A Complete Guide to Azure DevOps Integration

Tools like Azure DevOps offer software development teams what they need to do their best work, but they rarely exist in isolation. Developers work on escalated requests from customer success agents sent from CRM tools. Team leads plan sprints based on information from project management tools, while stakeholders might want reports in spreadsheets or other tools. That’s why Azure DevOps integration is so important; it standardizes context across tools.

Here’s how.

What is Azure DevOps?

Azure DevOps is a cloud-based platform for software development, helping software teams manage everything from planning to project management and actual code development. Teams can use Azure DevOps to implement agile practices into their software projects and optimize the way they handle development work.

What is Azure DevOps integration?

An Azure DevOps integration connects Azure DevOps with other tools, bridging the gap so teams can work more efficiently without copying and pasting data back and forth. These integrations are especially suited to pushing development work to tools where team leads, managers, and leaders can get detailed reports and align that work to broader strategies.

Azure DevOps is often integrated with tools like:

• Project management platforms like Jira, Asana, and Smartsheet.
• CRM tools like HubSpot and Salesforce.
• Customer support apps like Freshservice and ServiceNow.
• Other software development platforms like GitHub and Bitbucket.

Why does Azure DevOps integration matter?

Having the right Azure DevOps integration comes with some significant benefits, each more than worth the initial investment:

• Increased productivity: Software developers often need to get extra context for their work and answer questions from other teams. If they can do that without leaving Azure DevOps, they’ll be a lot more productive in their day-to-day.
• Rigorous reporting: Team leads and managers need visibility into software development work, but Azure DevOps doesn’t have the same rigorous reporting as tools like Jira. Integrating the two means you get the best of both worlds.
• Smoother sprint planning: Spring planning sessions often involve centralizing requests and context from multiple platforms. Integrating these platforms with ADO means that information’s always on hand.
• Better code quality: The more context software developers have as they work, the better that work can be.
• Saving time and effort: Constantly copying and pasting data from other tools into Azure DevOps takes time and energy your teams could otherwise spend on mission-critical tasks. Integrations free both of these up.

4 types of Azure DevOps integration

Not every Azure DevOps integration is the same. Some are built with incredible depth for a few specific use cases, while others might automate a broad set of actions without syncing much data. Integrations also vary by deployment time, accessibility for less technical users, and more. Here are a few examples of integrations possible in Azure DevOps.

• Built-in Azure DevOps integrations: Azure DevOps offers a number of built-in integrations, often for specific features in other tools. That includes, for example, GitHub Advanced Security, which plugs GitHub features right into Azure DevOps.
• Automation platforms: Platforms like Zapier use straightforward, if-this-then-that logic to automate a broad range of actions across thousands of apps. These actions include creating new work items (e.g., Azure DevOps issues) and pushing small bits of data to update individual fields.
• Two-way sync: A solution like Unito creates two-way relationships between work items in Azure DevOps and other tools, automatically keeping everything up to date as your teams work. This creates true seamless collaboration between tools.
• Agentic AI: AI agents can automatically take many actions a human developer can, like manually creating Azure DevOps issues, writing bits of code, and updating information. Azure’s built-in agentic AI can integrate natively with other AI features like GitHub’s Copilot.

How to integrate Azure DevOps with Unito

Here’s a look at how an integration between Azure DevOps and other tools works with Unito.

Step-by-step integration guide

1. Connect tool accounts to Unito: After signing up for Unito, click +Create Flow and connect Azure DevOps and the tool you’re integrating it with to Unito.
2. Choose flow direction: Flow direction tells your Unito flow where you need new work items created. Most Unito flows are two-way, meaning they automatically create work items in both connected tools.
3. Set rules: Unito rules use trigger-action logic to filter out work items you don’t want or automate certain actions. To build a rule, set the trigger Unito should look for and the action you want it to take.
4. Map fields: In most flows, Unito can automatically map fields in Azure DevOps with fields in other tools. From there, you can customize field mappings to match statuses across tools, send data from some fields to fields specific to your workflow, and more.
5. Launch your flow: Once you map your fields, your flow is ready to launch. After an initial sync, Unito will check for changes in real-time.

Want to know more? Check out these video tutorials for syncing Azure DevOps with other popular tools:

• Syncing Azure DevOps with Airtable
• Connecting Azure DevOps to Wrike
• Integrating Azure DevOps with ServiceNow
• Syncing Smartsheet with Azure DevOps
• Connecting Azure DevOps to Asana
• Integrating Azure DevOps with ClickUp

Challenges to watch out for when integrating Azure DevOps

Every Azure DevOps integration method comes with its challenges. Here are a few to watch out for.

Data Mapping and transformation

Integrations naturally need to take data from one tool, map it to similar data in another tool, and transform it in transit. Most integrations do this by using each tool’s built-in API (Application Programming Interface), which essentially provides a roadmap for doing this, allowing developers to build their own integrations in many cases. But the more different tools are (or the more data you need to sync) the more complex this mapping and transformation becomes. That’s why some integrations only support a few fields while others offer more depth.

Real-time integration and event-handling

Not all integration solutions can sync data in real-time, and not all can handle the events (e.g., work item creation, updates in specific fields) your teams need to sync. Some integrations only push data between tools in batches, which can support workflows that only need scheduled updates from certain tools (e.g., reporting on sprint work). Others might support some event types but not others.

Authentication and security

Integration solutions can naturally create security vulnerabilities since they’re transferring data back and forth between otherwise closed systems. They need access to these systems, too, which is often done through authentication standards like OAuth. Most integration solutions have advanced, industry-standard security protocols, but these need to be reviewed for each platform you consider.

Performance and scalability

An integration platform has to perform reliably across workflows so you don’t miss crucial data, and it has to scale with you as you grow. Automation platforms generally perform reliably, but rarely follow the scale of your workflows without adding unnecessary complexity — and the accompanying maintenance.

How to keep Azure DevOps integrations secure

Because integration solutions can inherently create a security vulnerability as they transfer data between systems, keeping them secure is vital. Here’s what that involves.

Compliance

Like other software tools you use, integration platforms have to comply with data privacy and security regulations in your jurisdiction. Organizations based in, or with customers in California have to comply with the California Consumer Privacy Act (CCPA), as do the integration solutions they rely on. This is a relatively common requirement, and most integrations abide by it. Some regulations however, like HIPAA in healthcare, are less common.

Access control

Because integration platforms can connect a wide range of tools to Azure DevOps, it’s all too easy for someone to accidentally send confidential data (like code) out to a system that’s either less secure or shouldn’t have any of that data on it. That’s why organizations often control who can and can’t access integration platforms, ensuring alignment on which systems should be integrated with Azure DevOps.

Security certifications

Security certifications like SOC 2 Type 2 provide guidelines for organizations that want to make data security a priority, covering elements like unauthorized access protection, confidentiality, data privacy, and audit evidence. Integration providers, like any other software provider, can pursue these certifications. That means you can look for them when looking for an integration solution.

Best practices when integrating Azure DevOps

When rolling out your first Azure DevOps integration, consider these best practices:

1. Start with a small pilot project between one Azure DevOps project and a block of work in another tool. This allows you to get a feel for an integration solution before it has access to all your organization’s data.
2. Evaluate the results of a pilot project before implementation integrations at scale.
3. Consider if you need an integration solution that requires technical knowledge to use or if you need something that’s more accessible for all your teams.
4. Review the integration vendor you’ve chosen at least yearly to ensure they’re competitive compared to the broader market.
5. Use built-in Azure DevOps where possible to enhance any third-party integration solution you use.

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