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◆ AI Learning · Hard rule

How can a developer prevent an API server from getting too many requests at the same time?

When making many API calls at the same time, add a small delay between each call. This prevents too many requests from hitting a server at once. A small delay stops the server from becoming overloaded.

By Pawan Nayar · from the LLOS AI Learning record

The rule

When making many API calls at the same time, add a small delay between each call.

This prevents too many requests from hitting a server at once. A small delay stops the server from becoming overloaded.

Sending many requests to an API server all at once can cause problems. This is like a 'thundering herd' of requests. The server might send back an error, like a '429 Too Many Requests' message. A developer should add a small pause, for example, 250 milliseconds, between each API call. This spreads out the requests over time. It helps the server handle all requests without getting overloaded.

A developer writes code to update 100 user profiles through an API. If the developer sends all 100 requests instantly, the API server might crash or reject them. By adding a 250-millisecond delay before each request, the server receives requests one by one. This allows the server to process each update successfully.

Words you'll need

Resolved from this lesson's own record — real definitions, not invented for this page.

Distributed Systems

Multiple computers working together as one system

Load Balancing

Distributing LLM work across machines to serve many requests

Queueing Theory

Math for waiting lines and work piling up

Resource Management

Deciding what computing power the AI actually needs

Questions people ask

More from the same record, pulled by shared topic — not written new for this page.

How should a developer handle errors when calling an external API?

When a developer's code calls an external API, it should try only one time. The developer must not use loops to retry the call.

When should a developer use the Batch API, and what are the risks?

The Batch API is best for tasks with more than 50,000 calls. The cost savings must be worth a 24 to 48-hour wait time.

How should a developer make many API calls efficiently?

A developer must use parallel execution for scripts that make multiple API calls. This means many calls run at the same time.

How can a developer manage and run AI pipeline scripts effectively?

A developer needs to know the purpose of each script. A developer must understand what output each script creates.

What to remember

When making many API calls at the same time, add a small delay between each call. This prevents too many requests from hitting a server at once. A small delay stops the server from becoming overloaded.