Merge commit 'd803bfe2b1fe7f5e219e50ac20d6801a0a58ac75' as 'vendor/ruvector'
This commit is contained in:
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vendor/ruvector/benchmarks/docs/README.md
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# RuVector Benchmarking Suite
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Comprehensive benchmarking tool for testing the globally distributed RuVector vector search system at scale (500M+ concurrent connections).
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## Table of Contents
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- [Overview](#overview)
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- [Features](#features)
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- [Prerequisites](#prerequisites)
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- [Installation](#installation)
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- [Quick Start](#quick-start)
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- [Benchmark Scenarios](#benchmark-scenarios)
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- [Running Benchmarks](#running-benchmarks)
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- [Understanding Results](#understanding-results)
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- [Best Practices](#best-practices)
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- [Cost Estimation](#cost-estimation)
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- [Troubleshooting](#troubleshooting)
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- [Advanced Usage](#advanced-usage)
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## Overview
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This benchmarking suite provides enterprise-grade load testing capabilities for RuVector, supporting:
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- **Massive Scale**: Test up to 25B concurrent connections
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- **Multi-Region**: Distributed load generation across 11 GCP regions
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- **Comprehensive Metrics**: Latency, throughput, errors, resource utilization, costs
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- **SLA Validation**: Automated checking against 99.99% availability, <50ms p99 latency targets
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- **Advanced Analysis**: Statistical analysis, bottleneck identification, recommendations
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## Features
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### Load Generation
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- Multi-protocol support (HTTP, HTTP/2, WebSocket, gRPC)
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- Realistic query patterns (uniform, hotspot, Zipfian, burst)
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- Configurable ramp-up/down rates
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- Connection lifecycle management
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- Geographic distribution
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### Metrics Collection
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- Latency distribution (p50, p90, p95, p99, p99.9)
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- Throughput tracking (QPS, bandwidth)
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- Error analysis by type and region
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- Resource utilization (CPU, memory, network)
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- Cost per million queries
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- Regional performance comparison
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### Analysis & Reporting
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- Statistical analysis with anomaly detection
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- SLA compliance checking
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- Bottleneck identification
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- Performance score calculation
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- Actionable recommendations
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- Interactive visualization dashboard
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- Markdown and JSON reports
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- CSV export for further analysis
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## Prerequisites
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### Required
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- **Node.js**: v18+ (for TypeScript execution)
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- **k6**: Latest version ([installation guide](https://k6.io/docs/getting-started/installation/))
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- **Access**: RuVector cluster endpoint
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### Optional
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- **Claude Flow**: For hooks integration
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```bash
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npm install -g claude-flow@alpha
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```
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- **Docker**: For containerized execution
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- **GCP Account**: For multi-region load generation
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## Installation
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1. **Clone Repository**
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```bash
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cd /home/user/ruvector/benchmarks
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```
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2. **Install Dependencies**
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```bash
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npm install -g typescript ts-node
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npm install k6 @types/k6
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```
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3. **Verify Installation**
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```bash
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k6 version
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ts-node --version
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```
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4. **Configure Environment**
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```bash
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export BASE_URL="https://your-ruvector-cluster.example.com"
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export PARALLEL=2 # Number of parallel scenarios
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```
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## Quick Start
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### Run a Single Scenario
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```bash
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# Quick validation (100M connections, 45 minutes)
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ts-node benchmark-runner.ts run baseline_100m
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# Full baseline test (500M connections, 3+ hours)
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ts-node benchmark-runner.ts run baseline_500m
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# Burst test (10x spike to 5B connections)
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ts-node benchmark-runner.ts run burst_10x
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```
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### Run Scenario Groups
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```bash
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# Quick validation suite (~1 hour)
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ts-node benchmark-runner.ts group quick_validation
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# Standard test suite (~6 hours)
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ts-node benchmark-runner.ts group standard_suite
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# Full stress testing suite (~10 hours)
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ts-node benchmark-runner.ts group stress_suite
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# All scenarios (~48 hours)
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ts-node benchmark-runner.ts group full_suite
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```
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### List Available Tests
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```bash
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ts-node benchmark-runner.ts list
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```
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## Benchmark Scenarios
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### Baseline Tests
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#### baseline_500m
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- **Description**: Steady-state operation with 500M concurrent connections
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- **Duration**: 3h 15m
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- **Target**: P99 < 50ms, 99.99% availability
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- **Use Case**: Production capacity validation
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#### baseline_100m
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- **Description**: Smaller baseline for quick validation
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- **Duration**: 45m
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- **Target**: P99 < 50ms, 99.99% availability
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- **Use Case**: CI/CD integration, quick regression tests
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### Burst Tests
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#### burst_10x
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- **Description**: Sudden spike to 5B concurrent (10x baseline)
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- **Duration**: 20m
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- **Target**: P99 < 100ms, 99.9% availability
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- **Use Case**: Flash sale, viral event simulation
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#### burst_25x
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- **Description**: Extreme spike to 12.5B concurrent (25x baseline)
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- **Duration**: 35m
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- **Target**: P99 < 150ms, 99.5% availability
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- **Use Case**: Major global event (Olympics, elections)
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#### burst_50x
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- **Description**: Maximum spike to 25B concurrent (50x baseline)
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- **Duration**: 50m
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- **Target**: P99 < 200ms, 99% availability
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- **Use Case**: Stress testing absolute limits
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||||
### Failover Tests
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#### regional_failover
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- **Description**: Test recovery when one region fails
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- **Duration**: 45m
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- **Target**: <10% throughput degradation, <1% errors
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- **Use Case**: Disaster recovery validation
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#### multi_region_failover
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- **Description**: Test recovery when multiple regions fail
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- **Duration**: 55m
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- **Target**: <20% throughput degradation, <2% errors
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- **Use Case**: Multi-region outage preparation
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### Workload Tests
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#### read_heavy
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- **Description**: 95% reads, 5% writes (typical production workload)
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- **Duration**: 1h 50m
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- **Target**: P99 < 50ms, 99.99% availability
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- **Use Case**: Production simulation
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||||
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||||
#### write_heavy
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- **Description**: 70% writes, 30% reads (batch indexing scenario)
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- **Duration**: 1h 50m
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- **Target**: P99 < 80ms, 99.95% availability
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- **Use Case**: Bulk data ingestion
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#### balanced_workload
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- **Description**: 50% reads, 50% writes
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- **Duration**: 1h 50m
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- **Target**: P99 < 60ms, 99.98% availability
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- **Use Case**: Mixed workload validation
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### Real-World Scenarios
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#### world_cup
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- **Description**: Predictable spike with geographic concentration (Europe)
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- **Duration**: 3h
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- **Target**: P99 < 100ms during matches
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- **Use Case**: Major sporting event
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#### black_friday
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- **Description**: Sustained high load with periodic spikes
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- **Duration**: 14h
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- **Target**: P99 < 80ms, 99.95% availability
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- **Use Case**: E-commerce peak period
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## Running Benchmarks
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### Basic Usage
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```bash
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# Set environment variables
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export BASE_URL="https://ruvector.example.com"
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export REGION="us-east1"
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# Run single test
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ts-node benchmark-runner.ts run baseline_500m
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# Run with custom config
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BASE_URL="https://staging.example.com" \
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PARALLEL=3 \
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ts-node benchmark-runner.ts group standard_suite
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```
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### With Claude Flow Hooks
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```bash
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# Enable hooks (default)
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export ENABLE_HOOKS=true
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# Disable hooks
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export ENABLE_HOOKS=false
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ts-node benchmark-runner.ts run baseline_500m
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```
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Hooks will automatically:
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- Execute `npx claude-flow@alpha hooks pre-task` before each test
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- Store results in swarm memory
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- Execute `npx claude-flow@alpha hooks post-task` after completion
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### Multi-Region Execution
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To distribute load across regions:
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```bash
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# Deploy load generators to GCP regions
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for region in us-east1 us-west1 europe-west1 asia-east1; do
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gcloud compute instances create "k6-${region}" \
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--zone="${region}-a" \
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--machine-type="n2-standard-32" \
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--image-family="ubuntu-2004-lts" \
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--image-project="ubuntu-os-cloud" \
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--metadata-from-file=startup-script=setup-k6.sh
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done
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# Run distributed test
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ts-node benchmark-runner.ts run baseline_500m
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```
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### Docker Execution
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||||
```bash
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# Build container
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||||
docker build -t ruvector-benchmark .
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# Run test
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docker run \
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-e BASE_URL="https://ruvector.example.com" \
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-v $(pwd)/results:/results \
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ruvector-benchmark run baseline_500m
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```
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## Understanding Results
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||||
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||||
### Output Structure
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||||
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||||
```
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results/
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run-{timestamp}/
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{scenario}-{timestamp}-raw.json # Raw K6 metrics
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{scenario}-{timestamp}-metrics.json # Processed metrics
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{scenario}-{timestamp}-metrics.csv # CSV export
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{scenario}-{timestamp}-analysis.json # Analysis report
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{scenario}-{timestamp}-report.md # Markdown report
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SUMMARY.md # Multi-scenario summary
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```
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### Key Metrics
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#### Latency
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- **P50 (Median)**: 50% of requests faster than this
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- **P90**: 90% of requests faster than this
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- **P95**: 95% of requests faster than this
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- **P99**: 99% of requests faster than this (SLA target)
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- **P99.9**: 99.9% of requests faster than this
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**Target**: P99 < 50ms for baseline, <100ms for burst
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#### Throughput
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- **QPS**: Queries per second
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- **Peak QPS**: Maximum sustained throughput
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- **Average QPS**: Mean throughput over test duration
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**Target**: 50M QPS for 500M baseline connections
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|
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#### Error Rate
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- **Total Errors**: Count of failed requests
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- **Error Rate %**: Percentage of requests that failed
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- **By Type**: Breakdown (timeout, connection, server, client)
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- **By Region**: Geographic distribution
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**Target**: < 0.01% error rate (99.99% success)
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#### Availability
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- **Uptime %**: Percentage of time system was available
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- **Downtime**: Total milliseconds of unavailability
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- **MTBF**: Mean time between failures
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- **MTTR**: Mean time to recovery
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**Target**: 99.99% availability (52 minutes/year downtime)
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#### Resource Utilization
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- **CPU %**: Average and peak CPU usage
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- **Memory %**: Average and peak memory usage
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- **Network**: Bandwidth, ingress/egress bytes
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- **Per Region**: Resource usage by geographic location
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**Alert Thresholds**: CPU > 80%, Memory > 85%
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||||
#### Cost
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||||
- **Total Cost**: Compute + network + storage
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||||
- **Cost Per Million**: Queries per million queries
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||||
- **Per Region**: Cost breakdown by location
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||||
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||||
**Target**: < $0.50 per million queries
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### Performance Score
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||||
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Overall score (0-100) calculated from:
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- **Performance** (35%): Latency and throughput
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- **Reliability** (35%): Availability and error rate
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- **Scalability** (20%): Resource utilization efficiency
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||||
- **Efficiency** (10%): Cost effectiveness
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||||
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||||
**Grades**:
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- 90-100: Excellent
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||||
- 80-89: Good
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||||
- 70-79: Fair
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- 60-69: Needs Improvement
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||||
- <60: Poor
|
||||
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### SLA Compliance
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||||
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✅ **PASSED** if all criteria met:
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- P99 latency < 50ms (baseline) or scenario target
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||||
- Availability >= 99.99%
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||||
- Error rate < 0.01%
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||||
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||||
❌ **FAILED** if any criterion violated
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||||
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||||
### Analysis Report
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||||
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||||
Each test generates an analysis report with:
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||||
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||||
1. **Statistical Analysis**
|
||||
- Summary statistics
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||||
- Distribution histograms
|
||||
- Time series charts
|
||||
- Anomaly detection
|
||||
|
||||
2. **SLA Compliance**
|
||||
- Pass/fail status
|
||||
- Violation details
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||||
- Duration and severity
|
||||
|
||||
3. **Bottlenecks**
|
||||
- Identified constraints
|
||||
- Current vs. threshold values
|
||||
- Impact assessment
|
||||
- Recommendations
|
||||
|
||||
4. **Recommendations**
|
||||
- Prioritized action items
|
||||
- Implementation guidance
|
||||
- Estimated impact and cost
|
||||
|
||||
### Visualization Dashboard
|
||||
|
||||
Open `visualization-dashboard.html` in a browser to view:
|
||||
|
||||
- Real-time metrics
|
||||
- Interactive charts
|
||||
- Geographic heat maps
|
||||
- Historical comparisons
|
||||
- Cost analysis
|
||||
|
||||
## Best Practices
|
||||
|
||||
### Before Running Tests
|
||||
|
||||
1. **Baseline Environment**
|
||||
- Ensure cluster is healthy
|
||||
- No active deployments or maintenance
|
||||
- Stable configuration
|
||||
|
||||
2. **Resource Allocation**
|
||||
- Sufficient load generator capacity
|
||||
- Network bandwidth provisioned
|
||||
- Monitoring systems ready
|
||||
|
||||
3. **Communication**
|
||||
- Notify team of upcoming test
|
||||
- Schedule during low-traffic periods
|
||||
- Have rollback plan ready
|
||||
|
||||
### During Tests
|
||||
|
||||
1. **Monitoring**
|
||||
- Watch real-time metrics
|
||||
- Check for anomalies
|
||||
- Monitor costs
|
||||
|
||||
2. **Safety**
|
||||
- Start with smaller tests (baseline_100m)
|
||||
- Gradually increase load
|
||||
- Be ready to abort if issues detected
|
||||
|
||||
3. **Documentation**
|
||||
- Note any unusual events
|
||||
- Document configuration changes
|
||||
- Record observations
|
||||
|
||||
### After Tests
|
||||
|
||||
1. **Analysis**
|
||||
- Review all metrics
|
||||
- Identify bottlenecks
|
||||
- Compare to previous runs
|
||||
|
||||
2. **Reporting**
|
||||
- Share results with team
|
||||
- Document findings
|
||||
- Create action items
|
||||
|
||||
3. **Follow-Up**
|
||||
- Implement recommendations
|
||||
- Re-test after changes
|
||||
- Track improvements over time
|
||||
|
||||
### Test Frequency
|
||||
|
||||
- **Quick Validation**: Daily (CI/CD)
|
||||
- **Standard Suite**: Weekly
|
||||
- **Stress Testing**: Monthly
|
||||
- **Full Suite**: Quarterly
|
||||
|
||||
## Cost Estimation
|
||||
|
||||
### Load Generation Costs
|
||||
|
||||
Per hour of testing:
|
||||
- **Compute**: ~$1,000/hour (distributed load generators)
|
||||
- **Network**: ~$200/hour (egress traffic)
|
||||
- **Storage**: ~$10/hour (results storage)
|
||||
|
||||
**Total**: ~$1,200/hour
|
||||
|
||||
### Scenario Cost Estimates
|
||||
|
||||
| Scenario | Duration | Estimated Cost |
|
||||
|----------|----------|----------------|
|
||||
| baseline_100m | 45m | $900 |
|
||||
| baseline_500m | 3h 15m | $3,900 |
|
||||
| burst_10x | 20m | $400 |
|
||||
| burst_25x | 35m | $700 |
|
||||
| burst_50x | 50m | $1,000 |
|
||||
| read_heavy | 1h 50m | $2,200 |
|
||||
| world_cup | 3h | $3,600 |
|
||||
| black_friday | 14h | $16,800 |
|
||||
| **Full Suite** | ~48h | **~$57,600** |
|
||||
|
||||
### Cost Optimization
|
||||
|
||||
1. **Use Spot Instances**: 60-80% savings on load generators
|
||||
2. **Regional Selection**: Test in fewer regions
|
||||
3. **Shorter Duration**: Reduce steady-state phase
|
||||
4. **Parallel Execution**: Minimize total runtime
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
### Common Issues
|
||||
|
||||
#### K6 Not Found
|
||||
```bash
|
||||
# Install k6
|
||||
brew install k6 # macOS
|
||||
sudo apt install k6 # Linux
|
||||
choco install k6 # Windows
|
||||
```
|
||||
|
||||
#### Connection Refused
|
||||
```bash
|
||||
# Check cluster endpoint
|
||||
curl -v https://your-ruvector-cluster.example.com/health
|
||||
|
||||
# Verify network connectivity
|
||||
ping your-ruvector-cluster.example.com
|
||||
```
|
||||
|
||||
#### Out of Memory
|
||||
```bash
|
||||
# Increase Node.js memory limit
|
||||
export NODE_OPTIONS="--max-old-space-size=8192"
|
||||
|
||||
# Use smaller scenario
|
||||
ts-node benchmark-runner.ts run baseline_100m
|
||||
```
|
||||
|
||||
#### High Error Rate
|
||||
- Check cluster health
|
||||
- Verify capacity (not overloaded)
|
||||
- Review network latency
|
||||
- Check authentication/authorization
|
||||
|
||||
#### Slow Performance
|
||||
- Insufficient load generator capacity
|
||||
- Network bandwidth limitations
|
||||
- Target cluster under-provisioned
|
||||
- Configuration issues (connection limits, timeouts)
|
||||
|
||||
### Debug Mode
|
||||
|
||||
```bash
|
||||
# Enable verbose logging
|
||||
export DEBUG=true
|
||||
export LOG_LEVEL=debug
|
||||
|
||||
ts-node benchmark-runner.ts run baseline_500m
|
||||
```
|
||||
|
||||
### Support
|
||||
|
||||
For issues or questions:
|
||||
- GitHub Issues: https://github.com/ruvnet/ruvector/issues
|
||||
- Documentation: https://docs.ruvector.io
|
||||
- Community: https://discord.gg/ruvector
|
||||
|
||||
## Advanced Usage
|
||||
|
||||
### Custom Scenarios
|
||||
|
||||
Create custom scenario in `benchmark-scenarios.ts`:
|
||||
|
||||
```typescript
|
||||
export const SCENARIOS = {
|
||||
...SCENARIOS,
|
||||
my_custom_test: {
|
||||
name: 'My Custom Test',
|
||||
description: 'Custom workload pattern',
|
||||
config: {
|
||||
targetConnections: 1000000000,
|
||||
rampUpDuration: '15m',
|
||||
steadyStateDuration: '1h',
|
||||
rampDownDuration: '10m',
|
||||
queriesPerConnection: 100,
|
||||
queryInterval: '1000',
|
||||
protocol: 'http',
|
||||
vectorDimension: 768,
|
||||
queryPattern: 'uniform',
|
||||
},
|
||||
k6Options: {
|
||||
// K6 configuration
|
||||
},
|
||||
expectedMetrics: {
|
||||
p99Latency: 50,
|
||||
errorRate: 0.01,
|
||||
throughput: 100000000,
|
||||
availability: 99.99,
|
||||
},
|
||||
duration: '1h25m',
|
||||
tags: ['custom'],
|
||||
},
|
||||
};
|
||||
```
|
||||
|
||||
### Integration with CI/CD
|
||||
|
||||
```yaml
|
||||
# .github/workflows/benchmark.yml
|
||||
name: Benchmark
|
||||
on:
|
||||
schedule:
|
||||
- cron: '0 0 * * 0' # Weekly
|
||||
workflow_dispatch:
|
||||
|
||||
jobs:
|
||||
benchmark:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- uses: actions/setup-node@v3
|
||||
- name: Install k6
|
||||
run: |
|
||||
sudo gpg --no-default-keyring --keyring /usr/share/keyrings/k6-archive-keyring.gpg --keyserver hkp://keyserver.ubuntu.com:80 --recv-keys C5AD17C747E3415A3642D57D77C6C491D6AC1D69
|
||||
echo "deb [signed-by=/usr/share/keyrings/k6-archive-keyring.gpg] https://dl.k6.io/deb stable main" | sudo tee /etc/apt/sources.list.d/k6.list
|
||||
sudo apt-get update
|
||||
sudo apt-get install k6
|
||||
- name: Run benchmark
|
||||
env:
|
||||
BASE_URL: ${{ secrets.BASE_URL }}
|
||||
run: |
|
||||
cd benchmarks
|
||||
ts-node benchmark-runner.ts run baseline_100m
|
||||
- name: Upload results
|
||||
uses: actions/upload-artifact@v3
|
||||
with:
|
||||
name: benchmark-results
|
||||
path: benchmarks/results/
|
||||
```
|
||||
|
||||
### Programmatic Usage
|
||||
|
||||
```typescript
|
||||
import { BenchmarkRunner } from './benchmark-runner';
|
||||
|
||||
const runner = new BenchmarkRunner({
|
||||
baseUrl: 'https://ruvector.example.com',
|
||||
parallelScenarios: 2,
|
||||
enableHooks: true,
|
||||
});
|
||||
|
||||
// Run single scenario
|
||||
const run = await runner.runScenario('baseline_500m');
|
||||
console.log(`Score: ${run.analysis?.score.overall}/100`);
|
||||
|
||||
// Run multiple scenarios
|
||||
const results = await runner.runScenarios([
|
||||
'baseline_500m',
|
||||
'burst_10x',
|
||||
'read_heavy',
|
||||
]);
|
||||
|
||||
// Check if all passed SLA
|
||||
const allPassed = Array.from(results.values()).every(
|
||||
r => r.analysis?.slaCompliance.met
|
||||
);
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
**Happy Benchmarking!** 🚀
|
||||
|
||||
For questions or contributions, please visit: https://github.com/ruvnet/ruvector
|
||||
Reference in New Issue
Block a user