$ ~/cicdcalculator

Java and JVM CI/CD cost in 2026
./jvm-ci --gradle --maven --where-mins-go

JVM CI builds are slower than they look. Gradle and Maven both have warmup overhead, dependency resolution that scales poorly with project size, and annotation-processing-heavy frameworks like Spring Boot or Quarkus that compound compilation time. The result is build minutes that consume more CI budget than equivalent pipelines in Go or Node. The good news: Gradle's build cache and configuration cache, properly configured, recover most of the slowness. The bad news: most teams do not configure them properly. This page works through where the time and money goes in a typical JVM CI pipeline in 2026 and how to claw it back.

Pricing references each vendor's public pricing page in May 2026. Gradle build cache documentation at docs.gradle.org.

Where JVM build minutes go

A typical Spring Boot pipeline running compile, test and package consumes time in this approximate distribution on a Linux 2-core hosted runner without warm caches:

JVM startup + Gradle daemon init: 30-60 sec
Dependency resolution + download: 60-180 sec
Compile main + tests: 60-150 sec
Run unit test suite: 120-300 sec
Package JAR: 20-40 sec
Cold pipeline total: ~6-12 min
With proper cache:
Skip dependency download: save 60-160 sec
Skip incremental compile: save 30-90 sec
Warm pipeline total: ~3-5 min

The 50 percent reduction from warm caches is the single biggest CI optimisation a JVM team can make. It costs nothing to enable (the cache action and Gradle build-cache config are both free) and pays back immediately on per-minute platforms.

Per-platform monthly cost for a JVM team

Numbers below assume a 15-developer Java team consuming 8,400 monthly Linux build minutes (50 daily builds at 8-minute warm-cache average over 21 working days).

PlatformPlanSeatsComputeTotal / mo
GitHub ActionsTeam$60$54 (5.4K over 3K)$114
GitLab CIPremium$435$0 (in 10K free)$435
TeamCityCloud (15 users)$675$0 (in credits)$675
TeamCityServer (5 agents)$0 (license $300 / mo amort.)$140 (infra)$440 + admin
CircleCIPerformance$225$0 (in 375K credits)$225
JenkinsSelf-hosted$0$120 (controller + 3 agents)$120 + admin

The TeamCity premium, justified

TeamCity Cloud at $675 monthly looks expensive next to GitHub Actions at $114. The premium is real and only makes sense for teams that genuinely benefit from the TeamCity-IntelliJ integration. For a 15-developer Java team where every engineer uses IntelliJ Ultimate (already paying $599 per user per year, $7,485 annually for 15 seats), TeamCity is roughly $8,100 annually adding 8 percent to the total JetBrains spend.

The benefit is the Gradle and Maven first-class support: parallel build distribution across agents, detailed dependency analysis, build configuration that opens directly in IntelliJ for debugging, and Kotlin DSL for pipeline definitions that engineers already know from their build.gradle.kts files. For a team that values uniform tooling across IDE and CI, the premium is justified.

For a team that does not specifically value JetBrains integration, GitHub Actions is meaningfully cheaper at any team size and the JVM-specific advantage TeamCity offers is small. Most Java shops adopting CI/CD greenfield in 2026 land on GitHub Actions or GitLab CI; TeamCity adoption is concentrated in JetBrains-loyal organisations.

Build cache strategies in detail

For Gradle: enable the build cache (org.gradle.caching=true in gradle.properties) and configure a remote build cache backend. Local file backend works for small teams; for distributed teams, an S3-backed cache (via the gradle-build-cache-s3 plugin) lets every CI run benefit from work done by other developers' machines. Configuration cache (org.gradle.configuration-cache=true) saves 10-30 seconds per build but requires plugin compatibility checks.

For Maven: cache the entire ~/.m2/repository directory between CI runs, restored on Maven file content hash. Enable the parallel build flag (-T 1C) to use all available CPU cores. Maven does not have a build cache equivalent to Gradle's, so the win is mostly in dependency download avoidance and parallel execution.

For multi-module monorepos: invest in change-detection logic that skips unchanged modules. The reactivecircus/android-cache-fix-gradle-plugin (also useful for non-Android projects) helps with this. Or use Develocity's predictive test selection if budget allows. The best Java CI shops have made this work routine; the result is a typical PR build of 2-4 minutes regardless of monorepo size.

JVM-specific considerations

JVM warmup is real but mostly invisible on per-build pricing. The JVM compiles bytecode to optimised native code in the first few seconds of execution; workloads benefit cumulatively as the same code paths run more times. CI builds typically run each JVM process for 30-300 seconds, which is too short for full JIT warmup. This is not a cost lever in itself but it means JVM CI builds are slightly slower per workload than the same logic in a precompiled language like Go or Rust.

For workloads that genuinely benefit from native compilation (Spring Boot AOT mode, Quarkus native, GraalVM native-image), the build itself becomes much more expensive. Native-image compilation can take 5-15 minutes per artifact. Run native builds on dedicated CI workflows, not on every PR; merge-only or nightly is typical. The runtime startup benefit pays back in production but not in CI minutes consumed.

Larger heap settings on CI runners (-Xmx4g typical for medium projects) help with parallel test execution but require runners with adequate RAM. Linux 2-core runners on most platforms have 7 GB RAM available, enough for typical JVM CI workloads. Larger projects (50+ modules, 10+ GB heap usage during tests) may need 4-core or 8-core runners with more RAM, which doubles or quadruples the per-minute cost.

Related deep dives

TeamCity pricingAndroid CI cost (also Gradle)cost optimizationJenkins vs Bamboocompare all platformscost calculator

Frequently Asked Questions

# click any question to expand

Why are JVM CI builds slower than Node or Go?>
Three reasons. JVM warmup adds 5-15 seconds before any compilation starts, which compounds across multi-step pipelines. Gradle daemon initialisation adds another 30-60 seconds on cold runs. Annotation-processing-heavy frameworks (Spring Boot, Quarkus, Lombok) trigger expensive recompilation cycles, especially with KAPT. A typical Spring Boot pipeline that compiles, runs unit tests and packages a JAR consumes 6-12 minutes of CI time, roughly double the equivalent Go or Node pipeline.
What does a Java pipeline cost monthly?>
A 15-developer Java team running 50 daily builds at 8-minute average consumes 8,400 monthly Linux build minutes. On GitHub Actions Team plan, that is around $54 in overage on top of $60 in seats, total $114 monthly. On TeamCity Cloud at $45 per user including credits, total $675 monthly (the price is the JetBrains tooling and integration value, not raw CI/CD cost). On self-hosted Jenkins or GitLab CE, around $100 monthly in infrastructure plus operator time.
Is Gradle or Maven cheaper to run in CI?>
Gradle is faster per build with proper cache configuration; Maven is more predictable. A warm Gradle build with build cache enabled can be 30-50 percent faster than the equivalent Maven run because Gradle skips work that has not changed. Maven is more deterministic and easier to cache because the dependency model is simpler. For new Java projects starting in 2026, Gradle is usually the right choice for CI speed; for legacy Maven shops, the migration cost typically outweighs the per-build saving.
Why is TeamCity popular in JVM shops?>
JetBrains is the dominant Java tooling vendor (IntelliJ IDEA), and the IntelliJ-TeamCity integration is genuinely tight. Build configurations open directly in IntelliJ for debugging. Pipeline-level annotations show up in the IDE. The first-class Gradle and Maven support includes parallel build distribution and detailed dependency analysis that other CI/CD platforms lack. For Java teams already paying for IntelliJ Ultimate, the marginal cost of TeamCity is small and the integration benefit is real.
Should I cache the JVM itself?>
If you are using a JVM with native compilation (GraalVM native-image, AOT-compiled Java), absolutely. Native-image compilation can take 5-15 minutes and the result is large but caches well. For standard JIT-compiled Java, the JVM itself is small enough that re-extracting it on each run is cheap; the wins come from caching the dependency graph (Gradle / Maven cache) rather than the JVM itself. Distribution-class JVMs (Temurin, Corretto, GraalVM CE) all install fast on hosted runners.
What about multi-module Gradle projects?>
Multi-module Gradle projects are where the Gradle build cache delivers the largest wins. A 50-module project building only the changed modules can complete in 2-3 minutes versus 15-20 minutes for a full build. Configure the build cache to skip unchanged modules; combine with conditional CI jobs that only test the modules a PR touches. Most large Java shops invest heavily in this kind of incremental-CI tooling because it is the single biggest CI cost lever for monorepo-style codebases.
Is Develocity worth the cost?>
Develocity (formerly Gradle Enterprise) is Gradle's commercial build-acceleration product. It provides a remote build cache, build scans for performance analysis, predictive test selection and developer-facing performance reporting. Pricing is sales-led, typically starting around $80-150 per user per month for medium teams. The value depends on team size and codebase complexity. For 50+ developer Java shops with large multi-module Gradle builds, the per-build time savings often pay for the licence within the first few months. For smaller teams or simpler builds, the open-source Gradle build cache is sufficient.