# workflow automation Published articles for workflow automation. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## n8n Patches 18 Security Vulnerabilities in Bi-Weekly Update DevFeed: [n8n Patches 18 Security Vulnerabilities in Bi-Weekly Update]() Original publisher: [Read original article]() Author: Christian Rakoot Published: 2026-09-06T06:31:02Z Content type: article Language: en Sources: [Self Host Lab]() Topics: [Security](), [Vulnerabilities](), [workflow automation](), [Automation](), [Code](), [Homelab](), [OAuth](), [Regular expression](), [data](), [Git](), [JSON](), [OpenAI]() Tags: [article](), [automation](), [code](), [data](), [external](), [git](), [json](), [n8n](), [n8n-patches-18](), [news](), [oauth](), [openai](), [security](), [self-hosted](), [update](), [vulnerabilities](), [workflow](), [workflow-automation]() ### AI overview n8n's September 2, 2026 bi-weekly security update fixes 18 vulnerabilities: five high-severity and thirteen medium-severity issues. The most serious flaws are two expression-sandbox escapes that can enable arbitrary code execution on self-hosted servers. Other high-severity fixes address denial-of-service, ReDoS, and an OpenAI model-search domain-restriction bypass. ### Source excerpt Read this article in French: n8n corrige 18 failles de sécurité dans sa mise à jour bi-hebdomadaire n8n is one of the most widely deployed self-hosted workflow automation platforms, often described as the fair-code alternative to Zapier and Make. People use it to move data between apps, trigger scripts on a schedule, and glue together [...] ## Build and run Datadog workflows from Bits Chat or AI agents DevFeed: [Build and run Datadog workflows from Bits Chat or AI agents]() Original publisher: [Read original article]() Author: Neha Haresh; Gabriel Margolis; Brianna Wang; David Robert-Ansart Published: 2026-09-03T00:00:00Z Content type: tutorial Language: en Sources: [Datadog | The Monitor blog]() Topics: [AI Bots](), [cursor](), [incident]() Tags: [ai](), [ai-agents](), [ai-coding](), [bits-ai](), [claude-code](), [codex](), [cursor](), [debug](), [incident-management](), [mcp](), [workflow-automation](), [workflows]() ### AI overview Datadog describes using Bits Chat and AI coding agents to create, run, and debug automated workflows with Datadog and development context. ### Source excerpt Build, debug, and run Datadog workflows from Bits Chat and AI coding agents using the operational and development context where you're working. ## Centralize human and agentic work with Datadog Work Management DevFeed: [Centralize human and agentic work with Datadog Work Management]() Original publisher: [Read original article]() Author: Roxanne Moslehi Published: 2026-08-18T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [AI Agent](), [incident](), [site-reliability-engineering](), [Slack](), [SRE](), [SIEM, Security](), [GitHub](), [error tracking](), [dashboards](), [Traces]() Tags: [agentic](), [ai](), [ai-agent](), [cloud-siem](), [dashboards](), [devops](), [devsecops](), [error-tracking](), [github](), [incident](), [management](), [slack](), [sre](), [traces](), [work-management](), [workflow-automation]() ### AI overview Datadog Work Management centralizes work created by people, automations, and Datadog AI agents. It preserves context from logs, traces, monitors, alerts, ownership, assignments, approvals, artifacts, and activity while integrating with Datadog and external collaboration systems. ### Source excerpt Learn how Datadog Work Management helps you coordinate human and AI agent-driven work while preserving context, ownership, and activity across tools. ## How to measure ROI for an enterprise CMS migration DevFeed: [How to measure ROI for an enterprise CMS migration]() Original publisher: [Read original article]() Author: Webflow Team Published: 2026-08-07T00:00:00Z Content type: article Language: en Sources: [Webflow Blog]() Topics: [Content Management System](), [migration](), [workflow automation](), [Web](), [code productivity]() Tags: [analysis](), [article](), [automation](), [business](), [content](), [core-web-vitals](), [developer](), [development](), [efficiency](), [enterprise](), [how-to](), [metrics](), [migration](), [platform](), [productivity](), [strategy](), [tools](), [web](), [workflow](), [workflow-automation]() ### AI overview This article explains how enterprises can measure the return on investment of migrating to a modern content management system. It covers migration costs, expected gains, baseline metrics, operational efficiency, development costs, website performance, and developer productivity. ### Source excerpt Find out how to measure the ROI for your enterprise's CMS migration. Learn about the timeline you can expect and the improvements your team might see. ## Building an Internal Developer Portal for a Serverless Architecture DevFeed: [Building an Internal Developer Portal for a Serverless Architecture]() Original publisher: [Read original article]() Author: Mor Paz Published: 2026-07-30T10:11:28Z Content type: article Language: en Sources: [Developer Experience & Platform Engineering Blog | Port]() Topics: [internal developer portal](), [Serverless](), [sdlc](), [workflow automation](), [Platform Engineering](), [DevOps](), [CI/CD](), [API](), [dora metrics](), [Amazon Simple Queue Service (SQS)](), [incident](), [Security]() Tags: [api](), [automation](), [catalog](), [ci-cd](), [developer-portal](), [devops](), [dora-metrics](), [incident](), [internal-developer-portal](), [platform-engineering](), [security](), [serverless](), [serverless-architecture](), [workflow-automation]() ### AI overview This article explains how an internal developer portal can support software development in a serverless architecture. It describes software catalogs, self-service actions, workflow automation, APIs, and scorecards for improving developer independence, operational decision-making, security responses, and engineering standards. ### Source excerpt This post covers how to set up and use an internal developer portal to support the software development life cycle in a serverless architecture. ## Preparing for OMB M-26-14: How Datadog supports federal logging maturity DevFeed: [Preparing for OMB M-26-14: How Datadog supports federal logging maturity]() Original publisher: [Read original article]() Author: Chris Leffler; Sophie Wang Published: 2026-06-29T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [SIEM, Security, Observability](), [log management](), [Monitoring](), [threat detection](), [incident](), [Incident response](), [observability](), [Security](), [Security Operations Center](), [Resilience](), [Cybersecurity]() Tags: [bits-ai](), [cloud-siem](), [compliance](), [cybersecurity](), [fedramp](), [govcloud](), [incident-response](), [log-management](), [logging](), [monitoring](), [observability](), [resilience](), [security](), [security-operations-center](), [soc](), [systems](), [telemetry](), [threat-detection](), [workflow-automation]() ### AI overview This article explains how OMB Memorandum M-26-14 changes federal logging guidance from prescriptive requirements to a risk- and maturity-based model. It describes continuous event monitoring and threat hunting, investigation, response, and forensics, including centralized security telemetry, visibility across IT, OT, and IoT environments, threat detection, searchable and retrievable logs, cross-source correlation, incident response, and forensic analysis. It also presents Datadog as a unified observability and security platform for helping agencies meet these requirements. ### Source excerpt Learn how Datadog helps federal agencies prepare for OMB M-26-14 by providing centralized telemetry data, threat detection, and automated incident response. ## Ship internal applications from your AI Agent with Datadog Apps DevFeed: [Ship internal applications from your AI Agent with Datadog Apps]() Original publisher: [Read original article]() Author: Barak Shoushan; Addie Beach; Scott Kennedy Published: 2026-06-09T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [AI-assisted coding](), [AI, ML & Data Engineering](), [CI/CD](), [GitHub Actions](), [dashboards](), [cursor]() Tags: [ai](), [ai-agent](), [ai-coding](), [app-builder](), [applications](), [apps](), [ci-cd](), [codex](), [cursor](), [dashboards](), [internal-developer-portal](), [observability](), [react](), [workflow-automation]() ### AI overview Datadog Apps is a preview, code-first way to build internal applications with AI coding agents and run them inside Datadog. It supports existing development workflows, secure platform integrations, governance, observability, and embedding apps across Datadog surfaces. ### Source excerpt Learn how Datadog Apps lets you build and deploy apps from your AI agent directly into Datadog, with built-in governance, observability, and secure integrations. ## Codex is becoming a productivity tool for everyone DevFeed: [Codex is becoming a productivity tool for everyone]() Original publisher: [Read original article]() Published: 2026-06-02T02:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [codex](), [Artificial Intelligence](), [Data analysis](), [workflow automation](), [Automation]() Tags: [ai](), [analysis](), [automation](), [codex](), [content](), [data](), [global-affairs](), [productivity](), [tools](), [work](), [workflow-automation]() ### AI overview OpenAI describes Codex as expanding beyond coding into a productivity tool for knowledge work. The article highlights its use for research, data analysis, workflow automation, content creation, and lightweight tool building, alongside growing adoption among knowledge workers. ### Source excerpt The Next Era of Knowledge Work report explores how Codex is transforming productivity through AI-powered research, data analysis, workflow automation, and content creation. ## How to Sell Figma Plugins and Templates DevFeed: [How to Sell Figma Plugins and Templates]() Original publisher: [Read original article]() Author: Aarthi Poonia Published: 2026-03-28T00:00:00Z Content type: tutorial Language: en Sources: [Dodo Payments Blog]() Topics: [Figma](), [Figma plugins](), [Figma Community](), [API](), [Back end]() Tags: [api](), [backend](), [developer](), [digital-products](), [figma](), [figma-community](), [figma-plugins](), [guide](), [how-to](), [monetization](), [payment](), [payment-processing](), [payments](), [plugin](), [products](), [subscriptions](), [tools](), [ui](), [workflow-automation]() ### AI overview This guide explains how to monetize Figma plugins and templates. It covers license-key sales for plugins, direct file delivery for templates and UI kits, payment processing, subscriptions, pricing, and customer management. ### Source excerpt Complete guide to monetizing Figma plugins and templates. Set up payment processing, license key delivery, and manage subscriptions for your Figma products. ## Two startups at global scale without DevOps DevFeed: [Two startups at global scale without DevOps]() Original publisher: [Read original article]() Author: Ben Sabic Published: 2026-03-19T13:00:00Z Content type: article Language: en Sources: [Vercel News]() Topics: [DevOps](), [Artificial Intelligence](), [Automation](), [workflow automation](), [REST API](), [Vercel]() Tags: [2025](), [ai](), [ai-agents](), [apac](), [australia](), [automation](), [devops](), [infrastructure](), [rest-api](), [vercel](), [workflow-automation]() ### AI overview The article examines how Leonardo.AI and Relevance AI operate at global scale without dedicated DevOps teams. It attributes this model to lean infrastructure, limited DevOps talent in APAC, and automation. Relevance AI uses autonomous agents across business tools and the Vercel REST API to create, test, and deploy web experiences. ### Source excerpt Leonardo.AI processes more than 4.5 million images every day across cities worldwide, and Relevance AI's agents run autonomously across time zones, touching Salesforce, HubSpot, Slack, and dozens of other systems without pause. Neither company has a dedicated DevOps team. That's not an oversight. It's an operational model. The startup ecosystem in APAC is a clear example of why this model is taking hold. AI-native startups are surging across the region: over 1,000 are building in Australia alone, according to the State of Australian Startup Funding Report. Meanwhile, nearly a third of Singapore's new startups last year were focused on AI. Startups can find capital, but not DevOps talent Billions in AI venture capital are flowing into APAC. In Australia alone, more than $1 billion was invested in AI-native startups in 2025. Singapore attracted $8.4 billion, accounting for 75% of the region's total. The money is there. The infrastructure talent is not. A single DevOps engineer in Australia costs $150K+, takes months to close, and that's only if you can find one. Sixty to 80 percent of APAC organizations report difficulty filling IT roles, according to IDC. For a 15-person startup, that math means shortening the runway by three months. Factor in tooling, on-call overhead, and the opportunity cost of pulling engineers off product work, and the true cost extends well beyond the salary line. That's why companies are increasingly deploying on infrastructure that keeps them lean and accelerates their ability to ship. Two Australian startups didn't solve this problem by hiring faster; they solved it by not needing to hire at all. Relevance AI 50,000 agents, zero infrastructure team Relevance AI, based in Sydney, builds a platform that lets sales and marketing teams run AI agents across their existing tools. Their agents run autonomously across systems like Salesforce, HubSpot, and Slack, handling lead qualification, customer support, and outbound workflows. What makes their ## Platform Engineering Extends DevOps by Treating the Internal Developer Platform as a Product DevFeed: [Platform Engineering Extends DevOps by Treating the Internal Developer Platform as a Product]() Original publisher: [Read original article]() Author: Wix Engineering Published: 2025-12-21T09:12:39Z Content type: opinion Language: en Sources: [Wix Engineering]() Topics: [Platform Engineering](), [DevOps](), [internal developer platform](), [Kubernetes](), [workflow automation](), [Deployment Strategies](), [GitHub Actions](), [GitLab](), [networking](), [Security]() Tags: [automation](), [deployment-strategies](), [devops](), [github](), [gitlab](), [internal-developer-platform](), [kubernetes](), [networking](), [pipelines](), [platform-engineering](), [policy](), [workflow-automation]() ### AI overview The article argues that platform engineering is a distinct discipline from DevOps. It focuses on treating an internal developer platform as a product and providing reusable, self-service systems that reduce infrastructure friction and operational complexity for developers. ### Source excerpt Imagine starting your day as a senior engineering manager at a fast growing tech company. You're barely through your first coffee when your phone lights up with a critical ticket. The Kubernetes environments don't match across stages. DevOps is in place. CI/CD, automation, monitoring, on-call rotations. And still, developers spend more time fighting infrastructure than building products. This is the moment many organizations mistakenly try to "add more DevOps." In reality, this is the moment... ## 1 million business customers putting AI to work DevFeed: [1 million business customers putting AI to work]() Original publisher: [Read original article]() Published: 2025-11-05T05:00:00Z Content type: news Language: en Sources: [OpenAI News]() Topics: [OpenAI](), [Artificial Intelligence](), [ChatGPT](), [codex](), [AI-assisted coding](), [Developer Platform](), [workflow automation](), [multimodal](), [GitHub]() Tags: [ai](), [chatgpt](), [code-generation](), [codex](), [company](), [developer-platform](), [github](), [multimodal](), [openai](), [slack](), [workflow-automation]() ### AI overview OpenAI reports that more than 1 million business customers worldwide directly use its business offerings through ChatGPT for Work or its developer platform. The article highlights enterprise adoption across industries and describes growth in ChatGPT for Work, Codex usage, company knowledge, enterprise agents, and multimodal models. ### Source excerpt More than 1 million business customers around the world now use OpenAI. Across healthcare, life sciences, financial services, and more, ChatGPT and our APIs are driving a new era of intelligent, AI-powered work. ## Self-Host Your Own Automation Platform with n8n + Docker DevFeed: [Self-Host Your Own Automation Platform with n8n + Docker]() Original publisher: [Read original article]() Author: Techno Tim Published: 2025-07-11T13:00:00Z Content type: tutorial Language: en Sources: [Techno Tim]() Topics: [n8n](), [Self-hosted](), [Docker](), [Docker Compose](), [.env](), [workflow automation](), [Linux]() Tags: [compose](), [discord](), [docker](), [environment-variables](), [google](), [linux](), [n8n](), [self-hosted](), [tutorial](), [workflow-automation]() ### AI overview A tutorial showing how to self-host n8n on Linux with Docker and Docker Compose. It covers environment configuration with a .env file, persistent volumes, optional Traefik integration, startup verification, and building workflows that connect to external services such as Google Sheets and Discord. ### Source excerpt n8n is a powerful self-hosted workflow automation tool. In this tutorial, I'll show you how to self-host n8n on Linux using Docker. You'll learn how to set up the environment, configure it with a .env file, and build workflows that connect to services like Google Sheets and Discord. We'll start with a simple manual trigger, then create a scheduled workflow, and move on to a more advanced auto... ## Codename One Updates and Developer Questions DevFeed: [Codename One Updates and Developer Questions]() Original publisher: [Read original article]() Author: Shai Almog Published: 2017-03-23T00:00:00Z Content type: article Language: en Sources: [CodeName One]() Topics: [Java](), [Exception](), [Swing](), [releases](), [workflow automation](), [Android]() Tags: [android](), [exception](), [java](), [release](), [workflow-automation]() ### AI overview A Codename One blog post covers upcoming Java API features including exception chaining, Android density changes for newer phones, developer support, app-store upload tooling, workflow automation, and source-image resolution guidance. ### Source excerpt This is our last blog post for the next 2 weeks, during the bootcamp we won't be blogging and won't have Friday releases until April 10th where the blog should return. This comes at a bit of a bad time when there is so much to write! Just yesterday Steve committed many new Java API's features such as support for exception chaining and a lot of other cool features. These should be in the Friday release that we are putting out today.