Delivery lead time refers to the delay between a code change being entered into version control and that change being deployed in production. It starts when code is merged to the main branch and ends when the change is fully deployed and observable in production.
Delivery lead time encompasses build, test, deploy, and release gates, such as canary or feature flag flips. The cycle repeats with every commit, forming a tight loop of idea → code → customer.
A long lead time hides risks, slows feedback, and allows defects to pile up. Shortening the delivery time gives engineers faster validation and provides quicker value to the business.
Measuring Lead Time in Practice
Start by adding two timestamps to your pipeline logs: one at merge, one after production health checks pass. Store those events in any time series store or even a plain CSV; simple is fine.
Calculate the difference for every commit and chart p50, p90, and p99 so spikes stand out. A tiny shell snippet can do the math:
awk -F, '{print $3-$2}' lead_times.csv | sort -n | datamash median 1 q90 1 q99 1
Review the graph in each retro. If numbers drift upward, pick the biggest delay and apply the fixes listed earlier.
Key Metrics Around Lead Time
Cycle Time vs. Lead Time
- Cycle time measures the duration from the first line of code to merge.
- Delivery lead time measures from merge to production.
- Teams often mix the two and misdiagnose the cause of delays.
- Track both together. Cycle time vs. lead time charts reveal whether waiting happens in development or in the delivery path.
- Clear visibility keeps debates factual.
Deployment Frequency and Delivery Time
- Frequent deploys keep batch size small.
- Smaller batches limit test scope, make rollbacks trivial, and surface integration issues within minutes.
- Aim for at least one production deploy per service per workday.
Common Causes of a Long Lead Time
- Manual approvals can take hours. Turn the rules into code that checks tests, ownership, and risk in seconds.
- Monolithic test suites run serially and grow without pruning. Split tests into smaller groups. Run slow tests at night.
- Shared test environments build queues by keeping teams lined up for the same staging cluster. Create a fresh, throw-away environment for each build with infrastructure-as-code.
- Configuration drift triggers an emergency rollback, resulting in failed deployments. Keep configs in code and apply them the same way every time.
- Snowflake release steps mean each service has its own script, so only the person who wrote the script can debug it. Use one standard pipeline template for all services.
These problems stack up. Each issue multiplies the others, turning seconds into hours and creating an unacceptably long lead time.
Practical Ways to Shorten Delivery Time
- Parallel builds: Build each module on its own runner. A 12-minute build can be reduced to 4 minutes.
- Incremental tests: Run unit tests on every commit. Run heavy integration tests only when a tag like needs_integration is set.
- Progressive delivery: Ship to 1% of traffic first (canary). If it stays green, move to 100%. This lets you deploy many times a day.
- Automated rollback: deploy rollback <sha> returns to the last good version in under a minute. Less fear means more deployments.
- Lean approvals: Allow small, low-risk changes to bypass human review. Keep humans for security-critical code.
Apply one fix at a time and watch the numbers. As each bottleneck is eliminated, your delivery lead time will shrink and remain predictable.
How Platform Engineering Speeds Delivery Lead Time
A platform in software development refers to the shared tooling, scripts, and cloud services that every team uses. Platform engineering builds and runs this shared layer, allowing product teams to avoid repeating the same work. Typical platform engineering tools include:
- Reusable CI/CD templates: one YAML file works for every repo.
- Secure base images: patched OS and language runtimes ready to pull.
- Self-service environments: a single command spins up a test stack.
With one team owning the “paved path,” horizontal upgrades become easy: faster runners, parallel test grids, and on-demand clusters appear once and help everyone.
Platform Engineer vs. Software Engineer
- Platform engineers build and maintain the paved path.
- Software engineers use that path to ship features.
Clear roles stop blame games and make ownership obvious. When the path is smooth, delivery lead time and its variations drop across all services.
Conclusion
Delivery lead time converts the abstract idea of “speed” into a single, observable metric that links engineering practice to customer value. By measuring it, identifying bottlenecks, and applying practical fixes, teams reduce risk, accelerate feedback, and ship features with confidence. Start small: instrument the pipeline, identify the worst delay, automate it, and watch delivery time decrease week by week.
