Eight microservices on EKS, CloudWatch logs with no trace IDs, and a 45-minute MTTD on every payment incident. We instrumented the full stack with OpenTelemetry Collector, Grafana Tempo, and auto-instrumentation β and found an N+1 query that had been adding 200ms to every payment for months.
A fast-growing DeFi startup brought us in to harden their stack before a Series A. We found the typical patterns of a team that prioritized shipping over security β exposed credentials in CI, permissive network rules, and a few blockchain-specific gaps. Here's every finding and every fix.
We built an autonomous SRE agent that connects to Datadog, Kubernetes, AWS, and Cloudflare simultaneously β then gave it RAG access to every runbook, post-mortem, and line of source code the company ever wrote. MTTR dropped from 45 minutes to 8. Here's the architecture.
In high-traffic news environments, traffic arrives in seconds and Cluster Autoscaler reacts in minutes. The only way out is to pre-scale before the spike β using the editorial CMS as your signal. Here's the full pattern: CMS webhooks, KEDA, and Karpenter.
We replaced Cluster Autoscaler with Karpenter, moved 80% of workloads to Spot, and implemented scale-to-zero for non-critical services. Monthly bill went from $47K to $14K.
We built an AI agent that reads logs, correlates traces, and suggests fixes before the on-call engineer finishes their coffee. Here's exactly how we did it.
We built a real-time cost visibility dashboard with Grafana, Prometheus, and custom exporters. Now every team sees exactly what they spend β and they started caring.
A healthcare SaaS was spending $38K/month on AWS with no idea where the money went. We audited everything, implemented 12 changes, and brought it down to $18K. Here's the full breakdown.