How Doordash designed a successful write-heavy scalable and reliable inventory platform

Case study: Write-heavy scalable and reliable inventory platform

Logs are like the footprints of your LLM, tracking every move it makes. We will look at how logging can help you see beneath the top layer of a system, which can help you troubleshoot problems and better understand the system behavior.

Logging

Metrics give you the rundown on how your LLM’s performing. We will show how to use these metrics to identify issues, increase efficiency, and make changes for improved outcomes.

Metrics

Observability in AI is all about understanding what’s going on inside complex systems. It gives you the tools - logs, metrics, and traces - to monitor, troubleshoot, and optimize how AI models and services run.

Observability in AI platforms

Tracing is like following your LLM’s journey, step by step. We will explain how tracing makes it easy to identify and address problems by allowing you to track the entire process.

Tracing

A practical guide to building monitoring systems that actually work. We share our approach to making smart decisions about what to monitor, how to collect data, and when to add complexity.

Approach to building monitoring

A practical guide to choosing the right metrics for system health monitoring. We cut through the noise to focus on metrics that directly impact your users and business.

#observability

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