Karpenter
https://dev.to/techwithpatil/kubernetes-cost-saving-secrets-a-50-workload-cost-reduction-story-5gph
Here’s a structured explanation, separating Kubernetes migration and Karpenter implementation:
Kubernetes Migration
1. Achievement (What You Did)
"I successfully migrated our Docker-based application to Kubernetes, improving scalability, reliability, and resource efficiency."
2. Challenges Faced (Problems Encountered)
Handling persistent storage and ensuring data consistency.
Managing service discovery for internal communication between microservices.
Optimizing resource allocation to prevent over/underutilization.
Ensuring zero-downtime deployments and seamless traffic shifting.
3. Solution & Results (How You Solved It & Impact)
Implemented persistent volumes to manage stateful workloads.
Used Kubernetes services for internal networking and DNS resolution.
Fine-tuned resource requests and limits to optimize CPU and memory usage.
Adopted rolling updates with readiness probes, improving uptime from X% to Y%.
✅ Result: The migration improved system scalability, enhanced reliability, and reduced infrastructure costs by Z%.
Karpenter Implementation
1. Achievement (What You Did)
"I implemented Karpenter for dynamic node provisioning in our Kubernetes cluster, leading to better resource utilization and cost savings."
2. Challenges Faced (Problems Encountered)
Configuring IAM roles and permissions for Karpenter to provision nodes securely.
Ensuring efficient node provisioning to match workload demand.
Preventing over-provisioning while avoiding pod scheduling delays.
Handling spot instance interruptions and maintaining high availability.
3. Solution & Results (How You Solved It & Impact)
Set up the correct IAM roles and Karpenter controller permissions.
Defined provisioner configurations to optimize instance selection.
Implemented scaling policies, reducing unnecessary node allocations by X%.
Used Node affinity & interruption handling to maintain workload stability.
✅ Result: Improved cost efficiency, reduced pod scheduling latency, and optimized resource utilization across the cluster.
This clear separation helps you explain both contributions effectively. Let me know if you want to add specific metrics or further refinements! 🚀
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