Accelerate Spring Apps to Cloud at Scale - Discussion with Azure Spring Cloud Customers

hello welcome to the session on accelerate spring apps to the cloud at scale my name is adeep psychology i'm a principal platform architect with vmware came through the pivotal acquisition uh i am a software developer and my customers like to call me the code janitor because they frequently say hey here's a large application can you tell us how to take this application and take it to the cloud today we've assembled a a wonderful panel with our friends from morgan stanley bosch and digital reality that are going to talk to you about how they're using azure spring cloud in production and we're going to start off the session though with a with an overview of the architecture of azure spring cloud and a demo to get you to see what the developer experience is like so that when the panelists are you know providing you with wonderful details about what they're doing you'll be able to kind of understand that in the context of what the user experience will look like i'm also at microsoft i'm on point for everything developers and customers need to build migrate and scale java applications on azure i'm also a java developer i started in 1995 with jdk one and i have been having an amazing time with java ever since so what is azure spring cloud azure spring cloud is a fully managed service for spring boot applications that lets you focus on building and running the apps that run your business without the hassle of managing the underlying infrastructure you can simply deploy your charts or code and azure spring cloud will automatically wire your apps with spring service runtime once deployed you can easily monitor application performance fixed errors and rapidly improve applications it's fully integrated into azure's ecosystem and it's ready for the enterprises the service is jointly built operated and supported by microsoft and vmware a little more details the big rectangle is azure spring cloud it is built on kubernetes particularly azure kubernetes servers each service instance has two dedicated kubernetes clusters they are managed by azure spring cloud and fully abstracted away from users service runtime with managed spring cloud components log streaming app lifecycle and many more service runtime components are managed in one of the two kubernetes clusters it is the one represented on the right side your apps are running in the second kubernetes cluster it is represented in the left side box in the diagram your apps can interact with any azure service or external service or on-premise systems logs metrics outlets are available through azure monitor you can pick them up using elastic splunk or azure log analytics you can secure your apps using azure active directory you can automate end-to-end from idea to production using your favorite tools and platforms you can continue to use your development tools that you're familiar with uh from intellij eclipse vs code maven to cradle all everything is supported net net it's an easy way to get started focus on your business objectives and everything else is taken care for you in the cloud do you have to manage anything here no not at all you don't have to manage anything azure spring cloud has absorbed all the complexities with infrastructure hosting applications app lifecycle managing applications blue green deployments probably publishing logs and metrics and so on and on everything is taken care of and all of these are supported by microsoft and vmware we'll show you a very quick demo of azure spring cloud and show you how simple it is are you ready let's take spring boot applications to cloud at scale i have an app composed of java micro services and i want to run them on azure this is a popular repo distributed version of spring boot back clinic you can see an api gateway as the entry point the operator comes in and there are three micro services and one spring boot admin server we're going to deploy to azure spring cloud i took three simple steps to deploy to azure sprint cloud i created the service created apps and deployed the chart files you see an instance of azure spring cloud for the pet linux project you can see the apps are up and running at scale right now api gateway is the entry point so i go here and start clicking this particular assign fqtn at this point i see the actual application coming up i can see all my customers and their pets as well you can see john coleman has about two pets i can also see my talks here i can also start scheduling visits using this uh system so here when i open up john coleman you can see that he has two two packs and i can start adding a visit right here when i deploy these jar file i did not have to do anything other than just deploy them do we have enough instances of the customer service let me scale that out right now there are about six instances i can increase to say say 200 instances or maybe 500 instances as soon as i save it'll start scaling out i can also auto scale here i'm looking at auto scale now i can auto scale by metric or by schedule let's look at the metric in this i'm scaling out by the cpu usage right now here when the when the when the app usage cpu usage goes up by 50 i'm going to ask it to increase the number of instances by 2. similarly when the cpu usage goes down i'm going to ask it to when it particularly goes down below 30 i'm going to ask it to reduce the number of instances by 2. i can also auto scale by schedule for example i can scale in on saturday morning and scale out on monday morning again so many things are managed for you now what if there's a problem with your app and how can you see what is going on you can view the logs for all your apps and even run custom queries you can send all your logs and metrics to any log aggregator say log analytics or elastic or splunk here i sent them to log analytics workspace here i'm running a query and to bring all the logs for my applications particularly the ones where i see errors and exceptions i can quickly go through and open up one of these and understand what is going on i can also render them as a pie chart now if you're a developer like me you probably want to get your logs directly on your on your dev machine here and say azspring cloud app logs so when i run it it will directly bring all the logs right to my dev machine this way i can figure out what went wrong in this project i used many microservices to scale out my components individually you can use application insights to monitor which app calls is slow so that you can tune them or know when app instances are bombed out because of some production data that came in so here you see the api gateway is here the calls are coming in and they're going into customer service and some calls are going into bets and some calls are going into the visit service now behind them there's a pet clinic sql database mysql database right so let's zoom in let's say i want to drill into one of these paths right so i go here and i drill into one of those paths when i drill in it gives me some meaningful insights it gave me an option to investigate the performance i can drill into it when i drill it gives me all the calls that happen in the last four hours i can choose one of them and go deeper when i go deep it gives me the complete end-to-end transaction that happened along this path and you can see all the way down to here is the sql and the sql query that went that was executed for those particular operations now back to the application map it gives you some incredible views of all your applications meaningful insights and actionable logs and metrics did you see five million calls in the last four hours yes they are in production at cloud scale running at 30 million calls per day now you can simply run manual scale slider or the auto scale to multiple billion calls a day in a matter of minutes now you can also go deeper into performance of failures and availability so here you see the performance plate where all the methods are all the operations are listed here you can also look at the dependencies so these are all the dependencies the dependency costs were about in the last four hours there were about 40 million costs right you can also start looking at your failures right now you may have some business metrics you can track them right here let's see uh in this particular application there are pet owners there are pets and there are visits we keep track of them that way you have to you can see the rhythm of your business across time do you have to write any code for all these monitoring no not at all i simply deployed my trials nothing else all these data frozen effortlessly azure spring cloud is a fully managed service for spring boot apps that lets you focus on building and running the apps that run your business without the hassle of managing infrastructure monitoring or automation or apply cycle and so and so on today aviva and i invited a great set of panelists from morgan stanley bosch and digital reality trust who have been very successful in adopting azure sprint cloud and accelerating their springboard applications to cloud scale we are very excited let's start with the introduction hello everyone my name is diran shah i'm part of operations technology at morgan stanley i have two roles here i'm a tech area lead for security settlements fleet and i'm also the lead architect for operations technology i'm leading a very talented and innovative team to build our next generation of security settlements platform security settlements platform facilitates movement of stocks and bonds between market participants based on trading activity we process millions of messages per day in our global settlements platform across major financial markets we have decided to approach this project in stages with the goal of developing a cloud-based message-oriented item-potent solution that can horizontally scale with separate data stores command and event handlers for the first phase we migrated from mainframe to springboot apps second we deployed springboard apps to azure spring cloud and ran a production parallel across a few selected markets the final phase will be scaling to markets across the globe and sunsetting our mainframe systems azure spring cloud is at the heart of our solution running modern spring services for command and event handlers and also for reporting we are also leveraging other azure services including sql databases for storing business data keyword for managing secrets and zero trust azure monitor log analytics and application insights for end-to-end monitoring and we also leverage azure networking for secure communications hello everyone my name is georg daschler you can also call me george and i'm with bosch since 2008 i've been working in various projects and positions there including development solution architecture and project management and currently i'm a development team lead and agile coach for a really amazing team and with this team i'm developing and operating an iot solution for tracking of shipping assets and materials and it's called track and trace tracking trays can be used to track many kinds of assets today as mentioned our focus lies on customers that use it for logistics assets like containers of any size they can save effort for finding their assets and save money by managing their empty assets more efficiently because it's quite clear finding an empty asset is much cheaper than buying a new one now how does it work someone on the shop floor attaches a wireless tag to an asset which is continuously broadcasting its id they also create a logical link between the asset and the tag with the mobile app gateways are receiving these broadcasts and transfer the information to the backend so you know where the tag is and by that you also know where your asset is data is received by an application gateway and handed over to the track and trace call system which is consisting of about 15 micro services which are running on the azure spring cloud there are many different views and reports based on the data that we present in our ui and process data can also be sent to customer systems hi everyone i'm the principal architect within the it infrastructure leadership team at digital reality and i'm not a java developer my role spans across our cloud systems and network landscape i favor repeatable scalable and secure architectural patterns i've led the architecture and implementation of large-scale multi-region azure spring cloud project this year and my team is made up of a lot of different people like developers business analysts cloud engineers and product managers i'm an engineer at heart and i love solving complex technology problems with creativity and elegance digital reality supports the data center co-location and interconnection strategies of customers around the world ranging from cloud and information technology services communications and social networking to financial services manufacturing energy healthcare and consumer products we operate over 290 data centers in 24 countries and on six continents the architecture on the screen is our design for a new platform for our customers that will allow them to build integrations and consume data from us about their services azure spring cloud is at the center of hosting these rest apis they power the platform and we leverage multiple regions for spring boot microservices we follow a hub and spoke model our solution is fully automated and including our virtual palo alto firewalls at the edge awesome thank you so much uh for such a wonderful introduction i'm just blown away by how how awesome and how extensive your use of spring boot is and also on azure so one of the things that i hear a lot from cios is okay this cloud is big it's got a lot of services so can you tell us a little bit about how does azure spring cloud fit into your overall cloud strategy and what were some of the considerations in selecting the azure spring cloud service we leverage spring frameworks for most of our development and azure spring cloud is at the heart of our strategy for implementing global security settlements platform we are leveraging open source technologies and multi-cloud portability is a key design principle improving developer productivity is one of the goals of our transformation and azure spring cloud contributes towards that goal by taking away the complexities of managing our own kubernetes cluster azure spring cloud allows us to focus on implementing complex business features and not having to keep our infrastructure up to date we use automatic containerization from springboot source or jars which allows us to define a roadmap for modernizing on-prem applications to cloud faster azure spring cloud makes it very easy for us to configure deploy monitor and scale our applications and also handles the life cycle management with the ease of automation and ease of monitoring that comes with it we have been able to scale our development team without compromising code quality and robustness of our application azure spring cloud is at the heart of our platform all our command and event handlers are deployed in an azure sprint cloud well we also didn't have much interest in getting involved with kubernetes docker images and the like for a team that's focused on development and that has been previously working with cloud foundry and its built packs azure spring cloud was an attractive option now in the meantime we've migrated about 15 microservices as i said to azure spring cloud and we still want to use the major share of the team's capacity for further development of our product and so it's really helpful not having much more to do than building a fat char to get the service deployed we weren't sure if this would also work for some of our services that are still based on vertex but it does and so we were able to move the complete solution to azure spring cloud as our single runtime for the services another important thing for us is scalability from a business perspective as well as technically track and trace is still growing and we're placing many more tracking devices in the field the monitoring functionalities are very valuable not only to identify issues during daily operations but also to see which parts of the system we need to focus on to allow our business to grow so if you're listening closely there's a trend here we also selected azure spring cloud because we didn't have the skill set or the desire to manage kubernetes and we also wanted to be able to start development almost immediately without long runways of setting up infrastructure and networks azure spring cloud allows us to scale horizontally quickly and easily and we leverage several sets of arm templates for new region deployments globally including fully automated management of virtual palo alto firewalls and a baseline of v-net peering rules currently we have around 30 spring boot microservices deployed to azure spring cloud across two regions and we aren't even in production yet when it's all said and done we anticipate having somewhere in the neighborhood of 90 microservices within our current scope for our project cloud strategy i like how you approached it from portability productivity and faster time to market and then shows azure spring cloud where you can focus on your business without worrying about the underlying infrastructure to recap some of the key points what we heard today azure spring cloud is fully managed service by microsoft and vmware it is built on kubernetes you don't have to learn or manage kubernetes it's easy to create configure deploy monitor and scale as we saw today azure spring cloud is the heart of morgan stanley bosch and digital reality trust architectures and the service powers springboard applications for them day in and day out our customers and developers tell us that security is a critical consideration for any enterprise applications so we love to hear how do you enforce security policies across your spring boot applications the architecture of our spring boot microservices follows application development best practices dtap cloud and network security best practices of segmentation and a zero trust model cross environment routing is disabled for example forcing the use of the release pipelines we leverage managed identities certificates access policies and key secrets inside of segmented azure key vaults by environment our application then follows the rbac model in each end user or machine is authorized via claims all of our code is scanned as part of the pipeline for credentials using veracode as a financial institution security is extremely critical our dedicated team of cyber security experts is drawn from former senior professionals at government security agencies and the technology industry i think all developers should be thinking about how we make each interaction secure and think through various threat scenarios this is very important for building secure cloud-native applications we implement every application in a lending zone with our back policies that are reviewed by a centralized accuracy to ensure consistency and strength of controls we use infrastructure escort to configure these services to mitigate any risk of human error we handle security at multiple levels in our solution we are leveraging concepts like network segmentation and v-net peering capabilities of azure spring cloud we also use private endpoints as another network control implementing zero trust based interactions model which assumes nobody is trustworthy by default even though already they are inside the network segment we are leveraging azure keyword to manage our secrets we encrypt all our data in transit at rest and in use we have shorter expiration durations for our identity tokens as well as we do frequent certificate rotations having we also have checks in our build pipelines to ensure any secrets don't leak out via code repository for bosch security is an undisputable quality requirement of our iot solutions and that's why we have a process in place that we follow to ensure it's considered sufficiently in software engineering so this has really also the level of and central directive now to make application of measures even easier for the teams we have a corporate implementation guide for azure that our central i.t department elaborated together with microsoft this tells us how to use azure services properly to reach the required level of security so for example it tells us to use a certain service tier to be able to use the v-net integration or it tells us how to set certain configuration parameters to have a service properly in place we also implemented the reference architecture for spring cloud as it's recommended by microsoft azure helped us together with some guys uh in germany and i think you remember other reviewing our architectural ideas and giving us feedback how to do it that was also very helpful to build it in a in a reasonable and secure way so among other things we realize network segregation keep our secrets in keyword we use managed identities of course uh encrypt data in transit and addressed and important to mention the respective policies and measures are implemented using bicep so we make sure they are incorporated on provisioning the services additionally we are also able to trace requirements um from our implementation guide or also additional requirements we make up on on our own simply by commenting these scripts properly awesome uh wow i mean this is uh pretty impressive what i'm hearing from you guys is that you're able to build on top of the existing security processes and apply some of the best practices um in particular like you know if we kind of recap that i really like how you guys talked about how you're able to isolate your services and apps from the internet how you're able to do zero trust and integrate into the azure rbac system use private endpoints to connect to things and and you know encrypt all of your data at rest and in transit um and you know really the comment about how developers have to think about security and be part of it can agree more with that so this is this is truly truly nice so um when we uh when we do this you know we secured our applications uh the question now is that our applications available so how do you handle end-to-end monitoring of your application and what tools are you using to do this yeah so for us the security settlements platform is a very critical platform and if like availability is very very important so we have a lot of real-time monitoring implemented for that we use application insights to collect our application logs traces and metrics with open telemetry for log correlations using traces and spans we leverage the application map functionality in app insights to spot performance bottlenecks for failure as well as identify issues with latency and it allows us to kind of monitor the health of the whole platform as well as drill into any issues that are ongoing we use azure monitoring monitor for querying the collected telemetry information and we have integrated with leading observability players to enable monitoring and alerts and automated notifications for any issues to be resolved we also use our logs to measure measure processing rates and response rates to maintain our slos yeah we also use application insights and log analytics we have alerts configured for critical metrics and we have dashboards for quick overview for our team alerts work quite simply via email or what we also use for really urgent incidents we have some web hooks that can send direct messages to the members with log analytics we are also able to handle our logs very similarly to our old environment where we used another logging and monitoring platform um but it worked similarly in terms of querying the logs so learning custom as a new language isn't too difficult to get for the team for checking the health of our apps and investigating issues we found the application map to be very very useful this was a real wow effect for us when others showed it to us the first time in the call it draws our attention to the right spots certain services or also the interaction between them and then when we see something turning red in the application map from there on we're able to dig deeper by just clicking on it and we identify issues that way this helped us a lot directly after migration to identify some configuration issues and bottlenecks that we couldn't find with our tests we also use azure monitor app insights and log analytics and those are central to our application monitoring the devops team receives web hook actions in teams for critical log alerts so that they can be actioned immediately we have a vision to go beyond traditional monitoring and incorporate self-healing technology and event aggregation leveraging products such as moog soft and app dynamics to adopt a more event-driven architecture i really like how you have set up some real-time end-to-end monitoring dashboards as i was watching those monitoring graphics we can see that you have some incredible views of your systems some meaningful insights into your business as seen through the system and with some actionable logs and metrics it's also amazing how you can dig deeper into those issues directly from the dashboard to recap you can monitor your spring boot applications and end-to-end solutions including all the azure resources and your on-premise resources around azure spring cloud you can monitor apps and end-to-end solutions using any platform and tools of your choice you can troubleshoot your applications measure slas or slos of your solution just like the way it didn't explain you can plan capacities by running your performance establish baseline for everyday workload and peak workload just like the way george explained and you can keep an eye on production just like the way tibon explained and of course you can use app app insights new relic dynatrace or app dynamics log analytics elastic rspark today we learned a lot about different architectures by bosch digital reality trust and morgan stanley it looks like you have different drivers for scaling your applications we heard about iot devices trades and end users how do you scale your applications and what is driving that need what types of approaches do you use for efficient use of resources in the cloud yeah other i think you already guessed it as we have an iot application the number of connected devices is the primary driver for our scaling needs data is transferred from the devices to our backend at a quite constant rate that's why so far we're quite happy with manually scaling the app yet this is not a trivial task there is quite some processing and enrichment going on in the back end with the raw device data and to determine the needed capacity for the different microservice we are running load tests regularly and with these load tests we are simulating a number of devices we expect in the near future on our qa environment and then we checked the system health using the application map again that we saw before so um when we see something red there or poor performance between services or something we configure the service instances until everything runs smoothly of course we also stumble upon parts of the system that could run more efficiently where you maybe don't want to throw resources just to make them go but where you say oh we could improve something in our code if we find these places we think about the necessary changes derive them and place them in the backlog for further planning and then our product management simply needs to prioritize them versus let's say new features or something additionally we also use azure cost management to keep track of the budget so we don't get surprised by huge bills per architecture was designed in a way to scale globally because our customers are literally everywhere except maybe antarctica for efficient use of resources we rely upon auto scaling in our upper environments and leverage features in azure cost management to establish spend thresholds and alerts we're working on identifying a long-term strategy for log retention to minimize log analytics costs and also to be in compliance with corporate retention policies spring boot microservices will be the engine behind a new product launch for the company and we anticipate very heavy loads we're modeling multiple different volume trends based upon current usage insights from existing products by performing regular load testing with jmeter our load tests are originated from several different geographical locations around the world and also from multiple device types including cell phones tablets virtual desktops and machine to machine the average number of trades varies per day this can be driven by various economic events and company specific news we also have cutoff times for various markets and we generally see a in activity happening towards the cut-off time with end of day and the volumes increasing there so from a scalability perspective we have to look at two angles one is how do we handle the varied volumes day over day plus the spikes towards the cutoff times and second is as we deploy additional markets and onboard new flows onto our platform how are we going to scale out we when we first started the project and built our framework we ran performance tests to define what we call as the scale unit and as we roll out new markets we are going to make decisions on how we leverage that scale unit and make sure we can handle the increased volumes we also have implemented geo-redundancy in our platform and we run our apps very in a very scaled down version in us in the secondary region we will be configuring auto scaling as a azure spring cloud apps based on depth of incoming subscriptions and we have also enabled financial transparency to monitor the price of our cloud usage wonderful uh i love how you have you're able to use azure spring cloud to handle your short-term scaling needs with the auto-scaling capabilities and that you're able to handle your business growth and scale up your applications as that grows so we all know that you know scaling is part of the part of the solution but it's also important that we scale the humans and that we're able to automate things so can you tell us a little bit about what automation tools you're currently using uh with azure sprint cloud yeah sure thing i'm sure for all of you listening you can relate to this but we have to move fast our business is rapidly growing and we struggle to keep up with workloads that require manual processes or intervention also standardization is nearly impossible if application and infrastructure are not automated repeatable processes azure devops build and release pipelines are our primary way of automating and managing the environments directly and we do leverage arm templates our pipeline architecture includes automatic code scanning with vericode and we're working on integrating azure devops with servicenow for complete end-to-end automation of production releases for compliance adherence but also for ease of promotion we use infrastructure as code and terraform for everything we have multiple environments fully managed by infrastructure as code we have implemented robust ci cd pipelines with different levels of automated testing and this includes chaos testing as well as deploying in an ephemeral environment and running into an acceptance test our deployments are 100 automated using azure devops pipelines and this includes creation and configuration of all the azure resources we also do staged zero downtime deployments and we have already seen benefits right like where we have increased our release cadence from monthly to weekly and just a couple of weeks ago we did a release on demand to address an issue as i mentioned we started with a smaller set of developers right and now we have scaled out our development number of developers on the team and they are implementing different flows in parallel using the same code base and we want to stay confirmed with our architectural principles and we want to make sure we can deploy good quality code with confidence so automation is very very critical for us yeah i fully agree with what dewan said speed is key we want to deliver fast but also in high quality and this is a clear qm requirement to us we need a high automate automation level um to be allowed to do continuous delivery as a team therefore we have multiple environments we use bicep to describe them and so we are able to provision them automatically we use different pipelines on azure devops one for the provisioning that i just mentioned the next one is for continuous integration on our qa environment this is done whenever the master branch of the service is changed then we automatically automatically build it and deploy it to our qa environment of spring cloud this includes at least automatic unit tests on build we also have automated system tests that are quite time consuming we need to simulate some real timing behavior there so they run for some hours and we run them nightly we have also one pipeline scanning code and dependencies for open source compliance and vulnerabilities and last but not least we have release pipelines for every service that allow us to deploy to production and run smoke tests automatically it's really great to see how you all have automated end-to-end digital reality users arm template morgan stanley uses terraform and bosch uses bicep for automated provisioning and configurations you all are using multiple pipelines using azure devops you also automate testing and delivery of services that sounds great now anyone can build end-to-end automation from idea to production using a wide range of tools and platforms typically just like morgan stanley porsche and digital reality trust vc developers create pipelines multiple pipelines that are broadly classified into three categories the first one provisioning pipelines you can provision azure resources using terraform arm template cli or bicep build pipelines you can build use your favorite maven or gradle and store it in an artifactory deployment pipelines you can use github actions jenkins azure pipelines and azure cli blue green deployment strategies are very popular for minimizing the downtime when we were staring at your architecture diagrams we saw that you were leveraging many services and on-premise systems to build holistic solutions so what are some other requirements of your applications our application is a mission critical application with lot of complex business functionality required the transformation program we are running is not just a technology migration we are looking to add significant capabilities which will drive end-user efficiencies when we started the program we made a decision to take a evolutionary approach to evolve or architecture which will mean which means we will be introducing new services that allow us to deliver required capabilities with low or no code implementations currently we use azure sql azure keyword service bus app service and storage account we have already started integrating azure api management into our stack we use azure sdk spring starters for java to interact with azure resources our partnership with microsoft is helping us to get new capabilities in azure services asar has been helping us getting some new features in azure spring cloud to keep our implementation simple our goal is to maintain our architectural principles as the ecosystem and our implementation evolves yeah it's about a month now that we finished our migration to azure and after that we currently use azure sql service bus redis cache application gateway storage keyword and some others and now we're starting to investigate which services we could integrate into our architecture for improving certain parts of the system our main drivers for this are again future reliability and scalability requirements and we really also see a promising opportunities uh there but to be honest at the moment we are primarily happy that we made the step over there and now we will take our time to investigate what else can be useful for us our key requirement is resiliency and scalability we need to be able to support a minimum of 25 million api calls per month we have an availability sla target of four nines for our entire platform because it's deemed business critical to our customers azure spring cloud is just our microservices layer of a broader platform architecture these microservices are sourcing data from endpoints and other public clouds as well as on-premises resources our latency target is to be sub 20 milliseconds all fronted by an external but cloud-native api platform we leverage cloud cloud peering for resilient fast connectivity between our public clouds and multiple azure express routes in addition to private microsoft backhauling within the azure ecosystem between regions some of the other services that we use are the azure app service and plan cosmos db redis cache azure front door key vault event hub and jit i like how you have taken advantage of a range of services to build holistic java and spring solutions particularly database cache storage service bus vault for secrets load balancers and network elements thank you thank you for explaining the purpose behind these choices java and spring on azure is a holistic solution that brings together many azure services microsoft and vmware brings the expertise of running enterprise spring workloads at scale azure offers a differentiated portfolio of managed databases to serve java applications of all types you can enable asynchronous messaging at cloud scale in java apps using service bus and event hubs you can secure access to your spring boot apps using azure active directory you can set up end-to-end monitoring using any monitoring platform or tools of your choice you can automate end-to-end using automation tools or platforms of your choice you can secure your workloads by isolating them from the internet and secure them by applying many of the policies that we discussed today on behalf of ativ and myself thank you george and devon for joining us and sharing all the details your experience and in your experiences and insights it's truly inspiring to hear your journeys to production and how you all have navigated through azure services particularly azure spring cloud framed cloud strategies enforce security setup end-to-end monitoring and automation and built holistic solutions for your workloads also happy to see that you have used tools and platforms that your teams know and familiar with everyone watching today and anyone can build cloud native solutions and advance them to production we love to hear how you are building impactful solutions using hydro sprinkler you can get started today you can deploy your first spring boot app today you can also use a self-paced workshop to learn the details of the service if you prefer videos we have some bite size videos part of the youtube you can simply follow the playlist you can also leverage best practices for deploying spring boot apps you should let us know how you are building impactful solutions microsoft and vmware announce azure sprinkler enterprise if you are interested then please sign up you can scan the qr code or go to that url that will take you to the registration form and please click contact me there and you will receive information to activate the private preview everybody on the live stream thank you for joining us today thank you you

Channel: Microsoft Developer

Views: 868

Keywords: Azure, Microsoft, Tech, Technology, Dev, Development, Cloud Computing

Id: jzGP8PdlN1M

Length: 51min 50sec (3110 seconds)

Published: Thu Dec 09 2021