DORA vs SPACE Metrics: A Guide to the Science of DevOps & DevEx

You will start rolling your eyes when you know how an event was announced, which has changed how developer and operation teams work together. (And look at that logo. Soothing yet wild!)

The first DevOpsDays conference, organized in 2009 by a Belgium IT consultant named Patrick Debois, is believed to be the birthplace of DevOps we know today.

One of the most prominent discussions of the event was Culture Over Tools. He presented a thought that DevOps isn’t just about tools—it’s about fostering a culture of collaboration, learning, and shared responsibility.

However, leaders must have meaningful metrics that reflect both technical performance and team dynamics, and this ultimately scales the culture.

This thought later evolved into the DORA metrics.

The DORA Framework - introduced years later by Google’s DevOps Research and Assessment (DORA) team moulded the cultural and technical best practices into measurable success indicators. DORA successfully validates what early DevOps pioneers believed,

• Strong IT performance is a competitive advantage

• DevOps practices improve IT performance

• Organizational culture matters

• Job satisfaction is the No. 1 predictor of organizational performance

What Are DORA Metrics: The Basics, The Advanced (And The Science!)

When the DevOps movement grew after the first DevOpsDays conference in Ghent, Belgium, there was no standardized way to measure DevOps success.

But in 2014, Nicole Forsgren, Jez Humble, and Gene Kim—key figures in DevOps research —started studying DevOps performance and published the State of DevOps Report, which they have later continued publishing annually - even today.

After aggressive research on high-performing global teams, in 2018, the team introduced DORA Metrics to the World with the publication of their book, ‘Accelerate: The Science of Lean Software and DevOps’.

The four key metrics of DORA are… (! The Basics)

1. Deployment Frequency (DF): How often a team successfully releases code to production.

Example: If a team deploys 10 times in 5 days, the DF = 10/5 = 2 deployments per day.

High DF depicts agile, responsive, and competitive DevOps practices, whereas Low DF depicts slow, risk-prone, and less adaptive practices.

2. Lead Time for Changes (LTC): The time it takes from code commit to successful deployment in production.

Example:

A developer commits code at 10 AM → The code goes live at 2 PM → LTC = 4 hours (Fast)

Another team commits code on Monday → Deployment happens on Friday → LTC = 5 days (Slow)

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

Example:

10 deployments this week → 1 failed and required a rollback → CFR = 10% (Good)

10 deployments this week → 5 failed → CFR = 50% (Risky)

4. Mean Time to Resolve (MTTR): The average time taken to recover from a failure in production. This is also referred to as Time to Restore Service (TRS) sometimes.

A system outage happens at 3 PM, and the team fixes it by 3:30 PM → MTTR = 30 mins (Great!)

Another team takes 6 hours to fix a critical issue → MTTR = 6 hours (Needs improvement)

(! And now the Advanced)

While DORA metrics significantly help managers and leaders to check the pulse of their DevOps effectiveness, sticking solely to the 4 cores of DORA isn’t a good choice for high-velocity engineering teams. Because, many times, things get upside down when they hit the floor of reality!

DORA is not all about performance, it also reflects your culture.

Here is how.

High Deployment Frequency? – It prominently signals that your DevOps team is doing great when it comes to experimentation, continuous learning, and low fear of failure.

Low Change Failure Rate? - It suggests that you have a very strong test coverage and the team has a very good psychological safety, which empowers them to innovate without fear.

• The Unseen Trade-offs in DORA Optimization

Let’s assume that you all of sudden get overly impressed by DORA and instruct your team to pursue it all at cost. Let us warn you. The cost might get unmeasurably high. And here is how.

• Increasing Deployment Frequency may reduce stability unless you also increase the quality check.

• Optimizing for Change Failure Rate alone may reduce your teams’ innovation velocity as they could become over-cautious.

(! And now the Science)

Well, science talks about evidence. And we have a lot of evidence that DORA really matters.

In the 2018 edition of the State of DevOps report, the authors have divided teams into four Performance Profiles (Elite, High Performers, Medium Performers, and Low Performers) based on their software development & delivery practices. And their findings were truly eye-opening, solidifying the importance of DORA.

Compared to Low Performers, Elite Performers have…

• 46 times more frequent code deployments

• 2555 times faster lead time from commit to deploy

• 7 times lower change failure rate

• 2604 times faster time to recover from incidents

What Are the Major Limitations of DORA Metrics?

Yes. There are some real wrestling fights (and no pillow fights) when it comes to DORA metrics limitations. Here are a few.

1. Lack of Context: DORA prioritizes speed and stability but gives cold shoulders to other crucial factors like team workload, tech debt, and business priorities.

2. Surface-Level View of Productivity: DORA metrics measure the delivery efficiency but don’t capture developer experience, collaboration, and cognitive load.

3. Not a One-Size-Fits-All Model: DORA does not stay relevant to all industries. For example, a business operating in a highly regulated healthcare industry may not prioritize daily deployments, and this makes DORA benchmarks less relevant for them, at least.

4. Challenges in Accurate Data Collection: One thing DORA needs all the time is data. But siloed data due to multiple tools does not help leaders and managers to have accurate insights into DORA.

And here is where two things suddenly start making a lot of sense. The number one is SPACE metrics, and number two is Hivel.

Let’s start with number two!

What Are the Major Limitations of DORA Metrics?

Inconsistencies in CI/CD pipelines, deployment settings, and tool configurations make it difficult to collect DORA data reliably. Hivel makes this simpler by:

• Unified Data Integration: Provides consistent tracking by integrating with Jira, Git, and CI/CD systems.

• Custom Dashboards: Show important metrics instantly with advanced filtration options.

• AI-powered insights: Finds trends and makes recommendations for improvements.

• Consistency between teams is ensured by standardized metric definitions.

Oops, had a quick pit stop! Now, full speed ahead!

What Are SPACE Metrics? - The Art, The Artist (and The Stage!)

Consider SPACE Metrics as a framework to assess developers’ productivity in 5 major main areas.

1. Satisfaction and Well-being:  How happy and fulfilled developers feel at work.

‍Why does it matter? Developers do their best work when not overburdened. As per the report published by Sentry (a leading Application Monitoring Software), after surveying more than 1,000 full-time developers, a developer who is 10% happier requires 10% less time to complete common programming tasks.

2. Performance: The quality and effectiveness of the work delivered.

‍Why does it matter? There are plenty of correlations. Good code quality → fewer bugs, easy maintainability. Efficient problem-solving → Faster bug fixes, high system reliability. Well-structured architecture → Scalable and maintainable software. Thorough testing practices → Minimized production failures, smoother releases.

3. Activity: The quantity of work done, like code commits or pull requests.

Why does it matter? At the top-of-the-funnel level, it speeds up the time-to-market. And in a competitive market, it matters a lot.

The 2021 State of Continuous Delivery Report shows that 31.3% of developers release updates weekly or monthly, while 10.8% deploy multiple times a day. This approach is called RERO (Release Early, Release Often), which helps teams deliver value faster and respond quickly to user needs.

4. Communication and Collaboration: How effectively teams work together.

‍Why does it matter? Well, here we go. Straight from the legend. "Great software comes from great collaboration." — Linus Torvalds, Creator of Linux & Git

5. Efficiency and Flow: How smoothly developers work without interruptions.

‍Why does it matter? Nearly 70% of developers lose at least three hours per week due to delayed feedback and inefficient feedback loop in place. (source)

That was all about art. Now, let’s move to the artist.

The Origin:

Before SPACE, developers’ productivity was often measured by the lines of code written and the number of commits. This approach had nothing to do with the well-being of developers, collaboration, and quality of work.

The Launch:

Nicole Forsgren, Margaret-Anne Storey, and Team introduced SPACE metrics in 2021 with their research paper ‘The SPACE of Developer Productivity’. They belong to GitHub, Microsoft Research, and the University of Victoria.

The Adoption:

Considering its worthiness and impact, several giants have so far adopted SPACE for their software engineering teams. These companies include (but are not limited to) Microsoft, GitHub, Docker, Factorial, TrueLayer, Aiven, Miro, Postman, Peloton, Atlassian, and Spotify.

The Merger (with DORA):

With DevOps becoming a high-value, high-impact unit of companies, DORA is getting popular along with SPACE, and companies are leveraging both as their strategic drivers. Because this duo drives operational excellence along with team satisfaction and well-being.

And now, Curtains up! Hivel is where your SPACE metrics perform - The Stage!

How Hivel Empowers Companies with SPACE Metrics?

By centralizing data from multiple developer tools like Git (BitBucket, GitHub, GitLab), JIRA, and CI/CD tools, Hivel transforms SPACE metrics into actionable insights.

Through a single dashboard, you can track team-wise activity, potential burnout indicators, and key metrics such as cycle time, MTTR, and pull requests.

This holistic visibility helps engineering leaders optimize workflows, balance workloads, and improve developer satisfaction.

With AI-driven insights, Hivel identifies bottlenecks and recommends data-backed improvements for sustained engineering excellence. (Icing on the cake!)

Conclusion (DORA vs SPACE Metrics)

Fun Fact: Readers (yes, you!) often skim through the entire blog but never miss the conclusion! So, let us be honest with your time.

Also, read: What is Cycle Time Vs Lead Time - What is important for SDLC?