Indexify is a Function Execution Engine, not a container orchestration engine. Self Hosting Indexify involves -
  1. Deploying the Indexify Server
  2. Building and Deploying Container Images capable of running functions of your workflow.
  3. Deploying your Graphs to Indexify Server using the SDK.
Indexify doesn’t depend on Kubernetes or Docker, it is very flexible and can be deployed in the following manner -
  • Bare Metal and VMs
  • Docker Compose
  • Kubernetes (or any other container orchestrator)

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Bare Metal

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Download Indexify Server and Python SDK

  • The server can be downloaded from here.
  • Install the Python SDK using pip.
pip install indexify

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Start Server

Start the server on one machine. Read the configuration reference to understand how to customize the server to use blob stores for storing function outputs. 
indexify-server
By default the server will save graphs, invocations, and function outputs in the indexify_storage folder. Deleting that folder will require redeploying the graphs.
We have a replicated mode for the server, based on Raft consensus protocol. It’s not public yet because we are still figuring out how to make it easy to configure, operate and use by developers. If you are interested in using it, please reach out to us.

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Start Executor

Start as many executors you want in different machines. 
indexify-cli executor --server-addr <server-ip>:<server-port> [--image-version=<version>]
Arguments:
  • server-addr the address of the indexify server to connect to. Default: 127.0.0.1:8900.
  • image-version the version of the image exposed by this executor. Default: 1. Enables identifying the version of images run by this executor for function placement.
If interested, see more technical details about Executors in this README.

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Docker Compose

You can spin up the server and executor using docker compose, and deploy and run in a production-like environment. Copy the docker-compose.yaml file from here. 
docker compose up
This starts the server and two replicas of the executor in separate containers. Change the replicas field for the executor in docker compose to add more executors (i.e parallelism) to the workflow. This uses a default executor container based on Debian and a vanilla Python installation. We generally provide docker compose files for local testing of every example project in the repository.

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Kubernetes

We provide some basic Helm charts to deploy Indexify on Kubernetes. If you’d like to try with your own cluster, check out the instructions.