# version-control Version control is a system that records and manages changes to files or code over time, allowing versions to be recalled, compared, and restored. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## When Feature Flags Weren't Enough DevFeed: [When Feature Flags Weren't Enough]() Original publisher: [Read original article]() Author: Global Technology Published: 2026-06-09T13:33:43Z Content type: article Language: en Sources: [McDonald's Technical Blog - Medium]() Topics: [configuration](), [feature flags](), [Back end](), [version-control](), [pull-requests](), [ci](), [real-time](), [Tooling]() Tags: [backend](), [ci](), [configuration](), [configuration-management](), [devops](), [distributed-systems](), [feature-flags](), [infrastructure](), [pull-requests](), [real-time](), [software](), [software-architecture](), [tooling](), [version-control]() ### AI overview McDonald's engineers describe replacing a third-party feature-flag platform with a remote configuration system for structured, hierarchical restaurant settings. The system treats configuration like code through version control, pull requests, CI validation, peer review, and auditable live delivery to running backend services without redeployment. ### Source excerpt We rebuilt remote configuration because tooling must match the problem and working like code with review, validation, and live delivery without redeploys. By: Mikhail Baranov, Software Engineer III, & Erick Lopez, Software Engineer III Quick Bytes: Feature flags worked for tracking changes, but they fell short when we needed richer configuration across thousands of restaurants We rebuilt remote configuration to work like code -- version-controlled, validated in CI, and delivered live to running services without redeploys Teams now manage configuration by exception, ship changes safely in real time, and operate with far more confidence and control Runtime configuration carries real weight in a restaurant technology environment. Thresholds get tuned. Features roll out region by region. One location needs a special rule; another needs a noisy signal dialed down. These aren't hypotheticals -- they're everyday decisions that shape how our backend fleet behaves across thousands of restaurants. For a long time, we managed these decisions through a third-party feature-flag platform. It gave us auditability and a clear record of who changed what. But over time, an uncomfortable truth emerged: the tool wasn't built for the shape of our problem. We didn't need toggles and targeting rules. We needed rich, structured configuration -- hierarchical defaults, per-restaurant overrides, clear environment promotion, and real-time delivery to distributed backend services. Forcing that model into a flags-first product created friction: awkward workarounds, unnecessary cost, and extra operational steps for changes that should have felt routine. We wanted configuration changes to feel as safe and controlled as code changes, while still reaching running services immediately. So, we set out to build exactly that. Treating configuration like a managed product Our solution treats configuration with the same rigor as production code. Structured configuration lives in version control. Changes move ## Git sync & workspace forks: your entire workspace, version controlled DevFeed: [Git sync & workspace forks: your entire workspace, version controlled]() Original publisher: [Read original article]() Author: Tristan Lécuyer Published: 2026-04-02T00:00:00Z Content type: release Language: en Sources: [Windmill Blog]() Topics: [Git](), [version-control](), [CI/CD](), [GitLab](), [GitHub]() Tags: [azure](), [bitbucket](), [ci-cd](), [fork](), [git](), [gitlab](), [launch-week](), [merge](), [pipelines](), [repository](), [review](), [rollback](), [sync]() ### AI overview Windmill introduces redesigned bidirectional Git sync and workspace forks. Git sync commits and pushes deployed items to a configured repository and can pull updates from Git, while forks provide isolated feature-development workspaces with deployment, merge, and Git-based workflows. ### Source excerpt Introducing improved Git sync and workspace forks: sync workspaces to Git, fork for feature development, and deploy via CI/CD. ## Don't Let Flakes Pin You Down: Unlocking Better Inputs DevFeed: [Don't Let Flakes Pin You Down: Unlocking Better Inputs]() Original publisher: [Read original article]() Author: toastal Published: 2026-03-26T00:00:00Z Content type: tutorial Language: en Sources: [Nixcademy Blog]() Topics: [Nix](), [version-control](), [Git](), [Tooling]() Tags: [best-practices](), [features](), [fetch](), [reproducibility](), [version-control]() ### AI overview This article examines the limitations of Nix flakes' input-pinning model and introduces nixtamal as a way to work with better inputs. It explains how pinning supports reproducibility, contrasts flakes with earlier tooling such as niv and npins, and discusses limitations including restricted version-control support. ### Source excerpt Flakes gave us input pinning, but you might be missing out on better inputs. Let's see how nixtamal unlocks them. ## first-class merges and cover letters DevFeed: [first-class merges and cover letters]() Original publisher: [Read original article]() Published: 2025-09-11T01:26:47Z Content type: opinion Language: en Sources: [Tony Finch's blog]() Topics: [Git](), [version-control](), [Development](), [pull-requests](), [Code review]() Tags: [branch](), [git](), [merge](), [review](), [version-control](), [workflow]() ### AI overview This commentary examines shortcomings in Git branches and common merge and rebase workflows. It argues that improving merges, rather than branches alone, could make branch-based development more effective, while considering trade-offs between detailed history and clean logical changes. ### Source excerpt Although it looks really good, I have not yet tried the Jujutsu (jj) version control system, mainly because it's not yet clearly superior to Magit. But I have been following jj discussions with great interest. One of the things that jj has not yet tackled is how to do better than git refs / branches / tags. As I underestand it, jj currently has something like Mercurial bookmarks, which are more like raw git ref plumbing than a high-level porcelain feature. In particular, jj lacks signed or annotated tags, and it doesn't have branch names that always automatically refer to the tip. This is clearly a temporary state of affairs because jj is still incomplete and under development and these gaps are going to be filled. But the discussions have led me to think about how git's branches are unsatisfactory, and what could be done to improve them. branch merge rebase squash fork cover letters previous branch workflow questions branch One of the huge improvements in git compared to Subversion was git's support for merges. Subversion proudly advertised its support for lightweight branches, but a branch is not very useful if you can't merge it: an un-mergeable branch is not a tool you can use to help with work-in-progress development. The point of this anecdote is to illustrate that rather than trying to make branches better, we should try to make merges better and branches will get better as a consequence. Let's consider a few common workflows and how git makes them all unsatisfactory in various ways. Skip to cover letters and previous branch below where I eventually get to the point. merge A basic merge workflow is, create a feature branch hack, hack, review, hack, approve merge back to the trunk The main problem is when it comes to the merge, there may be conflicts due to concurrent work on the trunk. Git encourages you to resolve conflicts while creating the merge commit, which tends to bypass the normal review process. Git also gives you an ugly useless canned commit messa ## How I created my first Course with Datacamp DevFeed: [How I created my first Course with Datacamp]() Original publisher: [Read original article]() Published: 2025-01-22T00:00:00Z Content type: article Language: en Sources: [Mutt0-ds Notes]() Topics: [Microsoft](), [Security](), [Deployment](), [configuration](), [version](), [version-control](), [data analytics]() Tags: [configuration](), [course](), [data-analytics](), [deployment](), [microsoft](), [security](), [version]() ### AI overview The author describes creating and publishing a DataCamp course on advanced Microsoft Fabric topics, including security, configuration, version control, and deployment. The article explains how DataCamp's Fabric sandbox supports hands-on exercises and outlines the course-development process. ### Source excerpt I just published an online course! covering advanced Microsoft Fabric topics like security, deployment, admin settings, and version... ## Why and how I switched from Medium DevFeed: [Why and how I switched from Medium]() Original publisher: [Read original article]() Published: 2025-01-06T00:00:00Z Content type: opinion Language: en Sources: [Gaurav Sarma's Blog]() Topics: [Hugo](), [Self-hosted](), [static-site-generator](), [version-control](), [Markdown]() Tags: [hugo](), [markdown](), [self-hosted](), [static-site-generator](), [terminal](), [version-control]() ### AI overview The author explains why they moved from Medium to a self-hosted blog, citing terminal-based writing, Markdown support, version control, custom features, and automation. They chose Hugo as a lightweight starting point for the new setup. ### Source excerpt . [Why I Switched from Medium](why-i-switched-from-medium-cover... ## Adopting Docs as Code in Developer Workflows DevFeed: [Adopting Docs as Code in Developer Workflows]() Original publisher: [Read original article]() Author: Tiffany Chen Published: 2024-11-19T00:00:00Z Content type: tutorial Language: en Sources: [Mintlify Blog]() Topics: [Documentation](), [Git](), [Markdown](), [version-control](), [Pull Request]() Tags: [ai-trends](), [also](), [docs-as-code](), [documentation](), [git](), [markdown](), [version-control]() ### AI overview This article explains how a Docs as Code approach brings documentation into existing developer workflows through plain-text formats such as Markdown, Git-based version control, change reviews, and automated builds. It also recommends cultural practices such as recognizing documentation work in performance reviews and requiring documentation updates alongside code changes. ### Source excerpt We all suffer from documentation lagging behind product updates. ## Git Version Control Tutorial: A Beginner's Guide to Git Version Control DevFeed: [Git Version Control Tutorial: A Beginner's Guide to Git Version Control]() Original publisher: [Read original article]() Author: admin Published: 2024-05-03T07:28:35Z Content type: tutorial Language: en Sources: [Posts on Chris Banes]() Topics: [Git](), [version-control](), [Tutorial](), [coding](), [Development](), [Code]() Tags: [beginner](), [code](), [coding](), [collaboration](), [commands](), [commit](), [core](), [developers](), [distributed](), [distributed-system](), [efficiency](), [files](), [git](), [guide](), [machine](), [merge](), [projects](), [repository](), [tutorial](), [uncategorized](), [version-control]() ### AI overview A beginner-focused tutorial explaining Git as a distributed version control system for tracking changes, managing repositories, creating commits and branches, and collaborating with other developers. ### Source excerpt Have you ever worked on a project and accidentally overwritten your progress? Maybe you spent hours coding a new feature, then realized you needed to go back to a previous version. This is where git version control can help! Git is a lifesaver for developers, allowing you to track changes, collaborate effectively, and ensure you [...] ## Simplify Teleport - July Newsletter DevFeed: [Simplify Teleport - July Newsletter]() Original publisher: [Read original article]() Author: ben@goteleport.com (Ben Arent) Published: 2023-07-17T00:00:00Z Content type: article Language: en Sources: [Teleport]() Topics: [Deployment](), [DevOps](), [version-control](), [Amazon EC2](), [Kubernetes](), [ssh](), [cross-platform](), [ui](), [Zero Trust]() Tags: [clusters](), [cross-platform](), [deployment](), [devops](), [ec2](), [newsletter](), [ssh](), [ui](), [updates](), [version-control](), [zero-trust]() ### AI overview This Teleport newsletter presents practical ways to simplify Teleport deployment and ongoing operations, including automatic updates, version-controlled RBAC roles, automatic resource enrollment, Teleport Connect, and access based on user identity rather than IP address. ### Source excerpt Five top tips to simplify your Teleport deployment. ## An overview of best RBAC practices using Teleport, Terraform, and Git. DevFeed: [An overview of best RBAC practices using Teleport, Terraform, and Git.]() Original publisher: [Read original article]() Author: kenneth.dumez@goteleport.com (Kenneth DuMez) Published: 2023-07-14T00:00:00Z Content type: tutorial Language: en Sources: [Teleport]() Topics: [Git](), [version-control](), [Authorization](), [Code review](), [DevOps](), [audit]() Tags: [compliance](), [database](), [devops](), [git](), [least-privilege](), [permissions](), [pr-reviews](), [version-control]() ### AI overview The article explains why Teleport RBAC roles should be managed in version control. It highlights accountability, change history, reduced complexity, audit and compliance benefits, and pull-request reviews that can catch permission mistakes before deployment. ### Source excerpt An overview of best RBAC practices using Teleport, Terraform, and Git. ## Implementing Data Validation with Great Expectations in Hybrid Environments DevFeed: [Implementing Data Validation with Great Expectations in Hybrid Environments]() Original publisher: [Read original article]() Author: Kamila Widyanto Full time DevOps; Site Reliability Engineer; Part Time Rubberduck Linkedin Profile Published: 2023-04-25T00:00:00Z Content type: tutorial Language: en Sources: [Trivago]() Topics: [data-processing](), [Hadoop](), [hdfs](), [integrity](), [Apache Spark](), [configuration](), [Library](), [Python](), [JSON](), [Open Source](), [YAML](), [version-control]() Tags: [configuration](), [data](), [data-pipeline](), [data-processing](), [data-validation](), [devops](), [distributed](), [hadoop](), [hdfs](), [integrity](), [json](), [library](), [open-source](), [python](), [version-control](), [workflow](), [yaml]() ### AI overview This article describes implementing Great Expectations for data validation in a hybrid Hadoop environment. It explains the framework's core concepts and how the authors ran it as a PySpark job in an automated data pipeline, including configuring the Data Context for HDFS constraints. ### Source excerpt Data validation is an essential step in any data processing pipeline, as it ensures the integrity and accuracy of the data to be used across all subsequent processing steps. ## Value Statements for My New Company DevFeed: [Value Statements for My New Company]() Original publisher: [Read original article]() Author: Fuzzygroup Published: 2022-07-15T07:39:00Z Content type: opinion Language: en Sources: [Scott Johnson]() Topics: [Software](), [test-coverage](), [cloud-infrastructure](), [Support](), [unit tests](), [version-control]() Tags: [coverage](), [culture](), [distributed](), [ethics](), [github](), [software](), [startup](), [support](), [test-coverage](), [unit-tests](), [version-control](), [work-from-home]() ### AI overview The author presents draft values for a new company, emphasizing ethical behavior, written documentation, respectful communication, commitment-keeping, transparency, work-life balance, technical support, software quality, version control, and test coverage. ### Source excerpt Welp, it looks like I'm starting a new company after all. Here are the values that I drafted for it. Values These things we believe: Ethics. We will behave ethically in all situations. Writing Things Down. We will work from home and be a distributed culture. And in a distributed culture, things have to be written down. Good writing is a skill for everyone not something reserved for writing. Having the Hard Conversations Respectfully. In any culture there will be conflict. This can be done respectfully and without tripping anyone's bozo bit. Do What We Say. We will keep our commitments and do the things we say. If we fail - and that's expected - then we will apologize and accept responsibility. Openness and Transparency. Shining light on things makes the badness scurry away. That's the power of openness and transparency. Revenue Disclosure. Every organization is, correctly, driven by its revenue sources - and that's ok. Problems occur, however, when you fail to disclose your revenue sources. Ethical Capitalism. Capitalism has been the single most transforming force in history and it has done more to lift people from poverty than anything else. Now, that said, capitalism without regulation and restraint is a violent beast. The capitalism I believe in was taught to me by my grandfather and it could be summarized as "do the right thing; don't chase every dollar; pay it forward; treat everyone with kindness". Code of Conduct. We will treat each other with mutual respect. We have adoped the Github code of conduct it appends to every repo. Work Should Be Secondary to Life. This is a business but business was not supposed to take over our lives. All staff are encouraged to take acknowledge this and, hopefully, take four day work weeks as often as they like. World Class Technical Support. The high tech industry can - and should - offer world class support. Great support is possible when you have high gross margins - which is all of the technology business - although most peo ## The MLOps Playbook: Best Practices for Ensuring Reliability of ML Systems DevFeed: [The MLOps Playbook: Best Practices for Ensuring Reliability of ML Systems]() Original publisher: [Read original article]() Author: Headspace Published: 2021-09-28T21:04:00Z Content type: opinion Language: en Sources: [Stories by Headspace on Medium]() Topics: [MLOps](), [Machine learning](), [Model Development](), [version-control](), [Software Engineering]() Tags: [benchmarking](), [data-science](), [dataops](), [datasets](), [machine-learning](), [mlops](), [model-development](), [observability](), [quality](), [software-engineering](), [version-control]() ### AI overview This article presents an MLOps playbook for assessing the production readiness and operational reliability of machine learning systems. It recommends version-controlling model code, data, parameters, and metrics; accounting for model complexity and operating cost; evaluating quality across important data slices; and testing for inclusion and potential bias. ### Source excerpt Author: Mo Messidi, a seasoned DataOps leader at Headspace with a decade of experience in both startups and enterprises. His mission is to help organizations operationalize their data. This article presents a simple, yet comprehensive, set of MLOps best practices for organizations to assess the production readiness of machine learning systems. It has also proved beneficial for assessing off-the-shelf MLOps platforms for feature and functionality completeness. There may be a whole range of software engineering best practices towards producing trustworthy software, but similar best practices for machine learning system operations are only in their infancy. Stage A: Model Development Model code, data, parameters, and metrics are version controlled It is important to know the code, data, and artifacts that produced a model. You can do this by having good version control for the model specification, including hyper-parameters and experiment artifacts. This ensures reproducibility, enables rollbacks, and de-risks system changes. A simpler model is not better The more complex a model, the higher its cost to operate. Adding a complexity tax to model assessment equations can help reveal the true incremental value of a given model. Model quality is sufficient for all important data slices ML models quality metrics can easily get lost in the averages when benchmarking against full datasets. It is important to examine quality independently for temporal and location variations. It is common for models to exhibit large drops in quality for specific data slices e.g. users in Denmark vs. users in Europe. The model is tested for considerations of inclusion ML unfairness may occur due to the way that people's choices affect what training data is used for something like word embedding. This can then lead to biased system behavior because it is based on these bad choices done during training data set creation. Measuring what you are doing is important to make systems for everyone. For ## A few words on Git. DevFeed: [A few words on Git.]() Original publisher: [Read original article]() Author: Hadi Hariri (mail@hadihariri.com) Published: 2020-10-13T22:00:00Z Content type: opinion Language: en Sources: [Hadi Hariri]() Topics: [Git](), [version-control](), [User Experience]() Tags: [developers](), [git](), [user-experience](), [version-control]() ### AI overview An opinion piece argues that Git's widespread adoption does not make it successful at its core job as a distributed version control system. The author focuses on Git's user-experience problems and rejects the idea that complexity should simply be overcome by learning the tool. ### Source excerpt I tweeted something about Git. Do I regret it? A little bit. Why? Because it had a grammar mistake. Git is not a success story. Git is a failure as a system with a crap user experience that forces you to learn more about the tool you're using that about getting your work done. -- Hadi Hariri (@hhariri) October 8, 2020 The tweet made some rounds and died off. Then someone posted it on Hacker News, and it made more rounds, and then it died. Then someone posted it on Reddit, and the damn thing just doesn't die off! The feedback The replies to the tweet can be grouped in two: Folks that agree Those that don't agree (and some are very angry) I want to address the second group because it seems many of them don't seem to get my point, and I keep repeating myself in replies to the tweet. Of course, it's wishful thinking if anyone reads this post because at times, I find folks often don't even read Twitter threads. Having said that, let's try and categorize the responses: You're an idiot for saying it's not successful. It's used everywhere! Let's first address what I mean by success. If we're talking about reach, Git is successful, yes. It's probably the most used Version Control system. If we're talking about people being frustrated and banging their heads to the wall because of Git, I'd say it probably is also successful. Jokes aside though, the success I was talking about is actually in the context of the tweet - it is not (remember, this is my opinion) successful at its job of being a distributed version control system, because it fails at the user experience. More on why later. So let's put success into context - especially on Twitter. Remember we only read single tweets. You're a professional. Learn the tool or GTFO. I suck at Git. But let's say for a moment that I didn't suck at Git. The response of "learn the tool" is not only assuming that you know my knowledge about Git, but also implying that everything is wonderful, and the problem lies only in that we, as users, ## Embrace Your Tagline at Every Opportunity DevFeed: [Embrace Your Tagline at Every Opportunity]() Original publisher: [Read original article]() Author: Fuzzygroup Published: 2020-07-03T00:00:00Z Content type: opinion Language: en Sources: [Scott Johnson]() Topics: [Code](), [version-control](), [ui]() Tags: [code](), [marketing](), [project](), [startup](), [startups](), [user-interface](), [validation](), [version-control]() ### AI overview The author recommends treating a startup tagline as a concise description of what is being built, preserving candidate taglines in code under version control, and displaying the selected tagline in the project's user-interface footer. The article also recommends seeking early validation. ### Source excerpt I have been, since my very first foray into startups, a huge advocate of the tag line. A tag line is that one to 10 word phrase that encapsulates exactly what you are building. I talk about this in my document on Opportunity Profiles where I identify it as one of the first things you write down when planning a new venture. This morning, as I engaged in my "just out of bed, the brain is fresh, work on something new and interesting" moment of my day, I found a new way to embrace the tag line. Yesterday was I brainstormed on something and what felt like a new perfect tag line was uttered. So I did two things today: I put that tag line and the other candidates into code. This means that not only are the written down but they are under version control so I can get back to them as needed. You never know how a project morphs and changes as it weaves its way towards the market and being able to get back to a tag line, I've found, is vital. I added it to the project's user interface as part of its footer. This means that every time that I look at what I'm building, I will see it and, hopefully, be inspired by it. Here's an example of #2 (this is just the footer not the project itself). The tag line is the text on the left in bold. And if you find that tag line intriguing then: That's great; it means it might be right; validation on these things is key and should be sought as early as possible You know where to find me if you want to ask about it (contact info is on the bottom of every page; look down) ## The Communicative Value of Using Git Well DevFeed: [The Communicative Value of Using Git Well]() Original publisher: [Read original article]() Published: 2020-01-14T07:00:28Z Content type: opinion Language: en Sources: [Jeremy Kun]() Topics: [Git](), [version-control](), [Code](), [Pull Request]() Tags: [commit](), [git](), [mercurial](), [pull-request](), [twitter](), [version-control]() ### AI overview This opinion article argues that Git's distinctive value lies in treating code changes as manipulable data that can be shaped into clear stories. Granular changes, history manipulation, and inexpensive branching help developers draft, decompose, recombine, and narrate changes for easier review and communication. ### Source excerpt Recently my employer (Google) forced me to switch to Mercurial instead of my usual version control system, git. The process of switching sparked a few discussions between me and my colleagues about the value of various version control systems. A question like "what benefit does git provide over Mercurial" yielded no clear answers, suggesting many developers don't know. An informal Twitter survey didn't refute this claim. A distinguished value git provides me is the ability to sculpt code changes into stories. ## When You Forget Your Branch Name Use Git Reflog DevFeed: [When You Forget Your Branch Name Use Git Reflog]() Original publisher: [Read original article]() Author: Fuzzygroup Published: 2019-11-25T00:00:00Z Content type: tutorial Language: en Sources: [Scott Johnson]() Topics: [Git](), [version-control](), [GitHub Issues](), [Pull Request](), [ci]() Tags: [cmn](), [command](), [commit](), [git](), [github](), [github-issues](), [pull-request](), [version-control]() ### AI overview This article explains how Git reflog can help recover the name of a branch that was forgotten in a workflow using issue branches, pull requests, and separate master and develop branches. The author uses reflog output, including local dates, to identify the branch and resume work. ### Source excerpt For my current side project, cmn, I'm using a version control model of issue branches as described here back in June (about when I started this). Basically the model is: The master branch is always pristine and always deployable. The develop branch takes changes from issue branches and is then merged into master by a CI server. Anything you work on, no matter how small, gets a github issue and goes thru a pull request approach. I've never been a real big fan of structured engineering approaches and my last boss, Taylor Williams, did a fantastic job of teaching us this and - he was right. Even on a small side project, there are definite benefits to solid, well defined workflow processes. One disadvantage when you work this way is that you end up with a lot of branches. And since branches tend to be named for the issue, it isn't always apparent the difference between say 444 and 445. When branches are transitory such as "fix this bug", that isn't a big deal. But when a branch is longer lived, because it just can't be completed in a short period of time, you are likely to simply forget the branch name. As an example, last Thursday night, I started work on a pretty complex enhancement and then a new bug came up Friday morning. My response was to do an add / commit and then change back to develop and create a new issue and fix that bug. And, somehow, between Friday morning and tonight, Monday night, the issue number has jumped by 30 issues (if you work this way then you make a lot of issues). So I went to find the branch and I simply couldn't. I was at 480 and I looked back at the Github Issues page and I thought it might have been 460 but that turned out not to be it. As I thought about it, I realized that I knew when I last worked on it, the preceding Thursday, and there had to be a way to to look at branches by date created. A bit of Internet research led me to the git reflog command: git reflog --date=local Here is an example of reflog's output: e95bf81 HEAD@{Fri Nov ## What a developer learned at PDX DevOpsDays DevFeed: [What a developer learned at PDX DevOpsDays]() Original publisher: [Read original article]() Author: Graham King Published: 2019-09-13T17:54:30Z Content type: article Language: en Sources: [Graham King]() Topics: [DevOps](), [YAML](), [version-control](), [site-reliability-engineering](), [Amazon Web Services](), [Kubernetes](), [Monitoring](), [Ansible](), [Slack](), [Terraform](), [GitLab]() Tags: [aws](), [ci-cd](), [conference](), [developer](), [devops](), [devops-conference](), [kubernetes](), [monitoring](), [software](), [version-control](), [yaml]() ### AI overview A developer recounts two days at PDX DevOpsDays and explains that the event presented DevOps primarily through systems administration, automation, version control, YAML, cloud infrastructure, monitoring, incident response, and reliability practices. ### Source excerpt Two days at PDX DevOpsDays, a gathering of system administrators who use version control, and write a lot of YAML. ## Enforcing Consistent Coding Conventions with Shared IDE Settings and Build Checks DevFeed: [Enforcing Consistent Coding Conventions with Shared IDE Settings and Build Checks]() Original publisher: [Read original article]() Published: 2019-06-27T00:00:00Z Content type: tutorial Language: en Sources: [Paweł Chudzik]() Topics: [coding](), [configuration](), [ide](), [version-control](), [Maven](), [Gradle](), [IntelliJ IDEA](), [Vim]() Tags: [code-style](), [coding](), [configuration](), [git](), [gradle](), [ide](), [maven](), [version-control](), [vim]() ### AI overview The article recommends exporting shared IDE code-style settings into version control and using build-time checks to enforce coding conventions across tools and team members. ### Source excerpt When the whole team agrees on coding standards we tend to be optimistic. We think that from now on everything will be exactly as we decided. The truth is that usually after a couple of months you'll reinstall IDE or system and forget about configuration or new people join and it's the Wild West all over again. Read more ## Jonathan Marcil's Threat Modeling Toolkit talk DevFeed: [Jonathan Marcil's Threat Modeling Toolkit talk]() Original publisher: [Read original article]() Author: Adam Published: 2018-01-30T00:00:00Z Content type: article Language: en Sources: [Shostack & Friends Blog]() Topics: [Application Security](), [Security](), [Architecture & Design](), [plantuml](), [version-control](), [trust]() Tags: [appsec](), [blog](), [diagram](), [github](), [plantuml](), [requirements](), [security](), [talk](), [trust](), [version-control]() ### AI overview A report on Jonathan Marcil's threat modeling toolkit talk, covering collaborative threat modeling, data flow diagrams, attack trees, controls checklists, and system models. The talk includes an Electrum example in which investigations driven by a system model found a real JSON-RPC vulnerability, and discusses using PlantUML and version control for attack trees. ### Source excerpt [no description provided] ## The Pragmatic Programmer DevFeed: [The Pragmatic Programmer]() Original publisher: [Read original article]() Author: Tom Published: 2017-12-03T00:00:00Z Content type: opinion Language: en Sources: [Tomasz Gągor]() Topics: [Programming](), [Go Language](), [Code quality](), [version-control](), [Testing](), [Automation](), [Refactoring](), [Java](), [Perl]() Tags: [automation](), [code-quality](), [go](), [go-programming](), [java](), [management](), [perl](), [productivity](), [programming](), [refactor](), [review](), [technology](), [testing](), [version-control]() ### AI overview A retrospective review of The Pragmatic Programmer finds that some tools and examples feel dated in 2025, but its core lessons remain relevant. The article highlights continuous learning, mastering an editor and workflow, version control, testing, automation, code quality, and adaptability, with personal reflections on using Go and Python. ### Source excerpt Pragmatyczny programista Od czeladnika do mistrza Authors: Andrew Hunt, David Thomas I first read this book almost 10 years ago, but didn't write a proper review at the time. Over the recent Christmas break, I revisited it and gave it a second read which resulted in bit of Go programming 😁. Reading it in 2025, you can feel the book is dated. The authors are enthusiastic about Java and CORBA1, and use Perl for daily tasks. Even though I did similar things around 2015, my workflow has changed since then. Newer tools and architectures have made things even simpler. ## ReactOS Repository migrated to GitHub DevFeed: [ReactOS Repository migrated to GitHub]() Original publisher: [Read original article]() Published: 2017-10-03T00:00:00Z Content type: news Language: en Sources: [Front Page on ReactOS Website]() Topics: [ReactOS](), [migration](), [GitHub](), [Git](), [version-control](), [Code review](), [Continuous integration](), [jira]() Tags: [continuous-integration](), [free](), [git](), [github](), [jira](), [migration](), [open-source](), [os](), [pull-request](), [react](), [reactos](), [version-control](), [win32](), [winapi]() ### AI overview ReactOS migrated its source code from a central Subversion instance to a decentralized Git repository and joined GitHub for software development. The article explains the migration history, notes that the SVN repository is now read-only, and describes related tooling and documentation updates. ### Source excerpt Today, the ReactOS Source Code has been migrated from a central Subversion instance to a decentralized Git repository. Together with that, ReactOS joins the list of projects using the popular GitHub service for developing software. We expect that this move greatly improves the way we collaborate on ReactOS development and reduces the barriers for newcomers. Just fork our repository on GitHub, commit your changes and send us a Pull Request! ## Creating a Culture of Quality DevFeed: [Creating a Culture of Quality]() Original publisher: [Read original article]() Author: Jan Van Thoor Follow Published: 2015-08-31T00:00:00Z Content type: opinion Language: en Sources: [Trivago]() Topics: [bug](), [Development](), [Testing](), [legacy](), [version-control](), [unit tests](), [JavaScript](), [PHP]() Tags: [bug](), [development](), [engineering-culture](), [legacy](), [quality](), [testing](), [unit-tests](), [version-control]() ### AI overview A trivago development team describes its journey from frequent application bugs and a chronically broken SVN trunk toward a more structured release process. The excerpt highlights release branches, dedicated QA resources, process changes, and longer development cycles as measures intended to improve software quality. ### Source excerpt You know those bugs, like, **those**. Where the application state dances around you like a crazed Polynesian fire dancer. Where changing the sorting order of a search in London reverts the result list back to Paris... Seriously? Unfortunately, a lot of us are specialists in dealing with this kind of bug. ## Pull Requests: The Linchpin of Open Source DevFeed: [Pull Requests: The Linchpin of Open Source]() Original publisher: [Read original article]() Author: Bruce Eckel Published: 2015-08-03T00:00:00Z Content type: opinion Language: en Sources: [Bruce Eckel - Computing Thoughts]() Topics: [Pull Request](), [Open Source](), [version-control](), [Git](), [GitHub](), [Linux]() Tags: [git](), [github](), [linux](), [open-source](), [pull-requests](), [version-control]() ### AI overview This commentary explains how pull requests integrated patch review into distributed version control, using GitHub's workflow as an example. It argues that accepting or rejecting contributions gives project committers significant control over a project's direction and leadership. ### Source excerpt When Linus Torvalds started creating Linux, he managed the code base himself. People would email him patches and he would either include them or not. To maintain the code base - to have checkpoints and be able to back up to an earlier known point - he used a Distributed Version Control System (DVCS) which, as the name implies, is for managing versions. So there were these two seemingly-separate things: incorporating patches and managing versions. [Next page]()