💃 A guide to understanding DORA 🕺

Good morning, Salesforce Nerds! Are you able to show your leadership team metrics that prove the effectiveness of your development team? 🤔 

Most teams I know aren’t able to do this. 👆️ 

In fact, a lot don’t even know where to start or what data they could use to accomplish this. 🫢 

Fret not! 😟 

Today, we’re going to dig into some industry standard metrics that you can use to measure your teams engineering performance! 🔥 

Agenda for today includes

• A guide to understanding DORA

• Daily Principle

• All the Memes

A guide to understanding DORA

Today we will discuss -

💃 What is DORA? 🕺

💃 Unpacking each metric 🕺

💃 Why does this matter? 🕺

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🤔 What is DORA?

DORA= DevOps Research and Assessment 🧠 

It’s a research program dedicated to understanding what activities are responsible for driving software delivery/operations performance. 📈 

Throughout the software engineering community, it boils down to four (4) key metrics to measure your team against:

⏩️ Deployment Frequency - How often an team successfully releases to production

⏩️ Lead Time for Changes - The amount of time it takes a commit to reach production

🏗️ Change Failure Rate - The percentage of deployments causing failures in production

🏗️ Mean Time to Restore - How long it takes and team to recover from a failure in production

If we zoom out 🔭 a bit, you’ll see that the first two metrics measure velocity ⏩️ and the last two measure stability 🏗️.

These metrics give us a data-driven way to improve a teams efficiency, effectiveness, and transparency! 💥 

Let’s break them down a bit more … 👇️ 

📦️ Unpacking each metric

⏩️ Deployment Frequency

# of deployments / # of days = Deployment Frequency

We can calculate this by dividing the total # of deployments made in a given time period by the total # of days in that period. ➗ 

So, if you team deployed 10 times in a month with 31 days, the deployment frequency would be 10/31 = 0.32 deployments per day! 🚀 

⏩️ Lead Time for Changes

Time request is deployed - Time of first commit = Lead Time for Changes

This metric (aka change lead time) is determined from the time code is first committed towards a request to the moment it's deployed to production. ⏳️ 

This not to be confused with Lead Time or Cycle Time! 😕 

Here’s a handy image to help:

🏗️ Change Failure Rate

# of deployments resulting in failure / # of deployments = Change Failure Rate

This is found by dividing the # of code changes that require a hotfix or other remediation by the total # of deployments. ✍️ 

Keep in mind this does not measure failures caught by testing and fixed before code is deployed. 🧪 

This gives leaders insight into the quality of code being shipped and by extension, the amount of time the team spends fixing failures. 🪲 

🏗️ Mean Time to Restore 

Total time spent on repairs / # of repairs = Mean Time To Restore

This measures the ‌time it takes to restore a system to its usual functionality. ⏲️ 

Failures happen, but the ability to quickly recover from these in a production environment is key to the success of DevOps teams. 🗝️ 

This metric can be expanded on like this: 👇️ 

🤷 Why does this matter?

Of course, engineering leaders want to see KPI’s to they can see how their teams are performing. 📈

These metrics give them a quick, high-level view of just that. 💥 

From a developers perspective, these metrics can really help you view and understand your team through the same lenses that your manager, director, CTO, uses! 👓️ 

It’s all about continuous improvement! 💪 

These are just a few of the benefits of implement DORA:

✅ Informed & empowered decision making

✅ Proof of delivering value

✅ Spur organic improvements

Start researching more today and see if you can identify areas of improvement on your team! 📑 

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