Kubernetes Scaling: Predictive Insights and Automation with Dynatrace
Explore how you can leverage Dynatrace’s Davis® AI to forecast resource needs and automate pod scaling with workflows.
Key Highlights:
- Understand the importance of setting the correct quotas for your applications.
- Learn the differences between horizontal and vertical scaling and why HPA/VPA might not be enough.
- Discover how Davis® AI forecasts work and how they can predict resource usage.
- See how to integrate predictive scaling into a modern GitOps environment using GitHub for Workflows.
🔗 Useful links:
Explore our sample dashboards on the Dynatrace Playground: https://dynatr.ac/3TXDrxP
Get hands-on and deploy our predictive auto-scaling demo app using GitHub Codespace: https://dynatr.ac/3XQy1Wu
Implement predictive autoscaling in your environments with our detailed Dynatrace Documentation: Coming Soon!
📖 Chapters 📖
00:00 Introduction
00:42 Why is (auto-)scaling important?
01:10 How can you scale in Kubernetes?
02:00 What about Horizontal and Vertical Pod Autoscalers?
03:37 Predicting resource consumption with Davis® AI
10:18 Using Davis® AI to scale Kubernetes Workloads
14:34 Expecting the unexpected
15:42 Conclusion and key takeaways
🔬 Have a question about our platform? Visit our Dynatrace Community to connect with our experts and users → https://dynatr.ac/3FYfPB3
Try our platform with a free trial, or schedule a personalized demo at https://dynatr.ac/3VxvLDH.
👉✅ Stay up-to-date with Dynatrace! Follow us on:
Facebook → https://facebook.com/dynatrace
Instagram → https://instagram.com/dynatrace
LinkedIn → https://linkedin.com/company/dynatrace
X → https://twitter.com/dynatrace
Twitch → https://twitch.tv/dynatrace
Key Highlights:
- Understand the importance of setting the correct quotas for your applications.
- Learn the differences between horizontal and vertical scaling and why HPA/VPA might not be enough.
- Discover how Davis® AI forecasts work and how they can predict resource usage.
- See how to integrate predictive scaling into a modern GitOps environment using GitHub for Workflows.
🔗 Useful links:
Explore our sample dashboards on the Dynatrace Playground: https://dynatr.ac/3TXDrxP
Get hands-on and deploy our predictive auto-scaling demo app using GitHub Codespace: https://dynatr.ac/3XQy1Wu
Implement predictive autoscaling in your environments with our detailed Dynatrace Documentation: Coming Soon!
📖 Chapters 📖
00:00 Introduction
00:42 Why is (auto-)scaling important?
01:10 How can you scale in Kubernetes?
02:00 What about Horizontal and Vertical Pod Autoscalers?
03:37 Predicting resource consumption with Davis® AI
10:18 Using Davis® AI to scale Kubernetes Workloads
14:34 Expecting the unexpected
15:42 Conclusion and key takeaways
🔬 Have a question about our platform? Visit our Dynatrace Community to connect with our experts and users → https://dynatr.ac/3FYfPB3
Try our platform with a free trial, or schedule a personalized demo at https://dynatr.ac/3VxvLDH.
👉✅ Stay up-to-date with Dynatrace! Follow us on:
Facebook → https://facebook.com/dynatrace
Instagram → https://instagram.com/dynatrace
LinkedIn → https://linkedin.com/company/dynatrace
X → https://twitter.com/dynatrace
Twitch → https://twitch.tv/dynatrace