Browse Skills

Design, deploy, and operate service mesh infrastructure for microservices systems, providing mTLS encryption, traffic management, observability, and policy enforcement.

Designs Infrastructure as Code architectures using Terraform, Pulumi, or CDK with module patterns, state management strategies, drift detection, GitOps workflows, and multi-environment promotion.

Architects production-grade Kubernetes deployments with cluster design, workload management, autoscaling, security hardening, deployment strategies, and operational excellence.

Expert cloud cost optimization advisor that helps organizations reduce and manage cloud spending using FinOps principles, right-sizing strategies, reserved instance planning, and cost allocation frameworks across AWS, Azure, and GCP environments.

Designs and implements automated release pipelines using semantic versioning, Conventional Commits, and tools like semantic-release and Changesets. Covers changelog generation, branch-based release strategies, and multi-target publishing to npm, PyPI, and container registries.

Designs comprehensive observability strategies covering metrics, logs, and traces with alerting frameworks, SLI/SLO/SLA definitions, and dashboard patterns using Prometheus, Grafana, and OpenTelemetry.

Guides developers through setting up and managing Git worktrees for parallel feature development, AI-agent workflows, emergency hotfix isolation, and code review with local testing. Covers worktree lifecycle management, cleanup protocols, directory structure conventions, and integration with modern development patterns.

Deploy, optimize, and operate web applications on Vercel with production-grade configuration, serverless function tuning, edge caching, security hardening, and cost optimization.

Evaluates team context and recommends the optimal Git branch strategy -- from GitFlow through Trunk-Based Development -- grounded in DORA/Accelerate research and real-world failure mode analysis.

Apply SRE error budget principles to frontend applications — define client-side SLIs/SLOs, implement burn rate alerting, and use error budgets to balance feature velocity with frontend reliability.

Generates structured, blameless post-mortem documents from incident data following Google SRE methodology. Enforces psychological safety principles, validates action items for owner and deadline completeness, identifies systemic root causes rather than individual blame, and produces publication-ready post-mortems with timeline reconstruction, impact quantification, contributing factor analysis, and trackable corrective actions.

Optimize surface-mount technology production line performance through systematic OEE analysis, six big losses reduction, changeover optimization, and first pass yield improvement using TPM methodology and electronics manufacturing standards.

Structured triage protocol for production system failures based on Google SRE practices and observability-driven methodology. Guides engineers through symptom scoping, service localisation via distributed traces, hypothesis ranking, mitigation evaluation, and structured incident documentation. Reduces Mean Time to Resolution by enforcing systematic investigation over ad-hoc troubleshooting.