Digital sales automation for Government

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thank you very much for coming down guys my name is Govinda I'm a sales engineer for dynaTrace so the format is I'll go through initially a few slides to try and explain what it is that we're presenting this morning then I'll go through a demonstration of the product itself so what do we actually mean by accelerating innovation in government says you may be aware Minister Michael Keenan's announced that there will be a a digital government by 2025 what does it actually mean is it just uploading a bunch of documents into a PDF and expecting everything to be digital that's not really the future that we want to build right so that's where dynaTrace comes in people are starting to move into the cloud and if you are a public servant you've probably had some experience with cloud already where you've realized it's probably not as cheap as you thought it would be it's probably not as efficient as you thought it would be that's because most people tend to replicate the issues they've already had on Prem into the cloud how does Donna trace help we help you identify every single dependency they have within your data center and we were able to say the individual services they can move into the cloud to gain benefits and the services that you can leave on Prem so what does that actually mean so it's an agent based technology driven by artificial intelligence it will look at individual dependencies and tell you which ones are strongly coupled which ones are loosely coupled it'll automatically based line every single one of the metrics within your environment so who is donut race so this is the eighth year running in the Magic Quadrant Gartner Magic Quadrant we've been named as the leader and we're in AWS cloud partner as well just to give you a quick overview of the industry that we currently in as you can see over here we have the evolution of the industry self back in the day we used to use very static infrastructure the likes of mainframe very basic client is server communication to solve issues and then we moved into the service-oriented architecture very large monoliths at that point the likes of CA wiley Microsoft's comm New Relic these were the applications people were using to get visibility so at this point we realized that the future is going to be all about the enterprise cloud the cloud that we currently in and we realized that there's a chasm we couldn't just take whatever we had previously lifted into the cloud and expect everything to work properly we had to fundamentally change the way we were thinking so we started another company from dynaTrace we've taken some of the best developers in Tony face at that point started another company called Ruxin they've come up with this amazing piece of technology which we brought back into dynaTrace and that ing to Gartner is the only third generation solution that mounts your cloud end-to-end it's built on three core principles end-to-end automation so every time there is an issue within your environment you make a change you shouldn't have to go in there and manually make changes monitoring is they would keep up automatically it's built on artificial intelligence so then there is an issue in the middle of the night you shouldn't have to wake people up to see exactly where the issue is no more war room scenarios and it's built on a POS so if you have scenarios where you can't just monitor things you want to use it for security purposes although the data you capturing we want to use it for data visualization purposes you can do that what do I mean by that so let's jump straight into a demonstration see what that looks like what I have over here is a very high level overview of an environment this is a live environment by the way the way we monitor this is through an agent-based technology you place your individual agents on the service that you have as soon as you place the agent on the server it automatically recognizes every single process you have on the server and every single service you have exposed to the Internet so it's able to break that open and show you everything that's happening in your environment what that means is it's a would give me a service dependency map so if you're looking to move us particular service into the cloud disable to tell you which particular services it's speaking to which services are speaking with it so as you can see over here the direction of communication is recognized automatically and the solid lines here represent a real-time communication that's happening the dotted line shows a historical connection so something that used to happen previously from here as an application owner we just want to know what's happening in our application regardless of where it's hosted we don't care whether it's on AWS so on trim we just want to know that the application is working dynaTrace automatically recognizes your individual applications and it gives us two different views the actual performance of the application and how they end users are behaving so it's giving us more information on the applications itself telling us which user is a new user as opposed to a returning user and how long it's actually taking for them make the transactions that they're meant to make from here we can ask more questions to stitch the entire transaction end to end automatically so for every single application when a new user comes in we can see the entire application architecture stitch together and again no manual intervention required you place the agent next next finish it automatically builds this out for you so finally I'll show you is more from our artificial intelligence perspective so currently when there are issues with in your environment you probably have multiple people come into a war room scenario people probably say no it's not a network issue it's not a hardware issue not an application issue but how do you know where the root cause is that's where donut rest comes in they would pull all this data together and baseline your environment they starts comparing Monday mornings with Monday mornings Sunday nights with Sunday nights so it knows exactly when something's changed so let's drill down into a problem here this scenario we've got a problem ticket not individual alerts for a problem ticket it's it's able to identify a problem that lasted almost an hour just looked at over six hundred and thirty million dependencies that's network communications method calls and user transactions log files everything that you can imagine more importantly it's telling us the number of people's are impacted so if as an organization you have say a million people coming in every day and you've only got 92 people affected in the middle of the night you know that this is probably not a p1 anymore by clicking on this link I can actually go down to the users the 92 users and what they were doing at that point in time we can see the impact to the actual application as a result of this issue it's telling is only two user actions were impacted not the entire application it's automatically baselined everything to tell us exactly what the impact with the application is with integration into JIRA or ServiceNow it automatically raised ticket and sends it to the relevant team to fix more importantly it's found the root cause to the issues for us this it's saying there is a CP issue on these boxes and by clicking on these we can actually drill down to those boxes and what happened at that point in time top right it changed the time frame automatically it's telling us there was a CPU saturation issue we can drill down further to understand what's actually consumed all of that so now that we've realized it's probably not a p1 it come back the next morning we can actually replay the entire issue as it traversed our data center so starting from the front end going where all the way back down to the infrastructure layer we can look every single incident that happened over time that caused this issue previously all these incidents would have been individual alerts that would have bombarded your mailbox at any point we can pause this drill down into any one of these incidents that happened to understand what actually happened so this is where the integration with the api's comes in with the likes of AWS lambda and so on we can integrate with your API and get it to take us in action in the middle of the night when incidents like this happen so what people are using this for in this particular scenario we have a CPU saturation issue we don't really need to wake people up anymore we've actually automate that process of either restarting the server or adding more servers more computer workload so that's how we move into auto remediation and self-healing IOT