Private and Secure

Get isolated and single tenant hosted environment in your GCP account with recommended configuration including Kubernetes.

Your code and data will be secure inside your account.

Productive and Powerful

Deploy 12-factor based applications and supercharge your workflow using better developer tools and integrations.

Focus on your "Apps" not on "Ops". No more App-engine idiosyncrasies.

Inexpensive & Optimized

Datacol optimizes your environment with best of community knowledge, providing seamless integration with cloud services.

Get lower bills via sustained discount.

What we offer

Container native

Use Docker images, containers and language buildpacks out of the box. Push your code and we'll do the rest.

Optimized for GCP

We integrate cloud services (like CloudSQL, Pubsub etc.) with recommended settings. You can save upto 40% on your cloud bill.

CI/CD Support

Use developer friendly CLI to configure and manage your apps.

Productivity tools

Send notifications to productivity apps like Slack, Github and others.

Open source

Datacol source code is open-sourced at Github and open to suggestions and contributions.


While Datacol is tied with Google, your apps are still portable, and run elsewhere unlike App-engine.

How It Works

Datacol is a control layer on top of GCP, to provide Heroku like experience with power of Kubernetes under the hood.

Get started by downloading our CLI to create a stack. It will create a Kubernetes cluster and other resources in your GCP account.

You can deploy multiple apps in cluster and share services among them.

curl -Ls > /tmp/ 
unzip /tmp/ -d /usr/local/bin
datacol init --project <project>

Build your apps and easily deploy them to cluster. You can -

  • Create 12-factor apps with Buildpacks, Dockerfile or docker-compose.yml on Kubernetes.
  • Provision infrastructure with helm charts managed by us.
  • Link GCP services easily (like automatically setting cloud-sql proxy , service-account and many more).
datacol apps create # create app
datacol deploy      # deploy app
datacol env set API_KEY=secret  # set env vars

We will automatically setup logging, metrics and alerts to become more productive.

  • Configuring Auto scaling
  • Executing scheduled and one-off tasks
  • HTTPS/SSL certificates using ACME
# install redis as backing service

datacol helm install stable/redis
datacol logs -t   # stream logs
datacol scale --count=3   # scale

Be part of our growing community to share knowledge. Our engineers are here to answer questions and help you set up your stack.

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