Kedify | AWS SQS

Use events from AWS SQS to trigger autoscaling with Kedify and KEDA

Amazon Web Services Simple Queue Service is a fully managed message queuing service that allows you to decouple and scale microservices, distributed systems, and serverless applications.

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It enables asynchronous communication and is designed to be highly scalable and simple to use in a broad range of scenarios. The integration with KEDA enhances this capability by enabling fine-grained, event-driven autoscaling that responds dynamically to the fluctuating demands on message processing, ensuring optimal resource utilization and performance without manual intervention.

Featured Use Cases

Scenario:

E-commerce platforms need to dynamically scale services that process customer orders during high traffic times like sales or promotions.

AWS SQS Scaler Usage:

Automatically scale based on the number of messages in the SQS queue, which represent incoming orders waiting to be processed.

KEDA Usage:

KEDA scales order processing backends by monitoring the SQS queue length, ensuring that each order is processed quickly even during peak times.

Get Started

                      apiVersion: keda.sh/v1alpha1
kind: ScaledObject
metadata:
  name: order-processing-scaledobject
  namespace: default
spec:
  scaleTargetRef:
    name: order-processor
  minReplicaCount: 1
  maxReplicaCount: 100
  triggers:
  - type: aws-sqs-queue
    metadata:
      queueURL: https://sqs.eu-west-1.amazonaws.com/account_id/order-queue
      queueLength: "10"
      awsRegion: "eu-west-1"

Scenario:

Handling real-time data for applications like social media analytics, where events must be processed as they come in.

AWS SQS Scaler Usage:

Scale services based on the volume of events that are queued in SQS, requiring rapid processing to provide timely insights.

KEDA Usage:

Utilizes KEDA to scale analytical services dynamically, managing large bursts of data and reducing latency in event processing.

Get Started

                      apiVersion: keda.sh/v1alpha1
kind: ScaledObject
metadata:
  name: event-processing-scaledobject
  namespace: default
spec:
  scaleTargetRef:
    name: event-processor
  minReplicaCount: 2
  maxReplicaCount: 50
  triggers:
  - type: aws-sqs-queue
    metadata:
      queueURL: https://sqs.eu-west-1.amazonaws.com/account_id/event-queue
      queueLength: "20"
      awsRegion: "eu-west-1"

Scenario:

Microservices architectures require decoupled services where components communicate through messages, often necessitating dynamic scaling based on workload.

AWS SQS Scaler Usage:

Efficiently scales microservices based on the load characterized by message queues in SQS, supporting decoupled architecture and improving system resilience.

KEDA Usage:

KEDA adjusts the number of service instances in real-time by monitoring the length of SQS queues, ensuring optimal performance and fault tolerance.

Get Started

                      apiVersion: keda.sh/v1alpha1
kind: ScaledObject
metadata:
  name: microservice-scaler
  namespace: default
spec:
  scaleTargetRef:
    name: microservice-handler
  minReplicaCount: 1
  maxReplicaCount: 30
  triggers:
  - type: aws-sqs-queue
    metadata:
      queueURL: https://sqs.eu-west-1.amazonaws.com/account_id/microservice-queue
      queueLength: "5"
      awsRegion: "eu-west-1"

Scenario:

Retail operations require robust systems to manage stock levels efficiently, particularly when dealing with multiple suppliers and fluctuating demand.

AWS SQS Scaler Usage:

Automates inventory adjustments and reordering processes by scaling services that monitor and react to messages related to stock changes.

KEDA Usage:

By tracking messages in SQS related to inventory levels, KEDA ensures that inventory management systems can dynamically adjust to changes, preventing stockouts or overstocking.

Get Started

                      apiVersion: keda.sh/v1alpha1
kind: ScaledJob
metadata:
  name: inventory-management-job
  namespace: default
spec:
  jobTargetRef:
   template:
      spec:
        containers:
        - name: inventory-handler
          image: inventory-management-system:latest
          command:
          - 'python'
          - '-u'
          - 'manage_inventory.py'
  maxReplicaCount: 10
  triggers:
  - type: aws-sqs-queue
    metadata:
      queueURL: https://sqs.eu-west-1.amazonaws.com/account_id/inventory-queue
      queueLength: "15"
      awsRegion: "eu-west-1"