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Performance Engineering Standard

Version: 1.0.0

Status: official

Author: Enterprise AI Standards

Description

Official engineering standard for designing, developing and operating high-performance enterprise applications.

Objective

Define mandatory engineering practices to maximize performance, scalability and resource efficiency across the entire software stack.

Philosophy

Performance is an architectural concern, not a final optimization step. Systems must be designed to scale horizontally, minimize latency and optimize resource utilization from the beginning.

Principles

  • Measure before optimizing.
  • Optimize only proven bottlenecks.
  • Simplicity over premature optimization.
  • Prefer scalability over raw speed.
  • Minimize allocations.
  • Reduce network round trips.
  • Fail fast.
  • Asynchronous IO whenever possible.
  • Resource efficiency is mandatory.

Project Structure

Language Features

Virtual Threads

Enabled:

Rules

  • Mandatory for IO-bound workloads.
  • Never create thread pools for virtual threads.
  • Executors.newVirtualThreadPerTaskExecutor preferred.

Structured Concurrency

Records

Sealed Classes

Pattern Matching

Collections

  • Choose appropriate collection types.
  • Immutable collections preferred.
  • Avoid unnecessary copies.

Streams

  • Streams for readability.
  • Avoid nested streams.
  • Avoid parallelStream unless benchmarked.

Optional

Exceptions

  • Exceptions are exceptional.
  • Never use exceptions for control flow.
  • Fail fast.

Logging

  • Async logging preferred.
  • Parameterized logging.
  • Never log inside hot loops.
  • Log levels appropriate.

Performance

Security

Testing

  • Performance tests.
  • Stress tests.
  • Soak tests.
  • Load tests.
  • Scalability tests.

Observability

Documentation

Best Practices

  • Virtual Threads.
  • Constructor Injection.
  • Immutable Objects.
  • Efficient SQL.
  • Cache wisely.
  • Benchmark continuously.
  • Profile regularly.
  • Monitor production.
  • Horizontal scalability.

Anti Patterns

  • Premature optimization.
  • SELECT *.
  • N+1 queries.
  • Thread per request (platform threads).
  • Blocking IO.
  • Large synchronized blocks.
  • Unbounded caches.
  • Logging inside loops.
  • Excessive object creation.
  • Large transactions.
  • Missing indexes.

Review Checklist

  • [ ] Virtual Threads enabled.
  • [ ] Database indexed.
  • [ ] Load tests executed.
  • [ ] Performance baseline recorded.
  • [ ] Monitoring enabled.
  • [ ] Cache configured.
  • [ ] Docker optimized.
  • [ ] JVM tuned.
  • [ ] Health checks implemented.
  • [ ] Metrics exported.

Examples

References

  • https://docs.oracle.com/en/java/
  • https://openjdk.org/projects/loom/
  • https://spring.io/projects/spring-boot
  • https://micrometer.io/
  • https://prometheus.io/
  • https://grafana.com/
  • https://openjdk.org/projects/jmc/