--- title: Why raising your serverless timeout won't save long jobs description: Raising a serverless timeout doesn't fix long jobs, because a job that still crosses the new ceiling loses all its progress. A $13B AI app platform tells teams... canonical: https://daily.dev/posts/why-raising-your-serverless-timeout-won-t-save-long-jobs-qdgq0mach twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Why raising your serverless timeout won't save long jobs | daily.dev og:description: Raising a serverless timeout doesn't fix long jobs, because a job that still crosses the new ceiling loses all its progress. A $13B AI app platform tells teams... og:url: https://daily.dev/posts/why-raising-your-serverless-timeout-won-t-save-long-jobs-qdgq0mach og:image: https://api.daily.dev/og/posts/QdGq0MaCH.png og:image:alt: Why raising your serverless timeout won't save long jobs og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Why raising your serverless timeout won't save long jobs **[Inngest Blog](https://daily.dev/sources/inngest)** · 8 min read · 0 upvotes · 0 comments ## Summary Raising a serverless timeout doesn't fix long jobs, because a job that still crosses the new ceiling loses all its progress. A $13B AI app platform tells teams that anything needing to run reliably past 10 minutes should use Inngest instead, since their serverless runtimes cap out at two to five minutes and the biggest use case was long-running internal agents. Inngest checkpoints each step's result, letting a function hand off between requests via a setting like checkpointing.maxRuntime so a deploy or crash resumes from the last step instead of starting over. Limits include a 2-hour max per step, 1,000 steps per function, and 32MB of run state. Durable execution doesn't give agents sandboxes or lower inference costs, though. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### why doesn't just increasing my serverless function timeout fix my long-running job failures Because raising the timeout only moves the failure point further out, and a job that crosses the new ceiling still loses everything it has done. The real risk isn't hitting the exact limit, it's failing partway through on a slow day, for example dying at 1:58 on a 2-minute limit while mid-write to three systems, with no saved progress. _Anyone debugging flaky long-running jobs can compare durable execution approaches like this one on daily.dev._ ### how can I run a 30 minute AI agent job on a serverless platform with a 2 minute timeout Split the job into steps that each fit under your host's timeout and use a tool that checkpoints each step's result, such as Inngest's checkpointing.maxRuntime setting in its TypeScript and Go SDKs. Inngest saves every finished step before the request is cut off, so the next request resumes at the next step instead of restarting; each step still has to fit within the host's own timeout, up to a 2-hour max per step on Inngest. _Developers architecting agent workflows around platform limits can track patterns like this on daily.dev._ ### what are the limits on steps and state when using Inngest for durable agent workflows Each step is bounded by the host's timeout, with a 2-hour maximum per step on Inngest, up to 1,000 steps allowed per function, and a cap of 32MB of run state. The Python SDK does not yet support checkpointing within a single request, so each step gets its own request there, though the outcome works the same as checkpointed SDKs. _Engineers planning agent infrastructure limits can keep up with SDK specifics like these on daily.dev._ ## Similar posts on daily.dev - [How to Build AI Agents That Don’t Start Over When They Fail](https://daily.dev/posts/how-to-build-ai-agents-that-don-t-start-over-when-they-fail-hdtnqpnlp) · System Design Newsletter · 3 upvotes · 1 comments - [AWS Lambda Pushes Serverless Toward Long-Running Workloads](https://daily.dev/posts/aws-lambda-pushes-serverless-toward-long-running-workloads-2zbrcptyu) · InfoQ · 0 upvotes · 0 comments - [Durable AI Workflows 2026: Inngest, Trigger.dev, Vercel Workflow](https://daily.dev/posts/durable-ai-workflows-2026-inngest-trigger-dev-vercel-workflow-un2tgyyqs) · Alex CloudStar · 0 upvotes · 0 comments - [The Queue is Durable. Your Worker is Not](https://daily.dev/posts/the-queue-is-durable-your-worker-is-not-ynde5ay4l) · Inngest Blog · 0 upvotes · 0 comments - [All your workflows are about to be long running. Build for it.](https://daily.dev/posts/all-your-workflows-are-about-to-be-long-running-build-for-it--ff8epi154) · Inngest Blog · 0 upvotes · 0 comments --- Tags: [#ai-agents](https://daily.dev/tags/ai-agents), [#backend](https://daily.dev/tags/backend), [#serverless](https://daily.dev/tags/serverless), [#inngest](https://daily.dev/tags/inngest) [View this post on daily.dev](https://daily.dev/posts/why-raising-your-serverless-timeout-won-t-save-long-jobs-qdgq0mach) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Why raising your serverless timeout won't save long jobs","url":"https://daily.dev/posts/why-raising-your-serverless-timeout-won-t-save-long-jobs-qdgq0mach","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/why-raising-your-serverless-timeout-won-t-save-long-jobs-qdgq0mach"},"datePublished":"2026-10-29T22:08:45.881Z","dateModified":"2026-10-29T22:09:43.140Z","description":"Raising a serverless timeout doesn't fix long jobs, because a job that still crosses the new ceiling loses all its progress. 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The real risk isn't hitting the exact limit, it's failing partway through on a slow day, for example dying at 1:58 on a 2-minute limit while mid-write to three systems, with no saved progress. Anyone debugging flaky long-running jobs can compare durable execution approaches like this one on daily.dev."}},{"@type":"Question","name":"how can I run a 30 minute AI agent job on a serverless platform with a 2 minute timeout","acceptedAnswer":{"@type":"Answer","text":"Split the job into steps that each fit under your host's timeout and use a tool that checkpoints each step's result, such as Inngest's checkpointing.maxRuntime setting in its TypeScript and Go SDKs. Inngest saves every finished step before the request is cut off, so the next request resumes at the next step instead of restarting; each step still has to fit within the host's own timeout, up to a 2-hour max per step on Inngest. 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