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  1. KEDA | Kubernetes Event-driven Autoscaling

    With KEDA, you can drive the scaling of any container in Kubernetes based on the number of events needing to be processed. KEDA is a single-purpose and lightweight component that …

  2. KEDA | Getting Started

    Welcome to the documentation for KEDA, the Kubernetes Event-driven Autoscaler. Use the navigation bar on the left to learn more about KEDA’s architecture and how to deploy and use …

  3. KEDA Concepts

    What is KEDA? KEDA is a tool that helps Kubernetes scale applications based on real-world events. It was created by Microsoft and Red Hat. With KEDA, you can adjust the size of your …

  4. Deploying KEDA

    This command installs KEDA in a dedicated namespace (keda). You can customize the installation by passing additional configuration values with --set, allowing you to adjust …

  5. Scalers - KEDA

    KEDA External Scaler that can obtain metrics from OTel collector and use them for autoscaling.

  6. Scaling Deployments, StatefulSets & Custom Resources - KEDA

    With KEDA you can scale any workload defined as any Custom Resource (for example ArgoRollout resource). The scaling behaves the same way as scaling for arbitrary Kubernetes …

  7. Setup Autoscaling with KEDA

    Follow the KEDA installation guide carefully, including any prerequisites specific to your Kubernetes setup. The installation guide provides instructions for different installation methods …

  8. AWS SQS Queue - KEDA

    When identityOwner set to operator - the only requirement is that the KEDA operator has the correct IAM permissions on the SQS queue. Additional Authentication Parameters are not …

  9. The KEDA Blog

    May 4, 2023 · In this blog post; we will briefly explain the areas that need to be considered, how KEDA aims to make application auto-scaling simple, and why Alibaba Cloud’s Enterprise …

  10. FAQ - KEDA

    KEDA stands for Kubernetes Event-driven Autoscaler. It is built to be able to activate a Kubernetes deployment (i.e. no pods to a single pod) and subsequently to more pods based …