In the rapidly evolving world of AI applications, deploying large language models (LLMs) in production is just the beginning. The real challenge? Keeping them running efficiently, cost-effectively, and reliably at scale. Without proper monitoring, your LLM-powered application can quickly become a black box that burns through budgets, frustrates users with slow responses, or worse—fails silently while you're none the wiser.
That's where real-time monitoring comes in. By tracking tokens, latency, and costs as they happen, you gain the visibility needed to optimize performance, control spending, and deliver exceptional user experiences. Let's explore how Requesty Live Logs makes this critical task not just possible, but surprisingly straightforward.
Why Real-Time LLM Monitoring Is Non-Negotiable
Think of LLM monitoring as the dashboard in your car. You wouldn't drive cross-country without knowing your speed, fuel level, or engine temperature. Similarly, running production LLMs without monitoring is asking for trouble:
Unexpected cost spikes can turn a $500 monthly budget into a $30,000 surprise bill
Performance degradation might go unnoticed until users start complaining
Compliance violations could expose sensitive data without your knowledge
Model failures may cascade through your application, creating poor user experiences
The three pillars of LLM observability—tokens, latency, and cost—form the foundation of operational excellence. Master these, and you'll have the insights needed to build reliable, efficient AI applications.
Understanding the Core Metrics
Token Usage: The Currency of AI
Tokens are the fundamental units that LLMs process—think of them as the "words" your AI reads and writes. Every API call consumes tokens, and every token costs money. Monitoring token usage helps you:
Identify inefficient prompts that waste tokens
Spot verbose model outputs that could be condensed
Track usage patterns across different users or features
Predict and control costs before they spiral
With Requesty's unified gateway, you can monitor token usage across 160+ models from a single dashboard, making it easy to compare efficiency between different providers like Claude 4, GPT-4o, or DeepSeek R1.
Latency: The Speed of Thought
Latency measures how quickly your LLM responds to requests. But here's the catch—averages lie. A service might average 500ms response times while some users wait 5 seconds. That's why monitoring tail latencies (P95, P99) is crucial.
Key latency metrics to track:
Time to first token (critical for streaming responses)
Total response time
P95/P99 latencies (what your slowest users experience)
Latency by model and provider
Requesty's smart routing automatically directs requests to the fastest available models, ensuring optimal latency while maintaining quality.
Cost: The Bottom Line
Every token processed translates directly to dollars spent. Real-time cost monitoring helps you:
Set and enforce budget limits
Identify cost-heavy operations or users
Compare pricing across different models
Optimize prompt engineering for cost efficiency
Through Requesty's routing optimizations, teams typically see up to 80% cost savings by intelligently routing requests to the most cost-effective models without sacrificing quality.
What Makes Requesty Live Logs Different
Traditional logging solutions weren't built for the unique challenges of LLM applications. Requesty Live Logs provides purpose-built monitoring that captures:
Comprehensive Request Data: Every prompt, response, token count, and timing metric
Real-Time Visibility: See what's happening now, not what happened yesterday
Intelligent Filtering: Quickly find specific requests by user, model, endpoint, or custom metadata
Cost Attribution: Know exactly how much each user, feature, or experiment costs
Error Tracking: Categorize and analyze failures, timeouts, and model-specific issues
Advanced Monitoring Patterns
Multi-Layer Observability
Effective monitoring happens at multiple levels:
Client Layer: Basic request tracking and user attribution
Gateway Layer: Rich logging of all LLM interactions (where Requesty shines)
Backend Layer: Application-specific metrics and business logic monitoring
By positioning monitoring at the gateway level, Requesty captures comprehensive data without requiring changes to your application code.
Proactive Anomaly Detection
Don't wait for problems to find you. Set up alerts for:
Token usage spikes (catch runaway prompts early)
Latency degradation (maintain user experience)
Error rate increases (identify reliability issues)
Cost threshold breaches (protect your budget)
Requesty's enterprise features include advanced alerting and budget controls, ensuring you're always in control.
Security and Compliance Monitoring
With Requesty's security guardrails, you can automatically:
Scan for PII and sensitive data in requests and responses
Detect potential prompt injection attacks
Ensure compliance with data residency requirements
Track and audit all LLM interactions for regulatory purposes
Practical Implementation Tips
Start with the Basics
Begin by monitoring these essential metrics:
Total tokens per request (input + output)
Response latency (P50, P95, P99)
Cost per request
Error rates by type
Requesty's quickstart guide gets you up and running in minutes with OpenAI-compatible SDKs.
Use Request Metadata Effectively
Tag your requests with custom metadata to enable powerful analytics:
```
user_id: Track per-user costs and usage
feature_name: Attribute costs to specific features
experiment_id: Compare different prompt versions
environment: Separate dev/staging/production metrics
```
Request metadata in Requesty enables granular tracking and analysis.
Implement Cost Controls
Prevent budget overruns with these strategies:
Set up real-time cost alerts
Implement per-user or per-API-key spending limits
Use cheaper models for non-critical tasks
Cache common responses to reduce API calls
Requesty's API spend limits and auto-caching features make cost control automatic.
Real-World Success Stories
Teams using Requesty Live Logs have achieved remarkable results:
A SaaS startup reduced their monthly LLM costs by 73% after identifying and optimizing inefficient prompts
An enterprise customer improved P95 latency by 2.3x using smart routing across multiple providers
A healthcare app ensured HIPAA compliance by implementing automated PII detection in their logs
An e-commerce platform prevented a $15,000 cost overrun by catching a recursive prompt bug within minutes
Best Practices for Long-Term Success
Treat Prompts as Code
Version your prompts and monitor their performance over time. Track metrics for each version to understand the impact of changes on cost, latency, and quality.
Monitor at Scale
As your application grows, ensure your monitoring solution can handle:
High request volumes (thousands per second)
Multiple models and providers
Complex routing logic
Team collaboration needs
Requesty's enterprise platform scales with your needs, supporting everything from startups to Fortune 500 companies.
Integrate with Your Existing Stack
Requesty works seamlessly with popular frameworks and tools:
LangChain integration for complex AI workflows
Vercel AI SDK for modern web applications
VS Code extension for development workflows
Standard OpenTelemetry export for custom observability pipelines
Getting Started with Requesty Live Logs
Ready to take control of your LLM operations? Here's how to get started:
1. Sign up for Requesty (free tier available) 2. Follow the quickstart guide to integrate with your application 3. Configure your monitoring preferences and alerts 4. Start seeing real-time insights into your LLM usage
With Requesty's unified gateway handling routing, caching, failover, and monitoring, you can focus on building great AI experiences while we handle the operational complexity.
Conclusion
Real-time monitoring of tokens, latency, and cost isn't just a nice-to-have—it's essential for any production LLM deployment. Without it, you're flying blind, risking budget overruns, performance issues, and compliance violations.
Requesty Live Logs provides the comprehensive observability you need, combined with powerful routing and optimization features that can reduce costs by up to 80%. By monitoring at the gateway level, you get complete visibility across all 160+ supported models while benefiting from intelligent routing, automatic failover, and enterprise-grade security.
Don't let your LLM costs spiral out of control or your users suffer from poor performance. Join the 15,000+ developers who trust Requesty to route, secure, and optimize their LLM traffic. Your future self (and your CFO) will thank you.
Start monitoring with Requesty today and experience the peace of mind that comes with complete LLM observability.