Optimize DORA Metrics with HyperTest for better delivery

If you haven't heard of DORA Metrics, you're already falling behind. But don’t worry, I’ll break it down, so you see exactly what you're missing out on.

Take Booking.com, for example. They were recently in the news for all the right reasons.

Their finance engineering team was struggling with delivery performance. They had top-tier engineers, great training programs, and all the resources they needed. Yet, results were slow.

The issue?

Too much time spent on training, onboarding, firefighting and too little on actual delivery.

So, they turned to DORA Metrics.

They started small- breaking their monolithic architecture into microservices and tracking key metrics like Deployment Frequency (DF) and Lead Time for Changes (LTC). But the transition wasn’t easy.

The team lacked confidence in refactoring and testing. Adopting DORA meant changing workflows, upgrading skills, and shifting mindsets.

But they pushed through.

The result? A twofold improvement in software delivery performance.

Some changes took heavy development effort. Others were simple process tweaks. But every step brought them closer to faster, more reliable releases.

And that’s exactly what DORA Metrics can do for you. Let’s discuss some background on DORA metrics before we actually tell you how HyperTest can help you achieve DORA metrics faster with more confidence.

What are DORA Metrics?

DORA metrics consist of four key performance indicators that measure the efficiency and reliability of software delivery:

1. Deployment Frequency (DF): How often code is successfully deployed to production.

2. Lead Time for Changes (LTC): The time it takes for a commit to reach production.

3. Change Failure Rate (CFR): The percentage of deployments that result in failures.

4. Mean Time to Recovery (MTTR): The average time it takes to restore service after a failure.

These metrics are crucial for organizations aiming to enhance their software delivery processes, as they provide a clear picture of performance and highlight areas that need attention.

Now that we’ve a basic understanding of DORA Metrics, let’s finally break it down on how you can use HyperTest in adopting DORA metrics faster and with more confidence.

Optimizing DORA Metrics with HyperTest

Before coming on the topic, let me give you a brief on HyperTest and that will establish the ground for us to continue diving deep on the topic.

✅ HyperTest

Developers spend a significant amount of time writing and maintaining unit (integration) tests for their services. These tests demand ongoing maintenance as the service evolves, impacting developer productivity and release speed.

HyperTest has developed a unique approach to automatically generating and updating mocks to efficiently test code and its dependencies. Integrated as an SDK on backend services, HyperTest constructs traces for all incoming requests and outbound calls, facilitating seamless regression testing during code changes.

DORA Metrics are the gold standard for measuring and improving software delivery performance. But achieving them isn’t always easy.

• teams struggle with slow deployments, long bug fixes, and unpredictable failures.

That’s where HyperTest comes in. By automating testing, reducing manual effort, and increasing confidence in every release, HyperTest makes it easier to improve all four DORA Metrics. Here’s how:

✅ Deployment Frequency (DF) – Ship Faster with Confidence

Many teams hesitate to deploy frequently because testing takes too long or third-party services aren’t always available. HyperTest solves these problems by enabling automated testing at every pull request, removing dependencies, and running only the tests that matter.

See the value of HyperTest for a faster RCA

• Test Every PR in CI/CD

HyperTest integrates seamlessly into CI/CD pipelines, automatically running tests on every pull request. No need to trigger tests manually.

With each PR tested automatically, engineers can merge with confidence, knowing regressions won’t slip through.

• Auto-Mocking for External Services

Many integration tests fail because they depend on unavailable third-party APIs. HyperTest eliminates this bottleneck by auto-mocking APIs and databases, allowing tests to run in isolation.

2. Lead Time for Changes (LTC) – Reduce Time from Code to Deployment

Slow debugging and inefficient test cycles increase lead time. HyperTest accelerates the process by providing instant failure insights, AI-powered test deduplication, and real-time code coverage.

• Faster Debugging with Distributed Tracing

Instead of digging through logs when a test fails, developers get a visual trace of what went wrong:

• Code Coverage Insights in Real-Time

Developers can see which parts of their code are untested and write focused tests instead of running an entire test suite.

This significantly reduces the time required to move a commit from development to production. Try HyperTest now

3. Change Failure Rate (CFR) – Reduce Deployment Failures

Frequent deployments mean nothing if they break production. HyperTest helps reduce failure rates by catching integration issues before they go live.

By mocking external services, teams can reduce their dependency on unreliable third-party APIs, ensuring that tests are more reliable.

• Contract Testing – Prevent Service Communication Failures

Microservices often fail due to unexpected API contract changes. HyperTest verifies if services are communicating correctly before deployment. This ensures backward compatibility and prevents failures in production.

4. Mean Time to Recovery (MTTR) – Fix Failures Faster

When failures do occur, HyperTest enables faster debugging and issue resolution, minimizing downtime. Its instant root cause analysis tracks failed requests, responses, and database queries, providing teams with the information they need to resolve issues quickly. Upstream failure alerts warn teams about potential breaking changes.

• Upstream & Downstream Impact Analysis

  If a service fails, HyperTest shows which other services are affected, making it easier to prioritize fixes.

HyperTest = Better DORA Metrics, Faster DevOps

In conclusion, HyperTest is a valuable tool for organizations looking to improve their DORA metrics and speed up their DevOps processes. By automating testing and providing real-time insights, HyperTest helps teams deploy code more frequently, shorten lead times, reduce change failure rates, and recover quickly from issues. As businesses recognize the importance of efficient software delivery, using HyperTest can lead to significant improvements in performance and reliability.

By adopting HyperTest, organizations not only improve their DORA metrics but also create a culture of ongoing improvement. This commitment to excellence in software development enables teams to ship high-quality software that meets the changing needs of their users.

In a way, HyperTest is a milestone towards better metrics and faster software delivery.

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