Deploy Your Apps and Agents Where Your Data Lives With Aiven Runtime

Everything that makes an app or agent real happens after it works on your machine.

Locally coding an app is a joy: hot reload, a seeded database, a mocked API key. Then you go to ship it, and "deploy" quietly expands into a Dockerfile that behaves in CI, somewhere to actually run the container, a database it can reach, TLS, secrets wired into the environment, and a pipeline to hold it all together. The feature took an afternoon. The plumbing takes the rest of the week.

Agents make the gap worse, because their whole point is acting on production data. A ticket-resolving agent that's impressive against sample data is useless in production until it can reach the real thing: live data, the right credentials, a network path to the database, and a straight answer for security about where that data goes and whether it ever leaves your environment. Your ten-minute demo just became a multi-week infrastructure project.

Beneath each scenario is the same structural problem: your code lives in one place and your data in another, and everything in between adds cost, latency, and attack surface. It's why teams so often wire local code straight to production data, with prod credentials on a laptop and query results landing wherever the code runs, well outside the environment built to protect them. Brittle by construction: every connection is one more thing to secure, and one more thing to fail.

That's the gap between "it works on my machine" and "it's running safely in production, next to real data."

Today we’re closing that gap. Aiven Runtime (formerly Aiven Apps) is now generally available to give builders one environment to run their apps and agents right next to their data.

Aiven Runtime: Unify your code and data

Aiven Runtime runs your AI agents and containerized apps next to your data, you spin up the app and the open-source services it depends on in one project, instead of standing them up separately and stitching them together. Your code executes right next to production data that stays private, fresh and governed.

Four things define the experience:

• Deploy anywhere. Run containerized apps on any cloud, AWS, Google Cloud or Azure (TBA). Write once, deploy anywhere, with nothing to re-architect when you move.
• Zero complexity. Your app runs beside your data and inherits its security and networking context automatically. Lower latency, a smaller attack surface, and none of the VPC, IAM or egress setup.
• Native tooling. Keep the tools and workflows you already use, Docker Compose, Containerfiles, your existing repos. Aiven detects your services and connects them for you. It just works.
• Agent-ready. Build and run AI agents with your favourite frameworks, right next to your data - so agents act on live, production data without it ever leaving your environment.

From repo to running, in minutes

Building with Aiven means building with best in class open-source engines and standards, which coding agents like Claude or Codex. git push a repo with a Containerfile or Compose file, and Aiven builds it, deploys it and wires it straight to your PostgreSQL, MySQL, Valkey, etc. No VPC peering, no secrets plumbing, no egress.

The workflow is the one you already know:

1. Write your app and describe it with a Containerfile or a Docker Compose file.
2. Deploy by pointing Aiven at it. Aiven builds the image, and for Compose files it automatically detects which services map to Aiven; a Postgres image becomes an Aiven for PostgreSQL service and wires the connection details in for you.
3. Run inside your data perimeter next to the services your app depends on.

Because it's all standard Compose and containers, the same definition runs on your laptop and on Aiven; so you can prototype locally and deploy to production in one click without changing a thing. The setup scales with you. What was once a multi-week, multi-pronged effort can be done in minutes.

What you can build

Aiven Runtime runs your code - any app or agent you can put in a container. That covers a lot of ground, so here are a few things builders run right next to their data:

• AI agents on live data: Support, ops or analytics agents that act on fresh, governed production data inside the perimeter, so the data never leaves.
• Alerting and monitoring: Real-time anomaly detection across tables, logs and streams, plus health-check services that keep your data services performing.
• Internal tools and APIs: Dashboards, notebooks and internal APIs with direct database access, without exposing data or building separate infra.
• Data jobs at the source: RAG embedding pipelines, ETL and enrichment, or PII stripping before storage beside the services they read and write.

Part of the Aiven Data & AI Cloud

Aiven Runtime is one layer of the Aiven Data & AI Cloud for builders. It brings the open-source services production AI depends on; Kafka, PostgreSQL, ClickHouse, Valkey, OpenSearch and DataHub, under one managed control plane, across any cloud, with no proprietary lock-in.

Runtime is where your applications and agents run. Aiven DataHub, generally available today alongside Aiven Runtime, gives those agents trusted, governed context: what data exists, what it means, and who's allowed to use it. And Aiven MCP gives them a standard, secure way to reach it. Put together, that's the difference between an AI project that stalls in a tangle of infrastructure and one that ships: fresh, governed data, and somewhere to run the code that acts on it - all in one place, on open source, on any cloud.

Runtime connects to the Aiven data services you already run with zero configuration.

Get started

Aiven Runtime is generally available today. If you can write a Containerfile, you can be running next to your data in minutes.

Deploy your first app

New to it, or want the guided version? Walk through it in the developer's guide, check out our documentation, or book a demo and we'll show you.