NudgeLang Documentation
Best Practices
Performance

Performance

This guide covers best practices for optimizing performance in NudgeLang applications.

Caching Strategies

1. Basic Caching 

states:
  - id: cache_state
    type: tool
    tool: process_data
    input:
      data: "${input.data}"
    cache:
      key: "${input.data}"
      ttl: 3600
      strategy: memory

2. Advanced Caching 

states:
  - id: cache_state
    type: tool
    tool: process_data
    input:
      data: "${input.data}"
    cache:
      key: "${input.data}"
      ttl: 3600
      strategy: distributed
      options:
        backend: redis
        cluster: true
        compression: true
      invalidation:
        pattern: "data:*"
        events:
          - update
          - delete

Parallel Processing

1. Basic Parallelization 

states:
  - id: parallel_state
    type: parallel
    branches:
      - id: task1
        states:
          - id: start
            type: initial
            next: process_task1
          - id: process_task1
            type: tool
            tool: process_data
            input:
              data: "${input.data1}"
      - id: task2
        states:
          - id: start
            type: initial
            next: process_task2
          - id: process_task2
            type: tool
            tool: process_data
            input:
              data: "${input.data2}"

2. Advanced Parallelization 

states:
  - id: parallel_state
    type: parallel
    branches:
      - id: task1
        states:
          - id: start
            type: initial
            next: process_task1
          - id: process_task1
            type: tool
            tool: process_data
            input:
              data: "${input.data1}"
    options:
      max_concurrent: 5
      timeout: 5000
      error_handling: continue
      resource_limits:
        memory: 100
        cpu: 50

Resource Optimization

1. Memory Optimization 

states:
  - id: optimize_state
    type: tool
    tool: process_data
    input:
      data: "${input.data}"
    optimization:
      memory:
        max_usage: 100
        cleanup:
          strategy: immediate
          threshold: 0.8
        pooling:
          enabled: true
          max_size: 1000

2. CPU Optimization 

states:
  - id: optimize_state
    type: tool
    tool: process_data
    input:
      data: "${input.data}"
    optimization:
      cpu:
        max_usage: 80
        threads:
          min: 2
          max: 8
        affinity:
          enabled: true
          cores: [0, 1]

Monitoring and Profiling

1. Basic Monitoring 

states:
  - id: monitor_state
    type: tool
    tool: process_data
    input:
      data: "${input.data}"
    monitoring:
      metrics:
        - response_time
        - memory_usage
        - cpu_usage
      threshold:
        response_time: 1000
        memory_usage: 80
        cpu_usage: 70

2. Advanced Monitoring 

states:
  - id: monitor_state
    type: tool
    tool: process_data
    input:
      data: "${input.data}"
    monitoring:
      metrics:
        - response_time
        - memory_usage
        - cpu_usage
        - throughput
        - error_rate
      threshold:
        response_time: 1000
        memory_usage: 80
        cpu_usage: 70
        throughput: 1000
        error_rate: 0.01
      profiling:
        enabled: true
        interval: 60
        depth: 10
      alerts:
        - type: email
          threshold: 0.9
        - type: slack
          threshold: 0.95

Load Balancing

1. Basic Load Balancing 

states:
  - id: load_balance_state
    type: tool
    tool: process_data
    input:
      data: "${input.data}"
    load_balancing:
      strategy: round_robin
      servers:
        - server1
        - server2
        - server3

2. Advanced Load Balancing 

states:
  - id: load_balance_state
    type: tool
    tool: process_data
    input:
      data: "${input.data}"
    load_balancing:
      strategy: weighted_round_robin
      servers:
        - name: server1
          weight: 3
          health_check: true
        - name: server2
          weight: 2
          health_check: true
        - name: server3
          weight: 1
          health_check: true
      options:
        sticky: true
        timeout: 5000
        retry: 3

Best Practices

  1. Caching: Implement appropriate caching
  2. Parallelization: Use parallel processing
  3. Resource Management: Optimize resource usage
  4. Monitoring: Monitor performance metrics
  5. Load Balancing: Distribute load effectively
  6. Documentation: Document performance optimizations
  7. Testing: Test performance improvements

Common Pitfalls

  1. Over-caching: Excessive caching
  2. Resource Exhaustion: Not managing resources
  3. Poor Monitoring: Insufficient performance monitoring
  4. Inefficient Parallelization: Poor parallel processing
  5. Load Imbalance: Uneven load distribution

Next Steps

Last updated on
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