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DevOps engineer tools: Deploy, test, evaluate, repeat

Dynatrace

As cloud-native, distributed architectures proliferate, the need for DevOps technologies and DevOps platform engineers has increased as well. DevOps engineer tools can help ease the pressure as environment complexity grows. ” What does a DevOps platform engineer do?

DevOps 180
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A guide to event-driven SRE-inspired DevOps

Dynatrace

This is a mouthful of buzzwords” is how I started my recent presentations at the Online Kubernetes Meetup as well as the DevOps Fusion 2020 Online Conference when explaining the three big challenges we are trying to solve with Keptn – our CNCF Open Source project: Automate build validation through SLI/SLO-based Quality Gates. Dynatrace news.

DevOps 242
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Up your quality and agility factor – using automation to build “performance-as-a-self-service”

Dynatrace

One way to apply improvements is transforming the way application performance engineering and testing is done. This involves new software delivery models, adapting to complex software architectures, and embracing automation for analysis and testing. Check out Dynatrace’s Load testing tool integration.

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Reinventing Performance Testing: New Technologies

Alex Podelko

– New Architectures. Quite often the whole area of load testing is reduced to pre-production testing using protocol-level recording/playback. Sometimes it even lead to conclusions like “performance testing hitting the wall” just because load generation may be a challenge. Programming API using a Load Testing Tool.

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Mobile Testing Lab: How to decide which way to go?

Testsigma

Here are the key reasons why it makes sense to have a dedicated mobile device lab: Find and fix bugs at the earliest Reduce the time-to-market Launch more features per app release Cover all possible mobile devices Agile and DevOps methodology. Once you have chosen your target devices, consider the architectural aspect of your hardware.

Mobile 52
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The Benefits of Tasktop’s Affinity Modeling

Tasktop

In software delivery tools, the data of interest exists as objects termed “artifacts”, which are work items like features, stories, tasks, test cases, defects and requirements. They are stored in the tools where the work gets done, like requirements tools, Agile planning tools and testing tools.