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Using SLOs for Continuous Performance Optimizations of Your k8s Workloads

Moving to k8s doesn’t prevent anyone from bad architectural decisions leading to performance degradations, scalability issues or violating your SLOs in production. In fact – building smaller services running in pods connected through service meshes are even more vulnerable to bad architectural or implementation choices.

To avoid any bad deployments, the CNCF project Keptn provides automated SLO-based Performance Analysis as part of your CD process. Keptn automatically detects architectural and deployment changes that have a negative impact to performance and scalability. It uses SLOs (Service Level Objectives) to ensure your services always meet your objectives. The Keptn team has also put out SLO best practices to identify well known performance patterns that have been identified over the years analyzing hundreds of distributed software architectures deployed on k8s.

Join this session and learn what these patterns are and how Keptn helps you prevent them from entering production

20 Minutes
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Andreas Grabner

Andreas Grabner, DevOps Activist at Dynatrace

Andreas Grabner is a contributor to the CNCF open source project Keptn. He has been working in performance engineering for the past 20 years and is sharing his experiences via blogs, videos or his PurePerformance podcast. You can follow him via @grabnerandi

P99 CONF OCT. 6-7, 2021

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