# continuous deployment Published articles for continuous deployment. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## How To Set Up a Staging Environment on Heroku in 3 Easy Steps DevFeed: [How To Set Up a Staging Environment on Heroku in 3 Easy Steps]() Original publisher: [Read original article]() Author: Andy Smith Published: 2026-07-16T18:23:58Z Content type: tutorial Language: en Sources: [Heroku]() Topics: [Heroku](), [Deployment](), [Continuous Delivery (CD)](), [Testing](), [pull-requests](), [Git](), [GitHub]() Tags: [continuous-delivery](), [continuous-deployment](), [deployment](), [engineering](), [github](), [heroku](), [heroku-pipelines](), [how-to](), [pull-requests](), [testing]() ### AI overview A tutorial explains how to create a staging environment on Heroku by separating configuration and databases, grouping applications in Heroku Pipelines, and promoting tested compiled slugs to production. It also covers continuous delivery, disabling automatic deployment during setup, and optional Review Apps for pull requests. ### Source excerpt Moving fast should not mean breaking things for your users. While testing on localhost is a good start, you need a near identical replica of production to catch any bugs before your code goes live. That is where a staging environment comes in. Heroku pipelines handle the infrastructure layout for you, keeping your deployment workflow clean and automated. The post How To Set Up a Staging Environment on Heroku in 3 Easy Steps appeared first on Heroku. ## Documentation team funding DevFeed: [Documentation team funding]() Original publisher: [Read original article]() Author: NixOS Published: 2026-07-10T12:00:00Z Content type: news Language: en Sources: [NixOS Announcements]() Topics: [Documentation](), [Nix](), [Deployment](), [navigation]() Tags: [2025](), [announcement](), [community](), [continuous-deployment](), [deployment](), [documentation](), [funding](), [improvements](), [navigation](), [nix](), [onboarding](), [team]() ### AI overview The NixOS Foundation is renewing its effort to improve Nix documentation and is seeking donations for a documentation team. Proposed funding would support a paid maintainer, framework evaluation, page splitting, continuous deployment, faster feedback, navigation, and redirects. ### Source excerpt tl;dr: There is a renewed effort to improve documentation, head to https://opencollective.com/nixos/projects/nix-documentation or contact foundation@nixos.org to chip in with funding! With the 2023 crowd-funding in documentation funding, we've seen some improvements, but a lot more is needed to make significant progress towards improving the overall experience with Nix documentation, including onboarding and discovery. Especially newcomers frequently struggle with our documentation, get frustrated and notice gaps, and have a hard time adopting Nix. In addition, in the Nix community survey 2025 we see that most people want excess funding to be allocated to improving documentation. While the NixOS Foundation doesn't have that much excess funding, @hsjobeki has stepped up to pick up leadership of the documentation team with support by @friedow. While they're volunteering their own time to lead the team, they'd like to have access to funding for not just ensuring that stuff gets done, but also maintained over time. They've collaborated to agree on a documentation vision (initial announcement) to work towards. For that reason, we're asking individuals and companies to donate to the renewed documentation team OpenCollective, so that we can reach the funding goals (more details on OpenCollective): (1.000 EUR /month) Paid documentation maintainer (4.000 EUR ) Framework evaluation (15.000 EUR ) Page splitting in nixos-render-docs (8.000 EUR ) Continuous deployment & Reduce feedback times (8.000 EUR ) Navigation & redirects If a company is interested in providing a significant amount of funding and would like a contract and invoice, please reach out to foundation@nixos.org. Furthermore, if you'd like to support documentation in non-monetary ways, feel free to join the Matrix channel and/or bi-weekly meetings (see "Nix documentation meeting" in the NixOS Calendar), or see where you can help from updates in the discourse category. You can also read and discuss this announcement on Discourse. ## Trust Factory DevFeed: [Trust Factory]() Original publisher: [Read original article]() Author: Kent Beck Published: 2026-06-02T13:33:57Z Content type: opinion Language: en Sources: [Software Design: Tidy First?]() Topics: [trust](), [Code](), [Testing](), [CI/CD](), [Continuous Deployment (CD)](), [observability](), [Refactoring]() Tags: [code](), [continuous-deployment](), [continuous-integration](), [observability](), [refactoring](), [testing](), [trust]() ### AI overview This commentary argues that software development practices can function as a "trust factory." It connects programmer testing, pairing, continuous integration, weekly planning, customer involvement, continuous deployment, refactoring, and observability with building trust among developers, customers, and teams. ### Source excerpt "We're accumulating code faster than we are accumulating trust." Sometimes a phrase just hits. ## How continuous deployment and coding agents are changing software development DevFeed: [How continuous deployment and coding agents are changing software development]() Original publisher: [Read original article]() Published: 2026-03-11T14:30:00Z Content type: opinion Language: en Sources: [Will Larson - Irrational Exuberance]() Topics: [CI/CD](), [Deployment](), [migration](), [AI-assisted coding](), [Heroku]() Tags: [coding-agents](), [continuous-deployment](), [deployment](), [heroku](), [migration]() ### AI overview The author contrasts manual deployment and database migration practices at Imprint with a later workflow in which most changes continuously deploy to production after pull-request review and merge. The article connects this migration to broader reflections on how coding agents may affect software development. ### Source excerpt When I joined Imprint a little less than a year ago, our deploys were manual, requiring close human attention to complete. Our database migrations were run manually, too. Developing good software is very possible in those circumstances, but it takes a remarkable attention to detail to do it. It was also possible to develop good software using Subversion and developing by ssh'ing into a remote server to edit PHP files, but the goal is making things easy rather than possible. Ten months later, the vast majority of our changes, including database migrations, continuously deploy to production without human involvement after the initial pull request is reviewed and merged. Reading aloud the relevant pages from the mandated gospel of continuous deployment, deploying changes this way doesn't make them less reliable, but more so. Each step of validation a human might do, is now consistently done on every deploy, including many steps that are just onerous enough to drop off the standard operating steps like meticulously checking the post-launch health on a production canary every minute for half an hour after each deploy. This migration has reminded me a lot of the Uber service migration, which prompted me to write Migrations: the only scalable solution for technical debt back in 2018, and in particular how different this sort of migration feels in the age of coding agents. The more I've thought about how these two migrations compared, the more it's solidified my thinking a bit about how this technology is going to impact software development over the next few years. Migrations as metaphor Although I really want to talk about how coding agents are changing software development, I want to start by expanding a bit on this recent migration at Imprint and how it compared with the migration at Uber. The Uber migration was: Spinning up a new self-service service provisioning platform, along the lines of a very minimal Heroku, including the actual scheduling algorithm across cluste ## App Hosting adds support for Turborepo DevFeed: [App Hosting adds support for Turborepo]() Original publisher: [Read original article]() Author: Julia Reid Published: 2026-01-08T00:00:00Z Content type: release Language: en Sources: [Firebase Blog]() Topics: [Continuous Deployment (CD)](), [CI/CD](), [JavaScript](), [TypeScript](), [Next.js]() Tags: [app-hosting](), [continuous-deployment](), [dependencies](), [deployment](), [firebase](), [javascript](), [monorepo](), [next-js](), [parallel](), [typescript](), [web]() ### AI overview Firebase App Hosting now supports Turborepo for JavaScript and TypeScript monorepos. The article explains how Turborepo uses task configuration, dependency graphs, and parallel execution to support reliable and efficient builds and deployments. ### Source excerpt Efficient builds in App Hosting's continuous deployment pipeline, even for large and complex monorepos. ## Heroku AppLink: Now Using JWT-Based Authorization for Salesforce DevFeed: [Heroku AppLink: Now Using JWT-Based Authorization for Salesforce]() Original publisher: [Read original article]() Author: Vivek Viswanathan Published: 2025-12-11T16:00:53Z Content type: release Language: en Sources: [Heroku]() Topics: [Heroku](), [JSON Web Tokens](), [Authorization](), [CI/CD](), [ci](), [Security](), [Microservice](), [OAuth]() Tags: [applink](), [authorization](), [ci-cd](), [continuous-deployment](), [continuous-integration](), [credentials](), [deployment](), [heroku](), [jwt](), [news](), [oauth](), [secrets](), [security](), [tokens]() ### AI overview Heroku AppLink now supports JWT-based authorization for Salesforce integrations. The update enables machine-to-machine authorization for automated CI/CD setup and reduces reliance on long-lived secrets and static credentials by providing on-demand tokens. ### Source excerpt Modern Continuous Integration/Continuous Deployment (CI/CD) pipelines demand machine-to-machine authorization, but traditional web-based flow requires manual steps and often rely on static credentials; a major security risk. Heroku AppLink now uses JWT Authorization to solve both: enabling automated setup and eliminating long-lived secrets. In today's evolving threat landscape, security attacks increasingly exploit systems that rely on [...] The post Heroku AppLink: Now Using JWT-Based Authorization for Salesforce appeared first on Heroku. ## Why Threat Modeling Is Now Even More Critical for AI-Native Applications DevFeed: [Why Threat Modeling Is Now Even More Critical for AI-Native Applications]() Original publisher: [Read original article]() Author: Snyk Team Published: 2025-11-20T05:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Security](), [ai security](), [Securing AI](), [Artificial Intelligence](), [Large Language Model](), [Continuous Deployment (CD)](), [Adversarial attacks]() Tags: [ai](), [ai-security](), [architecture](), [architectures](), [attacks](), [blog](), [continuous-deployment](), [engineering](), [executive](), [interest](), [language-models](), [large-language-models](), [security]() ### AI overview AI-native applications require continuous, adaptive threat modeling because their large language models, autonomous agents, evolving data flows, and runtime-integrated tools create dynamic and unpredictable security risks. The article explains why traditional manual, static, point-in-time assessments become stale and fail to scale, and highlights new attack surfaces such as data poisoning, model inversion, and adversarial attacks. ### Source excerpt AI-native applications demand a security approach as dynamic as they are. Traditional threat modeling is no longer enough. Discover the shift to continuous, adaptive threat modeling for AI security. ## How the Fury ecosystem manages high-frequency deployments with automation, monitoring, and resilience DevFeed: [How the Fury ecosystem manages high-frequency deployments with automation, monitoring, and resilience]() Original publisher: [Read original article]() Author: Juan José Orjuela Published: 2025-10-21T13:12:29Z Content type: tutorial Language: en Sources: [Mercado Libre Tech]() Topics: [Deployment](), [Deployment Strategies](), [Automation](), [Resilience](), [configuration](), [Environment Variables]() Tags: [architecture](), [automation](), [configuration](), [continuous-deployment](), [deployment](), [deployment-strategies](), [devops](), [environment-variables](), [metrics](), [on-call](), [optimization](), [resilience](), [scalability](), [vulnerabilities]() ### AI overview This article explains how the Fury ecosystem defines and manages deployments at high frequency. It covers deployment strategies, configuration changes, automatic redeployments, testing, monitoring, alerts, metrics, and on-call practices intended to maintain operational stability. ### Source excerpt "How do you manage to perform 30.000 deployments a day and still operate normally?" For many, that number sounds simply unattainable. Deploying thousands of times a day suggests chaos, constant risk, and an operation that's hard to sustain. But the reality is different: not only do we make it possible -- we do it with control, resilience, and full visibility. It's not magic or luck. It's about a deployment ecosystem built to scale, with robust processes, smart automation, and practices that let us maintain stability even with frequent changes. +750K deployments in July 2025, broken down by deployment strategy. In this article, we'll explain how our model works: what we consider a deployment, how our system is structured, what tools we use to monitor operational health, and how we respond to alerts and failures -- whether they happen in test environments or in the most critical areas of the business. Yes, we'll also cover alerts, metrics, and on-call rotations -- and why they're essential to maintaining a continuous and reliable deployment model at this scale. General outline of a deployment in the Fury ecosystem.What do we consider a deployment? In Fury, a deployment isn't just about pushing new code. We consider a deployment to be any action that updates the state of an application in a given environment. For example: Deploying a new code change to the platform using any of our supported strategies, such as Blue-Green, Canary-Safe, Rolling Update, or All-In. Updating environment variables or configuration properties: any change to these parameters requires a deployment, as it involves recreating the application with the new active configuration. Automatic re-deployments: these can be triggered not only due to detected vulnerabilities but also due to optimization opportunities that help reduce computing resource usage and operational costs. Running validations or tests in test environments before promoting changes to production. Supported deployment strategies Our plat ## Using Argo CD's targetRevision Field for Application Promotion DevFeed: [Using Argo CD's targetRevision Field for Application Promotion]() Original publisher: [Read original article]() Author: Kostis Kapelonis Published: 2025-08-01T13:57:26Z Content type: tutorial Language: en Sources: [Codefresh]() Topics: [argo-cd](), [GitOps](), [Kubernetes](), [Helm charts]() Tags: [argo](), [argo-cd](), [argocd](), [auditability](), [best-practices](), [continuous-deployment](), [gitops](), [helm-charts](), [kubernetes](), [usability]() ### AI overview This guide explains how Argo CD's targetRevision field tracks Git repositories or Helm chart versions and why using it as a promotion mechanism for developer applications can create usability and auditability problems. It recommends using targetRevision: HEAD in ApplicationSets, with specific Helm versions used sparingly for mostly static infrastructure applications. ### Source excerpt In our big guide on how to use ApplicationSets for Argo CD applications, we explained the best practice of having a 3-level structure for all manifests with a clear distinction between Argo CD Application files and Kubernetes resource files. In that article, we also outlined several anti-patterns that we have seen in the wild, meaning [...] The post Abusing the Target Revision Field for Argo CD Promotions appeared first on Codefresh. ## GoodRx Releases Lifecycle Solution for Ephemeral Developer Environments with Built-in Support for Codefresh Pipelines DevFeed: [GoodRx Releases Lifecycle Solution for Ephemeral Developer Environments with Built-in Support for Codefresh Pipelines]() Original publisher: [Read original article]() Author: Kostis Kapelonis Published: 2025-07-08T11:48:28Z Content type: release Language: en Sources: [Codefresh]() Topics: [releases](), [Open Source](), [Code]() Tags: [community](), [continuous-deployment](), [developer](), [kubernetes](), [open-source](), [pipelines](), [pull-request](), [releases]() ### AI overview GoodRx released Lifecycle as open-source software for creating temporary or ephemeral developer environments. Its build process includes built-in support for Codefresh pipelines, and the project can create preview environments from pull requests. ### Source excerpt GoodRx, a digital healthcare platform, has released the Lifecycle project as open-source code. Lifecycle is a complete solution for temporary/ephemeral environments. The project's build process includes built-in support for Codefresh pipelines. Creating preview environments from a Pull Request with Lifecycle Lifecycle was conceived as an internal project back in 2019, and today it is released [...] The post GoodRx Releases Lifecycle Solution for Ephemeral Developer Environments with Built-in Support for Codefresh Pipelines appeared first on Codefresh. ## Using Argo Rollouts for Header-Based Routing in Kubernetes Canary Deployments DevFeed: [Using Argo Rollouts for Header-Based Routing in Kubernetes Canary Deployments]() Original publisher: [Read original article]() Author: Kostis Kapelonis Published: 2025-06-23T13:39:25Z Content type: tutorial Language: en Sources: [Codefresh]() Topics: [Kubernetes](), [Deployment](), [Routing (disambiguation)]() Tags: [argo-rollouts](), [continuous-deployment](), [deployment-strategies](), [kubernetes](), [progressive-delivery](), [routing](), [technical-guides]() ### AI overview This guide explains how to use Argo Rollouts to control which users receive a canary deployment. It compares static routing with extra URLs and header-based routing, covering the tradeoffs between simplicity and flexibility. ### Source excerpt A Kubernetes cluster with default configuration has access to only two deployment strategies: To get access to more advanced deployment strategies such as blue/green and canaries you need to use a dedicated Progressive Delivery controller such as Argo Rollouts. We have previously covered several basic and advanced scenarios for Argo Rollouts in our blog. Today [...] The post Laser Focused Kubernetes Deployments Using Argo Rollouts and Header Based Routing appeared first on Codefresh. ## Why Environments Beat Clusters For Dev Experience DevFeed: [Why Environments Beat Clusters For Dev Experience]() Original publisher: [Read original article]() Author: Kostis Kapelonis Published: 2025-06-02T08:41:54Z Content type: article Language: en Sources: [Codefresh]() Topics: [Development](), [Kubernetes](), [Platform Engineering](), [Cloud]() Tags: [cloud](), [continuous-deployment](), [developers](), [devops](), [gitops](), [kubernetes](), [kubernetes-clusters](), [platform](), [product-and-tools]() ### AI overview This article argues that Kubernetes tooling has matured enough to handle many routine cluster operations, allowing teams to focus more on application developers and their experience. It contrasts environments with clusters as a way to frame developer needs. ### Source excerpt The cloud ecosystem has reached a turning point. Tools for operators/administrators are now mature and can handle most day-to-day operations that deal with Kubernetes clusters. Finally, we can turn our focus to application developers and their needs. If you look at all the Kubernetes tools available, you'll understand that most of them treat Kubernetes as [...] The post Why Environments Beat Clusters For Dev Experience appeared first on Codefresh. ## Combine the Codefresh GitOps Cloud with your existing Argo CD instance DevFeed: [Combine the Codefresh GitOps Cloud with your existing Argo CD instance]() Original publisher: [Read original article]() Author: Kostis Kapelonis Published: 2025-04-30T08:16:16Z Content type: article Language: en Sources: [Codefresh]() Topics: [argo-cd](), [GitOps](), [Kubernetes](), [Continuous Deployment (CD)](), [Deployment](), [Git]() Tags: [argo](), [argo-cd](), [argocd](), [codefresh](), [continuous-deployment](), [declarative](), [deployment](), [git](), [gitops](), [kubernetes](), [product-and-tools](), [pull-request]() ### AI overview This article explains Argo CD as a Kubernetes-native continuous deployment tool and describes how Codefresh GitOps Cloud can work with an existing Argo CD instance. It covers GitOps workflows, application promotion across clusters, declarative configuration, approvals, and deployment synchronization. ### Source excerpt We recently announced the new Codefresh GitOps Cloud, the easiest way to promote changes across Argo CD applications-even across different clusters. With Codefresh GitOps Cloud, you can model your own promotion flow with a graphical editor (although YAML is still available). You define exactly how an application reaches production, including all the requirements and approval [...] The post Combine the Codefresh GitOps Cloud with your existing Argo CD instance appeared first on Codefresh. ## Our Tech Journey Update & Planning DevFeed: [Our Tech Journey Update & Planning]() Original publisher: [Read original article]() Author: Denis Čahuk Published: 2025-04-02T09:36:57Z Content type: article Language: en Sources: [Crafting Tech Teams]() Topics: [AI Agent](), [Artificial Intelligence](), [Continuous Deployment (CD)](), [Test-driven development](), [Code review]() Tags: [ai](), [ai-agent](), [code-review](), [continuous-deployment](), [tdd](), [tech](), [update](), [video]() ### AI overview The article outlines a 10-week live content plan covering AI assistance for tech businesses, AI agent setups, development workflows, testing, deployment, code review, and the economics of AI in product engineering. It also provides streaming platforms and scheduling information. ### Source excerpt A recording from Denis Čahuk's live video ## Introducing Codefresh GitOps Cloud - Seamless environment promotions across clusters using your existing Argo CD DevFeed: [Introducing Codefresh GitOps Cloud - Seamless environment promotions across clusters using your existing Argo CD]() Original publisher: [Read original article]() Author: Kostis Kapelonis Published: 2025-03-30T23:48:40Z Content type: release Language: en Sources: [Codefresh]() Topics: [GitOps](), [argo-cd](), [Automation](), [Cloud]() Tags: [argo-cd](), [automation](), [cloud](), [codefresh](), [continuous-deployment](), [gitops](), [kubernetes](), [product-and-tools](), [reconciliation](), [sync]() ### AI overview Codefresh announces GitOps Cloud, an offering for GitOps deployments that supports multi-environment application promotions across clusters using existing Argo CD. The article also explains GitOps concepts and practices, including version-controlled desired state and continuous reconciliation. ### Source excerpt We're excited to announce our new Codefresh GitOps Cloud offering that lets you bring your GitOps deployments to the next level. You get: In this blog post, we'll dive into some of the key features of Codefresh GitOps Cloud. Multi-environment application promotions with Argo CD As more organizations adopt Argo CD, platform engineers need to [...] The post Introducing Codefresh GitOps Cloud - Seamless environment promotions across clusters using your existing Argo CD appeared first on Codefresh. ## Scaling Technology with Architectural Principles DevFeed: [Scaling Technology with Architectural Principles]() Original publisher: [Read original article]() Author: Shane Gibb Published: 2025-01-08T01:18:36Z Content type: article Language: en Sources: [REA Group]() Topics: [scaling](), [Software Engineering](), [Development](), [Continuous Deployment (CD)](), [maintenance](), [Design system](), [CI/CD]() Tags: [code](), [continuous-deployment](), [continuous-integration](), [design-system](), [engineering](), [maintenance](), [scaling](), [tech]() ### AI overview REA Group describes how architectural principles developed through 25 years of growth guide its software engineering practices, including decision-making, system resilience, team agility, platform reuse, and continuous deployment. ### Source excerpt REA Group, a global company with 1,000+ digital product builders, developed architectural principles from 25 years of growth. ## On Long Term Software Development DevFeed: [On Long Term Software Development]() Original publisher: [Read original article]() Published: 2024-12-22T17:00:00Z Content type: opinion Language: en Sources: [Bert Hubert's writings]() Topics: [Development](), [Software](), [Open Source](), [CI/CD](), [Programming](), [Framework](), [Esolang]() Tags: [ci](), [continuous-deployment](), [continuous-integration](), [dependencies](), [development](), [framework](), [mastodon](), [open-source](), [programming](), [programming-languages](), [software]() ### AI overview An opinion article reflecting on long-term software development through a talk about the Dutch Electoral Board's open-source Abacus vote tabulation software. It contrasts continuously deployed, heavily tested services with safety-critical software that must remain stable for decades, and discusses dependencies, programming languages, and frameworks as long-term design choices. ### Source excerpt Recently the Dutch Electoral Board (where I am also a very part time advisor) invited me to do a talk reflecting on their open source Abacus vote tabulation software. Much software is now provided as a service, and is typically deployed continuously (CD, continuous deployment), surrounded by enough automated testing (CI, continuous integration) that we can be reasonably sure that a new revision is likely to at least work to some extent. ## From Code to Customer - How Continuous Deployment can Accelerate Your Software Development Cycle DevFeed: [From Code to Customer - How Continuous Deployment can Accelerate Your Software Development Cycle]() Original publisher: [Read original article]() Author: tobi@techunicorn.builders (Tobias Mende) Published: 2024-10-17T00:00:00Z Content type: article Language: en Sources: [Tobias Mende]() Topics: [Continuous Deployment (CD)](), [CI/CD](), [Infrastructure as code](), [Testing](), [Monitoring](), [Software Engineering]() Tags: [automated](), [collaboration](), [communication](), [continuous-deployment](), [infrastructure-as-code](), [monitoring](), [pipelines](), [testing](), [trust]() ### AI overview This talk explains how continuous deployment can streamline software delivery through infrastructure as code, automated testing, monitoring, and efficient deployment pipelines. It also discusses organizational changes such as collaboration, communication, and trust, using an example of implementation across 15 teams. ### Source excerpt Many organizations struggle with streamlining the software delivery process, resulting in slower delivery, lower quality, and decreased customer satisfaction. They also face challenges in establishing efficient CD pipelines and implementing cultural changes necessary for successful CD implementation. ## A developer's first year in the Guardian Digital Fellowship DevFeed: [A developer's first year in the Guardian Digital Fellowship]() Original publisher: [Read original article]() Author: Guardian Staff Published: 2024-02-05T16:24:50Z Content type: opinion Language: en Sources: [Guardian]() Topics: [Learning](), [AWS Lambda](), [Code](), [Framework](), [Scala](), [API](), [React]() Tags: [api](), [aws-lambda](), [code](), [continuous-deployment](), [developer](), [framework](), [information](), [learn](), [react](), [scala]() ### AI overview A Guardian Digital Fellowship participant describes his first year learning software development through real editorial technology projects, workshops, team rotations, and production deployments. He discusses working with AWS Lambda, Scala, the Guardian API, data visualisations, and React while receiving support from teammates. ### Source excerpt A developer in the Fellowship Scheme shares his experiences of his first year at the Guardian I clearly remember my early days in the Guardian's Digital Fellowship as a mixture of excitement and being totally overwhelmed. I had joined the editorial tools team, which builds all our digital tools for our journalists. At morning stand-up people were mentioning more acronyms than I thought I could ever remember. Like many of the fellows from previous years I don't have a computer science degree, or even a STEM background, and getting thrown into a department with more than 80 engineers can be intimidating! Fast forward a couple of months I had written my first AWS lambda, contributed to various projects and was regularly deploying production code unsupervised. The value of the fellowship lies in the fact that while you are given the time to develop your skills independently - you might choose to attend workshops run by other members of the department, learn a new framework and give a talk about it or work on a personal project and present it on the amazing Hack Day - from day one you are treated as an integral part of your team. That means that you get your hands dirty on real projects, learning and improving at an incredible pace. Continue reading... ## The 4 best DevSecOps tools for a secure DevOps workflow DevFeed: [The 4 best DevSecOps tools for a secure DevOps workflow]() Original publisher: [Read original article]() Author: Liran Tal Published: 2024-01-23T05:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [DevSecOps](), [DevOps](), [Security](), [CI/CD](), [Deployment]() Tags: [article](), [awareness](), [ci-cd](), [continuous-delivery](), [continuous-deployment](), [continuous-integration](), [deployment](), [devops](), [devrel](), [devsecops](), [megawatt](), [monitoring](), [open-source-security](), [security](), [snyk-platform](), [testing]() ### AI overview This article explains DevSecOps as the integration of security into continuous integration, continuous delivery, and continuous deployment workflows. It describes security activities such as scanning, testing, validation, and monitoring across the development lifecycle, and discusses how suitable tools can improve security, feedback, and delivery efficiency. ### Source excerpt Learn how DevSecOps tools integrate security into your DevOps workflow from deployment to production. ## Standardisation: the merit of consistent patterns DevFeed: [Standardisation: the merit of consistent patterns]() Original publisher: [Read original article]() Author: Max Duval Published: 2023-10-24T10:18:33Z Content type: opinion Language: en Sources: [Guardian]() Topics: [Programming](), [Code](), [CI/CD](), [Pull Request](), [Deployment](), [Documentation]() Tags: [cognitive-load](), [consistency](), [continuous-deployment](), [continuous-integration](), [deployment](), [development](), [documentation](), [engineering](), [programming](), [pull-request]() ### AI overview The article explains how standardised patterns, documentation, code organisation, language learning, testing, code review, and automated deployment help Guardian developers focus on tasks and reduce extraneous cognitive load across complex systems. ### Source excerpt Coming back from a long holiday? Recently joined the department? Collaborating on a complex, cross-team problem that spans different tech stacks and programming languages? At one point, we're all going to find ourselves in one of these situations. So how can we ensure that no one feels overwhelmed or unable to make meaningful contributions? Short answer: by enabling everyone to quickly focus on the task at hand. By "focus" I simply mean deciding what is in scope and what is not. For a company that's been around for more than 200 years, and online for an eighth of that time, a proliferation of systems is bound to happen. No single person is ever going to grasp the complexity in its entirety. Zooming out, we create architectural diagrams to help us understand how the different parts fit together; and zooming in, we write code that requires as little context as necessary. discuss the benefits of standardisation; describe which tools we have created help keep consistency; offer some thoughts on balancing familiarity and innovation. Continue reading... ## End-to-end tests retry strategies DevFeed: [End-to-end tests retry strategies]() Original publisher: [Read original article]() Author: Giuseppe Donati Web Test Automation Engineer Not a stereotypical Italian guy; Except Published: 2023-09-27T00:00:00Z Content type: article Language: en Sources: [Trivago]() Topics: [Testing](), [Test automation](), [GitHub Actions](), [CI/CD](), [Continuous Deployment (CD)](), [Front end](), [web applications]() Tags: [continuous-deployment](), [core](), [feature](), [frontend](), [github-actions](), [pull-requests](), [quality-assurance](), [test-automation](), [tests]() ### AI overview This article describes how trivago's frontend QA team uses different end-to-end test retry strategies in GitHub Actions. It explains unconditional retries for core tests, filtered retries for specific failure causes in extended tests, and manual retries for a subset of scenarios, balancing stable results, pull-request confidence, and feedback speed. ### Source excerpt Why should you retry all tests on failure? Why not? This article will not go into details, listing pros and cons of each approach. There are already enough ## Doximity Mobile Releases Streamlined with Automation DevFeed: [Doximity Mobile Releases Streamlined with Automation]() Original publisher: [Read original article]() Author: Doximity Published: 2023-04-12T14:19:00Z Content type: article Language: en Sources: [Doximity]() Topics: [Automation](), [Mobile](), [releases](), [Deployment]() Tags: [automation](), [continuous-deployment](), [deployment](), [devops](), [efficiency](), [mobile](), [mobile-apps](), [performance](), [production](), [releases](), [versioning]() ### AI overview This article describes how Doximity's mobile team automated its release process to move from a three-week cycle to weekly releases. The team achieved the weekly cadence in November 2021, and weekly releases later required zero developer overhead while QA controlled the process. ### Source excerpt Releasing mobile apps to the store is inherently slower than web updates due to manual process overhead, such as versioning, packaging, and submitting to the App Store for review. While web developers have long enjoyed full buzzword-compliant Continuous Deployment, mobile teams generally use a defined release cadence, typically 2-4 weeks. The DORA metric, which stands for DevOps Research and Assessment, evaluates performance using four key metrics: Deployment Frequency (DF), Lead Time for Changes (LT), Mean Time To Recover (MTTR), and Change Failure Rate (CFR). These metrics are commonly used to gauge an organization's agility, efficiency, and ability to implement changes quickly. Organizations that excel in these areas tend to perform smaller, more frequent deployments. A few years ago, our mobile team was classified as a medium performer for deployment frequency and reported 47% for change rate failure, which should be from 0% to 15%. We knew we could do better. Doximity mobile teams historically used a three-week release cycle. However, the pace wasn't fast enough to quickly get new features out the door. As a result, almost every release would be delayed due to some "very important thing" that had to get in. We also had to do more patch releases to fix issues introduced in production, which were even harder to debug with so many changes in a single version. One of the essential features that forced us to accelerate our release cycle was the Dialer Video product. We launched Dialer Video soon after the beginning of the pandemic. We wanted to get something out and to iterate quickly to meet the needs of our doctors while they were going through a difficult time and learning to work remotely. In April 2020, we attempted to shift to a weekly release cycle to meet this demand. While some automation was in place, there was also a lot of overhead with each release, and the developers spent a significant amount of time just managing the process. We compromised on a two- ## How we deploy the Apollo GraphOS monorepo DevFeed: [How we deploy the Apollo GraphOS monorepo]() Original publisher: [Read original article]() Author: Ryan Wilcox Published: 2023-02-23T11:32:34Z Content type: tutorial Language: en Sources: [Apollo Blog]() Topics: [monorepo](), [CI/CD](), [CircleCI](), [Deployment]() Tags: [circleci](), [continuous-deployment](), [continuous-integration](), [deployment](), [engineering](), [graphos](), [guide](), [monorepo](), [workflow]() ### AI overview Apollo describes how it moved deployment of its Apollo GraphOS monorepo to continuous deployment in its staging environment using CircleCI. The article outlines the workflow triggered when developers push, approve, and merge code, including CircleCI dynamic configuration and change-scope detection. ### Source excerpt Did you know that the majority of Apollo GraphOS's features are shipped via a monorepo? Yes, these mythic beasts still roam the earth. Ours is a humble but temperamental creature that, until recently, required Apollo engineers to do a lot of manual deployment to get the fleet entirely rolled. This year our team undertook the effort to get things continuously deployed to our staging environment using our continuous integration (CI) provider, CircleCI. [Next page]()