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Use events from Prometheus to trigger autoscaling with Kedify and KEDA

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Prometheus Diagram

Prometheus is an open-source monitoring and alerting system designed for reliability and scalability

It supports service-oriented architectures through a robust data model with time series data identified by metric name and key/value pairs. It collects and stores metrics as time series data.

Featured Use Cases


An e-commerce platform needs to scale its recommendation service based on the number of user interactions to ensure personalized content is delivered quickly.

Prometheus Usage:

user_interaction_count - a custom metric tracking the number of user interactions with the recommendation engine.

KEDA Usage:

Adapt to changing user activity levels. By monitoring user_interaction_count with KEDA and Prometheus, the platform can dynamically scale the recommendation service in response to changing user interaction levels, ensuring personalized content is served efficiently.
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kind: ScaledObject
  name: business-metrics-scaledobject
  namespace: default
    name: recommendation-service
  minReplicaCount: 3
  maxReplicaCount: 25
  - type: prometheus
      serverAddress: http://prometheus.default.svc:9090
      threshold: '1000'
      query: sum(rate(user_interaction_count[5m]))