Java productivity is more important than ever as spending slows and teams are tasked with doing more with less. Compare your business’ development environment to ecosystem benchmarks, and get expert tips from our CTO on how to overcome common productivity pitfalls.
Read the JRebel 2025 Java Developer Productivity Report for insights on:
- Developers’ biggest barriers to productivity
- AI usage trends
- Cloud development challenges
- Java tech stack benchmarks
- IDE preference shifts
Download your free copy of the 2025 Java Developer Productivity Report today for Java ecosystem benchmarks and valuable takeaways on how to increase your team’s productivity.
Investments in Java Tools Matter More Than Ever
Long-forecasted economic headwinds have arrived in force for nearly all industries. Development teams are now being tasked with doing more with less — and many are also facing blanket hiring freezes.
While it’s clear development spending has slowed across the board, enterprises are still carving out budgets for the people and tools necessary to maintain their mission-critical business applications.
2025 Plans to add Java Developers and 2025 plans to increase Java Development Tool Budget
Remote vs. Local Redeploy times
Remote Redeploy Times Are a Barrier to Productivity
70% of respondents are now using remote, containerized, and cloud-based development environments, but that flexibility comes at the cost of staggeringly long redeploy times as compared to local development environments. 23% of respondents say their redeploys are five minutes or longer for local development environments, but 52% saw redeploys of that length for remote development environments.
"Cloud latency may cause frustration for development teams who are now burdened by more complex development environments. As a result, developers will get distracted while waiting, start doing other tasks, and get out of the flow — further magnifying those long redeploy times."
- Rod Cope, CTO, Perforce Software
AI is Everywhere
We not only asked respondents which AI tools they’re using for Java development, but also what use cases they’re turning to AI for. Top answers included code completion and refactoring, but error detection, documentation generation, debugging assistance, and automated testing are also prime use cases. That said, AI alone won’t help companies carve out the whitespace they need to continue innovating.
As AI development tools continue to mature, they will create a clear competitive advantage for companies that buy in. Companies that are skittish about adopting AI tools or create blanket policies prohibiting their use will get left behind. That said, AI coding assistants are far from perfect today, and it’s not easy to know which AI vendor and model will work best for a given programming language, codebase, use case, etc.
“AI coding assistants get better every month. Developers who tried AI a few months ago may think it’s annoying or gets in the way. My advice is to keep trying AI tools at least once a quarter.”
- Rod Cope, CTO, Perforce Software
AI Features Used Most Regularly for Java Development
Who Should Read the Java Developer Productivity Report?
The 2025 Java Developer Productivity Report provides valuable insights for everyone who works in Java.
Takeaways on high-level trends for busy executives
On-the-ground insights for managers and team leaders
