Cloud Cost Management: Scenario-Based Questions

Cost spikes in cloud infrastructure can result from unoptimized usage, idle resources, or configuration errors. A cost optimization strategy involves analysis, automation, and continuous monitoring.

🔍 Investigation Steps

• Review cost breakdown by service using tools like AWS Cost Explorer, Azure Cost Analysis, or GCP Billing Reports.
• Check for recent deployments, spikes in traffic, or misconfigured autoscaling.
• Filter high-cost services (e.g., RDS, EC2, EBS, S3, egress) by region, tag, and time period.
• Use tagging policies to identify team/feature/environment-level spend.

🧰 Optimization Techniques

• Rightsize Instances: Downsize overprovisioned EC2s, VMs, or containers.
• Turn Off Idle Resources: Schedule development clusters to shut down outside work hours.
• Reserved/Spot Instances: Use Reserved Instances or Spot/Preemptible for non-critical workloads.
• Storage Cleanups: Delete unused EBS volumes, orphaned snapshots, or duplicate S3 buckets.
• Data Transfer Review: Audit VPC peering, inter-region transfers, or CDN misconfigurations.

📊 Monitoring and Automation

• Enable billing alerts and budgets with thresholds.
• Use tools like CloudHealth, AWS Trusted Advisor, or GCP Recommender for savings insights.
• Run scheduled cleanup jobs or automated policies (e.g., with Lambda, GCP Scheduler).

✅ Best Practices

• Enforce tagging and cost center policies from day one.
• Review cost reports monthly as part of operational rituals.
• Use Infrastructure as Code to track unused or forgotten resources.

🚫 Common Pitfalls

• Leaving POCs and test environments running indefinitely.
• Misconfigured autoscalers leading to sudden overprovisioning.
• Ignoring network costs in multi-region architectures.

📌 Real-World Insight

Cloud cost optimization is not a one-time task — it’s an ongoing discipline. Teams that monitor spend daily, enforce tagging, and apply savings plans avoid budget surprises and increase operational efficiency.