Assess the systems behind software delivery.
Assess platform engineering, reliability, DevOps, FinOps, and production AI. Each assessment shows what to inspect, what evidence to collect, what good looks like, and how to improve it.
Platform Engineering
Golden paths, platform APIs, GitOps, and secure self-service.
- Platform product strategy grounded in developer journeys.
- Golden paths, portals, APIs, and ephemeral environments.
- GitOps promotion, drift control, and progressive delivery.
- Workload identity, policy as code, and measurable adoption.
Reliability Engineering
Production readiness, SLOs, change safety, and resilience.
- User-journey SLOs tied to release and product decisions.
- OpenTelemetry, continuous profiling, and signal quality.
- Production readiness, progressive verification, and safe change.
- Incident learning, dependency resilience, and toil reduction.
DevOps Modernization
Fast feedback, trusted delivery, and secure software supply chains.
- Team Topologies-aligned flow and ownership.
- GitOps, progressive delivery, and continuous verification.
- SBOMs, provenance, signing, and policy-enforced promotion.
- DORA and flow metrics used to improve systems, not rank people.
FinOps & Cost Optimization
Cloud and AI unit economics, allocation, and optimization.
- FOCUS-normalized billing and allocation quality.
- Unit economics across cloud, Kubernetes, observability, and AI.
- Capacity forecasting, commitments, and rightsizing automation.
- Savings tracked against billing evidence and accountable owners.
AI Engineering & AIOps
Agents, context, evals, observability, and bounded automation.
- Coding agents, reusable skills, MCP tools, and context systems.
- Model gateways, RAG, structured evals, and release quality gates.
- LLM and agent traces spanning prompts, tools, cost, and outcomes.
- Bounded operational agents with approvals, budgets, and audit logs.
The Methodology
Evidence-led discovery, thin slices, and measurable outcomes.
- Interviews plus workflow, system, and value-stream evidence.
- Baseline constraints before prescribing tools.
- Thin-slice delivery before broad rollout.
- Decision records, outcome reviews, and adaptive roadmaps.
How to use these assessments
Start with evidence. Find the constraint. Ship a thin slice.
Observe the real journey
Combine interviews with workflow traces, system data, incidents, cost, and risk.
Fix the constraint
Prioritize the bottleneck, not the loudest stakeholder or newest product category.
Expand what works
Test one end-to-end slice, compare it with the baseline, then decide whether to expand.
Platform playbook
Practical defaults, failure modes, and copyable checks
Filter by layer, search the collection, and copy the useful part from the full playbook.