Every engagement ships these as concrete artifacts you own — not slides, not hand-waving.
REST or GraphQL with OpenAPI / SDL contracts, generated SDKs, versioned, rate-limited, observable. Your frontend team gets typed clients on day one.
Postgres-first (with read replicas, partitioning, and pgvector if you need it), Redis for cache / queues, careful migrations with zero-downtime patterns.
Terraform (or CDK / Pulumi if you prefer). Multi-environment, secrets in AWS SM / Vault, blue-green deploys, automated DR drills.
Logs, metrics, traces (Datadog / Grafana / Honeycomb), error budgets, SLO dashboards. Alert fatigue prevention is part of the design.
Sequence diagrams, capacity model, failure modes catalogue, security review (data-flow, OWASP, OAuth flows). Get this right, save 6 months later.
API + DB + jobs + queues, with PR-level integration tests. Continuous deploy to staging from day one.
Load test (k6 / Artillery), chaos test (kill pods, drop connections), security scan, runbooks.
Blue-green rollout, monitor 7 days, retro, hand-off.
Best-in-class where it matters; boring and battle-tested everywhere else.
Greenfield builds quote per project after architecture review. Ongoing platform work runs as a pod retainer (1 staff eng + 2 senior + 1 SRE). Cloud spend passthrough at cost.
Modular monolith first, services later. Premature microservices is the most expensive mistake an early-stage product can make. We'll only break out a service when there's an actual scaling, deploy-cadence, or team-boundary reason.
Postgres, almost always. Document data fits fine in JSONB. Real ACID transactions and a mature ecosystem are worth more than the schema flexibility you think you need.
Yes — strangler-fig pattern, feature-flagged cutover, parallel-run validation. We've done it for monolith-to-services, on-prem-to-cloud, and Mongo-to-Postgres migrations.
Standard for any retainer. The first quarter typically lands a 20–40% AWS / GCP cost reduction — Reserved Instances / Savings Plans, right-sizing, S3 lifecycle, GPU spot pools.