Our team uses Jenkins pipelines to build, scan, and deploy several types of AWS workloads, including websites, Lambda functions, microservices, and infrastructure. Depending on the project, the pipeline may also deploy to development or test environments, with some test deployments managed by another IT team. The full process usually takes 20–40 minutes.
We want to improve overall delivery speed as development teams produce changes more quickly. Is there a CI/CD tool or approach that would make these pipelines faster and more reliable? We have considered GitHub Actions, but we are concerned about workflow inputs, approval gates, missed triggers, and general reliability. Moving to GitLab would be a substantial migration, and Azure DevOps is not a good fit for our AWS-based stack.
3 Answers
The CI platform itself probably isn't the main bottleneck. Jenkins can be just as fast as other tools if the pipeline is designed well. First look at what is actually being executed: cache dependencies and build outputs, build only the components affected by a change, skip work for documentation-only changes, and run independent stages in parallel. For larger projects, remote caching or execution tools such as Bazel, Buck, or similar systems can make a major difference. A previously cached 45-minute build was reduced to about three minutes with this kind of approach.
Changing tools will not automatically make the same workload faster. Before migrating, profile the pipeline and identify where the time goes: dependency installation, compilation, tests, image builds, security scans, environment provisioning, or deployment waits. Then optimize those areas. Jenkins may be unfashionable in some organizations, but it can handle many workloads efficiently when the pipeline and agents are configured properly.
If the goal is faster feedback, parallelization is one of the easiest wins. Run independent builds, scans, and tests concurrently, then use explicit dependencies only where one stage really needs another. Also consider a separate, tightly controlled emergency deployment path if the concern is handling production incidents; that is a different requirement from improving normal iteration speed.
This is mainly about improving the normal pipeline. The development teams are moving faster, so the CI process needs to keep up with regular changes, not just emergency fixes.
The runner's resources matter too. Faster or better-sized agents can help, but increasing capacity won't fix unnecessary work in the pipeline.