 Hi, this is your host Tamil Bhartia and welcome to our yearly Predictions video series. Today we have with us once again, Dvitan Oravits, Principal Developer Advocate and Cloud Native Ambassador at LogZio. Dvitan is going to have it back on the show. Glad to be here again. So thank you for inviting me. Yeah, it's my pleasure. Of course, I'm going to ask you to grab your crystal ball and share some predictions with us. But before that, just tell us a bit about the company. What do you folks do? LogZio provides a cloud native observability platform that's based on the best of breed open source out there. So Prometheus, Jega, Open Telemetry, Open Search and so on, and gives it in a managed and scalable fashion and cost effective fashion. That's in a nutshell. Now it's time for you to pick up your crystal ball and share your predictions with us. Maybe we should start with Open Telemetry. I've been involved with this open source project for quite a few years under the CNCF, the Cloud Native Computing Foundation, also in my capacity as a CNCF ambassador. And it's a significant element in the in the observability space. So starting there, we've seen a major milestone this year that we've reached the general availability of all the three pillars of observability, so logs being the latest and obviously joining metrics and traces. And now that we see this reaching general availability, I do expect to see the next step is that increased adoption among the end users, as well as the observability vendors themselves. So pushing out the proprietary and open source telemetry shippers and converging around this. So this is going to be a very interesting trend to see more deployments of open telemetry in GA in production. And obviously beyond that, beyond the logs, metrics and traces, we're going to go pass that to new signals. Now the focus is going to move into continuous profiling as yet another critical element within observability. And lastly, but very, very importantly is the productization. So I do see a lot of effort that we're going to put on making it production grade, so that you have a means to deploy, to configure, to monitor the the observability open telemetry at scale in production. So these are the main areas that we're going to see to make it more, also the instrumentation parts, ease of operation, stability, performance, these are going to be the focus. That's on open telemetry. And now looking on the broader observability scheme, I think that we've been struggling with the tool sprawl and the data silos. But this is definitely going to be a main challenge also and main focus for next year. We're going to see moving up the stack and going into focus on the data analytics backend. So instead of just collecting these logs, metrics and traces that I mentioned before, is going to actually look at the insights and how we draw insights into these vast amounts of data and making more focus on the data analytics backend, on data analytics paradigm shift, as I call it, and also in utilizing AI and machine learning to draw these insights out of the data. This is going to be very much a focus in 2024. And looking beyond that into the broader DevOps space, we've seen a lot of hype around platform engineering this year. What I expect for next year is actually to for the hype going beyond the hype and into actually implementing that in a production grade manner. So we already seen the new the seeds of the hyperscalers that have already implemented that at scale. And the started sharing their knowledge with the community. And what I foresee is that we can actually take this aggregated knowledge and actually implement it, especially the cultural change within the company, instilling this collaboration between a central platform engineering team and the distributed DevOps and product engineering teams to be able to avoid making it yet another silo. And I actually make it work in scale and across medium and small organizations as well, not just the large enterprises. What kind of challenges you see will be there in 2024, not just for the industry's ecosystem and even for LogZio to handle and tackle for users? I think one of the big things that we see is the need for organizational change to make sure I talked about platform engineering. So platform engineering, my concern is that it will become yet another organizational silo. And this is something that we need to be very mind focused on as an industry and as a community in general. And this will require a lot of adopting new culture. It's a bit of a maybe it can ring a bell from the days of DevOps that you and I remember, but maybe even a higher scale being able to make this central versus distributed DevOps versus the platform engineering versus the product engineering teams. This is something that has been quite challenging this year. And as we grow the adoption of platform engineering, I expect this to be definitely a challenge. This is one and another challenge that I see, especially in the current economic climate, I'll definitely see a lot of increased pressure on optimizing the IT costs. And that has a lot of aspects to it. There's the tool sprawl that I mentioned that a lot of organizations are looking to consolidate and find one tool to aggregate as much as possible under it. We're talking about the bloat of data. We heard a lot of high profile stories this year about costs of observability, for instance. So this is going to be a challenge. The big data challenge is now arriving to the operational side of the house. And also the complex cloud billing schemes. We just saw a few weeks ago, recently, sorry, at the end of 2023, we've seen with the Phenops Foundation the release of Focus, which is a new specification for cloud billing. And this is a step in the right direction that I expect to see accelerating into 2024. And this year, where we as an industry try to create better Phenops observability and control into our systems across cloud and cloud native systems. So these are the main challenges that I think we as an industry are going to face in this domain in 2024. And looking at these challenges, and of course opportunity, what do you see is going to be the focus for Log XIO? We at Log XIO are definitely going to focus on the unified observability experience. This is something that we've been hearing a lot of the growing demand around, both from a cost perspective and from efficiency perspective and the need for consolidation. So a lot of effort is going to be on a unified experience, more advanced and intuitive user experience and moving beyond the individual siloed interfaces. So we've been offering Yeager as an interface and the open search interface and Prometheus interface and so on. But our users actually expect also to have the higher tier that will consolidate all of these together. Something that does not exist, obviously, out there with the discrete open source projects. So this is going to be a fascinating journey that we've already started with Kubernetes 360 and the app 360 that we released. Another aspect is the AI assistance. As I mentioned, AI and machine learning is a way to surface issues in your system. It's something that is going to be a main focus, the ability to work on integration with generative AI to be able to express in natural language and get also input in natural language. So expressing queries in natural language instead of a specific Lucene on PromQL or something like that, the ability to get insights on what goes on in the system. Lots of effort is going to be around the AI. And the last part is about, I mentioned about the fact that we as an industry are going up the stack as in observability. There's a lot of convergence with APM application performance monitoring. We're going to double down on this. We're going to put a lot of focus on application observability that gives the essential capabilities that we grown used to in traditional maybe monolithic pre-cloud native era with APM, but in a cloud native fashion, in a lean fashion, and maybe less heavyweight one as part of LogzIO's Open 360 platform. Dothan, thank you so much for taking time out today and share these predictions with us. Of course, I would love to have you back on the show again next year to not only see how many of your predictions turn out to be true, but also to get this next set of predictions. Thank you so much. And I look forward to talking to you again soon. Thank you. Thank you so much for having me.