Lifecycle / DevOps

Dynatrace on Dynatrace: Detecting Regressions in Continuous Performance Environments

In my previous blog I addressed how we use Dynatrace on Dynatrace in our Continuous Functional Testing Environment. During that same visit to our engineering lab in Linz, Austria I also spoke with Thomas Steinmaurer, Performance Architect for Dynatrace. He oversees our Continuous Performance Environment. Dynatrace builds are deployed daily. Different load patterns are constantly running simulating traffic of thousands of agents. For this purpose we wrote our own performance testing tool because we have some … read more

Dynatrace on Dynatrace: Detecting Architectural Regressions in Continuous Functional Testing

At Dynatrace we not only sell our performance monitoring solutions to our customers – we use them in the way we want our customers to use them. The benefit of this “eat your own dog food” – or – “drink your own Champagne” (as we like to call it) is that we see first-hand if our features need to be improved to deliver what we promise. On my last trip … read more

Detecting the N+1 Asynchronous Thread Problem Pattern

I’ve been offering my help in analyzing performance data for quite a while now. Most of the time when analyzing PurePaths, load testing outputs or production log files, I find very similar problem patterns. This fact inspired us to automate problem detection in Dynatrace AppMon 6.5. Even though I think we cover a big part of common patterns, I am always on the lookout for something new – something I … read more

Sitecore Performance Tips: What’s Geography Got to Do with It?

It’s not very often that data aligns perfectly to illustrate a topic. Typically, there are very clear trends among the outlying data points that clearly support the topic in question, but it’s rarely absolute. So, while researching Sitecore performance topics this week, I spotted data points that almost perfectly align to support the premise of Geographical Performance Variance in User Experience, that is, in layman’s terms, the further away the … read more

Monitoring OpenShift Applications with Dynatrace

Based on Docker and the Kubernetes container cluster manager, Red Hat OpenShift is the next generation container platform for developing, deploying and running containerized applications conveniently and at scale. In this article, Chris Morgan (@cmorgan_cloud), Technical Director for OpenShift Ecosystem, and Martin Etmajer (@metmajer), Technology Lead at the Dynatrace Innovation Lab, discuss why OpenShift and the Dynatrace digital performance management solution are a perfect combination. The interview is led by Franz Karlsberger (@fraka7), … read more

Scaling DevOps Deployments with AWS CodePipeline & Dynatrace

AWS CodePipeline is a more recent addition to Amazon Web Services – allowing development teams to push code changes from source check-in all the way into production in a very automated way. While code pipelines like that are not new (e.g: XebiaLabs, Electric Cloud, Jenkins Pipeline), Amazon provides seamless integration options for AWS CodeCommit, S3, CodeDeploy, Elastic Beanstalk, Cloud Formation as well as integration options for popular external DevOps tools … read more

From 0 To DevOps in 80 Days: The Dynatrace Transformation Story!

Market disruption can spark innovation and radical change, and DevOps — as a set of best practices — has emerged from software industry disruptions. Why? Because, over the years, delivering software in many organizations has become harder, slower and more error prone. Outdated technology became a disadvantage for older, established companies competing against startups without years of accumulated technical debt. Rigid processes and an old fashioned mindset blinded these enterprises to new business models … read more

Transformation to Continuous Innovation and Optimization

Businesses have always had to transform to find better and more efficient ways to deliver value faster to their users, customers or consumers. The motivating factors are shorter lead times, automated and streamlined value flow, as well as reduction of overall costs and bound capital, requiring enterprises to transition to a continuous innovation and optimization model. Prominent examples can be found when studying the last decades in the automobile industry with Toyota and … read more

Get Ready for DevOps: Remove Code & Architectural Bottlenecks

I was honored to do a DevOps Handbook Lessons Learned webinar with the DevOps “Godfather” Gene Kim earlier this month. In preparation for it I not only started reading his new DevOps Handbook, but also revisited the main messages of his previous DevOps book – The Phoenix Project. Gene (and co-authors) talk about the three ways which represent a maturity path of organizations from a rigid, slow and manual value chain, towards … read more

The Artificial Intelligence-Driven Vision for Digital Performance Management

The goal is now in sight – if not yet in reach: a fully-automated operational production environment. The rise of DevOps shows the progress we’ve made in automating the provisioning and configuration of ops, as well as application deployment. Management of the ops environment isn’t far behind. IT Operations Management (ITOM), and in particular Application Performance Management (APM) are now well on their way to realizing this hands-off vision. But … read more

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