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CI/CD became production infrastructure for more organizations in 2024: 60% of respondents to the CNCF Annual Survey said they used it in production for most or all applications, up from 46% in 2023. Teams also reported checking in code and releasing more frequently. But adoption alone does not guarantee better delivery: the evidence points to integration, security checks and manageable toolchains as important parts of the picture.
CI/CD adoption moved from aspiration to routine operations
The 2024 CNCF Annual Survey found that 60% of respondents used CI/CD in production for most or all of their applications. In the 2023 survey, 46% reported that level of use. The change suggests CI/CD is no longer confined to pilot projects at many organizations; it is part of how they deliver production software.
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A separate measure points in the same direction, though it covers a different period and respondent base. The Continuous Delivery Foundation (CDF) reported that 83% of developers were involved in DevOps-related activities. Its report draws on six Developer Nation surveys conducted from Q3 2020 to Q1 2023, with more than 125,000 respondents. That long-running survey base should not be treated as a single 2024 snapshot or compared directly with platform telemetry.
How often teams checked in code and released
The CNCF Annual Survey found that 71% of respondents checked in code multiple times a day in 2024, compared with 52% in 2023. The share reporting releases multiple times a day rose from 23% in 2023 to 29% in 2024. These are self-reported survey results, not measurements of every team’s deployment logs.
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Frequent releases can help teams deliver changes in smaller increments, but cadence is not a complete measure of delivery quality. A useful assessment also considers whether changes can be delivered safely, whether failures are detected, and how quickly teams recover. The available figures establish that reported cadence increased; they do not show that every organization became faster or more reliable.
Which CI/CD tools were most widely used?
Among respondents using or testing CI/CD tools in the 2024 CNCF Annual Survey, GitHub Actions had the highest reported usage, followed closely by Argo, Jenkins and GitLab. These are not mutually exclusive market-share figures: organizations can use or test more than one tool, so the percentages do not add up to 100%.
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| Tool | Usage among respondents using or testing CI/CD tools | Year-over-year growth reported by CNCF |
|---|---|---|
| GitHub Actions | 51% | 19% |
| Argo | 45% | 16% |
| Jenkins | 44% | 40% |
| GitLab | 43% | 20% |
| Azure Pipelines | not stated | 3% |
| Flux | not stated | 3% |
The usage percentages and year-over-year growth figures are from the CNCF Annual Survey 2024. The survey figures supplied for Azure Pipelines and Flux give growth but not usage percentages. The growth figures are reported as percentages, not percentage-point changes.
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The 2024 figures do not establish a universal winner. They measure how commonly tools were used or tested, not which one delivered the best results for a particular team. GitHub Actions led reported usage in the CNCF survey, while Jenkins had the largest listed year-over-year growth. Neither fact, by itself, proves better performance, lower cost or a better fit.
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- Managed versus self-hosted: Decide how much of the service and infrastructure your team wants to operate. The CDF found the strongest performance among developers using both managed and self-hosted CI/CD tools, but that association does not mean every organization should combine them.
- Integration and interoperability: Check how a tool works with your source control, deployment process and existing systems. The CDF associated CI/CD tool use with better results across all DORA metrics, while warning that multiple tools of the same form were associated with worse deployment performance, likely because of interoperability challenges.
- Security and code quality: Evaluate whether checks can be incorporated into the workflow, rather than treating them as a separate afterthought. CircleCI reported that its most successful teams used security and code-quality tools in longer production workflows.
- Operational fit: Compare the capabilities your delivery process actually needs, including release cadence, visibility into delivery performance, recovery processes and governance for AI-generated changes. The survey data do not provide a head-to-head comparison of these capabilities across vendors.
- Total toolchain complexity: Account for the work of connecting, maintaining and governing every tool. Adding another system can fill a real gap, but overlapping tools can create integration overhead.
What delivery-performance data can—and cannot—tell you
CircleCI’s 2024 State of Software Delivery report analyzed nearly 15 million data points from teams on its cloud CI/CD platform. It reported throughput growth of 11% across branches and 68% on production branches, and a median error-recovery time of under 60 minutes. These figures describe CircleCI’s platform population; they are not industry-wide averages or a direct comparison with the CNCF survey.
The findings are useful as an example of what can be measured in delivery systems, but they should not be read as a promise that adopting a particular pipeline design will produce the same results. CircleCI also reported that its most successful teams ran longer production workflows and added security and code-quality tools. That observation supports a broader lesson: optimizing delivery means more than minimizing the number of steps in a pipeline.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Security and software-supply-chain controls remain uneven
GitLab’s 2024 Global DevSecOps Report surveyed more than 5,000 professionals. It found that 67% said at least a quarter of their code came from open-source libraries, while 21% reported using a software bill of materials (SBOM). The gap is a warning that widespread use of external code does not automatically mean organizations have equally widespread visibility into software components.
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1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsFor teams reviewing their delivery process, the practical question is whether security and code-quality checks are built into the workflow and whether component information is maintained in a form the organization can use. The report’s figures describe respondents’ reported practices; they do not establish that organizations without an SBOM lack all supply-chain controls.
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GitLab also reported a shift in cloud use among its respondents: the share running less than half of their applications in the cloud fell from 68% in 2023 to 43% in 2024, while the share running at least half in the cloud rose from 32% to 55%. This broader infrastructure change matters to CI/CD because delivery processes must work across the environments where applications actually run; the figures do not imply that cloud adoption alone improves delivery outcomes.
AI is entering delivery workflows, with governance still important
In GitLab’s 2024 Global DevSecOps Report, 78% of respondents said they used or planned to use AI in software development within two years. The same report found that 67% described their software development lifecycle (SDLC) as mostly or completely automated, and 64% wanted to consolidate their toolchains. These findings show interest in AI alongside a desire to reduce complexity; they do not show that AI adoption has already delivered measurable CI/CD gains.
A January 2025 Harness release summarizing a survey of 500 engineering leaders and developers said that 50% of engineering leaders planned to invest in AI for CI/CD. The release also reported that 78% of developers spent at least 30% of their time on manual, repetitive tasks. These are vendor-sponsored survey findings, not a neutral census of the software industry. Harness emphasized governance, validation and security controls for AI-generated code—issues teams should address before allowing generated changes to move through automated delivery without appropriate review.
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The evidence points to a mature but uneven CI/CD landscape. Adoption and reported delivery cadence increased, tools are widely used in overlapping combinations, and AI is attracting investment. At the same time, the CDF’s interoperability warning, GitLab’s SBOM finding and demand for toolchain consolidation show why simply adding automation or another product is not a complete delivery strategy.
Quick Recap
- Measure release frequency alongside reliability and recovery, rather than treating speed as the sole target.
- Choose tools around the systems and operational model your team needs, not a popularity ranking.
- Test whether tools integrate cleanly before adding overlapping systems to the same delivery workflow.
- Make security and code-quality checks part of delivery, and determine how your team tracks software components.
- For AI-assisted development, define validation and governance practices that fit the changes entering your pipelines.
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