Over my decade working in test automation across startups and enterprises, I’ve delivered quality and velocity improvements through intelligent tooling and process rigor. Now as an independent consultant, I advise clients on unlocking automation‘s true potential. This handbook distills battle-tested tips for one crucial arena – automated testing with Azure DevOps.
Having spoken at conferences like STARWest on CI/CD automation best practices, I’ll use my experience to guide you through the full life cycle – whether you’re automating tests for the first time or strengthening existing pipelines. We’ll move beyond theory to practical examples you can instantly apply.
If terms feel unfamiliar early on, don‘t fret! I remember first learning this and feeling overwhelmed. We‘ll build intuition before diving into the implementation. You’ll finish this guide with clarity and confidence to deliver test automation that transforms team outcomes. Buckle up for an illuminating tour!
Why Automated Testing and What Is Azure DevOps?
Before jumping into specifics, let‘s align on context with an overview of key drivers and capabilities.
The Imperative for Automated Testing
Manual testing without scripts is no longer sustainable in our rapid release world. Let’s reflect on a few compelling motivators for test automation:
- 66% lower costs over manual testing: Cigniti’s 2020 study analyzed savings from 200+ automations
- 80% faster test execution as per Capgemini’s global quality survey across sectors
- 60% shorter release cycles via test integration in CI/CD per IBM report
Adding my own experience, clients consistently see 4-5X productivity gains from well-architected automation. It frees up bandwidth for innovation and transforms release rhythms.
Clearly, exponential benefits await those who invest in test automation. But transforming manually executed test cases into automated scripts is just the first step. We need a robust platform to run these scripts – which brings us to Azure DevOps.
Overview of Azure DevOps Capabilities
Azure DevOps is Microsoft’s integrated set of services for software teams to manage work across the DevOps lifecycle.
Key capabilities include:
- Version control for source code and test artifacts using Git repositories or Team Foundation Version Control
- Boards to track work items like user stories, bugs, test cases etc.
- Pipelines with reusable workflows to build, test and deploy applications
- Tests to create and execute test plans and monitor test runs
The pipelines functionality provides the test automation orchestra – the ability to set up CI/CD style triggers to run our test suites every time code changes. We‘ll focus specifically on leveraging this to operationalize test execution.
Now that we‘ve framed the what and why, let me share some best practices I‘ve uncovered for the how from hundreds of successful automation initiatives.
Prerequisites to Set the Right Foundations
Too often teams rush into automation without laying the groundwork which leads to maintenance headaches or flaky tests. Let‘s first ensure we have the solid pillars in place:
Cloud Infrastructure
Since Azure DevOps and your test automation will run on cloud servers, having the right Azure subscription model affects cost, scalability and tool access.
Trial subscriptions allow limited durations and infrastructure. Production workloads require paid subscriptions with appropriate SLA, regions, resource quotas and support levels.
I guide teams through choosing suitable Azure environments depending on scale, availability needs and organization policies. Certain enhanced automation features may need higher configurations.
Test Automation Strategy
Instead of blind automation, analyze priority test scenarios, available skills and long term toolchain evolution. Know what, why and how much to automate based on ROI.
I‘ve developed a proven test automation strategy planning framework covering dimensions like:
- Application lifecycle stage: New development vs mature production
- Test types: Unit, integration, system, visual, performance etc.
- Execution environments: Dev workstations, on-prem, cloud
- Trigger mechanisms: Push vs pull strategies
With strategic clarity, we can craft smart automation roadmaps.
Tool Chain Familiarity
Get hands-on with your test framework like Selenium or Appium since Azure DevOps merely manages execution. Install drivers, set up sample test projects, review documentation – don‘t go fully theoretical!
For coding, know at least one DevOps-friendly language like Java or C#. I help teams assess skill gaps and conduct deep-dive hands-on workshops to uplift competency.
With core building blocks firmly in place through cloud, strategy and skills – let’s start constructing our automated execution pipeline.
Step-by-Step Guide to Configuring Test Automation
I’ll walk you through the 10 step process now to set up Azure DevOps for automated testing:
Step 1: Provision Azure DevOps Organization and Project
Log into the Azure portal to create a new Azure DevOps organization which is a container for multiple teams and projects. Give it a unique name and URL.
Under this, set up your first Azure DevOps project to represent your application or product. For example “Pet Clinic Application Test Automation”. Configure permissions like public or private based on policies.
Step 2: Install Azure DevOps Project Plugin in IDE
Your developers likely use an Integrated Development Environment (IDE) like Visual Studio. Install the Azure DevOps plugin here to allow interacting with Azure DevOps git repos, work items, builds etc. directly from the IDE.
Streamline developer workflows with IDE integration.
Step 3: Set Up Build Pipeline for CI/CD
Within the Azure DevOps project, navigate to Pipelines –> Builds to define a build pipeline which will orchestrate our automated test runs. Think of this as the central nervous system.
In the build pipeline, we’ll add tasks for source code fetching, test execution, publishing test reports and quality gates. Configure triggers for continual runs.
Tip: Follow build pipeline development best practices for optimizing performance. Segment across stages, utilize dependencies, leverage caching etc.
Step 4: Configure Project’s Source Code Repository
To access the test code, link your GIT repository which contains the test assets under Project Settings –> Repositories.
Options like Azure Repos, GitHub, Bitbucket or generic GIT servers are available. Set up service connections for credential management.
Use repository branching models like Gitflow to clearly demarcate test code from production code. Mirror staging environments for accurate results.
Step 5: Add Test Runner Tasks for Unit and UI Testing
Within the build pipeline, search the Tasks catalog to find relevant test runner tasks. For example:
- VSTest task to execute unit test cases written using MSTest, xUnit or NUnit
- Publish Test Results task to publish VSTest XML output files for reporting
- For UI testing, add Selenium test runner utilizing underlying test frameworks like NUnit, MSTest etc.
Parameterize the test runner with inputs like test assemblies to execute, test settings files and output directories.
Step 6: Insert Tasks to Set Up Test Environments
The test runners will need appropriate environments. Insert setup tasks accordingly:
- For web application UI testing, add tasks to deploy the application on pre-production testing environments along with test data population.
- For API testing, mock stub servers that mimic application dependencies and provide sample responses
- For mobile testing, leverage cloud providers like AWS DeviceFarm, Firebase Test Lab or third parties like BrowserStack
I guide clients in optimally anchoring test environments from on-prem data centers or hybrid cloud infrastructure.
Step 7: View Detailed Test Outcomes
After complete pipeline execution, click any run and navigate to the Tests tab to analyze test outcomes at granular levels.
- View test failures: Expand stack trace, inspect screenshots, analyze memory dumps, attach logs
- See chronological execution with metadata like duration, browser environment, test class name and more.
- Link failing tests to defect work items to streamline development hand-offs through Azure Boards integration
Leverage drill-down capabilities to unlock deep insights.
Step 8: Configure Notifications for Test Failures
Nothing erodes confidence in automation more than ignoring failures!
Set up proactive alert mechanisms through email, teams channels or even SMS bots by subscribing stakeholders to pipeline notifications under Settings–>Notifications
Promote accountability by involving upstream teams in remediating test debt through templatized comments.
Step 9: Create Custom Reports Using OData Queries
While default reporting meets basic needs, tailored analytics unlocks novelty.
Leverage OData queries to build custom reports spanning test runs like:
- Test status breakdown across browser types
- Historical trend of failure rate
- Top flaky tests needing refactor
I can guide you in shaping relevance from noise.
Step 10: Maintain Tests by Institutionalizing Best Practices
The most strategic step is sustaining test health via:
- Regular analysis to remove obsolete validations or platform dependencies
- Fixing root causes using my test design techniques to minimize false failures
- Enforcing comments for new tests or changes to ease maintenance
- Assessing coverage for right breadth across unit, integration, system testing types
By institutionalizing test hygiene habits, teams prevent entropy ensuring sustained ROI.
Additional Integrations for Enhanced Testing
While Azure DevOps provides rich capabilities, we can augment scope by:
Incorporating Third Party Test Frameworks: Bolt on testing needs beyond base providers. For example, adding Postman for API testing, Protractor for Angular or Gauge for business-readable tests.
Leveraging Real Device Cloud Providers: Expand test coverage across thousands of real mobile devices configurations in the cloud through integrations with SauceLabs, BrowserStack etc.
Building Custom Testing Toolchains: For niche needs, develop custom tasks using .NET SDK and C# code. Tap into full extensibility and personalization potential.
Determine peripheral gaps limiting test comprehensiveness. We can bridge them together!
10 Commandments to Scale Test Automation on Azure DevOps
Let’s conclude with cardinal rules accumulated from countless automation initiatives:
1. Institute Separate Pipelines for Functional vs Non-Functional Testing
Align test characteristics to pipeline runtime constraints for maximized efficiency.
2. Follow a Push-Based Execution Model by Default
Embed directly in developer commit workflows for rapid feedback loops.
3. Build Layered Reporting Dashboards
Deliver actionable visibility rather than just data.
4. Design Idempotent, Atomic Test Cases
Isolate test layers through loosely coupled logic and data.
5. Implement Risk-Based Test Prioritization
Allocate automation budgets more smartly by assessing test criticality.
6. Foster Joint Ownership Between Dev and QA
Reduce throw-over-the-wall anti-patterns through collaborative design.
7. Monitor Test Debt Through Rigorous Metrics
Quantify the erosion in automation ROI to prevent runaway costs.
8. Audit Tests Annually for Right-Sizing
Stay lean and relevant.
9. Treat Automation as a Software Engineering Discipline
Institutionalize the same rigor like coding standards, peer reviews etc.
10. Focus on Developer Experience and Productivity
Make it frictionless for adoption across the team.
These battle-tested commandments separate the best-in-class from the average.
Commit them wholeheartedly to propel your test automation into a formidable competitive advantage! Together we can deliver.
