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To find what is slowing a CI/CD pipeline, trace a representative change from version control to release and measure both elapsed time and time spent doing work at every step. The difference reveals where waiting may be occurring; tracking rework shows where work is being sent back for correction. Treat both as leads to investigate, not proof of a cause. Then check whether any proposed change improves delivery without harming reliability, security, or recovery.
Measure the whole path, not just build time
A change can spend time in review queues, waiting for a runner or test environment, undergoing security checks, or awaiting a manual release decision. A build-duration chart covers only one part of that path. DORA recommends recording total elapsed time and value-add time for each process from version control through release, then examining the difference between them. DORA’s continuous-delivery guidance describes value-stream mapping as a way to discover bottlenecks.
Choose one representative change and agree on the measurement boundaries before collecting data. For example, define the start as when the change enters version control and the end as when it is released. Follow the actual route it takes, including automated and manual testing, security review, change management, environment provisioning, and release. Record elapsed time, hands-on work time, and returns for correction at each process.
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- Elapsed time: the time from when work enters a process until it leaves, including time waiting.
- Value-add time: the time people or systems actively spend doing the process work.
- Rework: how often work returns for correction because it was not done right the first time. DORA calls the percentage of work completed accurately on the first attempt percentage complete and accurate, or %C/A.
A large elapsed-time/value-add-time gap points to waiting or handoffs worth examining. Low %C/A points to rework. Neither measure identifies the root cause on its own: investigate with the people who own the steps before changing a process, architecture, test, environment, or tool.
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Map where the change waits
Draw the route the selected change actually follows, not the idealized workflow in a diagram. Include every team and system that handles it, and mark where it waits, gets retried, or is returned. Review the map with representatives of the connected teams; agree on a desired future-state process and the capacity available to improve it. DORA recommends focusing on processes with long elapsed times and low %C/A. Its guidance on continuous delivery also recommends using value-stream mapping to anticipate bottlenecks.
Source control and review
Measure how long a change waits before review, how long review takes, and whether branches or review queues accumulate. Large batches can make feedback and integration harder to manage. DORA recommends trunk-based development with short-lived branches as a continuous-delivery practice, but measure the actual delay before adopting a workflow change.
Build and test
Separate time waiting for a runner or other resources from build execution, test execution, retries, and failure diagnosis. Check whether tests are reliable, whether they provide fast feedback, and whether suitable test data is available. DORA identifies reliable automated tests, continuous testing, and sufficient test data as important practices. A systematic review of 69 papers published through June 1, 2016, grouped continuous-practice approaches that included reducing build and test time, improving result visibility, and supporting automated testing; it is a historical taxonomy, not evidence of current tool adoption. The review by Shahin, Babar, and Zhu explains its scope.
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Include security testing, compliance review, and change approvals in the map rather than treating them as invisible overhead. DORA recommends pervasive security and notes the particular importance of testing and security practices in regulated and safety-critical domains. The goal is to improve flow while retaining the controls the service and its context require.
Environments and release
Check whether work waits for an environment, depends on another service, requires a database change, or stops at a manual release step. DORA recommends deployment automation, managed database changes, monitoring and observability, and loosely coupled teams as continuous-delivery practices. A delay that appears at deployment may originate in a dependency or unavailable environment earlier in the route, so follow the handoff rather than assuming the last visible step is the cause.
Handoffs across teams
Record when ownership changes and how long the change waits between teams. Pipeline delays can cross organizational boundaries; the map should include the people who own the steps. A handoff is a hypothesis to inspect, not automatically a defect: measure its elapsed time and understand why it exists before attempting to remove or automate it.
Pair stage measurements with delivery and stability outcomes
Stage-level timing explains where delay occurs. Outcome measures help determine whether a change improved delivery without making production less stable. Track a locally consistent set that includes lead time for changes, deployment frequency, change failure rate, time to restore service, and reliability or service objectives.
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Metric names and boundaries vary across reports and implementations. DORA’s 2021 report page describes five measures used for performance clusters: deployment frequency, lead time for changes, time to restore service, change failure rate, and reliability. DORA’s Core Model and contemporary product documentation commonly present four delivery metrics alongside reliability or service-level objectives in a separate role. State which definitions and boundaries your team uses rather than treating one list as timeless. DORA’s 2021 report summary documents its measures.
Implementation details can affect what a metric means. For example, GitLab’s DORA metrics documentation describes deployment-frequency and lead-time calculations based on GitLab CI/CD and merge requests, and notes incident-data requirements for failure and restoration metrics. Those are product-specific implementation details, not universal definitions.
Use the same boundaries before and after an intervention. If a test change shortens pipeline elapsed time but raises change failures or restoration time, it has not delivered an unambiguous improvement. Reliability and security remain part of the decision, not costs to ignore in pursuit of speed.
Choose an intervention that addresses the measured delay
Do not select a process or tool change simply because it is fashionable or because a stage looks slow in isolation. Compare candidates against the evidence from the map:
- Which measured wait or rework does the change target?
- Will it reduce elapsed time, value-add work, or both?
- What could it do to change failures, recovery time, reliability, or security?
- Will it work with the existing toolchain, or introduce another handoff?
- What team, process, or architecture changes does it require?
Tool adoption alone does not guarantee faster delivery. DORA notes that pipeline implementation often accompanies process and architecture changes. The CD Foundation’s 2024 report summary reports an association between CI/CD tool use and better performance, while also reporting worse performance when developers used multiple tools of the same form; interoperability is offered as a likely explanation, not a proven cause. The report does not establish a causal ranking of products. The CD Foundation / SlashData report summary includes its findings and methodology.
The same source says 83 percent of developers reported being involved in DevOps-related activities. Its methodology says the report drew on six Developer Nation surveys from Q3 2020 to Q1 2023, which together reached more than 125,000 respondents worldwide; the latest survey data was collected from December 2022 through February 2023. The combined reach is not the report’s analytic sample size, and the percentage does not measure pipeline speed.
Likewise, Google Research’s bibliographic record says the 2024 DORA report heard from more than 39,000 professionals. That is participation in the report, not a measure of CI/CD pipeline duration. The Google Research record provides the report details.
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- Set boundaries: Define where the measured change begins and ends, and agree on consistent local definitions for stage and outcome metrics.
- Trace the workflow: Follow a representative change through every automated and manual process, team, and environment it actually encounters.
- Capture a baseline: Record elapsed time, value-add time, and correction returns at each stage, alongside the chosen delivery and stability outcomes.
- Investigate the largest gap: Ask the process owners why elapsed time exceeds active work time. Check for queueing, dependencies, retries, resource limits, approvals, or other explanations rather than assuming one.
- Choose a targeted change: Identify the measured delay or rework it is meant to address, the people and process changes required, and the potential effects on security and production outcomes.
- Measure again: Use the same boundaries and definitions after the intervention. Keep it only if the evidence supports better flow without unacceptable deterioration in reliability, failures, recovery, or security.
The 2024 DORA findings summary highlights user-centricity and stable priorities, and describes potential tradeoffs involving stability or throughput for AI and internal developer platforms. These findings are a reason to evaluate interventions against outcomes rather than assume that a new platform or faster automation necessarily helps. DORA’s 2024 findings summary was last updated April 13, 2026.
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