 Docker is really good at you know providing you a standardized way to deploy your applications but it's quite another thing to understand if your applications are working the way that you would expect them to. Hi this is Sagan Bhatia and I want to take a quick moment to thank our sponsors who make the show not only possible but also a lot of fun. Being a sponsor of the show has its own benefits including but not limited to appearing on the show itself. So if you want to become a sponsor please check the details we have posted below and now let's go ahead and enjoy the show. Hi this is Sagan Bhatia and we are here at DockerCon in San Francisco today we have with us Rajesh from SignalFX. Can you tell us a bit about SignalFX what does the company do? Sure so SignalFX is a metrics based monitoring system we think of ourselves as an operational intelligence platform for people to understand their cloud infrastructure and cloud deployment. So this can be you know whether it's the infrastructure metrics themselves which might be coming from you know public cloud infrastructure like AWS or GCP or Azure but it's also their applications the services that they're deployed on those cloud environments and also perhaps even lambdas and you know serverless infrastructure. So we have a standard way of getting all these metrics and helping people understand how their environments are working. You have touched upon a lot of things already you know before we dive deep. So what is the need for monitoring in this kind of setup where you are doing everything by just clicking a button? So deployment is of course one aspect of it so Docker is is really good at you know providing your standardized way to deploy your applications but it's quite another thing to understand if your applications are working the way that you would expect them to. At the very least you'd need to know whether your infrastructure is performing the way it is that might be as simple as looking at CPU usage and memory usage but if your application is more complicated if it's performing some sort of workload or using third party open source systems you need to actually instrument what's interesting or important to you. You cannot really understand or you cannot really improve things that you don't measure. So the quantities that actually represent the performance or the working of your application are things that you want to kind of play a close eye to. So you want to get those metrics send it to a system like SignalFX and we'll help you visualize them perform analytics on them do anomaly detection let you know if things are working good or not. So that's kind of the value that SignalFX brings. You focus only on Docker containers or you're talking about cloud native words in general? So we are basically focused on the entire spectrum of cloud native infrastructure. Docker is of course one of the platforms that we do support but it can even be serverless like lambdas. There can even be applications that you're running. So we are basically we're happy to take metrics from anywhere. Okay so when you do talk about serverless that kind of changes the equation because you know you're talking about no function which are triggered by certain events you know so you don't have the same level of you know either access of control that you have in other space. So how does the whole equation changes you know of monitoring in the serverless space versus. So there are like two kind of you can decompose the problem into two parts. So one is like how do you grab the metrics how do you actually instrument what you need to do to get the information that you need. That is what primarily changes in the serverless world because you don't have a node that you can deploy a heavy weight agent to get these metrics from. So you need some APIs and you need some infrastructure to help you to get those metrics. So we of course provide some help for people to do that but once the metrics actually get to us from SignalFX perspective we are happy to get metrics and time series from anywhere and we are actually agnostic about where these metrics come from how they are measured and what they represent. So we provide a platform for you to then to perform analytics on it as a general purpose thing. So we help on both sides of it but to us the main solution as a platform we are agnostic about where those metrics come from and Lambda is just yet another form factor that we support. What are the concerns in the serverless space? So I think the concerns are so one is that there are some infrastructure kind of concerns with lambdas which is you want to know things like cold starts like how many cold starts are happening in the lambdas and this is something that Amazon does not actually give you a lot of insight about and then you want to know on each lambda invocation like what's the performance on and in single call like how long does that take. So that's something that we can give you almost like out of the bag without you having to do very much to instrument your own application but in addition you might go want to like change the code in your application and instrument the things that are important to you like how's it taking you know what are you doing in this specific action you might be doing two or three different things maybe looking up a cache putting something here or there and you want to instrument those metrics as well so that when you look at it and aggregate across all your lambda invocations not only do you want to know how many cold starts there are what's the average time for each lambda invocation but on the application of the lambda invocation itself like did you throw any errors you know what kind of work did you do what kind of metrics did you gather and so we kind of like gather both of that and let you visualize them again you can do a nominal detection on this and the other thing about lambdas is that people are very sensitive about the latency of how quickly you can make these measurements and how quickly you can provide intelligence or monitoring on this and that's something that signal effects is very good at like we are known for real-time streaming analytics so within you know a couple of seconds of something happening you immediately see that in a dashboard or you can have anomalies detected when you know lambdas can last for only a few seconds sometimes and so for something to be known like few minutes after it happened like does not provide enough value so that's one of the key strengths of signal effects is to provide real-time intelligence and since you are already doing with customers who are I mean you are in it next case you know you're talking monitoring so what kind of adoption is there for serverless already because very very new buzzword yeah yes we are actually seeing pretty good adoption I think it depends more on the company and where they are on their cloud native journey so we think of people having you know starting from somewhat an experimental phase where the company as a whole is using somewhat legacy IT but they might have a few labs or trying to experiment and see what should their next generation architecture look like and then there's kind of like companies that are in the middle phase that we call like somewhat decentralized chaos where you have different parts of the company they each want to find a tool chain that works for them so each team might be doing something different and then finally you have the teams that are thinking very strategically about deploying what kinds of architectures do they need what kind of tooling what kind of monitoring and so those guys we provide what we call organized enablement and so we help companies in each of these three stages of their of their kind of growth and their life cycle and different companies are thinking in slightly different ways about how they want to deploy these architectures but we are definitely seeing the companies who have gone through this journey and are seeing the value of kind of like lambdas lambdas of course not applicable to every single workload but there are a broad kind of class of workloads where lambdas provide a lot of value and and we are seeing pretty strong adoption for those kinds of workloads so we have like you know jump from one topic to the topic because so much is already happening but one thing that you did mention was matrix and i i did feel that you know you do want to you know talk about can you explain you know elaborate you know so there are a few different pillars to the whole monitoring and observability space you know there is like kind of like logs now traces is becoming a little bit hard uh matrix we believe plays an important role and then there are some structured event type uh solutions so uh matrix is something that is actually going to play an increasing role in this entire monitoring landscape because as we see as these platforms kind of like change your deployment models change the one thing that's common actually across all of them is like the concept of having to make measurements and do kind of like real-time streaming analytics on it and these measurements like there may be infrastructure type measurements like if they if you have a more traditional deployment but as you move to serverless these metrics are more like workload measurements of what your application is actually doing and so there can be very high level things like like how many transactions are you processing or you know if you're looking up a cash how many cash hits are you seeing how many cash misses are you seeing how many exceptions are seeing so these are the things that for a developer coming from a DevOps mindset character really characterize the health of your application it's not whether CPU higher is low because that may be normal that it's a little bit high maybe you're utilizing your resources very well but for people to think strategically about what are the quantities that I should measure that I should measure that really characterize whether my application or my infrastructure is working well or not and you get more and more into this what we call custom metrics ecosystem where people are measuring things that kind of bridge between operational and business metrics that really tell you okay is your service doing what it's supposed to be doing right so we talked about technology we talked about monitoring and all those things let's talk about Hugo bit no so when you're not doing all these tech stuff what do you do in your free time so I of course have two kids I have a dog that keeps me busy my hobby is playing guitar actually really yeah oh so okay that's interesting so when do you pick the hobby of playing guitar oh I've played it for a really long time I should be awesome but I don't practice as much so did you learn guitar to impress somebody or just for yourself uh because usually people learn guitar for a certain reason yeah I have a theory that people continue to play guitar for their own reasons but they all start playing guitar for the same reason uh-huh so I started playing guitar in high school you can imagine okay and uh and uh you still play right I still play yes so how much you have progressed you know have you progressed very you know if there is a next year there's a keynote and they need a band can you be on the stage well actually I recently switched to classical guitar which is a little bit different uh-huh but I'm really enjoying it it's very challenging it's much more theoretical it's much more you know you really have to pick up on your technique so it's a very different ball game to me I used to play a lot more rock before and that's kind of like more fun more gig kind of music but it's different now and I don't have enough time to dedicate to playing in a band but I do practice by myself so if I'm not wrong you know as a technologist you also travel a lot right sometimes yeah okay so how do you keep up with your guitar practices and the tech uh to be honest I don't keep up very well with what tech or guitar with guitar okay so do you wish there was something portable which you can just carry with you all the time yeah I they do have some traveling guitar type things uh but it's still you know some amount of infrastructure that you have to lug around so all right right uh anything else beyond beyond guitar kits and dogs uh no I think that's where most of my time goes it's with uh either spending time with the family working and uh yeah just keeping afloat as it was awesome awesome in the next video maybe we'll try to have a you know a uh demo of your guitar practice sure thank you why not and here I just thanks for talking to me thank you so much and hopefully we'll catch up with you again in the next event that'll be great thank you