Developer Platform Release Notes

Workers Analytics Engine: Expanded SQL capabilities

You can now perform more powerful queries directly in Workers Analytics Engine with a major expansion of our SQL function library.

Workers Analytics Engine allows you to ingest and store high-cardinality data at scale (such as custom analytics) and query your data through a simple SQL API.

Today, we've expanded Workers Analytics Engine's SQL capabilities with several new functions:

New aggregate functions

• countIf() - count the number of rows which satisfy a provided condition
• sumIf() - calculate a sum from rows which satisfy a provided condition
• avgIf() - calculate an average from rows which satisfy a provided condition

New date and time functions

• toYear()
• toMonth()
• toDayOfMonth()
• toDayOfWeek()
• toHour()
• toMinute()
• toSecond()
• toStartOfYear()
• toStartOfMonth()
• toStartOfWeek()
• toStartOfDay()
• toStartOfHour()
• toStartOfFifteenMinutes()
• toStartOfTenMinutes()
• toStartOfFiveMinutes()
• toStartOfMinute()
• today()
• toYYYYMM()

Whether you're building usage-based billing systems, customer analytics dashboards, or other custom analytics, these functions let you get the most out of your data.

Get started with Workers Analytics Engine and explore all available functions in our SQL reference documentation.

Enable automatic tracing on your Workers

Enable automatic tracing on your Workers, giving you detailed metadata and timing information for every operation your Worker performs.

Tracing helps you identify performance bottlenecks, resolve errors, and understand how your Worker interacts with other services on the Workers platform. You can now answer questions like:

• Which calls are slowing down my application?
• Which queries to my database take the longest?
• What happened within a request that resulted in an error?

You can now:

• View traces alongside your logs in the Workers Observability dashboard
• Export traces (and correlated logs) to any OTLP-compatible destination, such as Honeycomb, Sentry, or Grafana, by configuring a tracing destination in the Cloudflare dashboard
• Analyze and query across span attributes (operation type, status, duration, errors)

To get started, set:

{
  "observability": {
    "tracing": {
      "enabled": true,
    },
  }
}

Note

In the future, Cloudflare plans to enable automatic tracing in addition to logs when you set observability.enabled = true in your Wrangler configuration.

While automatic tracing is in early beta, this setting will not enable tracing by default, and will only enable logs.

An updated compatibility_date will be required for this change to take effect.

Want to learn more?

• Read the announcement
• Check out the documentation

Cloudflare Workflows account-level limits increased

• Instance creation rate increased from 100 workflow instances per 10 seconds to 100 instances per second
• Concurrency limit increased from 4,500 to 10,000 workflow instances per account

These increases mean you can create new instances up to 10x faster, and have more workflow instances concurrently executing. To learn more and get started with Workflows, refer to the getting started guide.

If your application requires a higher limit, fill out the Limit Increase Request Form or contact your account team. Please refer to Workflows pricing for more information.

Rerank for more relevant results

You can now enable reranking to reorder retrieved documents based on their semantic relevance to the user’s query. Reranking helps improve accuracy, especially for large or noisy datasets where vector similarity alone may not produce the optimal ordering.

You can enable and configure reranking in the dashboard or directly in your API requests:

const answer = await env.AI.autorag("my-autorag").aiSearch({
  query: "How do I train a llama to deliver coffee?",
  model: "@cf/meta/llama-3.3-70b-instruct-fp8-fast",
  reranking: {
    enabled: true,
    model: "@cf/baai/bge-reranker-base"
  }
});

Set system prompts in API

Previously, system prompts could only be configured in the dashboard. You can now define them directly in your API requests, giving you per-query control over behavior. For example:

// Dynamically set query and system prompt in AI Search
async function getAnswer(query, tone) {
  const systemPrompt = `You are a ${tone} assistant.`;
  const response = await env.AI.autorag("my-autorag").aiSearch({
    query,
    system_prompt: systemPrompt
  });
  return response;
}

// Example usage
const query = "What is Cloudflare?";
const tone = "friendly";
const answer = await getAnswer(query, tone);
console.log(answer);

Learn more about Reranking and System Prompt in AI Search.