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Every organization wants to be successful, but who decides which are successful or not? For Google, there’s a clear definition of how to measure the success of a DevOps team. At CloudNative London last year, Google Cloud Platform Advocate, and co-author of “Continuous Delivery,” Jez Humble explained Google’s four key metrics — commonly referred to as the DevOps Research and Assessment or DORA metrics — and how to become one of these few, proud elite teams.
Let’s start by clarifying how Google defines DevOps, namely as “an organizational and cultural movement that aims to increase software delivery velocity, improve service reliability, and build shared ownership among software stakeholders.” This definition further goes into how DevOps teams should work to “improve the speed, stability, availability, and security of your software delivery capability.”
Humble says a lot of teams think they can just install Kubernetes and start deploying apps, but few organizations have the technical and managerial capabilities that drive real success. So what those few top performers are doing right?
For Google, it comes down to three teams — software development, software deployment, and service operations — who care about four metrics plus one that can’t be measured directly, availability, but nonetheless can’t be compromised during this process. The four key DevOps DORA metrics are:
Successful DevOps teams understand the shared ownership of these objectives.
Humble further defines DevOps high performers as those that do better at throughput, stability and availability. These elite performers:
These elite performers reach corporate goals because they do well at the following metrics:
All of these pour into the belief that software delivery and operations (SDO) performance predicts the whole organizational performance. Humble also says there is a further correlation between your SDO’s performance and your cultural performance. “They predict culture. The extent to where your culture is mission-oriented, not pathological, controlling-oriented,” Humble said.
All these elite performers share in fostering a climate for learning, highly participatory retrospectives, and the encouragement of trust, voice, and autonomy.
But it’s also not just about the people. Tech is just as important as culture in DevOps.
The Google State of DevOps 2019 report found that 80% of its respondents were primarily hosting on some sort of cloud platform. Humble explained that Google applied the National Institute of Science and Technology’s definition of cloud computing to the SDO performance. This outlines the five essential characteristics of cloud computing:
Only 29% of respondents for Google’s survey met all five requirements. Unsurprisingly these lined up with DevOps performance. In fact elite performers were 24 times more likely to have met all these essential cloud characteristics than the low performers.
Last year’s report realized, along with this year’s, validated that it didn’t matter of they were working on a public, private or hybrid cloud, a team focusing on cloud-based execution should see success in terms of speed, stability, and availability.
Humble said enterprises are typically running hundreds of thousands of services, made up of heterogeneous tech, but there are many other companies where more than 70% of the IT budget is “keeping lights on and adding capacity.” Then when they have to support CI/CD, they need to buy unsupported hardware on eBay or they are “running something mission-critical that no one has the code to anymore.”
Elite teams have a clear understanding of who does what and automates as much as possible.
Humble said that that the hardest bit to measure of the four key DevOps metrics is lead time. This looks to answer questions like: How long would it take your organization to deploy a change that involves just one single line of code? Can you do this on a repeatable, reliable basis?
He went onto highlight different areas that dramatically affect lead time and the strongest software development and operations teams all seem to have answers to:
And probably most importantly, when there’s a vulnerability in your stack, how long will it take you to patch, build and redeploy all of your impacted applications? Humble referenced the need for this rapid patching up against what happened when Equifax had a headline-grabbing breach from a flaw in the Apache Struts framework.
During his keynote, Humble outlined the architectural outcomes that allow teams the flexibility needed for high-performing DevOps without security risks. It’s not surprising that Conway’s Law rears its head here.
Ask yourselves these questions:
Humble suggests the need for a Platform as a Service. He says a self-service, multi-tenant PaaS minimizes the attack service area.
For Humble, the key principles of PaaS is a separation of responsibilities, which are:
He calls this a “Function-as-a-Service model,” where ideally app stacks are part of the platform too so you can patch them easily. This all helps maintain compliance.
As you transition to a PaaS, Humble suggests you start by thinking about the outcomes and think about the contracts there are for the entire software development lifecycle. A PaaS will help you achieve short lead times and short times to restore.
He suggests a JAMstack — JavaScript, APIs and Markup — for your website and apps. Then anything involving business logic or state changes happens through functions that your API talks to. All on top of your PaaS.
Humble listed the advantages of a PaaS include:
Finally, Humble talked about how teams achieve outcomes not individuals, which is why team and organizational culture are what make or break these elite DevOps performers.
So, what’s the secret to building high-performing teams and enabling them to delivery with speed and stability? Psychological safety.
Organizations that foster psychological safety — where team members feel safe to take risks and be vulnerable around each other — have a greater capacity for dependability, structure, clarity, meaning and impact on the organization.
All of the above combines to strongly affect both culture and SDO performance which help org performance. And it also helps reduce burnout, deployment pain and, rework.
Author’s Note, November 22, 2023: For years, I have been driving part of the focus on defining DORA metrics as solely those famous four – or sometimes five if you include reliability – measurements. Yes, deployment frequency, lead time for changes, change failure rate, and failed delivery recovery time (previously called mean time to recovery, or MTTR) are important, especially when benchmarking yourself against your own team’s or company’s previous measurements, but they aren’t nearly the whole perspective of the sociotechnical power of DORA. In a more recent conversation with some of the creators of the recent State of DevOps Report 2023 report, I highlight several of the other 45 or so DORA questions, in my piece Google Says You Might Be Doing DORA Metrics Wrong.