Andreas Grabner

Andreas Grabner has 20+ years of experience as a software developer, tester and architect and is an advocate for high-performing cloud scale applications. He is a regular contributor to the DevOps community, a frequent speaker at technology conferences and regularly publishes articles on blog.dynatrace.com. You can follow him on Twitter: @grabnerandi

Andreas Grabner's articles

Why we love Dynatrace AppMon 2017 May

Just as Dynatrace has redefined monitoring for Cloud Native, Micro-Services and Web Scale DevOps through Dynatrace SaaS & Managed, we’ve also been innovating on our Dynatrace AppMon & UEM solution. Thanks to feedback from our users and our passionate engineering teams, Dynatrace AppMon 2017 May (= Version 7) clearly shows the biggest innovation leap that I can remember since my start at Dynatrace nine years ago. Here are some of my personal… read more

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… 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

DevOps tool chain: Shift-Left with Bamboo, SoapUI, JMeter and Dynatrace

Dynatrace is a true player in the DevOps tool chain. We built Dynatrace to provide fast feedback on code quality all the way from Dev, via Continuous Integration/Continuous Delivery, all the way into production. The same Dynatrace solution for every pipeline stage to provide fast metrics-based feedback loops on code changes that you are pushing from left (Dev) to right (Ops). Shift-Left therefore really means that we want to… read more

Automating Shared Infrastructure Impact Analysis: Why Monitoring Backend Jobs is as important as monitoring applications

This posting illustrates how to effectively automate shared infrastructure analysis to support both your back-end jobs and your applications. Last week Gerald, one of our Dynatrace AppMon super users, sent me a PurePath as part of my Share Your PurePath program. He wanted to get my opinion on high I/O time they sporadically see in some of their key transactions on their Adobe-based documentation management system. The hotspot he tried… read more

Using the Dynatrace DevOps Pipeline State UFO

The Dynatrace DevOps Pipeline State UFO was built out of the necessity to visualize alerts, problems, health and CI/CD pipeline state within the Dynatrace R&D organization. It sparked a cultural transformation as it made code quality that we pushed more frequently through our Delivery Pipeline more visible. You should read the background story from our Chief Software Architect Helmut Spiegl who invented the first versions of the UFO. read more

Business Innovation through APM Metrics-Driven DevOps

Innovating faster to meet end-user demand is one of the challenges addressed by DevOps. DevOps bridges the knowledge gap about the impact between business and application teams. Application teams have to better understand the impact they have on business with code or deployment changes. On the other hand, business wants to better understand the impact on current development commitments when they come up with new requirements and a tight schedule. The… 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… read more

Tracing is the new Debugging in Distributed App Development

Debugging is the developer’s best friend when it comes to understanding how code really executes – especially when trying to figure out why the code is not behaving as expected. Debugging works exceptionally well in monolithic apps or in service-oriented apps when you know exactly to which service instance you need to attach your debugger. In modern application architectures that embrace micro-services which either run on your machine, in a… 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… read more