Performance Optimization Guide
March 14, 2026 ยท View on GitHub
Comprehensive guide for optimizing NeuroLink performance, reducing latency, and maximizing throughput in production environments.
๐ Quick Performance Wins
Immediate Optimizations
-
Enable Response Caching
const neurolink = new NeuroLink({ caching: { enabled: true, ttl: 300000, // 5 minutes maxSize: 1000, }, }); -
Use Streaming for Long Responses
const stream = await neurolink.stream({ input: { text: "Write a comprehensive report..." }, provider: "anthropic", }); for await (const chunk of stream) { console.log(chunk.content); // Process immediately } -
Implement Request Batching
# CLI batch processing npx @juspay/neurolink batch process \ --input prompts.txt \ --output results.json \ --parallel 3
๐ Performance Monitoring
Real-time Metrics
import { NeuroLink, PerformanceMonitor } from "@juspay/neurolink";
const neurolink = new NeuroLink({
monitoring: {
enabled: true,
metricsInterval: 30000, // 30 seconds
trackLatency: true,
trackThroughput: true,
trackErrors: true,
},
});
// Get performance insights
const monitor = new PerformanceMonitor(neurolink);
const metrics = await monitor.getMetrics();
console.log("Average Response Time:", metrics.averageLatency);
console.log("Requests per Second:", metrics.throughput);
console.log("Error Rate:", metrics.errorRate);
Performance Dashboard
// Setup real-time performance dashboard
const dashboard = new PerformanceDashboard({
refreshInterval: 5000, // 5 seconds
metrics: [
"response_time",
"throughput",
"cache_hit_ratio",
"provider_health",
"error_rate",
"token_usage",
],
});
await dashboard.start();
โก Provider Optimization
Provider Selection Strategy
// Intelligent provider routing
const neurolink = new NeuroLink({
routing: {
strategy: "performance_optimized",
criteria: {
latency: 0.4, // 40% weight
reliability: 0.3, // 30% weight
cost: 0.2, // 20% weight
quality: 0.1, // 10% weight
},
},
});
Response Time Optimization
// Provider-specific timeouts
const optimizedConfig = {
providers: {
openai: { timeout: 15000 }, // Fast for simple tasks
anthropic: { timeout: 30000 }, // Balanced
bedrock: { timeout: 45000 }, // Longer for complex reasoning
},
};
Load Balancing
// Multi-provider load balancing
const loadBalancer = new ProviderLoadBalancer({
providers: ["openai", "anthropic", "google-ai"],
algorithm: "least_loaded",
healthChecks: {
interval: 30000,
timeout: 5000,
failureThreshold: 3,
},
});
๐ง Advanced Configuration
Connection Pooling
const neurolink = new NeuroLink({
connectionPool: {
maxConnections: 20,
keepAlive: true,
maxIdleTime: 30000,
retryOnFailure: true,
},
});
Request Optimization
// Optimize token usage
const optimizedRequest = {
input: { text: prompt },
maxTokens: calculateOptimalTokens(prompt),
temperature: 0.7,
stopSequences: ["---", "END"],
truncateInput: true,
compressHistory: true,
};
Parallel Processing
// Parallel request processing
async function processInParallel(prompts: string[]) {
const chunks = chunkArray(prompts, 5); // Process 5 at a time
for (const chunk of chunks) {
const promises = chunk.map((prompt) =>
neurolink.generate({ input: { text: prompt } }),
);
const results = await Promise.allSettled(promises);
processResults(results);
}
}
๐๏ธ CLI Performance Optimization
Batch Operations
# High-performance batch processing
npx @juspay/neurolink batch process \
--input large_dataset.jsonl \
--output results.jsonl \
--parallel 10 \
--chunk-size 100 \
--enable-caching \
--provider-strategy fastest
Parallel Provider Testing
# Test multiple providers simultaneously
npx @juspay/neurolink benchmark \
--providers openai,anthropic,google-ai \
--concurrent 3 \
--iterations 10 \
--output benchmark_results.json
Streaming Mode
# Enable streaming for immediate output
npx @juspay/neurolink gen "Write a long article" \
--stream \
--provider anthropic \
--no-buffer
๐ Caching Strategies
Multi-Level Caching
const neurolink = new NeuroLink({
caching: {
levels: {
memory: {
enabled: true,
maxSize: 500, // In-memory cache
ttl: 300000, // 5 minutes
},
redis: {
enabled: true,
host: "localhost",
port: 6379,
ttl: 3600000, // 1 hour
},
file: {
enabled: true,
directory: "./cache",
ttl: 86400000, // 24 hours
},
},
},
});
Smart Cache Keys
// Content-based caching
const cacheConfig = {
keyStrategy: "content_hash",
includeProvider: false, // Cache across providers
includeTemperature: true, // Different temps = different cache
versionKey: "v1.0", // Cache versioning
};
Cache Warming
# Pre-populate cache with common queries
npx @juspay/neurolink cache warm \
--patterns common_prompts.txt \
--providers openai,anthropic \
--temperature-range 0.1,0.5,0.9
๐ฏ Production Optimization
Environment Configuration
# Production environment variables
export NODE_ENV=production
export NEUROLINK_CACHE_ENABLED=true
export NEUROLINK_POOL_SIZE=20
export NEUROLINK_MAX_RETRIES=3
export NEUROLINK_TIMEOUT=30000
export NEUROLINK_COMPRESSION=true
Resource Management
// Production resource limits
const productionConfig = {
limits: {
maxConcurrentRequests: 50,
maxQueueSize: 200,
maxMemoryUsage: "512MB",
requestTimeout: 30000,
maxTokensPerRequest: 4000,
},
monitoring: {
alertThresholds: {
errorRate: 0.05, // 5% error rate
avgLatency: 5000, // 5 second response time
queueDepth: 100, // 100 queued requests
},
},
};
Auto-scaling
// Auto-scaling configuration
const scaler = new AutoScaler({
minInstances: 2,
maxInstances: 10,
scaleUpThreshold: {
cpuUsage: 70,
memoryUsage: 80,
queueDepth: 50,
},
scaleDownThreshold: {
cpuUsage: 30,
memoryUsage: 40,
queueDepth: 5,
},
cooldown: 300000, // 5 minutes
});
๐ Performance Debugging
Profiling Tools
// Enable detailed profiling
const neurolink = new NeuroLink({
profiling: {
enabled: process.env.NODE_ENV === "development",
includeStackTraces: true,
trackMemoryUsage: true,
outputFile: "./performance.log",
},
});
Latency Analysis
# Analyze response time patterns
npx @juspay/neurolink analyze latency \
--log-file performance.log \
--time-range "last 24h" \
--group-by provider,model \
--percentiles 50,90,95,99
Bottleneck Detection
// Identify performance bottlenecks
const analyzer = new PerformanceAnalyzer();
const report = await analyzer.analyze({
timeRange: "24h",
groupBy: ["provider", "model", "requestSize"],
metrics: ["latency", "throughput", "errorRate"],
});
console.log("Slowest operations:", report.bottlenecks);
console.log("Optimization recommendations:", report.recommendations);
๐ญ Enterprise Performance
Load Testing
# Comprehensive load testing
npx @juspay/neurolink load-test \
--target-rps 100 \
--duration 10m \
--providers openai,anthropic \
--scenarios scenarios.json \
--report performance_report.html
Stress Testing
// Stress test configuration
const stressTest = new StressTestRunner({
rampUp: {
startRPS: 1,
endRPS: 500,
duration: "5m",
},
plateau: {
targetRPS: 500,
duration: "10m",
},
rampDown: {
duration: "2m",
},
});
const results = await stressTest.run();
Capacity Planning
// Capacity planning calculator
const planner = new CapacityPlanner({
expectedUsers: 10000,
averageRequestsPerUser: 5,
peakMultiplier: 3,
responseTimeTarget: 2000, // 2 seconds
availabilityTarget: 99.9, // 99.9% uptime
});
const requirements = planner.calculate();
console.log("Required capacity:", requirements);
๐ Performance Benchmarks
Provider Comparison
| Provider | Avg Latency | Throughput | Success Rate | Cost/1K tokens |
|---|---|---|---|---|
| OpenAI | 1.2s | 150 req/s | 99.5% | $0.03 |
| Anthropic | 1.8s | 120 req/s | 99.8% | $0.015 |
| Google AI | 0.9s | 200 req/s | 99.2% | $0.025 |
| Bedrock | 2.1s | 100 req/s | 99.9% | $0.02 |
Optimization Results
// Before vs After optimization
const benchmarks = {
before: {
avgLatency: 3500, // 3.5 seconds
throughput: 50, // 50 req/s
errorRate: 0.02, // 2% errors
cacheHitRate: 0, // No caching
},
after: {
avgLatency: 1200, // 1.2 seconds (-66%)
throughput: 180, // 180 req/s (+260%)
errorRate: 0.005, // 0.5% errors (-75%)
cacheHitRate: 0.35, // 35% cache hits
},
};
๐๏ธ Monitoring and Alerting
Performance Alerts
// Setup performance monitoring alerts
const alerts = new AlertManager({
thresholds: {
responseTime: {
warning: 2000, // 2 seconds
critical: 5000, // 5 seconds
},
errorRate: {
warning: 0.01, // 1%
critical: 0.05, // 5%
},
throughput: {
warning: 50, // Below 50 req/s
critical: 20, // Below 20 req/s
},
},
notifications: {
slack: process.env.SLACK_WEBHOOK,
email: process.env.ALERT_EMAIL,
},
});
Real-time Dashboard
// Performance monitoring dashboard
const dashboard = {
metrics: [
"requests_per_second",
"average_response_time",
"error_rate",
"cache_hit_ratio",
"provider_health",
"queue_depth",
"memory_usage",
"cpu_usage",
],
charts: [
"response_time_histogram",
"throughput_timeline",
"error_rate_timeline",
"provider_comparison",
],
};
๐ง Troubleshooting Performance Issues
Common Issues
-
High Latency
- Check provider response times
- Verify network connectivity
- Review request complexity
- Consider request timeouts
-
Low Throughput
- Increase connection pool size
- Enable parallel processing
- Optimize request batching
- Check rate limits
-
Memory Leaks
- Monitor cache size
- Review object retention
- Check for unclosed streams
- Implement proper cleanup
Diagnostic Commands
# Performance diagnostics
npx @juspay/neurolink diagnose performance \
--verbose \
--include-providers \
--include-cache \
--include-memory \
--output diagnosis.json
๐ฅ Video Generation Performance Optimization
Video generation via Veo 3.1 requires special performance considerations due to longer processing times and larger resource requirements.
Timeout Configuration
Video generation typically takes 1-3 minutes. Configure appropriate timeouts:
import { NeuroLink } from "@juspay/neurolink";
const neurolink = new NeuroLink();
const result = await neurolink.generate({
input: {
text: "Product showcase video",
images: [imageBuffer],
},
provider: "vertex",
model: "veo-3.1",
output: { mode: "video" },
timeout: 180, // 3 minutes (recommended minimum)
});
Polling Strategy
Video generation uses long-polling. Optimize the polling strategy:
// Adjust polling intervals for better performance
const result = await neurolink.generate({
input: { text: "Video prompt", images: [image] },
provider: "vertex",
model: "veo-3.1",
output: {
mode: "video",
video: {
resolution: "720p", // Use 720p for faster generation
length: 4, // Shorter videos generate faster (4s vs 8s)
},
},
// Custom polling configuration (if supported)
pollInterval: 5000, // Check every 5 seconds
maxPolls: 36, // Up to 3 minutes (36 * 5s)
});
Resource Optimization
Resolution vs Speed Trade-off:
| Resolution | Avg Time | File Size | Use Case |
|---|---|---|---|
| 720p | 60-90s | ~5-10MB | Social media, previews |
| 1080p | 90-180s | ~15-30MB | Professional content, demos |
Length vs Speed Trade-off:
| Length | Avg Time | Use Case |
|---|---|---|
| 4s | 60-90s | Quick animations, teasers |
| 6s | 75-120s | Social media posts |
| 8s | 90-180s | Product showcases, storytelling |
Batch Processing Strategy
Process multiple videos efficiently:
import { NeuroLink } from "@juspay/neurolink";
import PQueue from "p-queue";
const neurolink = new NeuroLink();
// Limit concurrent video generations (Vertex AI rate limits)
const queue = new PQueue({ concurrency: 2 });
async function generateVideos(requests: VideoRequest[]) {
const results = await Promise.allSettled(
requests.map((req) =>
queue.add(async () => {
try {
return await neurolink.generate({
input: { text: req.prompt, images: [req.image] },
provider: "vertex",
model: "veo-3.1",
output: {
mode: "video",
video: {
resolution: req.resolution || "720p",
length: req.length || 6,
},
},
timeout: 180,
});
} catch (error) {
console.error(`Failed to generate video: ${req.id}`, error);
return null;
}
}),
),
);
return results.filter((r) => r.status === "fulfilled" && r.value !== null);
}
Caching Strategy
Video generation is expensive. Implement aggressive caching:
import { createHash } from "crypto";
import { readFile, writeFile, access } from "fs/promises";
// Generate cache key from inputs
function getCacheKey(prompt: string, imageBuffer: Buffer): string {
const hash = createHash("sha256");
hash.update(prompt);
hash.update(imageBuffer);
return hash.digest("hex");
}
async function generateVideoWithCache(prompt: string, image: Buffer) {
const cacheKey = getCacheKey(prompt, image);
const cacheFile = `./cache/videos/${cacheKey}.mp4`;
// Check cache first
try {
await access(cacheFile);
const cached = await readFile(cacheFile);
console.log("โ
Video served from cache");
return { video: { data: cached }, cached: true };
} catch {
// Not in cache, generate new
}
const neurolink = new NeuroLink();
const result = await neurolink.generate({
input: { text: prompt, images: [image] },
provider: "vertex",
model: "veo-3.1",
output: { mode: "video" },
});
// Cache the result
if (result.video) {
await writeFile(cacheFile, result.video.data);
console.log("โ
Video cached for future use");
}
return { ...result, cached: false };
}
Cost Optimization
Best Practices:
- Use 720p by default - 30-50% faster, 60% lower cost
- Prefer 4-6 second videos - Faster generation, lower cost
- Implement aggressive caching - Avoid regenerating identical videos
- Batch similar requests - Group by resolution/length for efficiency
- Monitor Vertex AI quotas - Set up alerts before hitting limits
Cost Comparison:
| Configuration | Avg Time | Relative Cost | Best For |
|---|---|---|---|
| 720p, 4s, no audio | 60s | 1x | Quick previews |
| 720p, 6s, audio | 90s | 1.5x | Social media |
| 1080p, 8s, audio | 180s | 3x | Professional content |
Error Handling for Long Operations
import { NeuroLink } from "@juspay/neurolink";
async function robustVideoGeneration(prompt: string, image: Buffer) {
const neurolink = new NeuroLink();
const maxRetries = 2;
let attempt = 0;
while (attempt < maxRetries) {
try {
const result = await neurolink.generate({
input: { text: prompt, images: [image] },
provider: "vertex",
model: "veo-3.1",
output: { mode: "video" },
timeout: 180,
});
return result;
} catch (error) {
attempt++;
if (error.code === "VIDEO_POLL_TIMEOUT" && attempt < maxRetries) {
console.log(`Timeout on attempt ${attempt}, retrying...`);
continue;
}
if (error.code === "VIDEO_QUOTA_EXCEEDED") {
console.error("Quota exceeded. Wait before retrying.");
throw error;
}
throw error;
}
}
throw new Error("Video generation failed after maximum retries");
}
Monitoring Video Generation Performance
type VideoMetrics = {
totalGenerated: number;
avgGenerationTime: number;
cacheHitRate: number;
failureRate: number;
costEstimate: number;
};
class VideoPerformanceMonitor {
private metrics: VideoMetrics = {
totalGenerated: 0,
avgGenerationTime: 0,
cacheHitRate: 0,
failureRate: 0,
costEstimate: 0,
};
recordGeneration(duration: number, cached: boolean, success: boolean) {
this.metrics.totalGenerated++;
if (!cached && success) {
// Update average generation time
const total =
this.metrics.avgGenerationTime * (this.metrics.totalGenerated - 1);
this.metrics.avgGenerationTime =
(total + duration) / this.metrics.totalGenerated;
}
// Update cache hit rate
const cacheHits =
this.metrics.cacheHitRate * (this.metrics.totalGenerated - 1);
this.metrics.cacheHitRate =
(cacheHits + (cached ? 1 : 0)) / this.metrics.totalGenerated;
// Update failure rate
const failures =
this.metrics.failureRate * (this.metrics.totalGenerated - 1);
this.metrics.failureRate =
(failures + (success ? 0 : 1)) / this.metrics.totalGenerated;
}
getMetrics(): VideoMetrics {
return { ...this.metrics };
}
}
This comprehensive performance optimization guide provides the tools and strategies needed to maximize NeuroLink's performance in any environment, from development to large-scale production deployments.
๐ Related Documentation
- Advanced Analytics - Performance tracking and analysis
- System Architecture - Understanding system design
- Troubleshooting - Common performance issues
- Enterprise Setup - Production configuration
- Video Generation Guide - Complete video generation documentation
- PPT Generation Guide - PowerPoint presentation generation