How to Achieve ALM and Jira Integration
It’s rare to find an organization where technology workers all operate happily within the same tool. Agreeing on a preferred tool is challenging within a single development team, let alone an entire organization.
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Often, development teams and product managers insist on working with Atlassian Jira, a customizable work-tracking tool known for its flexibility and single-tasker-plugin-ecosystem. On the other hand, quality assurance engineers and testers prefer to build and run tests in Micro Focus ALM (formerly HP ALM), which specializes in test design and execution.
To avoid tedious copy-pasting, manual errors, slow handovers, and gaps in traceability, businesses need to integrate work tracking with test management (ALM and Jira). Real-time integration ensures everyone has up-to-date information in their tool of choice, which improves collaboration and speeds up defect resolution.
In this article, you’ll learn everything you need to know about ALM and Jira integration, including:
- the most popular use cases,
- the benefits and challenges,
- different methods and best practices for integration, and
- tools to help you with your ALM Jira integration.
Use Cases for Micro Focus ALM JIRA Integration
The most common purpose for an ALM Jira integration is defect synchronization. When a Testing Engineer logs a defect in Micro Focus ALM, Planview Hub works behind the scenes to create a corresponding Jira issue which will appear in developers’ backlog. Then, when developers start working on it, any status changes, comments, or field changes they make in Jira will be mirrored back to ALM. Developers know about defects ASAP, and testers know when code is ready to be tested again.
The second most popular use case involves “flowing” stories from Jira to ALM. This integration helps testers plan for the right test coverage and creates traceability between a story and the test cases designed for it.
Other use cases include flowing data from ALM into Jira for reporting purposes, and synchronizing artifacts with a partner or supplier’s tool to collaborate.
Benefits of a Jira and ALM Integration
Integrating Jira and Micro Focus ALM boosts efficiency, improves collaboration, and raises the quality of your final product. Some specific benefits include:
- Faster resolution. When compared to manual copy/paste, real-time automated communication streamlines handovers and speeds up the process of defect resolution.
- Reduced time waste. Integration eliminates the need for manual copy-pasting, status meetings, and email updates.
- Improved focus and morale. Minimizing context-switching and interruptions means developers have more time and energy for high-value work.
- Simpler traceability. Robust traceability is crucial for product delivery organizations, especially those in regulated industries that undergo rigorous audits. The right integration solution will alleviate the stress of audits by automating traceability.
- Unified visibility: Integration allows you to consolidate data from both Jira and ALM into a single reporting platform. This enables you to create comprehensive reports that include data from both systems, providing a holistic view of your progress.
Challenges of a Jira Integration With ALM
Technical leaders often underestimate the complexity of software integrations. Jira and Micro Focus ALM have different data models, workflows, terminologies, and artifact relationships. Before you integrate them, understand the challenges to overcome:
- Data transformation and normalization: ALM and Jira use different syntax, so you need to transform data between the two systems. For example, mapping custom fields or fields with different values between ALM and Jira can be tricky.
- Conflict resolution: This challenge refers to conflicts between applications, not between workers. When twinned artifacts are modified simultaneously in two tools, some integrations will struggle to reconcile the discrepancy. Should the integration favor entries in ALM or in Jira?
- Multiple Micro Focus ALM tools: Micro Focus ALM is a set of tools that includes Micro Focus ALM/Quality Center (ALM QC) and Micro Focus ALM. Many organizations find it beneficial to use a combination of the two, favoring ALM QC for detailed test planning and design and ALM for test execution and tracking. To minimize manual data entry, it’s essential to integrate both ALM tools with Jira and with each other. This would significantly increase the work you have to do unless you’re using a model-based integration solution.
- Traceability: It is difficult, but worth it, to find a solution that automates traceability from requirements to development in Jira, to testing in ALM, to release.
Priorities When Integrating Micro Focus ALM and Jira
Before building or buying an integration solution, consider the nature of your integration needs. Writing down your priorities and referring to them throughout your decision-making process will help you stay focused on what matters.
Here are six criteria to consider when deciding how to integrate Jira and ALM:
- Scalability: How easy is it to expand integrations to more projects and more tools? What is the marginal increase in maintenance work each time you add an integration?
- Costs: In addition to the upfront cost, consider the opportunity costs and future maintenance costs.
- Quality: Some things to look for are real-time synchronizations and conflict resolution mechanisms.
- Flexibility and ease of use: Workflows change, so it pays to have an easily configurable integration that can accommodate a wide variety of use cases, including integrations with partner organizations.
- Traceability: You can save thousands of hours with automated traceability from requirement to code to test to release. Some methods have built-in traceability features that insert URLs to link twinned artifacts back to their source in another tool.
- Visibility and Reporting: To manage capacity and plan future work, product managers need comprehensive metrics and reports that combine data from both Jira and ALM.
The weight you give to different criteria will depend on the size of your organization, your use cases, and whether you eventually plan to integrate your whole value stream.
Pros and Cons of Different Integration Methods
There are four ways to create a Micro Focus ALM to Jira integration. Ranked least to most scalable, they are:
DIY integrations using REST APIs
An API, or application programming interface, is a set of rules that allows different software applications to communicate with each other. Most software development tools, including Micro Focus ALM and Jira, have public APIs, which developers use to build connectors between the two tools. These connectors dictate which fields synchronize, how often the integration runs, and how data transforms as it moves to a new system.
Note: The fact that the APIs are handed to you doesn’t mean building an integration is easy. If you were building a bridge, the APIs would be the foundations on either side of the lake. The hard task of building a bridge to connect them remains to be done by you.
Plugins are bits of software, typically single-tasking, that expand the functionality of your existing applications. They fulfill very specific needs. For example, the “ALM Test Management for Jira” plugin, which is available through Micro Focus ALM’s marketplace, provides workers in Jira with visibility into what tests are happening in ALM. If you wanted to synchronize artifacts and have visibility test statuses, you’d need multiple plugins.
Point-to-point integration tools
Point-to-point tools provide a simple and brittle approach to help manage your integrations. The underlying architecture is similar to DIY integrations, but the point-to-point tool includes the connection for you. Point-to-point integrations require you to map fields for every participating project in bidirectional integration.
Model-based integration solutions
Model-based integration solutions are the most technologically advanced type of integration software. The difference between point-to-point and model-based integration solutions relates to the underlying architecture, so it’s not always obvious in demo videos. Model-based solutions use a common data model to normalize data from each connected tool, which enables higher fidelity synchronization and reporting.
Put simply, these solutions use a model – a sort of schema – to understand each artifact type (defects, stories, test cases etc.). You can apply these models to any project in a supported tool to extract and normalize data. Then, you can flow this data between any number of tools, without mapping fields for every time.
Let’s look at how these methods perform with regards to each of our criteria.
Cost is usually the first consideration when making any change. At first, most leaders are attracted to the low upfront cost of DIY integrations. However, the opportunity costs of building often outweigh the cost of an off-the-shelf solution. It could take months to build an ALM Jira integration, even for an experienced developer. Instead, that time could have been spent reaping the benefits of software integration and adding value to their own products.
Plugins have a low upfront cost, and they are relatively quick to set up. But this method also brings costs in the long term. If you ever want to change or expand your use case, you’ll be writing custom code for weeks. As your organization outgrows the limited use cases offered by plugins, you’ll most likely have to find an alternative solution.
Point-to-point integrations are medium-to-high in price, but they integrate many tools, not just Jira and ALM. However, buyers should be aware of hidden set-up and maintenance costs, which increase exponentially as you add more projects. With a solution built on point-to-point integrations, it would take over 300 hours to integrate 25 projects between ALM, ALM QC, and Jira.
Model-based integration may have a slightly higher upfront cost, but it delivers a high ROI when used to its full potential.
A good quality integration synchronizes basic fields, like test ID, priority, and severity, as well as more complex information like custom fields, attachments, traceability URLs, and folder structures.
Without the right infrastructure, exchanging so much data in real-time will slow down your applications. This is a common problem when using DIY integrations and plugins. Out-of-the-box solutions, both point-to-point and model-based, are purpose-built by experts, so they will not slow your applications and will cost less in the long run. The best quality integrations come from model-based tools, which operate with a light touch and won’t strain your applications.
Growing organizations need an integration solution that can evolve and expand with them. After setting up a Jira to ALM integration, you’ll likely want to connect the rest of your value stream, including requirements management tools, release tools, and other best-of-breed applications. You might also want to collaborate with partners, who may use different tools or versions.
With homegrown integrations, adding new tools could take months. With a plugin, you can scale the number of projects quickly, but you would need a different plugin to incorporate more tools.
Point-to-point integrations may offer connectors for several tools, making it easy to expand your integration. However, maintenance costs increase exponentially. Here is a breakdown of the approximate time needed to maintain integrations as you expand your use:
|Point-to-Point Maintenance Time
|150 hours annually
|600+ hours annually
|2000+ hours annually
|2 artifacts types
|3 artifacts types
|4 artifacts types
Model-based integrations scale easily. You configure each artifact mapping once per tool, and then you can apply it to as many projects as you need. On average, set-up is 75% faster, and maintenance 90% lower compared to point-to-point integration solutions.
Flexibility and Ease of Use
To benefit from a Jira ALM integration in the long run, you need the ability to easily make changes to integration patterns. Your organization will flex and change; a good integration solution can flex and change alongside it.
Homegrown integrations are by far the most difficult to use and modify. The developers who first built the code would be able to make changes, but not easily.
Plugins are easy to set up and use. The downside of their simplicity is a lack of configurability. To add a new integration pattern, you’d have to write code or find a different plugin.
Point-to-point integrations are relatively easy to set up, but they also lack flexibility, because changing field mapping for 15+ projects takes an inordinate amount of time.
Model-based solutions connect each tool to a central hub, rather than building a complicated web between endpoints. This makes it faster and easier to change an integration or add a new one without disrupting the rest of your value stream.
ALM and Jira both have built-in traceability mechanisms, but these mechanisms aren’t designed to trace work that’s being done outside of their own domain. If you want to eliminate manual data transfer and errors, find an integration solution that automates traceability.
Automating cross-tool traceability is challenging, so DIY integrations usually skip this step. It may not affect how day-to-day work is done, but messy traceability is a recipe for painful audits later. Some plugin integrations and out-of-the-box solutions have traceability features, but the strength of these features varies.
Visibility and Reporting
Managers need visibility into the quality process being managed in ALM. An ALM Jira integration, which flows real-time test results into managers’ dashboards, will do the trick.
Any integration method can theoretically accommodate this use case, but speed and accuracy are not guaranteed. DIY integrations, plugins, and point-to-point solutions synchronize less frequently, so you’re more likely to have discrepancies. Model-based integration solutions’ unique architecture can support near real-time synchronization, providing the most up-to-date, accurate information.
If you want speedy, accurate reporting, look for a solution that can normalize and aggregate data from ALM and Jira into one database.
Although model-based integration is more expensive initially, the return on investment is worth it. Models enable fast and accurate flow, even for the most complex integrations. They make it easy to adapt to new workflows and use cases, and they are the only scalable way to connect your value stream.
Tools for an ALM to Jira Integration
The leading model-based integration solution is Planview Hub. Planview Hub has pre-built connectors for Jira, the entire Micro Focus suite, and over 60 other best-of-breed tools. Its sophisticated UI allows you to connect your applications quickly and easily – no code required. In fact, a single administrator operationalizes a Jira integration with ALM within hours of installing Planview Hub.
Planview Hub is the trusted value stream integration solution for over half of the Fortune 100 companies. The BMW Group is one example of an organization that used Planview Hub to transform into an Agile working environment and enable them to complete a key project one year ahead of plan, despite challenges from the Covid-19 pandemic.
With the Micro Focus ALM Jira integration from Planview Hub, you can:
- Streamline communication and speed up defect resolution
- Eliminate overhead associated with manual traceability and compliance
- Get workers the information they need, when they need it, in the tools they love
- Access support 24/7