# developer velocity Published articles for developer velocity. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Internal Developer Portals: Why Native CI/CD Drives Scale DevFeed: [Internal Developer Portals: Why Native CI/CD Drives Scale]() Original publisher: [Read original article]() Author: Rashmi Hegde Published: 2026-09-08T00:00:00Z Content type: article Language: en Sources: [Harness Blog]() Topics: [Platform Engineering](), [CI/CD](), [developer velocity](), [Automation](), [Scalability]() Tags: [automation](), [ci-cd](), [developer-velocity](), [idp](), [scalability](), [self-service](), [velocity]() ### AI overview This article argues that internal developer portals need native CI/CD integration to move beyond service catalogs and documentation. It explains that integrated pipelines can reduce context switching, support self-service workflows, help enforce standards, and improve developer velocity and scalability. ### Source excerpt Internal developer portals need native CI/CD integration to scale effectively. Learn how integrated pipelines improve velocity. Explore Harness IDP. | Blog ## Continuous Delivery Excellence with Harness IDP DevFeed: [Continuous Delivery Excellence with Harness IDP]() Original publisher: [Read original article]() Author: Rashmi Hegde Published: 2026-08-21T00:00:00Z Content type: article Language: en Sources: [Harness Blog]() Topics: [Continuous Delivery (CD)](), [internal developer portal](), [CI/CD](), [Platform Engineering](), [Deployment](), [Automation](), [Orchestration](), [Provisioning]() Tags: [automation](), [ci-cd](), [continuous-delivery](), [deployment](), [developer-velocity](), [idp](), [internal-developer-portal](), [orchestration](), [platform-engineering](), [provisioning](), [self-service](), [tooling]() ### AI overview This article explains how Harness Internal Developer Portal can support continuous delivery through self-service workflows, standardized deployment pipelines, and unified service catalogs. It argues that delivery friction often comes from cognitive overhead, unclear prerequisites, fragmented permissions and configuration, and insufficiently discoverable workflows rather than a lack of pipeline capability. ### Source excerpt Achieve continuous delivery excellence using Harness Internal Developer Portal. Streamline deployments, boost velocity, and empower developers. Learn more. | Blog ## Whatnot at Snowflake Summit 2026 DevFeed: [Whatnot at Snowflake Summit 2026]() Original publisher: [Read original article]() Author: Whatnot Engineering Published: 2026-08-12T17:54:54Z Content type: article Language: en Sources: [Whatnot Engineering]() Topics: [data](), [datasets](), [Artificial Intelligence](), [developer velocity]() Tags: [ai](), [ai-agent](), [analytics](), [data](), [data-science](), [datasets](), [developer-velocity](), [developers](), [machine-learning]() ### AI overview Whatnot's Data Platform team describes the data platform behind its live marketplace and its use of Snowflake Cortex AI and Semantic Views. The approach grounds AI in governed business definitions and trusted metadata so developers can find datasets and metrics and investigate issues using natural-language questions. ### Source excerpt Earlier this summer, several members of the Whatnot Data Platform team joined Snowflake on stage at Snowflake Summit to share how we're building the data platform behind Whatnot's live marketplace. This post covers what we talked about, why we built it, and future direction. Caption: The Whatnot team were everywhere at the Summit! Snowflake recently published a recap of our sessions, which you can read here: Observability at Scale: Whatnot at Snowflake Summit. Data at Whatnot Every live auction, bid, chat message, purchase, moderation action and recommendation produces data. That translates into billions of events each day powering recommendations, seller analytics, and customer support. For us, data isn't just for internal analysis. We use it to power the product while millions of people are buying and selling in real time. That creates an unique set of engineering challenges. As Whatnot has grown, we've had to evolve our platform to support thousands of datasets, hundreds of developers, and an increasingly diverse set of workloads while maintaining reliability, governance, and developer velocity. At Summit, we talked about the investments we have made to get engineers to vetted data faster Accelerating Builders with AI The Whatnot data platform is a living system. Schemas evolve, pipelines are deployed continuously, business definitions change, and new data products are published every day. Keeping up with that pace of change has become one of the biggest challenges for developers. In our first session, we shared how we're using Snowflake Cortex AI and Semantic Views to make that knowledge more accessible. By grounding AI in governed business definitions and trusted metadata (see this earlier post for more details), builders can ask natural language questions about their data, quickly identify the right datasets and metrics, and investigate issues without manually searching documentation or relying on the Data team. Whatnot's full-time employees now use AI weekly, ## Scaling Kubernetes governance: A platform engineer's guide to Kyverno and CEL DevFeed: [Scaling Kubernetes governance: A platform engineer's guide to Kyverno and CEL]() Original publisher: [Read original article]() Author: Koray Oksay Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Kubernetes](), [Platform Engineering](), [Security](), [developer velocity](), [Containers](), [supply-chain-security](), [YAML](), [opa](), [rego]() Tags: [common-expression-language](), [compliance](), [container-images](), [containers](), [cosign](), [deployment](), [developer-velocity](), [governance](), [hipaa](), [integration](), [kubernetes](), [kyverno](), [pci-dss](), [platform](), [policy](), [security](), [security-policies](), [sigstore](), [soc-2](), [supply-chain-security]() ### AI overview A guide to using Kyverno and its Common Expression Language support for Kubernetes governance. It explains how platform engineering teams can enforce policies, automate resource changes, generate resources, verify image signatures, and maintain security and compliance while preserving developer velocity. ### Source excerpt Kyverno with CEL support provides Policy-as-Code for Kubernetes governance. Enforce security, automate guardrails, and boost developer velocity for platform engineering teams. ## The missing link in developer velocity: Virtual registries and the rise of the Artifact Platform DevFeed: [The missing link in developer velocity: Virtual registries and the rise of the Artifact Platform]() Original publisher: [Read original article]() Author: Adrian Herrera Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Caching](), [CI/CD](), [developer velocity](), [Latency](), [Developer Platform]() Tags: [article](), [caching](), [ci-cd](), [cost](), [developer](), [developer-velocity](), [latency](), [packages](), [performance](), [platform](), [registry](), [saas](), [time]() ### AI overview The article explains how artifact retrieval slows CI/CD pipelines and reduces developer velocity. It presents virtual registries combined with high-performance caching as an acceleration layer that serves artifacts locally, reduces repeated downloads and latency, and lowers cloud egress costs. ### Source excerpt Virtual registries and high-performance caching cut CI/CD artifact download time, reduce egress costs, and boost developer velocity by turning artifact delivery into a core platform capability. ## How Spyne simplified their CDC pipeline with ClickPipes and ClickHouse Cloud DevFeed: [How Spyne simplified their CDC pipeline with ClickPipes and ClickHouse Cloud]() Original publisher: [Read original article]() Author: ClickHouse Published: 2026-06-22T11:37:29Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [schema-evolution](), [Kafka](), [MongoDB](), [MySQL](), [Streaming](), [developer velocity](), [Serverless](), [Cloud](), [real-time](), [DevOps]() Tags: [clickhouse](), [cloud-infrastructure](), [data](), [developer-velocity](), [devops](), [kafka](), [mysql](), [open-source](), [real-time](), [schema-evolution](), [serverless](), [streaming]() ### AI overview Spyne migrated its change data capture pipeline from a self-managed Debezium and Kafka stack to serverless ClickPipes and ClickHouse Cloud. The change reduced table onboarding time from more than 1.5 hours to minutes and automated schema evolution, improving data consistency and developer velocity. ### Source excerpt Spyne cut table onboarding from 1.5+ hours to minutes and eliminated schema drift by migrating their CDC pipeline from a self-managed Debezium/Kafka stack to ClickPipes and ClickHouse Cloud. ## Beyond code generation: rethinking engineering productivity in the age of AI agents DevFeed: [Beyond code generation: rethinking engineering productivity in the age of AI agents]() Original publisher: [Read original article]() Author: Yasmin McDowell,Lawrence Good,Ilya Yakovlev,Andrew Cheung,Binoy Dash,Simran Jumani,Dmitriy Meyerzon,Mark Breitenbach,Ishan Mishra,Kazuaki Okumura Published: 2026-05-28T18:00:00Z Content type: article Language: en Sources: [Dropbox Tech Blog]() Topics: [Artificial Intelligence](), [AI-assisted coding](), [code productivity](), [AI Development](), [Software Engineering](), [ci](), [pull-requests]() Tags: [agents](), [ai](), [ci](), [code-generation](), [code-quality](), [developer-productivity](), [developer-tools](), [developer-velocity](), [productivity](), [pull-requests](), [software-development](), [workflows]() ### AI overview Dropbox describes a shift from AI coding tools that accelerate implementation to agentic systems that execute scoped tasks. The article explains how increased code throughput creates pressure on review, CI, validation, release coordination, and production operations, requiring broader changes to engineering systems and workflows. ### Source excerpt How Dropbox is moving from AI tools that assist engineers to agentic systems that can execute scoped tasks, and how we're building platforms to support those workflows. ## Introducing Nova, our internal platform for coding agents DevFeed: [Introducing Nova, our internal platform for coding agents]() Original publisher: [Read original article]() Author: Yasmin McDowell,Lawrence Good,Ilya Yakovlev,Andrew Cheung,Binoy Dash,Simran Jumani,Dmitriy Meyerzon,Mark Breitenbach,Ishan Mishra,Kazuaki Okumura,Mike White,Kevin Altschuler Published: 2026-05-21T16:00:00Z Content type: article Language: en Sources: [Dropbox Tech Blog]() Topics: [AI-assisted coding](), [Nova](), [AI Development](), [software-development](), [Software Engineering](), [cloud-infrastructure](), [debugging](), [test-coverage]() Tags: [agents](), [ai](), [ai-agents](), [cloud](), [coding](), [debugging](), [developer](), [developer-productivity](), [developer-tools](), [developer-velocity](), [machine-learning](), [nova](), [platform](), [software-development](), [test-coverage](), [workflows]() ### AI overview Dropbox introduces Nova, an internal cloud platform for running coding agents. The platform supports parallel coding sessions and automated workflows across the software development lifecycle, including debugging, dependency updates, test-coverage improvements, and flaky-test fixes. ### Source excerpt Nova lets engineers run multiple coding sessions in parallel and lets internal systems use AI agents as part of automated workflows. ## Managing third-party images at scale DevFeed: [Managing third-party images at scale]() Original publisher: [Read original article]() Published: 2026-04-16T00:00:00Z Content type: article Language: en Sources: [Chainguard: Unchained]() Topics: [container images](), [Security](), [Vulnerabilities](), [cloud-infrastructure](), [code productivity](), [chainguard]() Tags: [appian](), [chainguard](), [chainguard-containers](), [chainguard-images](), [chainguard-os](), [cloud](), [compliance](), [container-image](), [container-images](), [containers](), [dependencies](), [developer-velocity](), [fedramp](), [hardened-images](), [scale](), [security](), [third-party-container-images](), [vulnerabilities]() ### AI overview This article explains how Appian approached managing third-party container images at scale with Chainguard. It describes the operational burden caused by image dependencies, vulnerabilities, maintenance, and compliance requirements, including the ongoing work needed for regulated environments such as FedRAMP. It also estimates that building a complete internal hardened-image program would require a dedicated team of 15 to 20 engineers. ### Source excerpt Learn how companies can scale third-party container image management with Chainguard to reduce risk, cut toil, and accelerate compliance and developer velocity. ## Removing supply chain friction: How PeopleTec improved developer productivity with Chainguard DevFeed: [Removing supply chain friction: How PeopleTec improved developer productivity with Chainguard]() Original publisher: [Read original article]() Published: 2026-04-02T00:00:00Z Content type: article Language: en Sources: [Chainguard: Unchained]() Topics: [Security](), [supply-chain-security](), [chainguard containers](), [Containers](), [code productivity](), [migration]() Tags: [accelerate](), [chainguard](), [chainguard-assemble](), [chainguard-containers](), [chainguard-developer-experience](), [chainguard-migration](), [ci](), [code](), [containers](), [cve-remediation](), [developer](), [developer-velocity](), [migration](), [migration-guides](), [peopletec](), [provenance](), [security](), [supply-chain](), [vulnerability-management]() ### AI overview PeopleTec describes how it used Chainguard Security controls and Chainguard Containers to reduce software supply-chain friction, address vulnerabilities in base images, improve provenance and compliance workflows, and support developer productivity. The approach emphasized early adopters, low-friction migration, and automated policy checks in CI. ### Source excerpt Learn how PeopleTec used Chainguard to reduce security friction, accelerate adoption, and align platform consistency with developer velocity. ## Reducing our monorepo size to improve developer velocity DevFeed: [Reducing our monorepo size to improve developer velocity]() Original publisher: [Read original article]() Author: Yasmin McDowell,Lawrence Good,Ilya Yakovlev,Andrew Cheung,Binoy Dash,Simran Jumani,Dmitriy Meyerzon,Mark Breitenbach,Ishan Mishra,Kazuaki Okumura,Mike White,Kevin Altschuler,Facundo Agriel,Ishan Mishr Published: 2026-03-25T17:00:00Z Content type: article Language: en Sources: [Dropbox Tech Blog]() Topics: [developer velocity](), [Git](), [GitHub](), [ci](), [Back end]() Tags: [ai](), [backend](), [ci](), [developer-velocity](), [developers](), [development](), [git](), [github](), [infrastructure](), [onboarding](), [performance](), [scale](), [storage](), [workflows]() ### AI overview Dropbox reduced its server monorepo from 87GB to 20GB, cutting full-clone time from more than an hour to under 15 minutes. The article explains how repository growth affected developer onboarding, CI pipelines, synchronization systems, and operational risk near GitHub's 100GB limit. ### Source excerpt Monorepos will continue to grow as products evolve, but growth doesn't have to mean friction. ## Weaving Security into the Flow: New Snyk Studio Capabilities Power the AI Security Fabric DevFeed: [Weaving Security into the Flow: New Snyk Studio Capabilities Power the AI Security Fabric]() Original publisher: [Read original article]() Author: Daniel Berman Published: 2026-02-17T05:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Securing AI](), [AI Development](), [Security](), [ai-coding](), [Claude Code](), [Command-line interface](), [pull-requests](), [cursor]() Tags: [ai](), [ai-development](), [ai-security](), [application-security](), [blog](), [claude-code](), [cli](), [code-security](), [cursor](), [developer](), [developer-velocity](), [devsecops](), [enablement](), [interest](), [pmm](), [pull-requests](), [scm](), [security](), [snyk-code](), [snyk-platform](), [supply-chain-security](), [vulnerability-insights](), [workflows]() ### AI overview Snyk Studio announces new capabilities for securing AI-driven development, including streamlined integrations with Gemini CLI and Claude Code, automated remediation that generates pull requests, and enterprise reporting and controls. The update embeds security into developers' existing workflows so AI-assisted code can be secured from the first prompt while supporting developer velocity and governance. ### Source excerpt Snyk Studio is redefining AI development security with new integrations for Gemini CLI and Claude Code, enabling developers to build fast without sacrificing safety. Bridge the gap between developer velocity and governance to ensure your code is secure at inception. ## Introducing automatic, short-lived credentials for Chainguard Libraries for Python DevFeed: [Introducing automatic, short-lived credentials for Chainguard Libraries for Python]() Original publisher: [Read original article]() Published: 2026-01-15T00:00:00Z Content type: article Language: en Sources: [Chainguard: Unchained]() Topics: [chainguard libraries for python](), [chainguard libraries](), [Authentication](), [pip](), [developer velocity](), [Usability]() Tags: [authentication](), [chainguard-libraries](), [chainguard-libraries-for-python](), [chainguard-libraries-python](), [chainguard-packages](), [chainguard-python-containers](), [developer-velocity](), [github-actions](), [pypi](), [python-libraries](), [python-packages](), [secure-python-packages](), [security](), [usability]() ### AI overview Chainguard announces integrated authentication for Chainguard Libraries for Python through a keyring package. The package provides short-lived credentials that refresh automatically, enabling secure pip access without repeatedly creating, copying, or managing long-lived tokens. It supports local development and GitHub Actions environments with assumable identities. ### Source excerpt New integrated authentication for Python Libraries with a keyring: use short-lived credentials for pip installs to stay secure without slowing developers down. ## Build Better Agents With MorphLLM DevFeed: [Build Better Agents With MorphLLM]() Original publisher: [Read original article]() Published: 2025-08-25T00:00:00Z Content type: article Language: en Sources: [The Fly Blog]() Topics: [AI Agent](), [Code](), [developer velocity](), [Tooling]() Tags: [agents](), [ai-agent](), [cdn](), [close-to-users](), [code](), [cost](), [deploy-app-servers](), [developer-velocity](), [docker](), [elixir](), [fly](), [fly-io](), [hallucinations](), [heroku-alternative](), [heroku-competitor](), [hosting](), [i](), [networking](), [postgresql-clusters](), [servers](), [tooling]() ### AI overview The article presents MorphLLM's Morph Fast Apply as a semantic, structure-aware code-editing tool for AI agents. It addresses the inefficiency and unreliability of full-file rewrites by enabling precise, context-aware edits that reduce token use, compute, cost, and time. ### Source excerpt I'm an audiophile, which is a nice way to describe someone who spends their children's college fund on equipment that yields no audible improvement in sound quality. As such, I refused to use wireless headphones for the longest time. The fun thing about wired headphones is when you forget they're on and you stand up, you simultaneously cause irreparable neck injuries and extensive property damage. This eventually prompted me to buy good wireless headphones and, you know what, I break fewer things now. I can also stand up from my desk and not be exposed to the aural horrors of the real world. This is all to say, sometimes you don't know how big a problem is until you solve it. This week, I chatted to the fine people building MorphLLM, which is exactly that kind of solution for AI agent builders. Slow, Wasteful and Expensive AI Code Changes If you're building AI agents that write or edit code, you're probably accepting the following as "the way it is": Your agent needs to correct a single line of code, but rewrites an entire file to do it. Search-and-replace right? It's fragile, breaks formatting, silently fails, or straight up leaves important functions out. The result is slow, inaccurate code changes, excessive token use, and an agent feels incompetent and unreliable. Full file rewrites are context-blind and prone to hallucinations, especially when editing that 3000+ line file that you've been meaning to refactor. And every failure and iteration is wasted compute, wasted money and worst of all, wasted time. Why We Aren't Thinking About This (or why I wasn't) AI workflows are still new to everyone. Best practices are still just opinions and most tooling is focused on model quality, not developer velocity or cost. This is a big part of why we feel that slow, wasteful code edits are just the price of admission for AI-powered development. In reality, these inefficiencies become a real bottleneck for coding agent tools. The hidden tax on every code edit adds up and your ## Faster Pulls, Smarter Builds: Introducing Multi-Layer Chainguard Containers DevFeed: [Faster Pulls, Smarter Builds: Introducing Multi-Layer Chainguard Containers]() Original publisher: [Read original article]() Published: 2025-05-28T00:00:00Z Content type: article Language: en Sources: [Chainguard: Unchained]() Topics: [chainguard containers](), [Containers](), [container images](), [Open Source]() Tags: [chainguard-containers](), [chainguard-images](), [chainguard-os](), [container-images](), [containers](), [developer-velocity](), [efficiency](), [open-source](), [rebuilds](), [speed](), [storage]() ### AI overview Chainguard introduces multi-layer Chainguard Containers with intelligent rebuilds to reduce unnecessary downloads when only small parts of an image change. The update is intended to improve pull times, bandwidth and storage efficiency, and the speed of builds, tests, and deployments. ### Source excerpt Multi-Layer Chainguard Containers with intelligent rebuilds are designed to increase bandwidth and storage efficiency and enable faster pull times. ## Explore engineering solutions from Temporal Replay 2025 speakers DevFeed: [Explore engineering solutions from Temporal Replay 2025 speakers]() Original publisher: [Read original article]() Author: Lauren Bennett Published: 2025-02-13T00:00:00Z Content type: article Language: en Sources: [Temporal Blog]() Topics: [Orchestration](), [Architecture & Design](), [Back end](), [legacy](), [Microservice](), [Resilience](), [Automation](), [developer velocity](), [Tech Debt]() Tags: [2025](), [architecture](), [automation](), [backend](), [community](), [developer-velocity](), [engineering](), [finance](), [legacy](), [microservices](), [orchestration](), [payments](), [php](), [resilience](), [ruby](), [solutions](), [workflow]() ### AI overview Temporal Replay 2025 features engineering talks from Salesforce, Vinted, and Datadog about workflow orchestration, durable execution, modernization, scaling, resilience, and developer velocity. ### Source excerpt Explore engineering solutions for workflow orchestration from Temporal Replay 2025, featuring experts from Salesforce, Vinted, and Datadog. ## Meet BaseHub: Developer Velocity And Efficiency Right Down to The Database DevFeed: [Meet BaseHub: Developer Velocity And Efficiency Right Down to The Database]() Original publisher: [Read original article]() Author: Carlota Soto Published: 2024-09-10T07:12:25Z Content type: article Language: en Sources: [Blog -- Neon Docs]() Topics: [developer velocity](), [Content Management System](), [Databases](), [autoscaling](), [Serverless](), [Supabase](), [Next.js](), [migration]() Tags: [autoscaling](), [case-studies](), [database](), [developer](), [developer-velocity](), [efficiency](), [migration](), [next-js](), [postgres](), [serverless](), [web]() ### AI overview This article profiles BaseHub, a headless CMS focused on fast, collaborative content management and developer-friendly APIs. It explains how the team moved beyond Supabase as production usage grew, seeking autoscaling, more efficient resource usage, and safer database operations. Neon's serverless Postgres architecture is presented as a way to handle variable traffic and reduce the cost of non-production environments. ### Source excerpt "Databases have always been such a pain in terms of the migration flow, backups, scaling, risk of breaking production... In Neon, everything feels easier and much safer to do" Julian Benegas, CEO of BaseHub BaseHub is a new kind of headless CMS, designed to make content managemen... ## Migrating Udemy's Homepage to Micro Frontends DevFeed: [Migrating Udemy's Homepage to Micro Frontends]() Original publisher: [Read original article]() Author: Eugenia Leong Kato Published: 2024-05-01T20:41:02Z Content type: article Language: en Sources: [Udemy Engineering]() Topics: [migration](), [Front end](), [Development](), [Web](), [React](), [modules](), [User Stories](), [Requirements]() Tags: [architecture](), [developer-velocity](), [development](), [frontend](), [micro-frontends](), [migration](), [module](), [react](), [requirements](), [user-stories]() ### AI overview Udemy describes migrating its logged-out homepage from a monolithic architecture to micro frontends. The article covers the migration's motivations, preparation through user stories and requirements, modular team organization, React component reuse, and shared npm packages, with reported improvements in development speed and web performance motivating the architectural change. ### Source excerpt By Eugenia Kato, Anthony Nichols, Sol Zhu, Eyupcan Bodur, Stephen Duke, David Gao, Michael Palisano, Izabela Bulska, Elaine Zhou, Matt Schaefer, Marty Note, Matthew Bise, Chris Nienhuis, Jilles Soeters, Trey Briggs, Seth Hodgson Introduction This blog delves into the migration of Udemy's logged-out homepage from a monolith architecture to a micro frontends architecture, detailing the motivations behind the migration, challenges faced, and the impact on developer velocity and web performance metrics as a result of the migration. Udemy's logged-out homepage is the second most frequently visited destination, following the course landing pages. Our current focus revolves around professional skills development to cater the needs of professionals seeking upskilling and reskilling opportunities. However, the design and content of the logged-out homepage did not align with this focus. As a result, a new homepage was redesigned that aimed to showcase Udemy's range of offerings and emphasize its commitment to professional skills development. Beyond a mere facelift, the redesign presented an opportunity for us to transition the logged-out homepage from a monolith architecture to micro frontend architecture. With the enhanced web performance metrics, especially for international users, and increased development speed demonstrated in the previous blog post, we are motivated to adopt the new frontend architecture. Preparing for the migration We laid the groundwork for the new logged-out homepage by creating a new micro-frontend application, keeping it isolated from other existing frontend applications. This allows for a more streamlined and efficient development process, as React components and pages that are not relevant can be excluded. As a preparatory step for the migration, we broke down each of the homepage modules into user stories. Then, we collaborated with our design and product partners to define clear and concise requirements for each module. This structured approach ## Announcing Monitoring and Organizations DevFeed: [Announcing Monitoring and Organizations]() Original publisher: [Read original article]() Author: Evan Shortiss Published: 2024-04-16T16:10:15Z Content type: release Language: en Sources: [Blog -- Neon Docs]() Topics: [dashboards]() Tags: [autoscaling](), [cache](), [collaboration](), [community](), [compute](), [cpu](), [database](), [developer](), [developer-velocity](), [extensions](), [metrics](), [monitoring](), [performance](), [postgres](), [release](), [serverless](), [storage](), [transactions](), [ui]() ### AI overview Neon announces a monitoring page for its console and Organizations in private preview. The monitoring dashboard exposes Postgres and resource metrics to help teams assess database performance, scaling, and storage usage. ### Source excerpt Neon's serverless Postgres improves developer velocity and allows organizations to ship faster. When using a database for your app, monitoring its performance is crucial. You can do that using Postgres extensions such as pg_stat_statements. However, if you'd rather do it from the... ## Neon: A New Approach to Database Development DevFeed: [Neon: A New Approach to Database Development]() Original publisher: [Read original article]() Author: Nikita Shamgunov Published: 2024-04-15T13:06:18Z Content type: article Language: en Sources: [Blog -- Neon Docs]() Topics: [Databases](), [Database](), [developer velocity](), [Provisioning](), [Developer experience](), [systems]() Tags: [company](), [data](), [database](), [databases](), [developer](), [developer-velocity](), [efficiency](), [github](), [postgres](), [provisioning](), [vercel]() ### AI overview Neon announces general availability of its Postgres-based database platform, describing improvements to its internals and experience scaling to more than 700,000 databases. The article presents Neon as a solution for business-critical workloads that emphasizes database scalability, fast provisioning, branching with copied data, point-in-time restoration, and improved developer velocity. ### Source excerpt Neon is now Generally Available. We've shipped major improvements to Neon internals that, combined with our operating experience scaling up to 700,000+ databases over the past year, give us the confidence that Neon is ready to support your business-critical workloads. If you're b... ## Apollo GraphQL to join Cloud Native Computing Foundation Membership as Silver Sponsor DevFeed: [Apollo GraphQL to join Cloud Native Computing Foundation Membership as Silver Sponsor]() Original publisher: [Read original article]() Author: Jennifer Tyrseck Published: 2024-03-19T09:00:00Z Content type: release Language: en Sources: [Apollo Blog]() Topics: [GraphQL](), [Platform Engineering](), [Cloud Native Ecosystem](), [API](), [GraphOS]() Tags: [announcement](), [api-platform](), [apollo](), [cncf](), [developer-velocity](), [graphos](), [graphql](), [graphql-federation](), [platform-engineering](), [schema]() ### AI overview Apollo GraphQL announced that it is joining the Cloud Native Computing Foundation as a Silver member. The release connects this membership with Apollo's GraphQL-based platform engineering approach, including Apollo GraphOS, supergraphs, and schema change workflows. ### Source excerpt Apollo GraphQL, the creator of GraphQL Federation, today announced its membership with the Cloud Native Computing Foundation (CNCF) as a Silver member. This strategic alliance reinforces Apollo GraphQL's commitment to fostering innovation, enhancing API efficiency, and promoting the importance of GraphQL in platform engineering. ## The Apollo Supergraph Architecture Framework DevFeed: [The Apollo Supergraph Architecture Framework]() Original publisher: [Read original article]() Author: Lucas Leadbetter Published: 2024-01-24T13:00:00Z Content type: article Language: en Sources: [Apollo Blog]() Topics: [GraphQL](), [Architecture & Design](), [developer velocity](), [Security]() Tags: [announcement](), [architecture](), [best-practices](), [developer-velocity](), [graphql](), [high-availability](), [security]() ### AI overview Apollo introduces the Supergraph Architecture Framework (SAF), an assessment based on the Apollo Solutions Architecture team's experience with enterprise organizations. It covers operational excellence, security, reliability, performance, and developer efficiency to help teams evaluate and improve GraphQL supergraphs in production. ### Source excerpt Building a scalable and effective enterprise supergraph is challenging, and often feels like there are countless numbers of ways to approach the challenges that arise without evidence of efficacy. Companies searching the GraphQL community for recommendations leads to a lack of consistency across the industry and doing things that may prove to be ineffective, thus requiring changes later down the line. ## How Nuon rebuilt its API with Temporal Workflows DevFeed: [How Nuon rebuilt its API with Temporal Workflows]() Original publisher: [Read original article]() Author: Justin Pirie Published: 2023-11-22T05:00:00Z Content type: article Language: en Sources: [Temporal Blog]() Topics: [developer velocity](), [API](), [distributed-systems](), [reliability](), [data-architecture]() Tags: [api](), [data-management](), [developer](), [developer-velocity](), [how-to](), [reliability](), [workflows]() ### AI overview A webinar recap describes how Nuon rebuilt its API with Temporal Workflows. The company replicated its existing API in one sprint and put it into production in a second sprint, reporting improved developer velocity, reliability, and operational insights. ### Source excerpt We were joined by Jon Morehouse and Jordan Acosta from Nuon for a webinar last week to share how they completely rebuilt their API using Temporal, the best practices for long-lived workflows, and how Temporal is helpful for startups. ## New report shows disconnect between developers and security teams on software supply chain security priorities and responsibilities DevFeed: [New report shows disconnect between developers and security teams on software supply chain security priorities and responsibilities]() Original publisher: [Read original article]() Published: 2023-11-08T00:00:00Z Content type: release Language: en Sources: [Chainguard: Unchained]() Topics: [supply-chain-security](), [chainguard](), [Security](), [developer velocity](), [Open Source]() Tags: [chainguard](), [ciso](), [container-security](), [developer-velocity](), [developers](), [open-source](), [report](), [security](), [software-developer](), [software-supply-chain](), [software-supply-chain-security](), [software-supply-chain-security-research](), [survey]() ### AI overview Chainguard and The Harris Poll released a 2023 survey of CISOs and developers about software supply chain security. The report found that both groups consider it important but differ in their views of security awareness, responsibilities, tooling, and associated risks. ### Source excerpt Chainguard's new report reveals a crucial gap between developers and security teams on software supply chain priorities. [Next page]()