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Netlify Releases Observability, AI Gateway and Prerendering Extensions

Netlify announced that Observability, AI Gateway, and Prerender extensions are now generally available to make it easier to understand how applications behave after deployment and reduce the operational work required to run them. 

They help developers ship with more confidence and less guesswork. Together, they mark the next step in Netlify's AI-native platform, bringing more of the development process onto one system so developers stay in flow from code to production.

Netlify offers Observability, AI Gateway, and Prerender extensions so developers stay in flow from code to production.

In October, Netlify introduced Agent Runners to help developers apply code updates through natural language instructions. That release built on earlier work with Why Did It Fail, which explains build failures in plain terms. Those efforts focused on creation and build. The new features extend that momentum into deploy and run, strengthening Netlify's Agent Experience (AX) vision: a workflow where developers and AI agents work in the same environment and move through the same steps. With more of the workflow in one place, developers can move from writing code to running applications without losing context. Netlifysupports the shift towards AI-supported development that spans the entire development workflow, not just the start of it.

"We're seeing developers move faster with AI when they write code, but deploy and run haven't kept up. We're changing that," said Matt Biilmann, CEO and Co-founder of Netlify. "When the work of writing code, understanding builds, and running applications lives on the same platform, developers don't have to stitch their workflow across different tools. It's a cleaner experience, and it's the direction modern development is moving."

  • Observability gives developers immediate insight into how an application behaves after each deploy. It surfaces request and function activity so it's easier to spot changes in latency, error patterns, or usage tied to recent updates. Developers can see what changed and why directly in the Netlify dashboard without maintaining a separate monitoring system. For enterprise teams, Observability provides the visibility needed to run AI-powered applications as dependable production workloads. This becomes even more important as teams begin relying on agents to generate and modify more of their code.
  • AI Gateway lets any agent or developer add AI features to applications that work from the first prompt, without creating or managing accounts, credentials, or environment variables. Like other Netlify primitives, it's ready to use the moment you deploy. AI Gateway securely centralizes credentials, simplifies billing, and tracks usage across providers including Anthropic, OpenAI, and Google Gemini, making it easier to manage and scale AI features in production. Teams can experiment with different models faster and get clearer visibility into AI usage across their applications.
  • Prerendering extensions fix this automatically by serving a fully rendered HTML version to crawlers while preserving the dynamic experience for users. Search engines and AI agents get a complete view of each page, and developers avoid maintaining separate rendering paths. 

These new capabilities strengthen Netlify's AI-native direction by supporting more of the workflow that developers and agents rely on together.

Availability Observability and AI Gateway are generally available now. Prerender extensions are available to all Netlify plans.

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Netlify Releases Observability, AI Gateway and Prerendering Extensions

Netlify announced that Observability, AI Gateway, and Prerender extensions are now generally available to make it easier to understand how applications behave after deployment and reduce the operational work required to run them. 

They help developers ship with more confidence and less guesswork. Together, they mark the next step in Netlify's AI-native platform, bringing more of the development process onto one system so developers stay in flow from code to production.

Netlify offers Observability, AI Gateway, and Prerender extensions so developers stay in flow from code to production.

In October, Netlify introduced Agent Runners to help developers apply code updates through natural language instructions. That release built on earlier work with Why Did It Fail, which explains build failures in plain terms. Those efforts focused on creation and build. The new features extend that momentum into deploy and run, strengthening Netlify's Agent Experience (AX) vision: a workflow where developers and AI agents work in the same environment and move through the same steps. With more of the workflow in one place, developers can move from writing code to running applications without losing context. Netlifysupports the shift towards AI-supported development that spans the entire development workflow, not just the start of it.

"We're seeing developers move faster with AI when they write code, but deploy and run haven't kept up. We're changing that," said Matt Biilmann, CEO and Co-founder of Netlify. "When the work of writing code, understanding builds, and running applications lives on the same platform, developers don't have to stitch their workflow across different tools. It's a cleaner experience, and it's the direction modern development is moving."

  • Observability gives developers immediate insight into how an application behaves after each deploy. It surfaces request and function activity so it's easier to spot changes in latency, error patterns, or usage tied to recent updates. Developers can see what changed and why directly in the Netlify dashboard without maintaining a separate monitoring system. For enterprise teams, Observability provides the visibility needed to run AI-powered applications as dependable production workloads. This becomes even more important as teams begin relying on agents to generate and modify more of their code.
  • AI Gateway lets any agent or developer add AI features to applications that work from the first prompt, without creating or managing accounts, credentials, or environment variables. Like other Netlify primitives, it's ready to use the moment you deploy. AI Gateway securely centralizes credentials, simplifies billing, and tracks usage across providers including Anthropic, OpenAI, and Google Gemini, making it easier to manage and scale AI features in production. Teams can experiment with different models faster and get clearer visibility into AI usage across their applications.
  • Prerendering extensions fix this automatically by serving a fully rendered HTML version to crawlers while preserving the dynamic experience for users. Search engines and AI agents get a complete view of each page, and developers avoid maintaining separate rendering paths. 

These new capabilities strengthen Netlify's AI-native direction by supporting more of the workflow that developers and agents rely on together.

Availability Observability and AI Gateway are generally available now. Prerender extensions are available to all Netlify plans.

The Latest

Over the last year, we've seen enterprises stop treating AI as “special projects.” It is no longer confined to pilots or side experiments. AI is now embedded in production, shaping decisions, powering new business models, and changing how employees and customers experience work every day. So, the debate of "should we adopt AI" is settled. The real question is how quickly and how deeply it can be applied ...

In MEAN TIME TO INSIGHT Episode 20, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA presents his 2026 NetOps predictions ... 

Today, technology buyers don't suffer from a lack of information but an abundance of it. They need a trusted partner to help them navigate this information environment ...

My latest title for O'Reilly, The Rise of Logical Data Management, was an eye-opener for me. I'd never heard of "logical data management," even though it's been around for several years, but it makes some extraordinary promises, like the ability to manage data without having to first move it into a consolidated repository, which changes everything. Now, with the demands of AI and other modern use cases, logical data management is on the rise, so it's "new" to many. Here, I'd like to introduce you to it and explain how it works ...

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