# Speeding Up Azure Durable Functions with Fan-Out/Fan-In and a Higher Concurrency Limit

DevFeed: [Speeding Up Azure Durable Functions with Fan-Out/Fan-In and a Higher Concurrency Limit](<https://devfeed.tech/articles/2-changes-made-our-azure-durable-functions-3x-faster-32183.md>)

Original publisher: [Read original article](<https://spin.atomicobject.com/azure-durable-functions-3x/>)

Author: Michael Li

Published: 2026-09-14T12:00:32Z

Content type: tutorial

Language: en

Sources: [Atomic Object](<https://devfeed.tech/sources/atomic-object.md>)

Topics: [Azure](<https://devfeed.tech/topics/azure.md>), [Concurrent Programming](<https://devfeed.tech/topics/concurrent-programming.md>), [Code](<https://devfeed.tech/topics/code.md>)

Tags: [apis](<https://devfeed.tech/tags/apis.md>), [azure](<https://devfeed.tech/tags/azure.md>), [azure-functions](<https://devfeed.tech/tags/azure-functions.md>), [batch](<https://devfeed.tech/tags/batch.md>), [concurrency](<https://devfeed.tech/tags/concurrency.md>), [development-practices](<https://devfeed.tech/tags/development-practices.md>), [file](<https://devfeed.tech/tags/file.md>), [storage](<https://devfeed.tech/tags/storage.md>)

## AI overview

An Azure Durable Functions batch job was accelerated by combining fan-out/fan-in orchestration with a higher function-host concurrency limit. Together, the changes reduced a representative run from about 710 seconds to about 240 seconds.

## Source excerpt

For one of our projects, we run a nightly job that generates a batch of files. It's a long process: pulling records from an upstream system, calling several APIs to gather info about each one, generating a file per record, and writing the results back to storage. For a small batch, this works fine, but [...] The post 2 Changes Made Our Azure Durable Functions 3X Faster appeared first on Atomic Spin.