# event driven Published articles for event driven. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Why Kafka retention.ms can delay message deletion DevFeed: [Why Kafka retention.ms can delay message deletion]() Original publisher: [Read original article]() Author: Rogerio Santos Published: 2026-09-16T13:05:06Z Content type: tutorial Language: en Sources: [Red Hat](), [Red Hat Developer]() Topics: [Kafka](), [Apache-Kafka](), [configuration](), [file](), [Event-Streaming]() Tags: [broker](), [configuration](), [diagnose](), [event-driven](), [how-to](), [kafka](), [lifecycle](), [retention](), [storage](), [stream-processing]() ### AI overview This guide explains why Kafka messages can remain readable beyond a topic's retention.ms setting. Kafka deletes closed log segments rather than individual messages, and the active segment and continuous writes can delay removal of older records. ### Source excerpt A customer opened a support case with a deceptively simple complaint: a Kafka topic was configured with a 12-hour retention (retention.ms), yet messages produced on July 24 were still readable 4 days later, on July 28. Nothing was broken. The broker logged no errors. The retention policy was working as designed, but the segment layout and continuous write pattern delayed when the old records could actually be removed. The post Why your Kafka topic ignores retention.ms (and how to fix it) appeared first on Red Hat Developer. ## Spring Office Hours Podcast: S5E23 - Java 27 Release Party with Billy Korando DevFeed: [Spring Office Hours Podcast: S5E23 - Java 27 Release Party with Billy Korando]() Original publisher: [Read original article]() Author: danvega Published: 2026-09-16T00:00:00Z Content type: release Language: en Sources: [Spring]() Topics: [Java](), [java-27](), [JDK 27]() Tags: [batch](), [boot](), [cloud](), [developer](), [ecosystem](), [event-driven](), [java](), [java-27](), [live](), [live-stream](), [microservices](), [podcast](), [reactive](), [release](), [serverless](), [spring](), [web-applications]() ### AI overview A Spring Office Hours podcast episode discusses Java 27 with Billy Korando and highlights related launch updates and selected JDK enhancement proposals. ### Source excerpt Join Dan Vega and DaShaun Carter for the latest updates from the Spring Ecosystem. In this episode, Dan and DaShaun are joined by Kansas City JUG organizer and Java Developer Advocate, Billy Korando. In this episode, we celebrate the release of Java 27. You can participate in our live stream to ask questions or catch the replay on your preferred podcast platform. Show Notes JDK 27 Java 27 Launch Stream JEP 534: Compact Object Headers by Default JEP 523: Make G1 the Default Garbage Collector in All Environments JEP 533: Structured Concurrency (Seventh Preview) JEP 531: Lazy Constants (Third Preview) JEP 536: JFR In-Process Data Redaction Transitioning Java to more frequent security updates Project Babylon S5E22 - Live from KCDC Billy Korando on LinkedIn The show: springofficehours.io - episodes, schedule, community Spring Developer on YouTube - join us live every Monday Dan Vega DaShaun Carter The Spring Blog - the news we cover each week ## This Week in Spring - September 15th, 2026 DevFeed: [This Week in Spring - September 15th, 2026]() Original publisher: [Read original article]() Author: joshlong Published: 2026-09-15T00:00:00Z Content type: article Language: en Sources: [Spring]() Topics: [Spring AI](), [Java](), [Security](), [OAuth 2.0](), [Spring Boot](), [JavaFX](), [IntelliJ IDEA](), [debugging]() Tags: [batch](), [boot](), [cloud](), [debugging](), [event-driven](), [intellij-idea](), [java](), [learn](), [microservices](), [oauth-2-0](), [reactive](), [security](), [serverless](), [spring](), [spring-ai](), [web-applications]() ### AI overview A September 15, 2026 roundup of Spring-related developer content, covering Java memory management, Spring AI chat-memory summarization, JavaFX application security with Spring Security and OAuth 2.0, OAuth 2.1 with Spring Authorization Server, Spring and Gemini video understanding, Java AI libraries, Netflix's Java and Spring story, Spring Batch, and Spring Boot debugging. ### Source excerpt Hi, Spring fans! Welcome to another rip-roarin' installment of This Week in Spring! I'm writing this to you from sun-kissed San Francisco, CA, sipping some coffee and watching the bay from my breakfast nook. What a wonderful day! A wonderful day in which to learn about the latest and greatest in Spring, even! Let's dive right in! I really loved this presentation by Oracle's Ron Pressler on the principles of memory management in Java More Craig Walls Spring AI goodness! Here's a nice recipe on summarizing chat memory Over the last few weeks, I've done some content on securing JavaFX applications with Spring Security and OAuth 2.0. That work has landed, and our friends at JFX-central.com have taken that video and the resulting code and transcribed the content into this lovely tutorial - check it out! I loved this post on securing modern applications with OAuth 2.1 and Spring Authorization Server This is a really cool video on understanding video with Spring and Gemini I just learned about this amazing new Java library called Quixotic.ai (what a name! LOL) that provides all sorts of cool stuff that might make your Java-based AI workloads even better. I wonder if there are amazing integration possibilities for Spring AI, too... In last week's A Bootiful Podcast, I was delighted to sit down and chat with Netflix's Paul Bakker on their Java and Spring story, scaling the system, and more. Huh! There's a new Spring Batch IntelliJ IDEA plugin, but search me for what's new! No release notes. Either way, get it while it's hot! Speaking of Spring Batch, there's a nice post here on scaling to millions of rows with Spring Batch that just dropped Speaking of Spring and IntelliJ, there's a nice article over on Baeldung on debugging Spring Boot-based workloads with the Spring debugger ## Introducing automatic remediation policies with Cloudflare CASB DevFeed: [Introducing automatic remediation policies with Cloudflare CASB]() Original publisher: [Read original article]() Author: Abe Carryl Published: 2026-09-11T13:00:00Z Content type: release Language: en Sources: [Cloudflare Blog]() Topics: [Software as a service](), [Cloudflare One](), [Orchestration](), [Authorization]() Tags: [automation](), [casb](), [cloudflare](), [cloudflare-one](), [event-driven](), [oauth](), [orchestration](), [policy](), [reactive](), [saas](), [security](), [security-operations-center](), [zero-trust]() ### AI overview Cloudflare introduces CASB policies that automatically remediate SaaS security findings, including revoking risky file shares and sending webhooks after a finding is detected. ### Source excerpt Cloudflare CASB policies introduce a native automation engine built directly on the Cloudflare developer platform to remediate SaaS risks automatically. Security teams can now design event-driven logic to revoke risky file shares and send webhooks without manual intervention. ## OpenAI split a voice model's brain. Then one team deleted 23,000 lines of code. DevFeed: [OpenAI split a voice model's brain. Then one team deleted 23,000 lines of code.]() Original publisher: [Read original article]() Author: Amanda Caswell Published: 2026-09-10T20:08:18Z Content type: news Language: en Sources: [The New Stack]() Topics: [Artificial Intelligence]() Tags: [agent](), [agents](), [ai-agents](), [ai-engineering](), [api](), [architecture](), [backend](), [benchmark](), [code](), [event-driven](), [gpt](), [large-language-models](), [openai]() ### AI overview OpenAI launched GPT-Live-1 in its API to give outside developers a full-duplex voice model that can manage live conversation while delegating heavier processing to other backend models. The article describes its interruption handling, conversational filler during handoffs, event-driven delegation, and reported benchmark results. ### Source excerpt Building an AI voice agent has always been clunkier than it seems. Most voice agents are really a chain of The post OpenAI split a voice model's brain. Then one team deleted 23,000 lines of code. appeared first on The New Stack. ## A Bootiful Podcast: Netflix's Paul Bakker DevFeed: [A Bootiful Podcast: Netflix's Paul Bakker]() Original publisher: [Read original article]() Author: joshlong Published: 2026-09-10T00:00:00Z Content type: article Language: en Sources: [Spring]() Topics: [Concurrency](), [Concurrent Programming](), [Tooling]() Tags: [ai](), [batch](), [boot](), [cloud](), [complexity](), [concurrency](), [event-driven](), [java](), [microservices](), [netflix](), [podcast](), [reactive](), [serverless](), [spring](), [tooling](), [web-applications]() ### AI overview A podcast interview with Netflix's Paul Bakker on scaling Java, adopting newer JDKs to reduce costs, and using virtual threads and structured concurrency instead of reactive complexity. It also previews AI-powered tooling and Project Valhalla's future. ### Source excerpt Hi, Spring fans! This week's interview is a must-watch if you care about where Java is headed next. This week, I talk to Netflix's Paull Bakker! We dig into Netflix's real-world playbook for scaling Java, cutting costs with newer JDKs, and replacing reactive complexity with virtual threads and structured concurrency. Plus, there's a sneak peek at the exciting future of Java, from AI-powered tooling to the upcoming Valhalla era. ## Announcing 90-minute function timeout on AWS Lambda Managed Instances DevFeed: [Announcing 90-minute function timeout on AWS Lambda Managed Instances]() Original publisher: [Read original article]() Author: Tarun Rai Madan Published: 2026-09-09T19:08:14Z Content type: release Language: en Sources: [AWS Compute Blog]() Topics: [data-processing](), [Transcodings](), [Amazon EC2]() Tags: [ai-inference](), [announcements](), [aws](), [aws-lambda](), [batch](), [data-processing](), [event](), [event-driven](), [foundational-100](), [serverless]() ### AI overview AWS Lambda Managed Instances now support a 90-minute timeout for asynchronous and event source mapping invocations, increasing the previous 15-minute limit by six times. The update targets longer-running data processing, media transcoding, AI inference, and batch workloads. ### Source excerpt AWS Lambda now supports a 90-minute function timeout for asynchronous and event source mapping (ESM) invocations on Lambda Managed Instances, a 6x increase from the previous 15-minute limit. Data processing, media transcoding, AI inference, and batch workloads can now run on Lambda without re-architecting. ## Spring Tools 5.4.0 released DevFeed: [Spring Tools 5.4.0 released]() Original publisher: [Read original article]() Author: martinlippert Published: 2026-09-09T00:00:00Z Content type: release Language: en Sources: [Spring]() Topics: [releases](), [Claude](), [Model Context Protocol](), [Visual Studio Code]() Tags: [batch](), [boot](), [claude](), [claude-code](), [cloud](), [event-driven](), [java](), [mcp](), [microservices](), [performance](), [reactive](), [release](), [release-notes](), [serverless](), [spring](), [tools](), [updates](), [validation](), [web-applications]() ### AI overview Spring Tools 5.4.0 has been released for several development environments, with new validations and quick fixes, Claude Code and MCP enhancements, and stability and performance improvements. ### Source excerpt On behalf of the team and everyone who has contributed, I am pleased to announce the 5.4.0 release of the Spring Tools for Visual Studio Code, Cursor, Eclipse, Theia - and Claude Code. Hightlights New Validations & Quick Fixes: Added validations and quick fixes to convert to @ApplicationModuleListener, @SpringJUnitConfig, @RestController, and specific @Scope annotations Claude Code / MCP Enhancements: Enabled the Claude Code plugin to render a project's logical structure Stability & Performance: Significant speedups around various quick fixes and repository-based version validation + improved reliability while indexing source code Updates to the Spring Tools for Eclipse distribution updated to the latest Eclipse 2026-09 release (new and noteworthy) Detailed changes can be found in the release notes: https://github.com/spring-projects/spring-tools/releases/tag/5.4.0.RELEASE Downloads To download the distribution for Eclipse and find links to the marketplace entries for Visual Studio Code, Cursor, and Theia, please go visit: Spring Tools: https://spring.io/tools/ Next up is the 5.5.0 release, currently scheduled for mid December 2026. ## Spring Office Hours Podcast: S5E22 - Live from KCDC DevFeed: [Spring Office Hours Podcast: S5E22 - Live from KCDC]() Original publisher: [Read original article]() Author: danvega Published: 2026-09-09T00:00:00Z Content type: article Language: en Sources: [Spring]() Topics: [Spring AI](), [Java](), [JDK 27]() Tags: [ai](), [batch](), [boot](), [cloud](), [conference](), [event-driven](), [events](), [java](), [jdk-27](), [live-stream](), [microservices](), [podcast](), [reactive](), [serverless](), [spring](), [web-applications]() ### AI overview Spring Office Hours Podcast episode S5E22 features Dan Vega and DaShaun Carter broadcasting from the Kansas City Developer Conference, with conference highlights, attendee and speaker conversations, and news from the Spring and Java ecosystems. ### Source excerpt Join Dan Vega and DaShaun Carter for the latest updates from the Spring Ecosystem. In this episode, Dan and DaShaun broadcast live from the Kansas City Developer Conference, one of the largest community driven developer events in the country. Expect conference highlights, hallway track conversations with speakers and attendees, and the latest news from the Spring and Java worlds. You can participate in our live stream to ask questions or catch the replay on your preferred podcast platform. Show Notes KCDC Spring AI Recipes Spring Modulith Spring AI Community Project Babylon JDK 27 The show: springofficehours.io - episodes, schedule, community Spring Developer on YouTube - join us live every Monday Dan Vega DaShaun Carter The Spring Blog - the news we cover each week ## This Week in Spring - September 8th, 2026 DevFeed: [This Week in Spring - September 8th, 2026]() Original publisher: [Read original article]() Author: joshlong Published: 2026-09-08T00:00:00Z Content type: article Language: en Sources: [Spring]() Topics: [Artificial Intelligence](), [Large Language Model](), [Electron](), [App](), [IntelliJ IDEA]() Tags: [ai](), [applications](), [article](), [batch](), [boot](), [cloud](), [event-driven](), [idea](), [intellij](), [intellij-idea](), [java](), [linux](), [llm](), [llms](), [microservices](), [oauth](), [reactive](), [serverless](), [spring](), [spring-ai](), [spring-boot](), [video](), [web-applications](), [windows]() ### AI overview This weekly Spring roundup highlights Spring AI content about running LLMs in the JVM and locally, building a Spring AI starter for agents.md, and improving tool use. It also covers Spring Boot and JavaFX desktop applications, native images, Spring Security OAuth clients, secure application images, external configuration, Spring Cloud AWS, and a Spring Boot Analyzer. ### Source excerpt Bonjour a tout le monde! Welcome to another rip-roarin' installment of This Week in Spring! It's a fabulous and fun day here in Paris, France, as I wait to board the train to Amsterdam for the IntelliJ IDEA conference! It's going to be amazing. We've got another incredible week's roundup to dive into, so let's do it! I feel like some of the best content over the past several months in this weekly roundup has been Craig Walls' Spring AI Recipes section. Fantastic stuff! This latest one looks at running an LLM in-JVM This is a nice article on using vertical slices in Spring Boot on Solodev.sk, by Dominik. Well done! Another amazing installment from Craig Walls, this one looking at running against local LLMs My friend and colleague DaShaun Carter talks about his Spring AI starter for agents.md Craig also has this lovely post on efficient tool use in Spring AI Last week, I did two videos on using Spring Boot, JavaFX, GraalVM native images, and Spring Security (and PKCE) to build native, lightning-fast, dynamic, efficient, reusable desktop applications that run well on Mac, Windows, and Linux, and look amazing, while taking small fractions of the RAM of a similar Electron-based application. Here's the first one, showing how to use Spring Boot and JavaFX together, so that you get the component model, event dispatch subsystem, internationalization, lifecycle management, and, of course, the entire and very rich ecosystem of Spring components and can use them to manage JavaFX components, too. We also look at native image compilation. Here's the second video, which looks at using Spring Security's OAuth client in the context of a desktop application, which can not, by definition, hold a client secret. In last week's installment of A Bootiful Podcast, I was delighted to chat with BellSoft's Catherine Edelveis about trusted and secure images for your Spring Boot applications This is a nice post on managing external configurations with Spring Cloud Config A nice recap of some of ## Five Years of Kafka at Razorpay's UPI Switch DevFeed: [Five Years of Kafka at Razorpay's UPI Switch]() Original publisher: [Read original article]() Author: Kshitij Nawandar Published: 2026-09-07T09:09:58Z Content type: article Language: en Sources: [Razorpay Engineering - Medium]() Topics: [Kafka](), [Architecture & Design](), [event driven](), [Amazon Simple Queue Service (SQS)](), [distributed-systems](), [Microservices](), [Amazon Web Services]() Tags: [aws](), [aws-sns](), [distributed-systems](), [event-driven](), [kafka](), [microservices](), [razorpay](), [redshift](), [sns](), [sqs]() ### AI overview Razorpay describes five years of evolution in its UPI Switch, from a monolith using AWS SQS to Kafka-based infrastructure. The article covers architectural decisions, operational challenges, and optimization work affecting payment-processing performance, reliability, and scale. ### Source excerpt Preface The UPI Switch at Razorpay has evolved significantly in the five years since we started building it. The Switch is the platform that enables real-time payment processing with NPCI. When the team began, it was little more than an idea. Today it powers more than 70% of Razorpay's total UPI volume. Because UPI is inherently asynchronous, a messaging system sits at the heart of the Switch and has a direct impact on performance, reliability, and scale. What began as a straightforward queue became the core of the system, shaping how every new feature was designed and delivered. This post covers that evolution: the decisions that enabled growth, the ones that slowed us down, the operational issues that forced us to rethink our assumptions, and the optimizations that ultimately stabilized our Kafka-based infrastructure. This is the story of what we got right, what we got wrong, and how we eventually built something stable enough to grow on. The First Version: Monolith and SQS When we began building the UPI Switch, we weren't thinking about massive scale, distributed systems, or elegant event routing. So we built Switch v1 as a monolith. No microservices, no distributed orchestration: just one solid block of code doing everything. That was the right call. We needed to move fast, experiment, and learn, and we followed the Keep It Simple, Stupid (KISS) principle deliberately. For messaging, we picked AWS SQS: reliable, managed, and low on cognitive load. We didn't need ordering guarantees at the time, so a standard queue worked fine. We started with just two queues, and this setup held its ground. It handled a peak of 400 TPS during the IPL. The limitations showed up as the ecosystem grew. A single event, like a successful payment, needed to fan out into multiple workflows: Update NPCI with an API call Send callbacks to merchants about payment status Push structured data into our warehouse (AWS Redshift) To handle this, we started bolting on AWS SNS plus SQS for fan-ou ## A Bootiful Podcast: BellSoft's Catherine Edelveis on hardened runtime images, container security, and more DevFeed: [A Bootiful Podcast: BellSoft's Catherine Edelveis on hardened runtime images, container security, and more]() Original publisher: [Read original article]() Author: joshlong Published: 2026-09-03T00:00:00Z Content type: article Language: en Sources: [Spring]() Topics: [container-security]() Tags: [batch](), [boot](), [cloud](), [container-security](), [event-driven](), [java](), [microservices](), [podcast](), [reactive](), [security](), [serverless](), [spring](), [spring-boot](), [web-applications]() ### AI overview A podcast conversation about using buildpacks and hardened images to ship Spring Boot applications with stronger security, cleaner defaults, and less Dockerfile work. ### Source excerpt Hi, Spring fans! I chat with BellSoft's Catherine Edelweiss about using buildpacks and hardened images to ship Spring Boot apps with stronger security, cleaner defaults, and far less Dockerfile pain. #BellSoft #Docker #Java #JRE #SpringBoot ## Hybrid cloud orchestration: Modernizing on-premises infrastructure management with AWS DevFeed: [Hybrid cloud orchestration: Modernizing on-premises infrastructure management with AWS]() Original publisher: [Read original article]() Author: Sandeep Singh Published: 2026-09-01T14:01:10Z Content type: tutorial Language: en Sources: [AWS Architecture Blog]() Topics: [Orchestration](), [Kubernetes](), [Amazon EKS](), [AWS Lambda](), [Server](), [Hardware]() Tags: [amazon-dynamodb](), [amazon-eks](), [aws](), [aws-lambda](), [aws-step-functions](), [data-centers](), [deployment](), [event-driven](), [hardware](), [kubernetes](), [observability](), [orchestration](), [server](), [serverless](), [thought-leadership]() ### AI overview Tutorial on designing an AWS-based hybrid cloud orchestration system for centralized lifecycle management of distributed on-premises servers and EKS Anywhere clusters. ### Source excerpt Learn how to build a hybrid cloud orchestration solution that manages distributed on-premises infrastructure at scale using AWS serverless technologies and Amazon EKS Anywhere. Part 1 covers the core event-driven architecture patterns for automating server lifecycle and cluster management across hundreds of sites. ## Human judgment doesn't leave the software factory. It relocates. DevFeed: [Human judgment doesn't leave the software factory. It relocates.]() Original publisher: [Read original article]() Author: Addy Osmani Published: 2026-08-21T14:31:12Z Content type: article Language: en Sources: [Elevate]() Topics: [Software](), [Testing](), [event driven](), [Architecture & Design](), [GitHub](), [pull-requests](), [mutation-testing](), [Security]() Tags: [agent](), [architecture](), [claude-code](), [codex](), [event-driven](), [github](), [mutation-testing](), [pull-requests](), [quality](), [security](), [software](), [testing]() ### AI overview This field guide explains how to build a repeatable software factory while preserving human judgment and ownership. It recommends human involvement in product intent, system design, quality standards, code review, and merge decisions, supported by automated checks and deliberate experimentation. The article argues that a factory is most useful when work must be repeatable and event-driven across queues such as GitHub issues, Slack, Linear, or a backlog. ### Source excerpt A field guide to building a software factory that still has an owner. ## Human judgment doesn't leave the software factory. It relocates. DevFeed: [Human judgment doesn't leave the software factory. It relocates.]() Original publisher: [Read original article]() Author: Addy Osmani Published: 2026-08-21T00:00:00Z Content type: article Language: en Sources: [Addy Osmani]() Topics: [Software](), [coding](), [event driven](), [implementation](), [GitHub](), [Claude Code](), [codex]() Tags: [agent](), [architecture](), [automated](), [batch](), [build](), [claude-code](), [codex](), [event-driven](), [github](), [linear](), [maintainability](), [mutation-testing](), [pull-requests](), [quality](), [scanners](), [slack](), [software](), [testing](), [verification]() ### AI overview A field guide to building a repeatable software factory while keeping humans responsible for product intent, system design, quality standards, code review, and final merge decisions. It recommends early and continuous quality checks, deliberate constraints, and event-driven automation when ordinary coding workflows are no longer sufficient. ### Source excerpt A field guide to building a software factory that still has an owner. ## Data pipeline monitoring 101: Tracking health and performance across the data stack DevFeed: [Data pipeline monitoring 101: Tracking health and performance across the data stack]() Original publisher: [Read original article]() Author: Aaron Kaplan; Ryan Warrier Published: 2026-08-14T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [Monitoring](), [data observability](), [observability](), [data](), [data streams monitoring](), [Kafka](), [Apache Spark](), [event driven](), [Streaming]() Tags: [ai-ml](), [analytics](), [data](), [data-analytics](), [data-engineering](), [data-observability](), [data-streams-monitoring](), [event-driven](), [kafka](), [learn](), [monitoring](), [observability](), [performance](), [spark](), [streaming]() ### AI overview This article introduces end-to-end monitoring for modern data pipelines. It explains how to track pipeline health, performance, data quality, and availability across varied architectures and technology layers, with examples including Kafka, Flink, Apache Spark, data lakes, warehouses, and lakehouses. ### Source excerpt Learn about monitoring the end-to-end health and performance of modern data pipelines. ## Fresh context: change data capture, not batch ETL DevFeed: [Fresh context: change data capture, not batch ETL]() Original publisher: [Read original article]() Author: Simran Regmi Published: 2026-08-12T00:00:00Z Content type: tutorial Language: en Sources: [Redis Blog]() Topics: [event driven](), [data](), [Database](), [PostgreSQL]() Tags: [agent](), [applications](), [batch](), [canada](), [customer](), [data](), [database](), [event](), [event-driven](), [events](), [guide](), [postgresql](), [systems](), [tech-de]() ### AI overview This guide explains how change data capture (CDC) keeps agent context current by forwarding database inserts, updates, and deletes as events. It contrasts CDC with nightly batch ETL, which can leave agents using stale policies or pricing, and describes log-based, trigger-based, and polling approaches. ### Source excerpt In many systems, the reason an agent quotes yesterday's data isn't the model. It's the pipeline behind it: a nightly ETL job that refreshed the agent's context hours ago. Change data capture (CDC) can shrink that staleness window from hours to seconds... ## We turned off Pub/Sub and nobody noticed DevFeed: [We turned off Pub/Sub and nobody noticed]() Original publisher: [Read original article]() Author: Patrick Hamann; Mike Fisher Published: 2026-08-11T13:56:40Z Content type: article Language: en Sources: [The incident.io Blog]() Topics: [event driven](), [Messaging](), [Publish-subscribe pattern](), [Availability](), [systems](), [Apache Pulsar](), [Cloud](), [Google]() Tags: [availability](), [broker](), [cloud](), [event-driven](), [incident](), [incident-channel](), [incident-management](), [incident-response](), [messaging](), [outage](), [post-mortem](), [production](), [scale](), [slack](), [slack-incident]() ### AI overview This developer article explains how incident.io made its predominantly event-driven platform more resilient by adding a secondary message broker alongside Google Cloud Pub/Sub. It describes the role of message brokers and publish-subscribe processing, the risks of a single point of failure, and the successful production test in which Pub/Sub was turned off without affecting customers. ### Source excerpt Our entire event-driven platform ran through a single message broker, which made it a single point of failure. So we added a second one. This is the story of building an event load balancer, the queuing theory behind it, and the final chaos test where we turned off Pub/Sub in production and nobody noticed. ## Low-latency, high-throughput SQS event processing with AWS Lambda provisioned mode DevFeed: [Low-latency, high-throughput SQS event processing with AWS Lambda provisioned mode]() Original publisher: [Read original article]() Author: Ben Freiberg Published: 2026-08-10T13:42:03Z Content type: article Language: en Sources: [AWS Compute Blog]() Topics: [Amazon Simple Queue Service (SQS)](), [AWS Lambda](), [Latency](), [Low Latency](), [Amazon Web Services](), [Concurrency](), [Kafka](), [Internet of things](), [telemetry]() Tags: [amazon-simple-queue-service-sqs](), [amazon-sqs](), [apache-kafka](), [aws](), [aws-lambda](), [concurrency](), [event-driven](), [flash](), [fraud](), [kafka](), [latency](), [low-latency](), [payment-processing](), [real-time](), [telemetry]() ### AI overview AWS explains how provisioned mode for Amazon SQS event source mappings with AWS Lambda provides explicit control over event pollers to support low-latency, high-throughput event processing. The article describes default and provisioned scaling, concurrency limits, throughput, and use cases including real-time payments, fraud detection, IoT telemetry, and flash-sale order fulfillment. ### Source excerpt Customers building event-driven applications on AWS rely on Amazon Simple Queue Service (Amazon SQS) and AWS Lambda event source mappings (ESMs) to process millions of events every day. The fully managed polling infrastructure of ESMs eliminates the need to write and maintain custom code. You can focus on business logic while Lambda handles scaling, batching, [...] ## Continuous Offensive Security & AI Pentesting: 20 FAQs DevFeed: [Continuous Offensive Security & AI Pentesting: 20 FAQs]() Original publisher: [Read original article]() Author: Snyk Team Published: 2026-08-05T04:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Application Security]() Tags: [agentic](), [agents](), [ai](), [ai-agents](), [apis](), [application-security](), [awareness](), [blog](), [cos](), [event-driven](), [security](), [snyk-platform](), [testing](), [validation](), [vulnerability]() ### AI overview An FAQ-style article on continuous offensive security, combining recurring and event-driven testing with DAST, AI penetration testing, and AI red teaming to identify and validate application risk as applications change. ### Source excerpt Get answers to 20 common questions about continuous offensive security, AI penetration testing, DAST, and AI red teaming. ## Worth Reading 080126 DevFeed: [Worth Reading 080126]() Original publisher: [Read original article]() Author: Russ Published: 2026-08-01T13:09:17Z Content type: article Language: en Sources: [rule 11 reader]() Topics: [DevOps](), [End-to-End Encryption](), [BGP](), [Encryption](), [Internet](), [Latency](), [Cloud](), [cloud-infrastructure](), [Databases](), [event driven](), [Artificial Intelligence]() Tags: [ai](), [article](), [bgp](), [cloud](), [databases](), [devops](), [encryption](), [event-driven](), [internet](), [latency](), [software](), [storage](), [systems](), [worth-reading]() ### AI overview A curated "Worth Reading" roundup covering goodput and latency targets, the efficiency costs of Big AI, internet infrastructure and BGP's ORIGIN attribute, and current debates over end-to-end encryption. ### Source excerpt The honest target is goodput, meaning requests per second that actually met your latency targets. Count anything else and you are counting cold plates. I find it strange that as a software industry, we put in so much effort to make our systems efficient to design, build, and scale with DevOps practices, cloud native architectures, event-driven functions, optimized databases and storage, and resource-sipping Lean IT -- then we threw it all out the window when Big AI came along. If there is one universal law in internet infrastructure, it is that no good intention goes unpunished by the practical realities of legacy software maintenance. This Article updates and expands on 2012 research on encryption and globalization, analyzing what the authors call "Round 3" of the Going Dark Debate: the current controversies over end-to-end encryption (E2EE). Using our unique position on the Internet, we took an investigative look at one of the well-known mandatory attributes in BGP, the ORIGIN attribute. ## Product release notes - May 2026 DevFeed: [Product release notes - May 2026]() Original publisher: [Read original article]() Author: Etay Alony Published: 2026-07-30T10:06:41Z Content type: release Language: en Sources: [Developer Experience & Platform Engineering Blog | Port]() Topics: [Release notes](), [event driven](), [Claude Code](), [configuration](), [Code]() Tags: [2026](), [agentic](), [claude-code](), [code](), [community](), [configuration](), [copilot](), [event-driven](), [model](), [plugin](), [product](), [product-release](), [release](), [ui](), [workflows]() ### AI overview Port's May 2026 release adds a public plugins repository, multiple workflow triggers and placement controls, Claude Code and Copilot integrations, organization-aware browser sessions, and an opt-in sidebar layout. ### Source excerpt May extends what teams can build on Port: a public plugins repo opens the ecosystem to community use and contribution, Workflows gain multiple triggers and richer placement controls, and two new integrations bring Claude Code and Copilot activity directly into Port. ## How to Connect Prometheus Alerts to an Event-Driven AI Agent for Initial Investigation DevFeed: [How to Connect Prometheus Alerts to an Event-Driven AI Agent for Initial Investigation]() Original publisher: [Read original article]() Author: Pramodh Kumar M Published: 2026-07-23T15:00:31Z Content type: tutorial Language: en Sources: [Kubernetes - KodeKloud Blog | DevOps, Cloud, Kubernetes, AI Tutorials & More]() Topics: [AI Agent](), [Prometheus](), [event driven](), [Kubernetes](), [Slack](), [Deployment]() Tags: [agents](), [ai](), [ai-agents](), [aiops](), [alert-fatigue](), [alert-manager](), [alert-triage](), [architecture](), [auto-remediation](), [automated-incident-response](), [automation](), [devaiops](), [event-driven](), [event-driven-ai-agents-with-prometheus-alerts](), [guide](), [how-to](), [kubernetes](), [kubernetes-ai-agent](), [prometheus](), [prometheus-alert-rules](), [prometheus-alertmanager-webhook](), [root-cause-analysis](), [slack](), [sre](), [sre-automation]() ### AI overview This guide explains how to connect Prometheus and Alertmanager to an event-driven AI agent that investigates alerts before a human responds. It covers the architecture, read-only investigation tools, alert-rule annotations, safety guardrails, and a progression toward guarded remediation. ### Source excerpt Every page interrupts a human, yet most alerts end in the same ten investigation steps. Here is how event driven AI agents catch Prometheus alerts and do that first pass before you even look at your phone. ## Durable Objects are Made for Agents DevFeed: [Durable Objects are Made for Agents]() Original publisher: [Read original article]() Author: Calvin French-Owen Published: 2026-07-22T12:00:00Z Content type: opinion Language: en Sources: [Calvin French-Owen]() Topics: [Cloudflare](), [Serverless](), [SQLite](), [V8](), [event driven](), [WebSocket](), [wasm]() Tags: [cloudflare](), [event-driven](), [serverless](), [sqlite](), [v8](), [websockets]() ### AI overview An opinionated technical article explains why Cloudflare Durable Objects can be a strong primitive for building agents and other stateful products. It describes their serverless V8 execution model, per-object SQLite storage, ID-based request routing, event-driven structure, and potential shortcomings. ### Source excerpt I've spent the last few months building almost exclusively on Cloudflare Durable Objects. They're a near-perfect primitive for building agents--here's where they shine, and where they fall short. [Next page]()