Azure DevOps introduces parallelism, allowing multiple tasks to run concurrently within development pipelines. This article explores the concept, benefits, and types of parallelism in Azure DevOps, highlighting its role in optimizing continuous integration and deployment processes. 

Parallelism in Azure DevOps

In Azure DevOps, parallelism allows for the simultaneous execution of multiple processes or tasks within a development or release pipeline. This functionality lets developers break down intricate operations into smaller, independent segments that can be run concurrently on separate agents or resources.

Using parallelism in Azure DevOps boosts the effectiveness of continuous integration and deployment processes, thereby speeding up overall build and release schedules.

This approach is particularly advantageous for extensive projects as it facilitates quicker feedback on code modifications and enhances the scalability and pace of software development pipelines hosted on the Azure DevOps platform.

Why is enabling Parallelism in Azure DevOps important?

Enabling parallelism in Azure DevOps is essential for optimizing development and release workflows. Developers can utilize parallel processing to effectively distribute workloads, allowing tasks to run concurrently across multiple agents or environments.

This approach not only reduces the time needed for complex build and deployment processes but also capitalizes on the scalability of cloud resources.

Parallelism becomes particularly crucial when managing extensive codebases. It empowers developers to exploit parallel builds and executions, resulting in quicker feedback loops and increased throughput.

This approach enhances resource efficiency, mitigates bottlenecks, and fosters a more agile and responsive continuous integration and continuous deployment (CI/CD) environment within Azure DevOps.

What Makes a parallel job in Azure DevOps?

A parallel job in Azure DevOps signifies the simultaneous execution of multiple activities or stages within a pipeline stage.

Each job represents an individual unit of work, and enabling parallel tasks allows these units to operate on separate agents or virtual machines concurrently. This concurrent execution is beneficial for enhancing the efficiency of the build or release process and reducing the overall pipeline completion time.

The capability to create parallel jobs within a stage in Azure DevOps enables developers to divide extensive workflows into smaller, independent tasks that can be executed simultaneously. This approach enhances resource efficiency, accelerates feedback cycles, and contributes to a more streamlined and agile continuous integration and continuous deployment (CI/CD) pipeline.

Types of Parallel Jobs in Azure DevOps

Microsoft Hosted Parallel Job:

Microsoft Hosted Parallel Jobs in Azure DevOps are execution environments provided by Microsoft that run concurrently on cloud-based agents. They offer a scalable and straightforward approach to parallelizing jobs in CI/CD pipelines, eliminating the need for users to oversee the underlying infrastructure.

Self-Hosted Parallel Job:

In Azure DevOps, self-hosted parallel jobs run concurrent tasks on agents managed by the user, providing greater control over the execution environment. Users can set up and manage their own build or deployment agents on their infrastructure, granting them control over resources and dependencies.

Microsoft-Hosted vs. Self-Hosted Parallel Jobs

If you prefer to run your jobs on machines managed by Microsoft, opt for Microsoft-Hosted Parallel Jobs. Your jobs will be executed on Microsoft-hosted agents.

If you want Azure Pipelines to manage your builds and releases, but wish to use your own machines for execution, choose Self-Hosted Parallel Jobs. To use self-hosted parallel jobs, you’ll begin by deploying our self-hosted agents on your machines. You can register any number of these self-hosted agents within your organization.

Microsoft-Hosted

 

For Microsoft-Hosted Parallel Jobs in public projects, you can access up to 10 free Microsoft-hosted parallel jobs, each running for a maximum of 360 minutes (6 hours) per instance. This free grant is not automatically provided when you create a new Azure DevOps organization.

For private projects, a single free job is available, which can run for up to 60 minutes per instance. This free grant is also not always automatically allocated when you create a new Azure DevOps organization.

It may take us 2-3 business days to respond to your request for the free tier.
There is no time constraint on parallel jobs for public projects, while private projects have a monthly time limit of 30 hours.

Public project: Up to 10 complimentary Microsoft-hosted parallel jobs, each capable of running for a maximum of 360 minutes (6 hours) per instance.

Time Limit: No overall time limit per month

Private project: One free job that can run for up to 60 minutes each time

Time Limit: 1,800 minutes (30 hours) per month

When the free tier no longer meets your needs, additional capacity for each parallel job can be purchased. For the cost per parallel job, refer to the Azure DevOps pricing page. Paid parallel jobs eliminate the monthly time limit, allowing each job to run for up to 360 minutes (6 hours).

New organizations are initially limited to 25 parallel jobs for Microsoft-hosted agents. Contact support to request an increase, subject to the available capacity in your organization’s region.

Upon purchasing your first Microsoft-hosted parallel job, the total number of parallel jobs in your organization remains at one. To run two jobs concurrently, you’ll need to buy two parallel jobs if you’re still on the free tier. The initial purchase only removes the time limits from the first job.

Self-Hosted

For self-hosted parallel jobs, you can register any number of self-hosted agents within your organization. The charges are based on the number of jobs you wish to run concurrently, not on the number of agents registered. There are no time constraints on self-hosted jobs.

For public projects using self-hosted agents, you can run an unlimited number of parallel jobs. In contrast, for private projects, one job is available, with an additional job provided for each active Visual Studio Enterprise subscriber who is a member of your organization.

Public Project: The number of Parallel jobs is unlimited and there is no time limit.

Private Project: You receive an extra self-hosted parallel job for each active Visual Studio Enterprise subscriber within your organization. There is no time limit.

When the free tier is inadequate for your self-hosted private project, you can purchase additional capacity per parallel job.

How many parallel jobs do I require?

When the number of queued builds and releases surpasses the number of parallel jobs you possess, your build and release queues will become longer. If you encounter excessively long queue delays, you can acquire additional parallel jobs as required. There are various methods available to check your parallel job limits and job history.

View Job History Using The Pool Consumption Report

You can utilize the Pool consumption report, accessible on the Analytics tab of your agent pool, to view a chart displaying running and queued jobs along with your parallel jobs over the past 30 days. If you have a backlog of queued jobs and your running jobs reach the concurrency limit, you might consider purchasing additional parallel jobs.

When working with code involving complex data operations, it’s often possible to enhance performance using techniques such as parallel programming and/or data parallelism.

Data parallelism refers to situations where the same operation is executed concurrently (in parallel) on elements within a source collection or array. In data parallel operations, the source collection is divided so that multiple threads can work on different segments simultaneously.

In the .NET Framework, the Task Parallel Library (TPL) facilitates data parallelism through the System.Threading.Tasks.Parallel class. This class offers method-based parallel implementations for and foreach loops using the Parallel.For and Parallel.ForEach constructs in C#.

Essentially, you write the loop logic for a Parallel.For or Parallel.ForEach loop much as you would for a sequential loop. There’s no need to create threads or queue work items, and in basic loops, you don’t have to use locks. The TPL manages all the low-level tasks for you.

The Parallel class’s ForEach method is a multi-threaded implementation of the common C# loop construct, the foreach loop. While a foreach loop allows you to iterate over an enumerable data set represented using an IEnumerable, Parallel.ForEach iterates over an enumerable data set but employs multiple threads to evaluate different invocations of the loop body.

These characteristics make Parallel.ForEach a versatile mechanism for data-parallel programming.

Incorporating this class into your code can significantly enhance performance, as your code can use the full processing power of your CPU.

There are two primary benefits to using parallelism:

• Increased Efficiency: By executing tasks concurrently, you can substantially reduce the overall pipeline execution time. This is particularly advantageous for complex pipelines with numerous steps.
• Improved Resource Utilization: Parallelism enables you to use available resources more efficiently. If multiple agents are available, you can run multiple jobs concurrently instead of waiting for each one to complete sequentially.

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Conclusion

Parallelism in Azure DevOps emerges as a crucial feature to meet these demands head-on. By allowing the concurrent execution of multiple tasks or processes within a development or release pipeline, parallelism significantly enhances the efficiency and speed of continuous integration and deployment workflows. Whether it’s the Microsoft-hosted or self-hosted parallel jobs, Azure DevOps offers flexible and scalable solutions tailored to the unique needs of different projects.

Bobcares DevOps support services add another layer of value to this equation. Their expertise in managing and optimizing Azure DevOps environments ensures that parallelism is effectively implemented and maintained. With their guidance, organizations can navigate the complexities of parallel processing, maximizing the benefits of Azure DevOps’ parallel jobs while minimizing potential pitfalls. Their hands-on approach and proactive monitoring help in identifying and resolving issues swiftly, guaranteeing a smooth and uninterrupted CI/CD pipeline.

Moreover, the integration of data parallelism through the Task Parallel Library (TPL) in the .NET Framework further empowers developers to leverage the full computational capabilities of modern CPUs. This not only improves code performance but also optimizes resource utilization, making the most out of available resources.

Parallelism in Azure DevOps is more than just a feature; it’s a strategic tool that enables developers to break down complex operations into manageable tasks, leading to faster feedback loops, reduced bottlenecks, and a more responsive and adaptive CI/CD ecosystem. As development projects continue to grow in complexity and scale, embracing parallelism in Azure DevOps becomes not just an advantage but a necessity for modern software development teams aiming to stay competitive and efficient.