DevOps Innovation Performance Testing Testing 
Dynatrace
SEPTEMBER 4, 2020
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.
Dynatrace
DECEMBER 18, 2023
Having laid the foundation during the deployment stage, we’ll now explore the benefits of Dynatrace visibility and orchestration during the testing phase. T he testing stage plays a crucial role in ensuring the quality of newly built code through the execution of automated test cases.
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Alex Podelko
JUNE 12, 2019
My post Good Times for Load Testing was published in 2014. It is difficult to believe that 5 years passed… Are times still good for load testing? If we speak about commercial load testing tools, we see rather a shrinking market and not too much innovation recently. Well, yes and no. Commercial Tools [Crisis?].
Dynatrace
FEBRUARY 21, 2024
This approach supports innovation, ambitious SLOs, DevOps scalability, and competitiveness. Quality gates after load/performance testing Teams can use quality gates to evaluate performance metrics. Several tools can be used to collect metrics in load/performance testing.
Dynatrace
JULY 16, 2021
The Dynatrace Software Intelligence Platform already comes with release analysis, version awareness , and Service Level Objective (SLO) support as part of the Dynatrace Cloud Automation solution , helping DevOps and SRE teams automate the delivery and operational decisions. Ready to create your first release validation automation?
Dynatrace
MARCH 3, 2020
The IDC FutureScape: Worldwide IT Industry 2020 Predictions highlights key trends for IT industry-wide technology adoption for the next five years and includes these predictions: Hasten to innovation. By 2024, over 50% of all IT spending will be directly put towards digital transformation and innovation (up from 31% in 2018).
Dynatrace
JUNE 11, 2019
Ideally, QA teams use production data for better test definitions (based on real use cases) and better workload modeling for load testing (based on real-world load behavior). Organizations that don’t look at production data may test the wrong things and simulate the wrong performance tests. This is good news.
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