As of OpenLMIS v3, the architecture has transitioned to (micro) services fulfilling RESTful (HTTP) API requests. A modularized Reference UI application runs in a browser and uses those APIs to expose functionality to end users. Other systems and mobile apps may also use the APIs to integrate and provide functionality. A Reporting and Analytics Platform uses a data warehouse strategy to offer visualizations of OpenLMIS data.

Extension mechanisms allow for components of the architecture to be customized without the need for the community to fork the code base:

  • UI modules give flexibility in creating new user experiences or changing existing ones
  • Extension Points & Modules - allows Service/API functionality to be modified
  • Extra Data - allows for extensions to store data with existing components
  • Reporting and Analytics Platform - allows for robust reporting solutions to be developed to meet implementation needs

Combined these components allow the OpenLMIS community to customize and contribute to a shared LMIS.

New Service Guidelines

OpenLMIS’ Service architecture is centered around the concept of Bounded Contexts. In this pattern we identify Service’s by grouping similar things (noun) into a Service, and define a clear boundary between that Service and others. Where to draw this line, and decide when to create a new Service or when to contribute to/extend an existing Service can sometimes be difficult to judge.

A quick set of guidelines for a OpenLMIS Service:

  • A Service owns its data. For example the Requisition Service owns all the data that pertains to a Requisition and moving it through the workflow. It depends on information to help it along: facilities, programs, user’s, etc. While these things are needed for a Requisition, they aren’t inherently a Requisition’s things. The Requisition service owns Requisition things: Requisitions and their Line Items, Requisition Templates, etc. It coordinates with other OpenLMIS Service’s to obtain references of those other things it needs, that it doesn’t own.
  • A Service owns transactions. Operations on a Service’s things almost always occur within a transaction. We read the state of a Requisition or write new state about that Requisition. Other Service’s may become involved, however the transaction as it appears to the User is owned by the original Service.
  • Service’s backing data stores (usually relational databases) do not know about one-another. Only Service’s know about other Services. Because of this it’s the responsibility of the Services for maintaining referential integrity, as Foreign Key’s can’t cross Services’s databases.

When considering creating a new Service, consider if that Service really owns its own things, and should be implemented as an OpenLMIS Service, or if instead the functionality needed is a re-use of existing things in a new way, in which case a contribution/extension should be made to an existing OpenLMIS Service. OpenLMIS does not follow Serverless architecture at this time.


Docker Engine and Docker Compose is utilized throughout the tech stack to provide consistent builds, quicken environment setup and ensure that there are clean boundaries between components. Each deployable component is versioned and published as a Docker Image to the public Docker Hub. From this repository of ready-to-run images on Docker Hub anyone may pull the image down to run the component.

Development environments are typically started by running a single Service or UI module’s development docker compose. Using docker compose allows the component’s author to specify the tooling and test runtime (e.g. PostgreSQL) that’s needed to compile, test and build and package the production docker image that all implementation’s are intended to use.

After a production docker image is produced, docker compose is used once again in the Reference Distribution to combine the desired deployment images with the needed configuration to produce an OpenLMIS deployment.