The World of Java Optimisation By Holly Cummins

Creators:: Tradeoffs, Bad Science, and Polar Bears
Title:: The World of Java Optimisation By Holly Cummins
Date:: 2023-10-05
Source:: https://youtu.be/PvZaDo_I21g

Slides: https://hollycummins.com/tradeoffs-bad-science-and-polar-bears-the-world-of-java-optimisation-devoxx-be/

Performance

performance can be:

• throughput
  • transactions per second
• latency
  • response time
  • start-up time
  • ramp-up time (warm-up)
• capacity
  • network bandwidth
  • memory usage
  • CPU usage
• utilization

trade-offs:

• throughput vs. latency
  • e.g. an optimization for more transactions per second may lead to a decrease of the start-up time

Frameworks & Runtimes

HotSpot vs. OpenJ9

Primary source: https://github.com/eclipse/openj9-website/blob/master/benchmark/daytrader7.md

→ OpenJ9 has a faster startup time and smaller memory footprint than HotSpot, however HotSpot has a higher throughput

GraalVM vs. OpenJDK

trading-off flexibility and throughput against startup speed and footprint

→ use GraalVM for ephemeral services or serverless
→ use OpenJDK for long running applications

Quarkus (OpenJDK) vs. Spring

• better startup time
• better footprint
• better throughput
• better developer experience

trade-offs:

• switch costs time and money
• not optimising for dynamism (nobody needs in the cloud)

How to optimize?

• measure and measure the right thing
• McNamara Fallacy: numbers are great, but they don't have to be helpful
• "Any improvements made anywhere besides the bottleneck are an illusion." — Gene Kim
• → you have to find the actual bottleneck
  • example: running jmeter on the same machine or on a different machine?
    • same machine: bottleneck is the CPU
    • different machine: bottleneck is the network as the app gives a big speedup

Tools

• method profiler:
  • VisualVM
  • Mission Control
  • IntelliJ Profiler
  • IBM Health Center (for OpenJ9)
• GC analysis
  • GCMV
• heap analysis
  • Eclipse MAT
• APM
  • GlowRoot
  • New Relic (not free)
  • AppDynamics (not free)
  • Dynatrace (not free)
• Distributed tracing
  • Zipkin
  • Jaeger
  • Open Telemetry

Carbon

cost: leading indicator for carbon
performance: leading indicator for carbon

→ Quarkus cuts carbon by ~2-3x
→ native consumes more carbon than JVM