# feature flags Published articles for feature flags. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Introducing SwiftTweaks DevFeed: [Introducing SwiftTweaks]() Original publisher: [Read original article]() Author: Khan Academy Published: 2016-05-09T22:00:00Z Content type: release Language: en Sources: [Khan Academy]() Topics: [Swift](), [iOS](), [Xcode](), [Objective-C](), [feature flags]() Tags: [code](), [engineering](), [feature](), [feature-flags](), [interface](), [ios](), [mobile](), [news](), [objective-c](), [swift](), [xcode]() ### AI overview Khan Academy introduces SwiftTweaks, a Swift library for adjusting parameters in iOS apps on a device without recompiling. The article explains how to create tweak libraries, use tweak values and bindings, adjust animation settings, and access the runtime interface. ### Source excerpt By Bryan Clark Today, we're releasing SwiftTweaks, a way to adjust your Swift-based iOS app without needing to ... Read more ## How Delphi ships 100 times a day with its Python backend on Vercel DevFeed: [How Delphi ships 100 times a day with its Python backend on Vercel]() Original publisher: [Read original article]() Author: Kevin Sundstrom Published: 2026-09-15T04:00:00Z Content type: article Language: en Sources: [Vercel News]() Topics: [Python](), [Vercel](), [Back end](), [feature flags](), [Amazon Web Services](), [Docker](), [airflow]() Tags: [aws](), [backend](), [docker](), [feature-flags](), [python](), [vercel](), [workflow](), [workflows]() ### AI overview A Vercel case study describes how Delphi rebuilt its Python backend on Vercel after previously using AWS, ECS, Docker Desktop, and local databases. The move gave the team a shared deployment workflow, faster onboarding, and more than 100 production deploys per day, while Vercel Workflows and Queues support long-running work and background jobs. ### Source excerpt Delphi on Vercel 10 engineers with no dedicated infrastructure role Everyone ships code, including product and design 100+ production deploys a day behind feature flags Delphi builds digital minds. They capture what someone has written, recorded, and taught, so anyone can tap that expertise on demand. Delphi is "a destination where you can find and interact with interesting minds," says founding engineer Spencer Schoeben. Nobody has built a digital mind network before, so Delphi figures out what to build by shipping features and watching how people use them. That only works if the product is fast to change. "If we are going to win, we need to have an excellent developer and agentic experience," Spencer says. "Otherwise, we could not adapt to how fast our user's demands change." Delphi's frontend had run on Vercel since day one. "The frontend has always been easy," Spencer says, "but the backend was a nightmare." Six months ago, the team rebuilt its Python backend on Vercel as well. Today the whole team ships to production 100+ times a day. Building a Python backend that's easy to work onThe backend slowed every change Delphi's backend previously ran on AWS, with ECS, Docker Desktop, and local databases. In the earliest days, the setup worked because the team was small and much of the context lived in people's heads. As Delphi grew, that made onboarding slower than the team wanted: getting a new engineer to their first deploy took a full day of environment setup. Delphi could have fixed that without leaving AWS. But fixing it properly would have meant designing and owning the infrastructure themselves, and the team didn't want to own infrastructure at all. "That is not our current goal as a company," Spencer says. After moving the backend to Vercel, new engineers could get to production much faster, with the same deploy workflow the rest of the team used every day. Workflows and Queues made the move possible When Delphi was founded, Vercel Workflows and Vercel Queues ## How to Implement Feature Flags for Safe and Gradual Rollouts DevFeed: [How to Implement Feature Flags for Safe and Gradual Rollouts]() Original publisher: [Read original article]() Author: Abisoye Alli-Balogun Published: 2026-09-14T14:58:55Z Content type: article Language: en Sources: [freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More]() Topics: [feature flags](), [CI/CD](), [Deployment](), [Development](), [Tech Debt](), [Testing]() Tags: [architecture](), [best-practices](), [ci-cd](), [deployment](), [development](), [experimentation](), [feature-flags](), [how-to](), [tech-debt](), [testing]() ### AI overview This article explains how to implement feature flags for safe, gradual rollouts. It covers separating deployment from release, boolean toggles, percentage-based rollouts, user segmentation, experimentation, kill switches, lifecycle management, and common anti-patterns. ### Source excerpt Feature flags are one of the most powerful tools in a team's deployment arsenal. They decouple deployment from release, meaning your CI/CD pipeline can push code to production servers on every merge, ## User Impersonation Can Trigger Analytics, Emails, Webhooks, and Background Jobs as the Wrong User DevFeed: [User Impersonation Can Trigger Analytics, Emails, Webhooks, and Background Jobs as the Wrong User]() Original publisher: [Read original article]() Author: WorkOS Published: 2026-09-11T00:00:00Z Content type: article Language: en Sources: [WorkOS Blog]() Topics: [Authorization](), [systems]() Tags: [analytics](), [authorization](), [automation](), [email](), [feature](), [feature-flags](), [notifications](), [support](), [webhooks]() ### AI overview The article explains that user impersonation is a session-level concern whose downstream effects can inherit the impersonated identity. It inventories risks including analytics, notifications, lifecycle email, chat activity, webhooks, feature flags, caches, and queued jobs, with examples of misleading user communications and unintended email automation. ### Source excerpt The side effects nobody documents: analytics, lifecycle email, feature flags, webhooks, and the background job that runs as the wrong person an hour later. ## Coordinate product launches with Datadog DevFeed: [Coordinate product launches with Datadog]() Original publisher: [Read original article]() Author: Milene Darnis; Adam Virani Published: 2026-09-08T00:00:00Z Content type: tutorial Language: en Sources: [Datadog | The Monitor blog]() Topics: [Instrumentation](), [experiments]() Tags: [ai](), [bits-ai](), [digital-experience-monitoring](), [experimentation](), [experiments](), [feature-flags](), [instrumentation](), [launch](), [product-analytics](), [session-replay]() ### AI overview A tutorial on using Datadog Product Analytics Launches to plan product releases, define measurement questions, create tracking plans, and identify missing events and properties before rollout. ### Source excerpt Learn how to turn a product brief and feature flag into a connected launch workflow for instrumentation, experimentation, QA, and reporting. ## On Rails -- Eddie Galindo & Kagen Hearn: Rate Limiting For Your Customers DevFeed: [On Rails -- Eddie Galindo & Kagen Hearn: Rate Limiting For Your Customers]() Original publisher: [Read original article]() Author: Rails Foundation Published: 2026-09-01T00:00:00Z Content type: article Language: en Sources: [Ruby on Rails: Compress the complexity of modern web apps]() Topics: [App](), [data](), [configuration]() Tags: [app](), [data](), [engineering](), [feature-flags](), [podcast](), [software](), [tooling]() ### AI overview A podcast episode about scaling and operating Ascend's Rails monolith as it serves larger customers, including data-ingestion limits, feature flags versus database configuration, and AI tooling in money-moving software. ### Source excerpt Eddie Galindo is an engineering lead at Ascend and Kagen Hearn is a senior software engineer there, working on a Rails app that helps insurance agencies move and reconcile money. ## Introducing Vercel for Slack DevFeed: [Introducing Vercel for Slack]() Original publisher: [Read original article]() Author: Kevin Corbett Published: 2026-08-19T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Slack](), [Vercel](), [Artificial Intelligence](), [Pull Request](), [ci](), [feature flags](), [configuration]() Tags: [agent](), [ai](), [collaboration](), [enterprise](), [feature-flags](), [features](), [logs](), [metrics](), [pull-request](), [reviews](), [slack](), [vercel](), [work](), [workflow]() ### AI overview Vercel introduces Vercel for Slack, a Public Beta integration for Pro and Enterprise teams. Vercel Agent can join channels, threads, and direct messages, use context from deployments, logs, metrics, code reviews, and pull requests, answer questions, investigate incidents, and propose fixes. Approved plans can also update code or configuration, roll back deployments, manage feature flags, and create tested pull requests without leaving Slack. ### Source excerpt Vercel Agent now works in Slack. Mention it the way you'd pull a teammate into a thread, and it reads the discussion, answers with the context of the platform running your app, and turns the team's decisions into changes you approve. Vercel for Slack is available today in Public Beta for Pro and Enterprise teams. Work starts in conversation. An alert gets noticed in a channel, a fix gets agreed on in a thread, and then someone leaves Slack to do the work. With Vercel Agent, you can tag it in for answers about your infrastructure or hand it the work, all without leaving the conversation. What is Vercel Agent? When we introduced Vercel Agent, we called it an AI teammate for your development workflow. Today it's the first responder for your production apps. When something changes, it investigates your logs, metrics, and deployments, finds the root cause, and proposes a fix, often before anyone's opened a laptop. Give it a PR and it flags the regressions and risky changes that a passing CI run won't show. In Slack, that agent joins the conversation itself. It is a core part of Vercel, so your deployments, build statuses, logs, metrics, code reviews, and PRs are in front of it before you've typed anything. Mention @Vercel in a channel, a thread, or a DM, and it answers like a teammate with every tab already open. And answering is only half of it, because once you know what's wrong, the agent can go fix it: Diagnose issues: Investigate incidents, trace errors to the deploy that caused them, explain a cost spike, and answer questions about your codebase. Code alongside your team: Fix failing builds and CI, review PRs with knowledge of how the code runs in production, and turn a thread's decision into a tested pull request. Operate your projects: Roll back deployments, update configuration, manage feature flags, and resolve unusual usage before it becomes a bill. The agent is read-only by default, and anything that changes code or configuration goes through a plan that you ## Implementing dynamic feature flags with AWS AppConfig on AWS Lambda DevFeed: [Implementing dynamic feature flags with AWS AppConfig on AWS Lambda]() Original publisher: [Read original article]() Author: Daniel Abib Published: 2026-08-14T16:25:51Z Content type: tutorial Language: en Sources: [AWS Compute Blog]() Topics: [AWS Lambda](), [Serverless](), [experiments](), [configuration](), [Latency]() Tags: [a-b-testing](), [advanced-300](), [aws](), [aws-lambda](), [feature](), [feature-flags](), [how-to](), [latency](), [real-time](), [serverless](), [technical-how-to]() ### AI overview A tutorial on implementing dynamic feature flags with AWS AppConfig on AWS Lambda. It explains how feature flags support safe deployments, experiments, gradual rollouts, and changes without redeploying functions, using the AWS AppConfig Lambda extension to cache configuration locally and reduce latency. ### Source excerpt Feature toggles allow you to change application behavior in real time without deploying new code. Learn how to implement dynamic feature flags with AWS AppConfig on AWS Lambda for safe deployments, gradual rollouts, and instant rollback. ## LaunchDarkly is now available on the Vercel Marketplace DevFeed: [LaunchDarkly is now available on the Vercel Marketplace]() Original publisher: [Read original article]() Author: Sam Halstead Published: 2026-08-11T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [feature flags](), [Vercel](), [experiments](), [SDKs]() Tags: [agent](), [experiments](), [feature-flags](), [sdk](), [vercel]() ### AI overview LaunchDarkly is now available through the Vercel Marketplace, providing feature flags with local evaluation, release targeting, experiments, metrics, rollback controls, and Vercel Toolbar management. ### Source excerpt LaunchDarkly is now available on the Vercel Marketplace, allowing you to quickly get started with feature flags without additional setup. You can: Sync flags into Global Config and evaluate them locally Target releases by user, attribute, or segment Run experiments with metrics, and roll back with a kill switch View and override flags from the Vercel Toolbar with the Flags Explorer To get started, run vercel install launchdarkly, add the @flags-sdk/launchdarkly adapter, and declare a flag with the Flags SDK: Using a coding agent? Hand it this prompt: Add LaunchDarkly from the Vercel Marketplace, or read the adapter docs. Read more ## How to Build an A/B Testing Framework for Modern CI/CD Pipelines DevFeed: [How to Build an A/B Testing Framework for Modern CI/CD Pipelines]() Original publisher: [Read original article]() Author: Aaron Newcomb Published: 2026-08-10T00:00:00Z Content type: tutorial Language: en Sources: [Harness Blog]() Topics: [A/B Testing](), [CI/CD](), [CI/CD Pipeline](), [feature flags](), [progressive delivery](), [Monitoring]() Tags: [a-b-testing](), [ci-cd](), [feature-flags](), [how-to](), [monitoring](), [progressive-delivery](), [rollback](), [verification]() ### AI overview This tutorial explains how to integrate A/B testing into CI/CD pipelines using feature flags, progressive delivery, real-time metrics, automated verification, and rollback controls. It argues that deployment should be decoupled from release so teams can validate changes before full rollout. ### Source excerpt Learn how to build an A/B testing framework in your CI/CD pipeline. Accelerate software delivery, reduce risk, and boost innovation. Start now! | Blog ## Blue Green and Canary Deployments Explained DevFeed: [Blue Green and Canary Deployments Explained]() Original publisher: [Read original article]() Author: Pramodh Kumar M Published: 2026-08-09T16:30:08Z Content type: tutorial Language: en Sources: [Kubernetes - KodeKloud Blog | DevOps, Cloud, Kubernetes, AI Tutorials & More]() Topics: [Deployment](), [Software](), [Database]() Tags: [argo-rollouts](), [automation](), [blue-green-and-canary-deployments](), [ci-cd](), [ci-cd-pipeline](), [cloud](), [database](), [deployment](), [deployment-strategies](), [devops](), [dora-change-failure-rate](), [expand-and-contract-migration](), [feature-flags](), [guide](), [kubernetes](), [progressive-delivery](), [release-management](), [rollback](), [rolling-update](), [schema](), [sre](), [traffic-splitting](), [zero-downtime-deployment]() ### AI overview This guide explains blue-green and canary deployment strategies for replacing running software versions. It emphasizes that effective rollback depends on detecting problems with reliable metrics and that database schema changes can limit reversibility. ### Source excerpt Both strategies buy you the same thing, which is a cheap way to be wrong. The mechanism is the easy part, and the two hard parts are noticing you are wrong and dealing with the database. ## Edge Config is now Global Config DevFeed: [Edge Config is now Global Config]() Original publisher: [Read original article]() Author: Luis Meyer Published: 2026-07-29T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [data](), [migration](), [SDKs]() Tags: [data](), [edge](), [feature-flags](), [global](), [migration](), [server](), [update](), [vercel]() ### AI overview Vercel renamed Edge Config to Global Config and introduced a replacement server-side SDK and environment variable. The underlying store is unchanged, while limits have increased and existing projects remain compatible. ### Source excerpt Edge Config is now Global Config. This rename better reflects that it is a globally replicated data store with ~1ms reads in every region, built for the configuration that applications read at runtime, such as feature flags, redirects, and experimentation settings. Global Config stores can now hold up to 1 MB on every plan, and Pro and Enterprise teams can create unlimited stores with more writes per day. The rename also ships with a new server-side SDK, @vercel/global-config, and a new environment variable. What changed Name: Global Config is the new name for Edge Config. The store itself is unchanged. Package: @vercel/global-config replaces @vercel/edge-config as a drop-in replacement. Environment variable: Connecting a Global Config store to a project creates a GLOBAL_CONFIG environment variable instead of EDGE_CONFIG. Limits: Raised on every plan. Pricing is unchanged. What you need to do Existing projects: no action required. Deployments, connected stores, and the EDGE_CONFIG environment variable continue to work. Upgrading proactively is safe. The new SDK reads GLOBAL_CONFIG by default and falls back to EDGE_CONFIG, so it works with stores connected before and after the rename. You can switch packages today without touching your stores. Creating stores and pushing new config values work without upgrading. Neither depends on which SDK version your project uses. Upgrade before connecting new stores to a project. Connecting a store now creates a GLOBAL_CONFIG environment variable, and the legacy SDK only reads EDGE_CONFIG by default. A project still on @vercel/edge-config cannot read a newly connected store. To upgrade, install the new package and update imports: New limits Limit Hobby Pro Enterprise Stores 1 (unchanged) Unlimited (was 3) Unlimited (was 10) Writes 250/month (unchanged) 100/hour (was 480/day) 100/hour (was 480/day) Store size 1 MB (was 8 KB) 1 MB (was 64 KB) 1 MB (was 512 KB) Pricing is unchanged at $3 per 1,000,000 reads and $1 per 100 writes. Se ## How Sandstone grew 40x in 147 days on Vercel DevFeed: [How Sandstone grew 40x in 147 days on Vercel]() Original publisher: [Read original article]() Author: Ben Sabic Published: 2026-07-27T14:00:00Z Content type: article Language: en Sources: [Vercel News]() Topics: [vercel ai sdk](), [AI, ML & Data Engineering](), [SDKs](), [User interface design]() Tags: [accessibility](), [agentic](), [ai](), [feature-flags](), [vercel](), [workflow]() ### AI overview Sandstone describes using Vercel and the AI SDK to automate legal-request data gathering and build agentic legal workflows. The article highlights preview deployments, feature flags, and a rapid accessibility fix as contributors to its operational speed. ### Source excerpt Sandstone on Vercel 1,000+ legal requests managed daily across customer teams 7-app turborepo monorepo deployed seamlessly to multiple Vercel projects Multi-step agentic legal workflows built end-to-end with AI SDK When in-house legal teams get a request from their business, it kicks off a manual process of pulling data from multiple systems. In a typical workflow, lawyers will pull deal details from Salesforce, review past contracts, and chase account teams for missing context, all before they start the legal work itself. Sandstone automates this data gathering process, and centralizes requests into a single platform. When a request is created, Sandstone automatically ingests context from every system, including messaging and email tools. By the time the lawyer sees it, they have all of the information they need to get to work. The founding team includes a McKinsey legal tech veteran, a lawyer-turned-engineer, and cybersecurity founder. At Sandstone, that mix shows up directly in the product: legal professionals work alongside engineers, catching the workflow details and legal nuances that only someone who has practiced law would notice. That is how Sandstone ships fast and correctly for one of the most demanding buyers in enterprise software. That attention to detail has paid off: in less than 6 months after their launch, their revenue grew 40x. Three things made their growth possible on Vercel: Preview deployments fast enough to win enterprise trust An AI layer flexible enough to ship agentic workflows in minutes Secure Compute that makes security a one-sentence answer Vercel deployments turned a Sunday request into a five-minute fix For Sandstone's customers, trust is built on responsiveness, and lawyers are trained to notice small details. Liam Germain, Co-Founder and CTO, puts it simply: when a customer asked for a scrollbar accessibility change on a Sunday, he had it live in production in five minutes. On any other platform, he said that same change would hav ## ITIL vs SRE: why the big clouds went their own way DevFeed: [ITIL vs SRE: why the big clouds went their own way]() Original publisher: [Read original article]() Author: Sridhar Rajarao Published: 2026-07-26T00:00:00Z Content type: opinion Language: en Sources: [Sridhar Rajarao]() Topics: [SRE](), [site-reliability-engineering](), [Development](), [Terraform](), [pulumi](), [Availability](), [feature flags](), [incident]() Tags: [automated](), [aws](), [azure](), [cloud](), [feature-flags](), [gcp](), [human-review](), [hyperscaler](), [incident](), [incident-management](), [infrastructure-as-code](), [itil](), [on-call](), [postmortems](), [pulumi](), [release](), [reliability](), [service-catalog](), [sre](), [terraform]() ### AI overview This opinion article compares ITIL practices with SRE operations at hyperscaler scale. It argues that human change boards, single production instances, developer-to-operations handoffs, documentation-first configuration management, and weekly release windows do not fit environments serving millions of external customers. It describes automated approvals, gradual deployments, service-team ownership, infrastructure as code, continuous release, error budgets, SLOs, and blameless postmortems as alternatives. ### Source excerpt The big clouds don't run ITIL. Five assumptions ITIL makes that break at hyperscaler scale, and what AWS, Azure, GCP, and OCI use instead. ## Safe Database Rollback Starts Before Deployment DevFeed: [Safe Database Rollback Starts Before Deployment]() Original publisher: [Read original article]() Author: Raul Junco Published: 2026-07-25T12:00:54Z Content type: tutorial Language: en Sources: [System Design Classroom]() Topics: [Database](), [Deployment](), [migration](), [feature flags]() Tags: [database](), [deployment](), [feature-flags](), [migrations](), [production](), [recovery](), [rollback](), [schema]() ### AI overview This article explains why rolling back application code does not automatically roll back database schema or production data. It presents backward-compatible schema changes, staged migrations, feature flags, and targeted recovery as ways to prepare for deployment failures and reduce the risk of data loss. ### Source excerpt Learn why safe database rollback starts before deployment, and how backward-compatible schema changes, staged migrations, feature flags, and targeted recovery keep production failures from turning into data loss. ## Building self-healing feature releases with Harness FME metric alerts and Event Relay DevFeed: [Building self-healing feature releases with Harness FME metric alerts and Event Relay]() Original publisher: [Read original article]() Author: Joshua Klein Published: 2026-07-24T00:00:00Z Content type: tutorial Language: en Sources: [Harness Blog]() Topics: [releases](), [feature flags](), [Automation](), [experiments](), [Resilience](), [Monitoring]() Tags: [automation](), [event](), [feature](), [feature-flags](), [metrics](), [monitoring](), [payload](), [pipelines](), [resilience](), [self-healing](), [webhooks]() ### AI overview This tutorial explains how to connect Harness FME metric alerts to Event Relay triggers so a pipeline can automatically mitigate risky feature releases through actions such as killing a feature flag. The pattern separates signal emission, webhook handling, and controlled remediation. ### Source excerpt Learn how to build self-healing feature releases with Harness Feature Management & Experimentation. Connect metric-alert webhooks to Event Relay triggers and au | Blog ## A Step-by-Step Guide to Feature Flag Implementation in CI/CD DevFeed: [A Step-by-Step Guide to Feature Flag Implementation in CI/CD]() Original publisher: [Read original article]() Author: Aaron Newcomb Published: 2026-07-23T00:00:00Z Content type: tutorial Language: en Sources: [Harness Blog]() Topics: [CI/CD](), [feature flags](), [GitOps](), [Automation](), [Microservices](), [Deployment]() Tags: [automation](), [ci-cd](), [deployment](), [feature-flags](), [gitops](), [governance](), [guide](), [microservices](), [pipelines](), [policy-as-code](), [rollback]() ### AI overview A step-by-step tutorial on implementing feature flags in enterprise CI/CD pipelines. It explains how governance, policy as code, GitOps workflows, automation, verification, gradual rollouts, and rollback capabilities can help teams manage releases across many services while maintaining control and compliance. ### Source excerpt Discover how to implement Feature Flags in CI/CD pipelines using governance, automation, and AI-driven delivery. Speed up your releases while keeping them safe. | Blog ## Feature Flag Security in your CI/CD Pipeline DevFeed: [Feature Flag Security in your CI/CD Pipeline]() Original publisher: [Read original article]() Author: Lena Sano Published: 2026-07-22T00:00:00Z Content type: article Language: en Sources: [Harness Blog]() Topics: [feature flags](), [Security](), [CI/CD](), [AI Agent]() Tags: [ai-agent](), [ci-cd](), [cleanup](), [feature](), [feature-flagging](), [feature-flags](), [governance](), [lifecycle](), [local](), [pii](), [privacy](), [remote](), [security]() ### AI overview This article explains security practices for Harness Feature Management and Experimentation. It covers local versus remote feature-flag evaluation, privacy considerations for sensitive user data, governance, automated cleanup, and an AI agent for feature-flag lifecycle management. ### Source excerpt Secure feature flags with Harness FME using local or remote evaluation, automated cleanup, governance, and AI-powered lifecycle management. | Blog ## Software Release Management: A Practical Guide in 2026 DevFeed: [Software Release Management: A Practical Guide in 2026]() Original publisher: [Read original article]() Author: Eric Minick Published: 2026-07-20T00:00:00Z Content type: tutorial Language: en Sources: [Harness Blog]() Topics: [Software](), [releases](), [Development](), [Deployment](), [Testing](), [CI/CD](), [feature flags]() Tags: [best-practices](), [ci-cd](), [deployment](), [feature-flags](), [guide](), [pipelines](), [release](), [release-management](), [rollback](), [software]() ### AI overview A practical guide to software release management, covering how code moves through testing, approval, deployment, monitoring, verification, and rollback. It explains the distinction between deployment and release and discusses feature flags, automated safety gates, and progressive delivery. ### Source excerpt Master software release management best practices. Learn how to reduce risk, speed up release pipelines, and ship faster with confidence in 2026. | Blog ## You don't have a deployment problem. You have a validation problem. DevFeed: [You don't have a deployment problem. You have a validation problem.]() Original publisher: [Read original article]() Author: Arjun Iyer Published: 2026-07-16T17:00:00Z Content type: opinion Language: en Sources: [Kubernetes Overview, News and Trends | The New Stack]() Topics: [Deployment](), [Microservice](), [Architecture & Design](), [feature flags]() Tags: [ai-agents](), [coding-agents](), [deployment](), [feature-flags](), [kubernetes](), [microservices](), [pipelines](), [platform-engineering](), [post-contributed](), [production](), [signadot](), [sponsor-signadot](), [sponsored-post-contributed](), [strategy]() ### AI overview The article argues that organizations often have mature deployment tooling but still release changes in batches because they lack confidence in validating individual service changes against the live versions of their dependencies. It presents validation, rather than deployment mechanics, as the main constraint on independent releases and says coding agents are increasing the volume and opacity of batch changes. ### Source excerpt Ask a platform team about their deployment capabilities, and you will usually hear a genuinely impressive story. Progressive rollouts that The post You don't have a deployment problem. You have a validation problem. appeared first on The New Stack. ## AI Is Writing More Code. Releases Haven't Kept Up DevFeed: [AI Is Writing More Code. Releases Haven't Kept Up]() Original publisher: [Read original article]() Author: Aaron Newcomb Published: 2026-07-14T00:00:00Z Content type: article Language: en Sources: [Harness Blog]() Topics: [releases](), [AI-assisted coding](), [feature flags](), [Deployment]() Tags: [ai](), [ai-coding](), [deployment](), [feature-flags](), [releases]() ### AI overview The article examines findings from the State of AI-Driven Software Releases 2026 report, arguing that AI-generated code is increasing production faster than release processes can handle. It highlights manual code review as a bottleneck, a gap in AI-specific guardrails, and feature flags as a way to separate deployment from release. ### Source excerpt AI is accelerating code creation, but releases are struggling to keep up. Explore key findings from the State of AI-Driven Software Releases 2026 report and how | Blog ## Flags SDK now evaluates flags 10x faster DevFeed: [Flags SDK now evaluates flags 10x faster]() Original publisher: [Read original article]() Author: Dominik Ferber Published: 2026-07-08T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [feature flags](), [SDKs](), [Vercel]() Tags: [documentation](), [feature](), [feature-flags](), [sdk](), [upgrade](), [vercel]() ### AI overview The Flags SDK and Vercel Flags now evaluate multiple feature flags in bulk around 10 times faster. The improvement comes from reducing microtask queue overhead and creating fewer promises, and it increases with the number of flags. ### Source excerpt Flags SDK and Vercel Flags now evaluate multiple feature flags in bulk around 10x faster. Flag evaluation time improved by reducing microtask queue overhead and creating fewer promises. The improvement scales with the number of flags. Use await evaluate([flagA, flagB]) instead of Promise.all([flagA(), flagB()]) to benefit from these optimizations: You can also pass an object to evaluate flags with named keys precompute() automatically benefits from these improvements as well. Upgrade flags and @flags-sdk/vercel to the latest versions to get started. Learn more in the documentation. Read more ## Strategies for Migrating from a Monolith to Microservices DevFeed: [Strategies for Migrating from a Monolith to Microservices]() Original publisher: [Read original article]() Author: Saurabh Dashora Published: 2026-06-23T07:55:12Z Content type: tutorial Language: en Sources: [System Design Codex]() Topics: [Architecture & Design](), [microservices architecture](), [migration](), [legacy systems](), [gateway]() Tags: [api-gateway](), [architecture](), [automated](), [big-bang](), [feature-flags](), [incremental](), [legacy-systems](), [microservices](), [migration](), [monolith](), [parallel](), [rewrite](), [strategies](), [testing]() ### AI overview This tutorial outlines patterns for gradually moving from a monolithic architecture to microservices. It describes the Strangler Fig Pattern, Parallel Run Pattern, and Collaborator Pattern, covering techniques such as API gateways, incremental migration, traffic splitting, feature flags, and automated comparison testing. ### Source excerpt Top Strategies ## How to migrate feature flags without breaking production DevFeed: [How to migrate feature flags without breaking production]() Original publisher: [Read original article]() Author: Anthony Rindone; Ryan Lucht; Natasha Silva Published: 2026-06-23T00:00:00Z Content type: tutorial Language: en Sources: [Datadog | The Monitor blog]() Topics: [migration](), [SDKs]() Tags: [developer-tooling](), [devops](), [feature-flags](), [how-to](), [migration](), [production](), [safety](), [software-delivery](), [sync](), [validation]() ### AI overview A guide to safely migrating feature flags by auditing legacy flags, checking evaluation parity, synchronizing configuration, and validating cutover safety. ### Source excerpt Feature flag migrations have a reputation for stalling. Learn how to structure the process in a few steps: audit legacy flags, validate evaluation parity with shadow mode, and cut over with confidence. [Next page]()