Understanding Parallel Jobs in Azure DevOps

Understanding Parallel Jobs in Azure DevOps

In Azure DevOps, parallel jobs enable a build or release pipeline to execute multiple tasks simultaneously, improving the overall efficiency and reducing the time taken for a pipeline to complete. Parallel jobs allow workloads to be divided and processed concurrently.

How a Parallel Job is Consumed by a Build or Release

When a build or release is triggered, Azure DevOps can divide the tasks into multiple jobs. Each job runs independently on an agent, and the results are aggregated back once all parallel jobs are complete.

Execution Flow:

• A pipeline is divided into multiple stages.

• Each stage can contain one or more jobs.

• Each job runs on a separate agent or on the same agent depending on the configuration.

• Jobs within a stage are executed in parallel, increasing throughput.

Simple Example of Parallel Jobs

Consider a simple build pipeline with two stages:

Stage 1:

• Job A: Runs unit tests

• Job B: Builds the application

• Job C: Runs integration tests

In this case, Job A, Job B, and Job C can be executed in parallel. Once these jobs complete, the pipeline moves on to subsequent stages.

Relationship Between Jobs and Parallel Jobs

• Job: Represents a single unit of work or task that runs within a stage.

• Parallel Job: Allows multiple jobs to be executed concurrently within the same stage or pipeline.

Example:

Stage 1 has two jobs:

• Job 1: Compiles the application

• Job 2: Runs unit tests on the compiled application

Both Job 1 and Job 2 are executed in parallel, leveraging multiple agents or cores to speed up the overall pipeline.

Benefits of Using Parallel Jobs

1. Faster Execution: Parallel jobs reduce the overall build or release time by running tasks concurrently.

2. Resource Utilization: Multiple agents or resources can be utilized effectively to complete jobs in parallel.

3. Scalability: Helps manage large workloads more efficiently by breaking them into smaller, parallel tasks.

Configuration of Parallel Jobs

1. Job Dependencies: You can specify dependencies between jobs to control execution order.

2. Max Parallelism: Control the number of jobs running in parallel to balance between speed and resource consumption.

Summary

By understanding and effectively utilizing parallel jobs, organizations can significantly optimize their CI/CD pipelines for performance and scalability.