Source URL: https://cloud.google.com/blog/products/containers-kubernetes/rearchitected-gke-hpa-improves-scaling-performance/
Source: Cloud Blog
Title: GKE delivers breakthrough Horizontal Pod Autoscaler performance
Feedly Summary: At Google Cloud, we are committed to providing the fastest and most reliable Kubernetes platform, Google Kubernetes Engine (GKE). Today, we are excited to announce an improved Horizontal Pod Autoscaler (HPA), the Kubernetes feature that automatically updates workload resources to match demand. We rearchitected the HPA stack, resulting in a significant improvement in scaling performance. You can apply it to your environment with the new Performance HPA profile, which delivers:
2x faster scaling: Workloads now scale up more than twice as quickly, enabling faster response times and improved application performance.
Improved metrics resolution: A new fast metrics path with improved metrics resolution allows for more granular scaling and reaction.
Linear scaling to up to 1000 HPA objects: HPA now supports high-scale deployments with consistent performance, helping you run large-scale applications with confidence.
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Why this matters
Faster HPA response times have been a common request from many GKE users, who frequently overprovision resources to account for delays in the autoscaling stack, sometimes resulting in higher costs and lower efficiency.
The Performance HPA profile addresses these challenges by:
Minimizing waste: The new HPA profile enables more precise scaling, reducing the need for over-provisioning and optimizing resource utilization.
Improving application responsiveness: Faster scaling helps ensure applications can quickly adapt to changing demands, delivering a better user experience.
Increasing operational efficiency: The new profile streamlines operations by simplifying scaling management and reducing the need for manual intervention.
Many GKE customers welcome the change.
“With GKE’s Performance HPA profile, we’ve witnessed a remarkable boost in horizontal auto-scaling speed. In our tests with over 1000 HPA objects, workloads scaled up twice as fast. We’re excited to leverage this performance enhancement in our production environments.” – Sophy Cao, Senior Engineer, Spotify
Get started today
The Performance HPA profile is available now as a preview opt-in feature for both GKE Standard and GKE Autopilot. We encourage all GKE users to try the new Performance HPA profile and experience its significant performance improvements firsthand. It only takes a single gcloud command to opt-in — see the guide to enable this feature in your cluster today!
AI Summary and Description: Yes
Summary: Google Cloud has enhanced its Kubernetes service with a new Performance Horizontal Pod Autoscaler (HPA), allowing for significantly faster scaling and improved resource management. This development addresses common user concerns about resource over-provisioning, leading to cost efficiency and improved application performance.
Detailed Description: Google Cloud’s announcement concerning the Google Kubernetes Engine (GKE) presents a noteworthy advancement in Kubernetes performance, particularly for organizations leveraging cloud-native applications. The adjustments made to the Horizontal Pod Autoscaler (HPA) include several key features and benefits:
– **2x Faster Scaling**: The HPA can now scale workloads up more than twice as quickly, enhancing responsiveness and application performance.
– **Improved Metrics Resolution**: A new fast metrics pathway allows for granular scaling, which leads to timely reactions to workload changes.
– **Support for High-Scale Deployments**: The HPA now accommodates up to 1000 objects, facilitating robust performance for large-scale applications without degradation.
Why this matters:
– **Minimizing Waste**: Users have historically over-provisioned resources due to slow scaling, resulting in financial inefficiencies. The Performance HPA helps optimize resource usage by delivering timely scaling based on real demand.
– **Improving Application Responsiveness**: Quick scaling capabilities mean applications can better meet fluctuating user demands, resulting in an enhanced experience for end users.
– **Increasing Operational Efficiency**: This new profile lessens the burden of manual scaling operations, streamlining processes and reducing potential errors or delays.
Endorsements from customers like Spotify highlight the effectiveness of this enhancement, with a noted improvement in scaling speed during tests with numerous HPA objects.
Actionable Insight:
– GKE users are encouraged to adopt the Performance HPA feature to realize substantial improvements in both performance and operational efficiency. The implementation process is straightforward, requiring only a single command for opt-in, demonstrating the ease of access to such powerful new features.