities, cloud native tooling and real true AI will be in a good position to ride the consolidation wave in 2024 and beyond. Okay, we're gonna leave it there for today. Thanks to Alex Morrison and Ken Schiffman on production and Alex Morrison who does our podcasts. We hit over 600,000 downloads this year. So thank you for listening and subscribing and downloading. Kristen Martin and Cheryl Knight help get the word out on social media and in our newsletters and Rob Holt is our editor in chief over at SiliconAngle.com. Does some wonderful editing. Thank you all. Hey, remember these episodes are all available as podcasts wherever you listen, just search breaking analysis podcast. I publish each week on thecuberesearch.com, formerly wikibon.com and siliconangle.com. You can email me davidotbalante at siliconangle.com or DM me at dbalante comment on our LinkedIn posts and please make sure you check out etr.ai. Every time I dig deeper, I'm more impressed. They get the best survey data in the enterprise tech business. Their data scientists are doing a great job and their custom work is off the charts amazing. This is Dave Vellante for the Cube Research Insights powered by ETR. Thanks for watching everybody and we'll see you next time on breaking analysis.