KEDA (Kubernetes Event-driven Autoscaling)
Posted on September 29, 2023
2 minutes • 238 words • Other languages: Deutsch
KEDA (Kubernetes Event-driven Autoscaling)
Definition
KEDA, short for Kubernetes Event-driven Autoscaling, is an open-source project that extends the capabilities of Kubernetes to enable automatic scaling of containerized applications based on external events or custom metrics.
Key Concepts
Event-Driven Scaling
KEDA allows Kubernetes clusters to scale applications dynamically in response to various types of events, such as message queues, HTTP requests, or custom-defined triggers. This ensures that resources are allocated efficiently to meet demand. At the time this glossar entry was written, there are more than 60 scalers available.
Custom Metrics
In addition to event-driven scaling, KEDA supports autoscaling based on custom metrics defined by developers. This flexibility allows applications to scale based on specific performance indicators, ensuring optimal resource utilization.
Scalability
KEDA enhances the scalability of applications in Kubernetes by enabling them to adapt to changing workloads, reducing the risk of underprovisioning or overprovisioning resources.
Benefits
Resource Efficiency: KEDA ensures that resources are allocated as needed, preventing overprovisioning and reducing operational costs.
Optimized Performance: Applications can automatically scale to handle increased workloads, maintaining optimal performance.
Customization: Developers have the flexibility to define custom scaling metrics tailored to their application’s unique requirements.
Improved Responsiveness: Event-driven scaling allows applications to respond quickly to fluctuations in demand.
Use Cases
KEDA is valuable in scenarios where applications need to scale rapidly in response to events, such as processing messages from queues, handling bursty traffic, or managing batch processing jobs in Kubernetes clusters.