Case Studies

Zero-downtime MySQL migration at TB scale

MySQL Kubernetes Migration

The Problem A fintech SaaS company was running a 2TB MySQL database on aging bare metal servers. The infrastructure was nearing end-of-life. Backups were manual and untested. There was no failover — if the primary went down, the platform went down. Migration had to happen soon, but the cost of downtime was unacceptable.

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Kubernetes cost reduction: 40% less cloud spend

Kubernetes AWS Cost Optimization

The Problem An e-commerce platform was spending $18,000/month on an AWS EKS cluster. The infrastructure team knew costs were high, but couldn’t identify where the waste was. No autoscaling was configured — nodes ran at 20% utilization. Reserved instances weren’t in use. Nobody had a clear picture of cost per workload.

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MySQL incremental backups at scale: From 12-hour backups to 30-minute operations

MySQL Backups Database Reliability Cost Optimization

The Problem A data-heavy startup was running 2TB of MySQL in production. Full backups took 12+ hours and failed regularly. The team had no reliable way to test recovery — full restoration took days. Backup failures went undetected until needed. The cost of managed backup solutions (Kasten, AWS DMS) was $150+/month just for backups.

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Kubernetes node autoscaling: Handling unpredictable traffic spikes without manual intervention

Kubernetes Autoscaling Operations Cost Optimization

The Problem A real-time data platform handled unpredictable traffic: election updates, breaking news, market announcements created sudden spikes of millions of requests in minutes. The team tried Horizontal Pod Autoscaler (HPA) to scale replicas, but it failed.

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