HomeJVM Startup Parameter Config

JVM Startup Parameter Config

Online JVM startup parameter configurator with visual tuning for memory, GC, compiler, and runtime options, generating startup commands in real time

Smart Recommendation

Generate JVM parameter combinations by server resources and workload scenario

Scenario Profile:

Memory Settings

M
M
%

GC Settings

G1 GC is a safe default for most server workloads, balancing latency and throughput.

Performance Tuning

Other Settings

Generated Startup Command

Multi-line command (better readability)

Single-line command (direct execution)
Startup command generated from current settings
Quick Presets
Parameter Notes
-Xms
Initial heap size. In production, it is often set equal to -Xmx.
-Xmx
Maximum heap size. A common rule is to keep it below 75% of host memory.
-XX:NewRatio
Controls young/old generation ratio and impacts promotion behavior.
-XX:MetaspaceSize
Initial metaspace size. Increase when class loading is heavy.
-Xss
Per-thread stack size. Tune with recursion depth and thread count.
JVM Tuning Best Practices
  • Keep -Xms and -Xmx equal in production to reduce runtime resizing overhead.
  • Leave memory headroom for OS and native allocations instead of maxing out heap.
  • Choose GC by target latency and throughput, then verify with real traffic patterns.
  • Enable GC logs and review pause time, frequency, and heap trend regularly.
  • Tune after load tests and measured bottlenecks rather than adding random flags.
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Documentation
About JVM Startup Parameter Config


This tool generates JVM startup parameter recommendations for memory, GC, compiler mode, and scenario-based tuning.


Key Features


    

  • Scenario Recommendations: Based on server memory, CPU, Java version, and workload type.
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  • Memory Tuning: -Xms/-Xmx, young-gen ratio, metaspace, stack size.
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  • GC Configuration: G1/Parallel/CMS/ZGC/Shenandoah options and logging settings.
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  • Tuning Toggles: Compressed oops, string deduplication, compiler mode.
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  • Apply/Reset Actions: Fast recommendation usage and rollback.
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Steps


    

  1. Select machine profile and workload scenario.
    2. 

  2. Apply recommended baseline or tweak manually.
    3. 

  3. Adjust memory/GC/extra tuning options.
    4. 

  4. Copy startup parameters for deployment.
    5. 



Use Cases


    

  • Initial JVM tuning before release.
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  • Comparing parameter sets during performance troubleshooting.
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  • Standardizing JVM baselines across teams.
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FAQ


Are recommendations production-ready as-is?


Use as a baseline. Final values should be validated with monitoring and load tests.


Why does switching GC change behavior a lot?


GC algorithms optimize different throughput/latency goals; choose based on workload characteristics.


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