What is Continuous Integration? A Comprehensive Overview | Harness Glossary

Software delivery keeps getting faster, with more services, more releases, and higher expectations for security and compliance. The biggest risk in that situation is making sure that change happens safely.

Continuous integration (CI) makes integration predictable by combining a simple habit of merging small changes often with automation that builds, tests, and validates every change. This way, problems come up early, and the main branch is always ready for the next release.

Harness CI is meant to keep pipelines fast, steady, and able to grow with the teams that use them. As AI and automation improve, CI is moving away from just "running a set of steps" toward faster, smarter feedback that tells you what went wrong, why, and what to do next.

What is Continuous Integration?

Continuous integration (CI) is a software development practice that keeps your codebase healthy by validating changes continuously.

CI tells developers to integrate early and often instead of letting work build up in long-lived branches and then paying the price during a painful "integration week." Automation does the same checks over and over again: it builds the code, runs tests, runs checks, and sends the results back to the team.

At a high level, CI has two main parts:

1. A collaboration habit: Developers merge small, incremental changes into a shared repository frequently.‍
2. An automated verification loop: Every change triggers an automated workflow that builds the code, runs tests, and reports results quickly.

When teams do CI right, integration stops being a fire drill. It becomes a regular, dependable part of daily growth.

Benefits of Continuous Integration

CI changes the economics of software delivery by finding problems early, when they’re cheaper to fix and easier to understand.

1. Earlier Detection of Integration Problems

Without CI, teams often find conflicts and regressions late, after working in parallel for weeks.

CI finds problems as they happen, such as:

• Builds that don't work
• Conflicts between dependencies
• Test regressions
• Integration mismatches between services

Timing is important. When CI flags an issue a few minutes after a commit, the developer still knows everything that was going on.

2. Faster Feedback Loops That Keep Developers in Flow

Fast feedback reduces context switching. Instead of waiting for nightly builds or discovering issues after a merge, developers get results while they’re still thinking about the change.

Over time, that improves:

• Confidence in changes
• Review quality
• Speed of delivery

3. More Consistent Quality

By nature, manual validation is inconsistent. CI makes sure that checks are standardized so that quality doesn't depend on who remembers what.

CI helps with:

• Consistent build and test execution
• Standardized quality gates
• Repeatable, auditable outcomes

4. Better Collaboration and Clearer Ownership

Frequent integration encourages frequent communication. Smaller PRs are easier to understand, and failures are easier to triage.

CI also improves shared ownership because:

• Code review becomes a daily rhythm
• Teams learn from failures quickly
• Standards are enforced consistently

5. A Stronger Foundation for Delivery and Deployment

CI is the first step to automating more tasks down the line.

If you can’t reliably build, test, and produce artifacts in CI, continuous delivery and continuous deployment will be weak. If you can, those practices become much more achievable.

Common Challenges of Continuous Integration (CI)

The idea behind CI is simple. In practice, teams often deal with issues like slow feedback, noisy feedback, or environments that aren't always the same.

Here’s how to recognize and fix them:

Challenge 1: Merge Conflicts and Painful Integration

PRs can stay open for days, and when they finally land, merges can be dangerous and take a long time. Developers put off integration because they don't want to deal with conflicts or builds that don't work. Integration can become a stressful event instead of just a normal part of the day.

How to solve:

• Keep PRs small and short-lived
• Integrate frequently (daily or more)
• Use trunk-based development where it makes sense
• Use feature flags to safely merge incomplete work 

Challenge 2: Slow Pipelines and Delayed Feedback

CI takes so long that developers give up on waiting for results and switch to other tasks. When builds start, they may sit in a queue for a while, then run for 30 to 60 minutes. This slows down reviews and merges. Over time, CI stops teams from moving forward instead of keeping them on track.

How to solve:

• Run independent steps (tests, linting, builds) at the same time (in parallel)
• Cache dependencies and build outputs safely
• Run only tests that are affected by code changes
• Make PR checks fast; run deeper suites after a merge or on a schedule
• Monitor and reduce queue time (it’s often the real bottleneck)

Challenge 3: Flaky Tests (Unreliable Signal)

The same test fails from time to time, even when the code hasn't had any meaningful changes. Developers run pipelines over and over again "until it passes," which teaches the team to ignore failures. When CI stops being reliable, it stops helping people make decisions and starts making noise.

How to solve:

• Use AI to detect flaky tests
• Treat flakiness as a flaw, not “normal”
• Quarantine flaky tests while fixing root causes
• Use retries sparingly and track a flaky-rate metric
• Isolate tests and control setup/teardown

Challenge 4: “Works on My Machine” (Environment Drift)

A change works in one place but not in CI, or it works in CI but acts differently in later environments. Instead of making the change, developers spend time fixing differences in the toolchain. As time goes on, teams start to doubt that their pipelines show the truth.

How to solve:

• Standardize build environments (containers are common)
• Pin tool and runtime versions
• Move toward reproducible builds

Challenge 5: Scaling CI as Teams and Codebases Grow

As more engineers and services use the same CI capacity, the wait times go up. Costs become harder to predict, and fixing and changing things in the pipeline becomes a full-time job. In the end, CI makes it harder for the company to ship.

How to solve:

• Adopt reusable pipeline templates
• Centralize governance (RBAC, policies, standardized steps)
• Scale runners elastically and monitor capacity

Track utilization and cost so you can right-size resources

CI vs. Continuous Deployment vs. Continuous Delivery

CI, Continuous Delivery, and Continuous Deployment are closely connected practices in modern software delivery. They share the same foundation, automation, and fast feedback, but each one optimizes a different part of the lifecycle, from integrating code safely to releasing changes reliably.

If you’re modernizing delivery, start with CI and build confidence step-by-step, then decide whether “always releasable” (delivery) or “always shipping” (deployment) matches your organization’s goals.

CI Best Practices (What High-Performing Teams Do Consistently)

Great CI requires consistent habits and a pipeline that developers trust.

1. Keep the Main Branch Healthy

Make it hard to merge broken code.

• Require green CI checks before merge
• Protect the main with branch rules
• Keep failure output actionable (clear logs and links to reports)

2. Commit Small and Integrate Often

Small changes reduce risk and make reviews faster.

• Encourage “vertical slices” instead of large batches
• Set a PR size guideline if needed
• Use feature flags to merge safely without exposing incomplete work

3. Make PR Pipelines Fast by Default

Your default PR pipeline should be the fastest path to confident feedback.

Common PR checks include:

• Linting and formatting
• Unit tests
• Lightweight static analysis and security signals

Run deeper suites at the right stage:

• On merge to main
• Nightly
• Before release

4. Parallelize What You Can

Many CI steps don’t depend on each other.

• Shard unit tests
• Run linting in parallel with builds
• Execute service-level pipelines concurrently in monorepos

5. Use Caching Carefully and Measure Outcomes

Caching should reduce time without changing results.

• Cache immutable dependencies
• Bust caches intentionally when inputs change
• Track cache hit rate and pipeline duration trends

6. Store and Version Artifacts

Artifacts are the bridge between CI and the rest of the delivery.

• Version artifacts with commit SHA or semantic versions
• Store artifacts in a trusted registry
• Record provenance: what commit built it, what pipeline ran, what checks passed

7. Bring Security Earlier, with Clear Developer Feedback

CI is a strong place for early security signals, including:

• Dependency vulnerability scanning
• Secret scanning
• Static analysis for common issues

The goal is clarity. Developers should understand what failed and how to fix it.

8. Treat CI as a Product

CI affects every developer. Treat it like a platform.

• Define ownership for templates and runner infrastructure
• Set targets (queue time, build time, broken-build MTTR)

Create a feedback loop to continuously improve CI

Where CI Is Going Next

CI started as automation for builds and tests. Today, it’s becoming a control plane for modern delivery: governance, security, traceability, and increasingly, smarter automation.

Here are the trends shaping what “good CI” will look like next:

AI-Powered Pipeline Creation

Engineering teams can build pipelines using AI and procing “golden” templates as the context to AI. This will help create secure and compliant CI pipelines much more efficiently.

AI-Assisted Troubleshooting and Optimization

As pipelines get more complex, the bottleneck often isn’t compute—it’s diagnosing failures and understanding systemic slowdowns. The next generation of CI will focus on helping teams reduce toil by surfacing likely root causes, highlighting recurring failure patterns, and recommending practical optimizations.

Policy and Guardrails That Scale with the Org

As more teams ship more often, standardization matters. Expect more pipeline guardrails that are expressed as policy: who can run what, where workloads can execute, what data can be accessed, and what needs approval, without slowing developers down.

Software Supply Chain Security Built into CI

Security teams are increasingly asking for provenance, audit trails, and clear artifact lineage. CI is the natural place to generate and attach that context, because it’s where artifacts are created and validated.

You don’t need to adopt every trend at once. But strengthening CI fundamentals now makes these capabilities far easier to roll out later.

CI That Scales With Your Team

CI is one of the most practical ways to increase delivery confidence without slowing teams down. It reduces integration risk, improves quality signals, and keeps the main branch in a releasable state.

If you want a strong next step, focus on two outcomes: faster feedback and a more trustworthy signal. Smaller PRs, reliable tests, consistent environments, and clear reporting will get you there and set you up for the next wave of automation in software delivery.

Harness CI directly tackles the foremost challenges in software development: cost, speed, security, and developer satisfaction. It delivers end-to-end ownership of the build process, incorporating both hardware and software optimizations to revolutionize build speeds at a fraction of the cost.

Continuous Integration: Frequently Asked Questions (FAQs)

What is continuous integration (CI) in simple terms?

CI is the habit of merging small code changes frequently and automatically checking each change with builds and tests. It helps teams find integration problems early on so that the main branch stays stable and ready to be released.

What’s the difference between CI, Continuous Delivery, and Continuous Deployment?

CI checks changes automatically, which keeps integration safe. Continuous Delivery makes it possible to release software whenever you want, and Continuous Deployment automatically ships every change that passes the pipeline when your testing and rollback maturity can handle it.

Should CI run on pull requests, on merges to main, or both?

Both are great: PR checks keep broken code from getting into the mainline, and merge-to-main pipelines make sure that what actually ships into the mainline is correct. A lot of teams keep their PR pipelines quick and run more tests after a merge or on a set schedule.

What tests belong in a CI pipeline?

Begin with quick, predictable checks, linting, unit tests, and basic static checks so that you get feedback quickly. Add integration and end-to-end tests only when they are needed, and put the slowest suites where they won't slow down every PR.

How can we speed up a slow CI pipeline?

Add parallelism and cut down on queue time first, because those usually give the biggest benefits. Next, add safe caching for dependencies and build outputs, and go back to test selection to make sure the heaviest suites run at the right time.

How do we keep CI secure?

Use access controls that give users the least amount of access they need, keep builds separate when you can, and use secure secrets workflows to keep secrets out of code and logs. Add early security signals like scanning for dependencies and secrets so that problems are found before they get too big.