Skip to content

The backend DAG processing engine for Boomerang Flow, a no-code, cloud-native workflow automation tool. Built in Java using Sprint Boot

Notifications You must be signed in to change notification settings

boomerang-io/flow.service.engine

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Flow Engine Service

based on Flow's Workflow Service and TektonCD

v3 to v4 Change Log

There has been an entire code base refactor from v3 to v4 for the engine. We suggest you read the following information to understand the full breadth of changes

Pre-Requisites

This service connects to MongoDB and requires Task Templates and indexes loaded through the Flow Loader. You can run these locally, or alternatively connect to a remote MongoDB service.

Run Local MongoDB w Docker

docker run --name local-mongo -d mongo:latest

Load Boomerang Flow Data

docker run -e JAVA_OPTS="-Dspring.data.mongodb.uri=mongodb://localhost:27017/boomerang -Dflow.mongo.collection.prefix=flow -Dspring.profiles.active=flow" --network host --platform linux/amd64 boomerangio/flow-loader:latest

Development

This project uses Gradle to compile

Build JAR

gradle build

Build Docker Locally

docker buildx build --platform=linux/amd64 -t flow-engine:latest .

Note: these commands have been validated on an M1 Mac

Running the Docker Container

docker run -e JAVA_OPTS="-Dspring.data.mongodb.uri=mongodb://localhost:27017/boomerang -Dflow.mongo.collection.prefix=flow -Dspring.profiles.active=flow" --platform=linux/amd64 flow-engine:latest 

Dependencies

Parameters and Results

The implementation is based on Tekton Params and Results.

There is limited support for Tekton Propagated Object Parameters in that Tekton requires you to provide the Spec for the JSON Object if you are going to reference child elements. We do not have this constraint, we essentially take the path from what is provided after params.<param-name>.

Locks

For distributed locking, we use this distributed lock project with the Mongo implementation.

The implementation in LockManagerImpl.java relies on the TTL Index for Retries having been added via the flow.loader.

Error Handling

The following provides design and reference information about the status codes and error messages.

Response Format

The format can be seen in io.boomerang.error.ErrorDetail.java

Field Description
timestamp UTC timestamp of when the error occurred
code unique identifier (int) that can be read and understood that detect and handle errors programmatically.
reason unique identifier (string) that can be used to quickly identify and search for more information regarding the error.
message a description of the error intended for a human and an end user to provide context.
status HTTP Status Code & Message
cause Optional present if flow.error.include-cause=true config property is provided
{
  "timestamp": "2023-01-31T00:15:12.672+00:00",
  "code": 1001
  "reason": "QUERY_INVALID_FILTERS",
  "message": "Invalid query filters(status) have been provided.",
  "status": "400 BAD_REQUEST",
  "cause": null
}

Implementation

The implementation allows for known and custom exceptions in the code.

Known codes are indexed in the io.boomerang.error.BoomerangError.java with the message text in messages.properties. Alternatively, a custom exception can be thrown in the code however this will lose the benefit of localization (future)

About

The backend DAG processing engine for Boomerang Flow, a no-code, cloud-native workflow automation tool. Built in Java using Sprint Boot

Topics

Resources

Stars

Watchers

Forks

Packages

No packages published