AutoKitteh
Write Python code, run durable, scalable workflows effortlessly
AutoKitteh lets developers build, deploy, and manage long‑running, reliable workflows in vanilla Python, with built‑in integrations, API‑first design, and optional self‑hosted or cloud deployment.
Overview
Who it's for
AutoKitteh targets developers who need programmable automation beyond the constraints of no‑code iPaaS tools. By letting you author workflow logic in plain Python (or Starlark), it blends the familiarity of code with the reliability of a managed execution engine.
Core capabilities
The platform exposes an API‑first surface via gRPC and HTTP, enabling you to trigger workflows from webhooks, schedulers, or the built‑in CLI. Built‑in integrations for Slack, GitHub, Twilio, ChatGPT, Gmail, and many others let you connect services without writing glue code. Under the hood, AutoKitteh leverages Temporal to provide durable, long‑running execution, automatic state recovery, and horizontal scalability. Management, monitoring, and debugging are available through a web UI, a VS Code extension, and command‑line tools.
Deployment flexibility
You can run AutoKitteh on‑premises or in your own cloud environment, or opt for the managed beta cloud offering. The serverless‑style architecture scales automatically, while the open‑source codebase (Apache‑2.0) lets you customize or extend the platform as needed.
Highlights
Pros
- Write automation in familiar Python without proprietary DSLs
- Automatic state recovery and scalability out of the box
- Self‑hosted or managed cloud deployment options
- Rich monitoring, debugging, and observability tools
Considerations
- JavaScript support is not yet available (coming soon)
- Building from source requires Go 1.24 and additional tooling
- Managed cloud offering is currently in beta
- Learning Temporal concepts may add initial overhead
Fit guide
Great for
- DevOps and infrastructure automation
- FinOps cost‑optimization pipelines
- MLOps model training and deployment workflows
- Security orchestration and automated incident response (SOAR)
Not ideal when
- Pure business users seeking drag‑and‑drop no‑code solutions
- Simple one‑off scripts where a full platform adds unnecessary complexity
- Environments lacking Python or Go runtime support
- Real‑time ultra‑low latency processing where workflow engine latency is unacceptable
How teams use it
Automated incident response
Enrich security alerts, notify stakeholders via Slack, and trigger remediation actions without manual steps.
Scheduled financial reporting
Collect data from accounting APIs, generate PDFs, and email monthly reports reliably.
ML model retraining pipeline
Orchestrate data extraction, model training, validation, and deployment on a recurring schedule.
GitHub pull‑request automation
Run tests, post results to ChatGPT for review, and auto‑merge approved PRs.
Tech snapshot
Frequently asked questions
Which programming languages can I use to define workflows?
Workflows can be written in vanilla Python or Starlark; JavaScript support is planned for a future release.
How does AutoKitteh ensure durability of long‑running workflows?
It runs on top of Temporal, which persists workflow state and automatically recovers from failures, guaranteeing no loss of progress.
Can I run AutoKitteh on my own infrastructure?
Yes, the server can be self‑hosted on‑premises or in any cloud environment using the provided binaries or Docker images.
Is there a managed cloud version available?
A managed cloud iPaaS offering is in beta; you can request access via the contact email.
How can I add integrations that are not built in?
New integrations can be added by implementing HTTP or gRPC calls within your Python workflow code, leveraging the platform’s extensible API.
Project at a glance
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