Workflow orchestration build vs buy should be decided on three numbers: your 3‑year engineering budget for runtime code, the monthly state-transition volume, and how many months of durable timers you need. Buy until those three values cross an inflection point where a dedicated runtime team is cheaper than vendor fees plus integration.
A single senior backend engineer in the U.S. costs roughly $180,000/year fully loaded. A 3‑engineer team running an in-house orchestrator for three years is therefore about $1.62M in salary alone. Compare that to managed service bills: AWS Step Functions at 10M state transitions/month costs roughly $250/month; paid orchestration platforms for production clusters commonly land between $40k and $300k/year depending on throughput and retention.
Direct answer: Workflow orchestration build vs buy is buy for most teams. If you run under ~100M state transitions/month, don't require sub-10ms task handoff latency, and your workflows need less than 3 months of durable retention, a managed product (AWS Step Functions, Temporal Cloud, Dagster Cloud, or MWAA) is cheaper and safer; build only when you need fine-grained control, portability, or expect >$1M/yr ops spend on orchestration.
Workflow orchestration build vs buy: TCO, latency, and lock-in
TCO arithmetic is simple and decisive. A 3‑engineer team over 3 years costs $1.62M in salaries. Add infra (3–6 EC2 instances, storage, HA, backups) and you cross $1.8M. Temporal Cloud or Dagster Cloud at mature scale runs between $40k and $300k/year depending on throughput and retention. AWS Step Functions at 10M transitions/month costs ~$250/month; at 300M transitions/month it costs ~$7,500/month or $90k/year.
Latency and SLOs are a second axis. Amazon Step Functions standard workflows introduce tens to hundreds of milliseconds per state transition; Step Functions Express targets sub-100ms for simple flows. Temporal and self-hosted Cadence give sub-20ms local scheduling in optimized deployments but require provisioning to hit 99.99% global latency. If you need sub-50ms task dispatch at the 99.9th percentile, you're in the 'build' lane or you must pay for high-end managed clusters.
Operational complexity and migration cost are real dollars. Rewriting 200 workflow definitions from Step Functions JSON + Lambda to Temporal prototypes takes 6–12 engineer-weeks. Two engineers for six weeks at $180k/year costs about $41k. Add testing, chaos runs, and staging and the engineering bill approaches $70k before you touch production cutover.
Feature delta matters more than license cost. Temporal and Step Functions both provide retries, timers, versioning, and signals; Temporal exposes richer local debugging, code-native workflows, and long-running workflows measured in months. Airflow and Dagster target batch-oriented DAGs with different execution semantics. If you have user-facing orchestrations with sub-second expectations, Temporal or Step Functions is the right primitive; for ETL pipelines that run hourly, managed Airflow or Dagster Cloud is cheaper.
Buy orchestration until the math forces you to own runtime: the moment your annual ops spend on orchestration plus migration risk beats 2–3 senior engineers’ salary, build.
What this means for a CTO or technical founder
You should prioritize vendor evaluation against five vectors: cost per state transition, durable-timer limits, latency percentiles, observability integrations, and migration path. For example, AWS Step Functions integrates with CloudWatch and X‑Ray; Temporal Cloud offers SDK-first observability and visibility APIs; Dagster Cloud connects to metadata stores and asset-aware lineage. Pick the vendor whose telemetry matches your SLOs.
Define your breakpoints in dollars and latency. If your workflows generate <100M state transitions/month and average end-to-end latency budgets are seconds rather than tens of milliseconds, buy. If you expect to pay >$250k/year in managed fees because of scale, and you have a platform team of 3+ engineers willing to own a runtime, build. That trade-off flips at roughly $1.5M in cumulative vendor spend vs. $1.62M for a 3‑engineer build over three years.
Treat portability as insurance, not a design principle. Lock-in cost is migration engineering: converting workflow definitions, reimplementing signals, and reconciling observability. Budget that migration at 1–3% of your three‑year SaaS spend when you buy, and at 20–30% of one-year team cost when you build.
Decision checklist — when to build, when to buy
- Buy if your monthly state transitions are under 100M, your latency SLO is >100ms, and your durable timers are under 30 days. Managed services are typically <$100k/year in this band.
- Buy if observability integrations (CloudWatch, X‑Ray, Datadog) and managed scale are your priority; the integration cost of rolling your own is 4–8 engineer-weeks per endpoint.
- Build if you need sub-50ms dispatch at scale, expect >$1M/year in orchestration expense, or require vendor-specific behavior not exposed by the market products. Building is defensible when you can amortize a 3‑engineer team across multiple platform capabilities.
- Build if you require strict portability across clouds for regulatory reasons; otherwise, accept the migration tax and move faster on product.
- Always prototype with production data. Implement 3 representative workflows on the candidate managed service and measure tail latency, developer ergonomics, and the runbook-edit cycle before deciding.
Key takeaways:
- Buy for most startups: a managed orchestrator costs <$100k/year until you reach very high throughput or extreme latency needs.
- Build when annual vendor bills approach the salary of 2–3 engineers and you need control over latency, scheduling semantics, or portability.
- Budget migration at $40k–$120k per major migration project; that’s the true lock-in cost, not an opaque vendor term sheet.
- Use prototype + metrics as the final arbiter: measure transitions/month, 99th-percentile dispatch latency, and on-call MTTR before you choose.
If you adopt a managed service, instrument aggressively for the metrics that change the decision: transitions/month, active workflows, median and 99.9th-percentile task dispatch latency, durable-timer retention, and monthly vendor spend. These five numbers let you replay the TCO every quarter and catch the inflection before it costs you months of rework.
