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There are many misconceptions about CD. There are also many things about CD that are not obvious on the surface. If you are “CD curious”, perhaps this will help.

“CI/CD or CD?”

It’s just “CD”. Just as DevOps encompasses security, business, compliance, user experience, etc., CD encompasses the entire development process.


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Hope creep is the plague of value delivery. We assume that since something worked in the past it will work again. We forget how much pain we’ve had in the past. “How hard can it be to build that? Looks pretty simple to me!” This is a big-bang, waterfall delivery mindset. We need a mindset that embraces reality. We need to internalize that everything is probably wrong and broken so we can prioritize our actions correctly.

There are many technical and process practices required for executing continuous delivery. It’s not easy, some are counterintuitive, and it requires a high degree…


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I was talking to a friend the other day about how her management is tracking teams’ “maturity” using “DORA Metrics”, the four measures the correlate with high-performing organizations mentioned by DevOps Research and Assessment in “Accelerate” and the State of DevOps reports.

  • Pipeline cycle time (Hard lead time in the book): The time between when a change is committed to version control and when the change delivers to production.
  • Delivery frequency: How frequently changes are made to production.
  • Change fail %: The percentage of changes that require remediation.
  • Mean time to repair (MTTR): The average time required to restore service.


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Should we use Scrum? Kanban? Is Kanban for support and Scrum for development? Is Scrum for newbs and Kanban for elites? Are we mature enough for Kanban?

These questions are a symptom of the Agile Industrial Complex selling certifications and people following the rules to get certified. Scrum or Kanban? The reality is that Scrum is not training wheels and Kanban is not for elites. Scrum is not for product development and Kanban is not for support work. Both are standardized approaches that emphasize small batches of work, feedback loops, limiting WIP, and frequent delivery. …


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In my last post, we talked about common metric anti-patterns that are focused on the process instead of value. In this installment, we will cover alternatives that can help us remove waste and improve the flow of value.

Defining Terms

Goal: Something we want to achieve that will improve the performance of our organization. In most businesses, performance can be measured by profitability, sales, etc. If we have goals focused on the business, we’ll probably perform better.

Signal: Something that tells us how we are tracking against our goal. A signal is something that may not be able to be measured directly…


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I was speaking at a DevOps meetup in Finland recently and was asked, “what does DevOps mean to you?” I love that they started the conversation that way. DevOps no longer means Development and Infrastructure teams cooperating and it has never truly been a job or a team. We are not solving a technical problem. We are trying to solve a business problem. How do we more effectively deliver value to our customers?

Note: If someone works for our company, they only become a customer when they buy something from our company.

DevOps is the way we work to improve…


As we try to improve the flow of value to the end-user, the first item that usually gains focus is the productivity of development teams and how to measure it. I’d like to propose that productivity is measured by customer value delivery, not team output. However, that reality is often lost as we rush to find easy numbers to get a handle on measuring teams. Misusing metrics undermines the goals of improvement efforts and playing Whack-a-Mole with metrics anti-patterns is tedious. Hopefully, the anti-patterns cheat sheet will help.

Story points:

Myth: How long it will take to complete a story

Reality: Story…


The following is fantasy. Any resemblance to persons living or dead is coincidental. However, too many people live this.

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ScrummerFall

Jackie is a buyer who needs better tools for forecasting demand so she can make better-informed decisions. She has a list of high value features she needs, so she contacts Dana, the product owner for the forecasting application, to request changes.

Dana discusses the features with Jackie and writes user stories for each feature with acceptance criteria for each story and adds them to the backlog. Since Q1 is half over, Dana schedules the new request to be discussed in the…


Copyright 2021 Bryan Finster — All rights reserved

Delivering value to the end-users means we need systems that are useful, secure, and resistant to the shark-filled acid bath of the cloud environment. Engineering for chaos is crucial.

There are many resources that discuss the architectural concerns of resiliency engineering. Circuit breakers to gracefully handle the instability of our dependencies. Incrementally reducing feature abilities if dependencies are offline. Switching loads seamlessly between regions if one goes down or SLOs are exceeded. Redundant data persistence, idempotent messages, and etc. While we may be able to predict many failures and make them part of the initial design, we won’t predict for…


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Code coverage is the measure of the amount of code being executed by tests. It’s an easy number to measure and a minimum value is frequently set as a goal. What is the actual value of code coverage?

True story, I was once in an organization where management told us that one of our annual goals was to ensure all applications had 90% code coverage. See, we were just starting to push testing in the area and they wanted to track our progress to make sure testing was happening. It was an interesting social experiment that I frequently see repeated…

Bryan Finster

Developer, Value Stream Architect, and DevOps insurgent who optimizes for sleep. All opinions are my own. https://www.linkedin.com/in/bryan-finster/

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