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[180.50 --> 187.98] 3.75. And again, it was one of my favorites. That was almost two years ago. I know that a lot of |
[187.98 --> 193.86] things have changed. First of all, Grafana was at version 6 back then. Now it's at version 8, |
[194.10 --> 198.70] which was a massive improvement from version 7, which was a massive improvement from version 6. |
[199.58 --> 204.14] What other things changed in the last two years, almost two years since we spoke? |
[204.38 --> 208.68] Oh, wow. Yeah. I mean, two years. How do we cover two years in five minutes? |
[208.68 --> 215.40] I think working backwards, we've launched Tempo, the tracing system from Grafana Labs, which is |
[215.40 --> 222.02] kind of cool. Slightly different take on distributed tracing, focusing on very efficient storage of the |
[222.02 --> 228.12] traces itself and very, very scalable. We've done Loki 2.0, our log aggregation systems, |
[228.64 --> 232.96] over two years old now. And with Loki 2.0 came a much more sophisticated query language. |
[232.96 --> 238.16] That's really cool because now you can start to use Loki and anger and really kind of |
[238.16 --> 243.52] extract metrics and really dig into your logs with it. That was a really exciting design process |
[243.52 --> 248.56] for the language as well, because we always wanted it to be really heavily inspired by Prometheus, |
[248.82 --> 253.24] but it's logs in the end. It's different to time series. So we actually collaborated with |
[253.24 --> 258.98] Frederick from the Prometheus team. And he really influenced the design. I remember one of the calls, |
[258.98 --> 264.32] we came up with one of the things that I think makes LogQL really cool, which is you've got the |
[264.32 --> 269.88] pipeline operator for filtering logs. So you use pipelines to filter your logs. And we kind of stuck |
[269.88 --> 274.08] with that for everything in the log space. And then the minute you start working with metrics, |
[274.36 --> 278.54] you start using brackets and it looks like PromQL, like the Prometheus query language. |
[278.84 --> 282.68] And it just means you look at a query and it's really obvious that that part of the query deals |
[282.68 --> 287.68] with logs and that part of the query deals with metrics. Working backwards more exemplars in Prometheus |
[287.68 --> 292.66] and in Grafana. So you can link from metrics to traces. You put little dots on the graphs and |
[292.66 --> 296.24] the dots indicate a trace and you can click on it. And that whole kind of experience works. |
[296.66 --> 302.74] And you bring up KubeCon 2019, right? I think that was the year Frederick and I gave a keynote address |
[302.74 --> 311.36] on the future of observability. And in that keynote, we predicted that linking metrics and logs and |
[311.36 --> 316.52] traces and correlating and building experiences that combine them would be the future. Now, of course, |
[316.52 --> 321.22] it's like a bit tongue in cheek because I have the great opportunity and I'm very lucky to be able |
[321.22 --> 325.72] to influence what we do at Grafana Labs. So, you know, we've kind of spent the last two years making |
[325.72 --> 331.78] that keynote happen and making it possible to combine those metrics and logs and traces in a |
[331.78 --> 335.12] single development experience, in a single on-call kind of instant response. |
[335.66 --> 340.96] I could go on. Like there's so many things that have changed, right? We've grown hugely at Grafana Labs. |
[340.96 --> 348.18] We're now over 400 people, which is just like I joined when we were about 25, 26 people three and |
[348.18 --> 354.68] a half years ago. So we launched a GEM, Grafana Enterprise Metrics, which is our kind of self-managed |
[354.68 --> 360.38] enterprise version of Cortex, the scalable version of Prometheus, the other CNCF project. |
[360.74 --> 364.60] Yeah, there's so many. And I'm really still only talking about kind of the second half of last year. |
[364.60 --> 368.88] And I guess, you know, when you ask that question, everyone always responds with pandemic as well. |
[369.26 --> 373.28] I kind of glossed over that, but we had a global pandemic. I think what's really interesting, |
[373.34 --> 378.80] obviously, is huge impact, but Grafana Labs was set up from day zero to be remote first. |
[379.44 --> 384.66] And so I think we've been super lucky that the impact has been less than it has been on other |
[384.66 --> 389.08] organizations. Yeah, like I could go into any more of those, but I'll stop there. |
[389.08 --> 393.70] Yeah. I think I remember that the future of observability keynote that you gave, |
[393.94 --> 399.86] that was a really good one, inspirational one. And I could see it. I could see it just as like |
[399.86 --> 405.78] the vision that you shared. And I remember thinking, wow, if they pull it off, this is going |
[405.78 --> 410.28] to be amazing. And guess what? You did. And even more so. |
[410.34 --> 413.34] I can't take all the credit, right? Like we did, I did the keynote with Frederick. |
[413.54 --> 417.70] When I say you, I mean Grafana Labs, like, you know, the whole org, right? |
[417.70 --> 422.96] That you're part of the whole team that you're part of. But you like, you know, you were there, |
[423.44 --> 427.90] you had this vision, you shared it. I'm sure everybody contributed to it. And then everybody |
[427.90 --> 434.12] made it happen. And I really love that journey, seeing how things have been happening with Loki. |
[434.20 --> 440.32] I remember when Loki version one came out and I thought, wow, this makes so much sense. I was so |
[440.32 --> 445.14] keen to start using it. And we did, even for changelog. We used Grafana for a long time, |
[445.14 --> 451.32] Prometheus. Then we went to Loki and that was great. And then we thought, hmm, if only we could |
[451.32 --> 456.84] delegate this problem to someone else. And guess what? Grafana Cloud came along, the hosted managed |
[456.84 --> 462.32] service. You had some very generous tiers. Once that changed, everything changed. So all of a sudden, |
[462.38 --> 465.88] we no longer had to run our own Grafana and Prometheus. Not that it was difficult, |
[465.88 --> 472.94] but it's much easier to just run the Grafana agent. That's all you need. Send everything to |
[472.94 --> 479.80] Grafana Cloud and it just works. And with the last changes of the alerts, like I think that was the |
[479.80 --> 484.72] weak point of Grafana for a long, long time. And now you saw that as well. So there are all these |
[484.72 --> 490.98] things just falling into place naturally and being able to know what's coming and seeing it happening |
[490.98 --> 496.30] every six months, right? There's like more and more and more. It's like, we know what to expect. |
[496.76 --> 499.86] You're delivering. Please carry on. That's what I'm thinking. |
[500.54 --> 504.52] Thank you very much. Yeah. You know, I miss so much out of my what's happened because yeah, |
[504.66 --> 511.42] unified alerting is a huge step in the Grafana story. I'm really pleased as the way the company |
[511.42 --> 515.22] came together. We used to have two alerting systems, right? We had the Grafana alerting system |
[515.22 --> 519.06] and the Prometheus alerting system. And they were worlds apart. You know, on one hand, |
[519.06 --> 523.22] the Grafana alerting system is probably the easiest one that exists out there, right? It's very |
[523.22 --> 527.50] accessible, very easy to get started with. And on the other hand, the Prometheus system is probably |
[527.50 --> 532.20] one of the most sophisticated and powerful ones. And so I think it was really exciting, right? How |
[532.20 --> 537.64] the team could combine the power of the Prometheus system, right? With multi-dimensional alerts, |
[538.22 --> 543.66] with alert managers, routing, grouping, and deduping, and silencing, and bundle all these features |
[543.66 --> 549.52] into Grafana in a way that makes them easy to use and gives you that level of user experience |
[549.52 --> 554.66] that people have come to expect. And best of all, like we haven't duplicated any features, |
[554.72 --> 559.08] right? We're just using Alert Manager under the hood. We're using the same API as Prometheus |
[559.08 --> 564.38] under the hood. So it's true to our open source routes as well. And that's like, the team did a |
[564.38 --> 569.98] fantastic job with unified alerting. I think the thing you say about cloud, right? The generous free |
[569.98 --> 574.40] tier, for instance, we launched that in January, I think. We've always had a kind of free tier. |
[574.66 --> 579.62] We've always allowed you to have a free Grafana instance, for instance. The work that goes into |
[579.62 --> 584.32] actually being able to offer a free tier, there's so much going on behind the scenes, |
[584.38 --> 588.86] right? Just at a very architectural level. The point I'd always make here is that |
[588.86 --> 595.80] you need the marginal cost of a new Prometheus instance, or of a new Loki instance, or a new |
[595.80 --> 599.96] Tempo instance. You need it to be effectively zero, right? You can't offer a free tier unless |
[599.96 --> 604.38] the cost of the thing you're offering is as close to zero as possible. So this means |
[604.38 --> 609.00] behind the scenes, right? We can't be spinning up a new Prometheus pod, or a new Loki pod, |
[609.10 --> 613.80] or a new Grafana pod, or a new Tempo pod for every customer that signs up, right? That would |
[613.80 --> 619.54] get too expensive for us to offer it. We're not that big a company yet. And so fundamentally, |
[619.68 --> 623.52] the architecture of all of these systems has to be multi-tenanted, right? And we've built, |
[623.86 --> 626.62] and this is where Cortex comes in, right? We've built this horizontally scalable, |
[626.62 --> 632.40] multi-tenant version of Prometheus, which means provisioning a new instance in that multi-tenant |
[632.40 --> 636.56] cluster is basically free. It doesn't really cost us anything. I mean, once you start sending |
[636.56 --> 641.26] metrics, there's some cost incurred, but because it's multi-tenanted, we can start to take advantage |
[641.26 --> 645.82] of kind of statistical multiplexing techniques and really get to a point and really drive down |
[645.82 --> 649.82] the cost of offering that service, which allows us to make the free tier so generous. |
[649.82 --> 655.68] And that architecture has been replicated in Loki. Well, not replicated. It uses the same code. |
[655.76 --> 660.52] It uses the same module system, the same ring, the same architecture, and the same techniques |
[660.52 --> 668.22] in Loki and in Tempo. And that consistency across the offerings just also carries over to the kind |
[668.22 --> 672.80] of operational and cognitive burden of running this because it's the same, because you scale it in |
[672.80 --> 677.70] the same way and you do instant response in the same way. So yeah, it's incredibly exciting to |
[677.70 --> 683.60] finally feel like you're in the last mile of delivering on a vision that's been in progress |
[683.60 --> 688.00] for kind of five or six years. So everything that you've said makes a lot of sense to me, |
[688.16 --> 694.90] but I know that many people will be confused because you are VP of product. How on earth does a VP of |
[694.90 --> 700.90] product know so many things about code and how things actually work? And I know that you're one of |
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