Update result-deployment.yaml

[sharique-42]

Summary by CodeRabbit

• New Features

  • Increased the number of application instances from 1 to 3, improving availability and scalability.

• Bug Fixes

  • Enhanced fault tolerance by allowing multiple instances to handle requests and recover from failures.

[coderabbitai]

Walkthrough

The changes involve updating the Kubernetes deployment specification for the result application by increasing the number of replicas from 1 to 3. This adjustment allows for greater availability and scalability of the application, enabling it to handle increased loads and improve fault tolerance.

Changes

File	Change Summary
k8s-specifications/result-deployment.yaml	Modified replicas: 1 to replicas: 3

Poem

🐰 In the meadow where bunnies play,
Three little instances hop and sway.
Scaling high, they stand so tall,
Ready to catch each request and call.
With fault tolerance, they’ll never fall! 🌼

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[coderabbitai]

Actionable comments posted: 0

Outside diff range and nitpick comments (1)

k8s-specifications/result-deployment.yaml (1)

8-8: Looks good! The replica count update improves availability and scalability.

Increasing the replica count from 1 to 3 is a positive change that enhances the application's ability to handle higher loads and provides fault tolerance. With multiple instances running concurrently, the application can continue serving requests even if one or more instances fail.

A few additional considerations:

1. Resource Allocation: Ensure that the cluster has sufficient resources (CPU, memory) to accommodate the increased number of replicas. Monitor the resource utilization and adjust the resource requests and limits if necessary.

2. Application Design: Verify that the application is designed to handle concurrent requests and maintain data consistency across replicas. If the application relies on shared state or resources, ensure that appropriate synchronization mechanisms are in place.

3. Deployment Strategy: Consider the deployment strategy for rolling out the updated replica count. Strategies like Rolling Update or Blue/Green Deployment can help ensure a smooth transition without downtime.

4. Monitoring and Scaling: Set up monitoring and alerting to track the performance and health of the replicas. Utilize Kubernetes' Horizontal Pod Autoscaler (HPA) if dynamic scaling based on CPU or custom metrics is desired.

Review details

Configuration used: CodeRabbit UI
Review profile: CHILL

Commits

Files that changed from the base of the PR and between 17c12ea and 5ee11d8.

Files selected for processing (1)

• k8s-specifications/result-deployment.yaml (1 hunks)