# reliability The ability of a system or component to function under stated conditions for a specified period of time. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## How API Design Is Evolving for AI Agents, Security, Reliability, and Compliance DevFeed: [How API Design Is Evolving for AI Agents, Security, Reliability, and Compliance]() Original publisher: [Read original article]() Author: J Simpson Published: 2026-09-17T07:00:00Z Content type: article Language: en Sources: [Nordic APIs]() Topics: [API](), [Architecture & Design](), [Artificial Intelligence](), [reliability](), [Security]() Tags: [agents](), [ai-agents](), [api](), [api-architecture](), [api-as-a-product](), [api-design](), [api-discovery](), [api-security](), [architecture](), [authorization](), [blog](), [mcp](), [microservices](), [rate-limiting](), [reliability](), [security]() ### AI overview This article examines six ways API design is evolving as APIs serve AI agents and other machine consumers, with implications for security, reliability, and regulatory compliance. ### Source excerpt For over two decades, API design and architecture remained remarkably consistent. Perhaps it's the outsized influence of Roy Fielding's RESTful dissertation, but API designers have stuck to the principles of stateless architecture, resource-based endpoints, and HTTP commands to an impressive degree. That's all starting to change, now that we've radically recontextualized the way we use ... ## Worker Backpressure (Part 1) DevFeed: [Worker Backpressure (Part 1)]() Original publisher: [Read original article]() Author: Mikalai Barysau Published: 2026-09-17T00:00:00Z Content type: article Language: en Sources: [Canva Engineering]() Topics: [backpressure](), [Back end](), [reliability]() Tags: [backend](), [backpressure](), [dependencies](), [outage](), [queue](), [reliability](), [worker]() ### AI overview Canva describes Worker Backpressure, a reliability mechanism for queue workers that slows processing when dependencies fail and speeds it back up after recovery. During a cloud-provider outage, the mechanism helped prevent failed messages from accumulating on the Dead Letter Queue and avoided an on-call page. ### Source excerpt How we taught Canva's queue workers to slow down when dependencies fail, then speed back up on their own. ## AI Changed How Spotify Builds. What We Learned (and Fixed) About Quality at Higher Velocity DevFeed: [AI Changed How Spotify Builds. What We Learned (and Fixed) About Quality at Higher Velocity]() Original publisher: [Read original article]() Author: Spotify Engineering Published: 2026-09-16T19:13:53Z Content type: article Language: en Sources: [Spotify Engineering](), [Spotify Engineering Blog]() Topics: [Monitoring](), [reliability](), [Microservices](), [Data pipelines](), [Artificial Intelligence](), [Job]() Tags: [ai](), [bug](), [data-pipelines](), [jobs](), [microservices](), [monitoring](), [reliability]() ### AI overview Spotify describes how rapid change, content-processing weaknesses, capacity limits, and a scheduling bug contributed to delays in publishing episodes. It reports adding end-to-end monitoring, fixing the scheduler, lowering batch-job priority, and increasing capacity. ### Source excerpt Quality and reliability have always been a point of pride for Spotify. We run an extraordinarily complex... The post AI Changed How Spotify Builds. What We Learned (and Fixed) About Quality at Higher Velocity appeared first on Spotify Engineering. ## AI safety does not stop at the model DevFeed: [AI safety does not stop at the model]() Original publisher: [Read original article]() Author: Samar Abbas Published: 2026-09-15T00:00:00Z Content type: opinion Language: en Sources: [Temporal Blog]() Topics: [ai safety](), [Agent Harness](), [reliability](), [retry](), [Security]() Tags: [agent](), [agent-harness](), [ai](), [reliability](), [retry](), [safety](), [security](), [temporal-voices]() ### AI overview The article argues that AI safety extends beyond model behavior to the application layer, where companies must control agent authority and enforce approvals, policies, and credential limits. It emphasizes that these controls must remain reliable through crashes, timeouts, and retries, and presents Temporal Agent Harness as an execution-layer control point around an agent SDK. ### Source excerpt Auditing what an agent did is only half the job. Companies also have to control what agents may do, and make those limits hold when systems fail. ## Temporal raises $550M at a $12.55B valuation as demand grows for reliable AI infrastructure DevFeed: [Temporal raises $550M at a $12.55B valuation as demand grows for reliable AI infrastructure]() Original publisher: [Read original article]() Author: Allanah Hughes Published: 2026-09-14T00:00:00Z Content type: release Language: en Sources: [Temporal Blog]() Topics: [AI Infrastructure](), [reliability](), [Orchestration](), [AI Platform]() Tags: [agents](), [ai](), [ai-infrastructure](), [announcements](), [funding](), [infrastructure](), [orchestration](), [outage](), [reliability](), [series](), [systems]() ### AI overview Temporal announces a $550 million Series E funding round at a $12.55 billion valuation. The company says the funding will support reliable infrastructure for long-running AI agents and applications, including orchestration and recovery across systems. ### Source excerpt AI is raising the bar for reliability. See why Temporal's $550M Series E, backed by Lightspeed and others, is built to meet that demand. ## A letter from Samar: a year of achievements, and what's next for us DevFeed: [A letter from Samar: a year of achievements, and what's next for us]() Original publisher: [Read original article]() Author: Samar Abbas Published: 2026-09-14T00:00:00Z Content type: opinion Language: en Sources: [Temporal Blog]() Topics: [reliability](), [Artificial Intelligence](), [OpenAI]() Tags: [agents](), [ai-agents](), [growth](), [openai](), [reliability](), [temporal](), [temporal-voices]() ### AI overview Temporal CEO Samar Abbas reviews a year of company growth, leadership changes, the Series E raise, platform usage, and customer examples. He argues that reliable infrastructure and Durable Execution remain important as AI increases application complexity and expectations. ### Source excerpt Temporal CEO Samar Abbas on a year of record growth, the Series E raise, and why Durable Execution is now core infrastructure for reliable AI agents. ## How Fixed Intervals Synchronize Distributed Clients and How Jitter Helps DevFeed: [How Fixed Intervals Synchronize Distributed Clients and How Jitter Helps]() Original publisher: [Read original article]() Author: hello@ankit-rana.com Published: 2026-09-07T00:00:00Z Content type: opinion Language: en Sources: [Ankit Rana | Mechanical Sympathy]() Topics: [reliability](), [distributed-systems](), [systems](), [Network](), [Cache](), [Redis]() Tags: [aws](), [cache](), [code](), [distributed-systems](), [jitter](), [network](), [reliability](), [resilience](), [retries](), [thundering-herd]() ### AI overview Fixed retry intervals, TTLs, restarts, reconnects, and other recurring events can cause independent clients in distributed systems to synchronize, producing repeated load spikes. Adding randomness, or jitter, helps break that alignment; the article cites AWS measurements indicating that full jitter improves total work and completion time under contention. ### Source excerpt Distributed systems synchronise themselves without being told to: every client that retries on a fixed interval, restarts after a deploy, or reconnects after a network blip ends up firing at the same moment as every other client. The resulting spike is a self-inflicted denial of service that no single component is responsible for. Adding randomness to any repeating interval breaks the alignment, and it is usually one line of code against a failure mode that otherwise requires capacity you never needed. ## Temporal expands its Google Cloud Partnership with Gemini integration and pay-as-you-go pricing on Google Cloud Marketplace DevFeed: [Temporal expands its Google Cloud Partnership with Gemini integration and pay-as-you-go pricing on Google Cloud Marketplace]() Original publisher: [Read original article]() Author: Jay Sivachelvan Published: 2026-08-31T00:00:00Z Content type: release Language: en Sources: [Temporal Blog]() Topics: [Google Cloud Platform (GCP)](), [SDKs](), [Google](), [reliability](), [Artificial Intelligence](), [Cloud Run](), [Resilience](), [API](), [Serverless]() Tags: [agent](), [agent-development-kit](), [agent-framework](), [announcements](), [api](), [billing](), [cloud-marketplace](), [cloud-run](), [execution](), [gemini](), [google](), [google-cloud](), [integration](), [launch](), [partnership](), [pricing]() ### AI overview Temporal announces expanded Google Cloud integrations, including Public Preview support for the Google Gen AI Python SDK, durable execution for Gemini-based workflows, and pre-release Serverless Workers for Google Cloud Run. Temporal Cloud is also available on Google Cloud Marketplace with pay-as-you-go pricing. ### Source excerpt Temporal expands its Google Cloud partnership with Gemini integration, durable execution, and pay-as-you-go pricing on Google Cloud Marketplace. ## Temporal Agent Harness: An early look at durable agent infrastructure DevFeed: [Temporal Agent Harness: An early look at durable agent infrastructure]() Original publisher: [Read original article]() Author: Cornelia Davis Published: 2026-08-20T00:00:00Z Content type: article Language: en Sources: [Temporal Blog]() Topics: [Agent Harness](), [AI Agent](), [reliability](), [interfaces]() Tags: [agent-harness](), [ai](), [ai-agents](), [announcements](), [execution](), [interfaces](), [production](), [tool]() ### AI overview Temporal presents an early look at Agent Harness, an infrastructure layer for production AI agents. It is designed to add durable execution, tool-call approvals, typed interfaces, enforceable policies, reliable execution, and a durable history of agent activity while allowing teams to keep using existing agent harnesses and tools. ### Source excerpt Temporal's new Agent Harness brings durable execution, tool-call approvals, and typed interfaces to production AI agents. An early look. ## How MongoDB Atlas and Temporal support reliable production RAG and AI agents DevFeed: [How MongoDB Atlas and Temporal support reliable production RAG and AI agents]() Original publisher: [Read original article]() Author: Suresh Ramappa Published: 2026-08-13T00:00:00Z Content type: opinion Language: en Sources: [Temporal Blog]() Topics: [MongoDB](), [Retrieval Augmented Generation (RAG)](), [AI Infrastructure](), [Artificial Intelligence](), [reliability]() Tags: [agentic](), [agents](), [ai](), [ai-infrastructure](), [api](), [data](), [embeddings](), [long-running](), [mongodb](), [outages](), [pipelines](), [production](), [rag](), [recovery](), [reliability](), [retries](), [retrieval](), [temporal-voices]() ### AI overview The article argues that MongoDB Atlas and Temporal address different reliability needs in production RAG and AI agent systems. Atlas provides operational data, embeddings, vector search, and agent memory in one platform, while Temporal provides durable execution for crash recovery, retries, and long-running ingestion and agent workflows. ### Source excerpt Why MongoDB Atlas and Temporal are better together for AI: one data platform, one durable execution layer, for RAG and agents in prod. ## The Pulse: Quitting Spotify Podcasts over reliability DevFeed: [The Pulse: Quitting Spotify Podcasts over reliability]() Original publisher: [Read original article]() Author: Ivan Klaric Published: 2026-07-30T15:51:38Z Content type: opinion Language: en Sources: [The Pragmatic Engineer]() Topics: [Spotify](), [reliability](), [Streaming](), [RSS Feed]() Tags: [article](), [reliability](), [rss](), [streaming]() ### AI overview The author stopped publishing video podcast episodes on Spotify after encountering repeated reliability problems processing video episodes. Audio episodes remain available through Spotify's RSS feed, while video episodes are published on YouTube. ### Source excerpt Spotify's podcast platform has become chronically unreliable since the company's leadership started boasting about AI adoption. Competitors haven't had similar issues, so I offboarded from Spotify. ## Control Reliability Engineering (CRE): Applying SRE Principles to Cybersecurity Controls DevFeed: [Control Reliability Engineering (CRE): Applying SRE Principles to Cybersecurity Controls]() Original publisher: [Read original article]() Author: phil7672 Published: 2026-07-25T05:52:21Z Content type: article Language: en Sources: [Risk and Cyber]() Topics: [Cybersecurity](), [SRE](), [Monitoring](), [reliability](), [plotting]() Tags: [benchmarking](), [cybersecurity](), [leadership](), [monitoring](), [reliability](), [reliability-engineering](), [risk](), [sre](), [technology]() ### AI overview This article applies SRE principles to cybersecurity controls, arguing that control effectiveness matters more than input-focused budget comparisons. It highlights continuous control monitoring to detect controls that are broken, misconfigured, or incomplete when needed. ### Source excerpt Security breaches are often not the result of awesome attacker capabilities or the sudden emergence of sophisticated zero-day exploits. Instead, what we usually find are the controls designed to stop the attack were believed to be operational but were actually broken or misconfigured at the moment when they were needed. Sometimes they were never fully in place to meet the security team's original intent. So, continuous control monitoring is needed to counter the natural decay that occurs to... ## Session revocations at scale DevFeed: [Session revocations at scale]() Original publisher: [Read original article]() Author: Llew Vallis Published: 2026-07-22T00:00:01Z Content type: article Language: en Sources: [Canva Engineering]() Topics: [sessions](), [Cookies](), [Authorization](), [Caching](), [MySQL](), [scaling](), [gateway](), [Redis](), [reliability]() Tags: [backend](), [caching](), [cookies](), [gateway](), [mysql](), [permissions](), [redis](), [reliability](), [scaling](), [security](), [sessions]() ### AI overview Canva describes how it manages session revocations for hundreds of millions of users. The system keeps revocations in memory for fast gateway checks, while MySQL handles refresh-time lookups; the article explains how loading the cache during deployments created database load and discusses evaluating Redis as a caching solution. ### Source excerpt How Canva keeps hundreds of millions of user sessions fast and secure ## Why Temporal is the front-of-shirt sponsor for Crystal Palace DevFeed: [Why Temporal is the front-of-shirt sponsor for Crystal Palace]() Original publisher: [Read original article]() Author: Samar Abbas Published: 2026-07-17T00:00:00Z Content type: opinion Language: en Sources: [Temporal Blog]() Topics: [Software](), [reliability](), [Job](), [OpenAI]() Tags: [announcements](), [communities](), [company](), [developer](), [enterprise-technology](), [reliability](), [software](), [sponsor]() ### AI overview Temporal explains its front-of-shirt sponsorship of Crystal Palace by comparing the club's supporter loyalty with Temporal's focus on reliable software workflows. The article also mentions Temporal's reported $300 million Series D and $5 billion valuation. ### Source excerpt Temporal and Crystal Palace are teaming up, uniting fan and developer communities built on a loyalty that's earned, not manufactured. ## How Rapidflare built a million+ document ingestion pipeline for Agents on Temporal DevFeed: [How Rapidflare built a million+ document ingestion pipeline for Agents on Temporal]() Original publisher: [Read original article]() Author: Vasanth Asokan Published: 2026-07-08T00:00:00Z Content type: article Language: en Sources: [Temporal Blog]() Topics: [Agent Harness](), [Documentation](), [reliability](), [data](), [Graphs]() Tags: [agent-harness](), [agents](), [community](), [knowledge-graph](), [pipeline](), [pipelines](), [reliability](), [scale](), [technical]() ### AI overview Rapidflare explains how it uses Temporal to build durable, observable document-ingestion pipelines for technical sales agents processing knowledge bases at million-document scale. The article describes the need to ingest and pre-structure extensive technical literature into proprietary knowledge-graph formats, while preserving completeness and reliability. ### Source excerpt Rapidflare explains how it uses Temporal to run durable, observable document ingestion pipelines for technical sales Agents at million-document scale. ## Essential Non Functional Requirements DevFeed: [Essential Non Functional Requirements]() Original publisher: [Read original article]() Author: Saurabh Dashora Published: 2026-07-07T08:33:34Z Content type: tutorial Language: en Sources: [System Design Codex]() Topics: [Requirements](), [Architecture & Design](), [Scalability](), [Availability](), [Latency](), [reliability](), [Replication](), [Users]() Tags: [availability](), [data-replication](), [failover](), [haproxy](), [kubernetes](), [latency](), [nginx](), [requirements]() ### AI overview This tutorial explains non-functional requirements as quality attributes that determine how software systems behave under real-world conditions. It covers availability, latency, scalability, and durability, with implementation approaches including load balancers, health checks, failover, CDNs, data replication, horizontal scaling, Kubernetes, and concurrent API design. ### Source excerpt Don't miss them ## pgcopydb v0.18 DevFeed: [pgcopydb v0.18]() Original publisher: [Read original article]() Author: Dimitri Fontaine PostgreSQL Major Contributor; Author Published: 2026-07-01T14:05:56Z Content type: release Language: en Sources: [Dimitri Fontaine]() Topics: [PostgreSQL](), [postgresql 18](), [Replication](), [migration](), [SQLite](), [reliability](), [Open Source]() Tags: [bug-fixes](), [builds](), [migration](), [open-source](), [postgresql](), [postgresql-18](), [release](), [reliability](), [replication](), [sqlite]() ### AI overview A release announcement for pgcopydb v0.18, covering PostgreSQL 16-18 compatibility, a pgoutput-default change-data-capture engine, filtering, Citus-to-Citus migrations, reliability improvements, and 24 bug fixes. ### Source excerpt Hot off the press: pgcopydb v0.18 is out! It's the biggest release the project has had -- 88 commits since v0.17, which shipped in August 2024. I took a break from my Open Source responsibilities for a while, because I was lacking employer support to make it happen. What is pgcopydb pgcopydb copies a PostgreSQL database to another PostgreSQL server, as fast as possible when physical file copy isn't available. It parallelises the COPY across all tables simultaneously, builds indexes in parallel after data is loaded, and supports Change Data Capture via logical replication for minimal-downtime migrations. It is designed to be restartable: state is tracked in a local SQLite catalog so an interrupted run can resume where it left off. Headline Features of pgcopydb v0.18 v0.18 brings compatibility with PostgreSQL 16, 17, and 18; a pgoutput-default CDC engine with significant reliability and performance improvements; regular-expression-based filtering; Citus-to-Citus migration support; and 24 bug fixes. ## Coinbase trading outage exposed single-availability-zone dependency DevFeed: [Coinbase trading outage exposed single-availability-zone dependency]() Original publisher: [Read original article]() Author: Gergely Orosz Published: 2026-06-23T16:30:59Z Content type: opinion Language: en Sources: [The Pragmatic Engineer]() Topics: [coinbase](), [reliability](), [Amazon Web Services](), [Availability](), [Raft](), [Latency]() Tags: [availability](), [aws](), [coinbase](), [latency](), [outage](), [raft](), [reliability]() ### AI overview A commentary article examines a nearly 10-hour Coinbase trading outage that coincided with a regional AWS outage. It says Coinbase confirmed that its matching engine depended on a single availability zone, a design chosen to avoid inter-zone latency for its Raft-based replicated cluster. ### Source excerpt Hi, this is Gergely with a bonus, free issue of the Pragmatic Engineer Newsletter. In every issue, I cover Big Tech and startups through the lens of senior engineers and engineering leaders. Today, we cover one out of four topics from this past The Pulse issue. Full subscribers received the ## In-place pod restarts: Boosting efficiency and workload reliability in Kubernetes v1.35 DevFeed: [In-place pod restarts: Boosting efficiency and workload reliability in Kubernetes v1.35]() Original publisher: [Read original article]() Author: Google Open Source (noreply@blogger.com) Published: 2026-06-18T18:30:00Z Content type: article Language: en Sources: [Google Open Source Blog]() Topics: [Kubernetes](), [reliability](), [Resilience](), [Containers](), [distributed-systems](), [etcd](), [benchmarking]() Tags: [ai](), [containers](), [control-plane](), [efficiency](), [etcd](), [google](), [kubernetes](), [ml](), [reliability](), [resilience]() ### AI overview This article explains how Kubernetes v1.35 introduces the RestartAllContainers action for in-place Pod restarts. It describes how restarting containers while preserving the Pod's runtime identity can reduce resource waste, control-plane churn, scheduling races, and recovery delays for complex, batch, and AI/ML workloads. ### Source excerpt by Duncan Campbell & Giuseppe Tinti Tomio, Kubernetes Operational efficiency and system resilience are critical when running scaled platforms. Yet, in Kubernetes, recovering from software crashes remains a headache because you couldn't trigger a clean restart of a Pod's containers without recreating the entire Pod object, leading to some amount of resource waste. To address this, Restart All Containers on Container Exits graduated to beta and is enabled by default in Kubernetes v1.36. Developed in close collaboration with the CNCF community, this capability represents Google's commitment to investing in the success of foundation-led open source projects. By sharing best practices from running large distributed systems internally, we are helping build a more resilient and efficient ecosystem. Letting containers restart while keeping the Pod's runtime identity provides a built-in way to perform in-place Pod recovery, boosting application reliability and saving resource costs. The Problem: The High Cost of Pod Re-creation Historically, Kubernetes managed failures using pod level restart policies. While sufficient for simple services, modern multi-container Pods often have complex dependencies. When a failure requires a full environment reset, your only option was deleting and recreating the entire Pod. This introduces massive control plane churn, causing latency and pressure on the etcd backend during large failures: Initialization Dependencies: If a main container corrupts a local environment, for example, single-use secrets that must be re-requested, restarting just that container is insufficient; the setup must run again. Watcher Interoperability: If a watcher sidecar detects a fatal error, it must trigger a full recreate of the entire pod and its infrastructure, including the sandbox. Stale States: If a database sidecar proxy restarts, the main application can get stuck attempting to use stale, broken connections. Resource Race Conditions: When a large job finds a ## Introducing OpenRL: A self-hosted post-training API for fine-tuning LLMs DevFeed: [Introducing OpenRL: A self-hosted post-training API for fine-tuning LLMs]() Original publisher: [Read original article]() Author: Google Open Source (noreply@blogger.com) Published: 2026-06-11T18:30:00Z Content type: release Language: en Sources: [Google Open Source Blog]() Topics: [API](), [Fine-tuning](), [Large Language Model](), [Self-hosted](), [post-training](), [Kubernetes](), [Orchestration](), [reliability]() Tags: [api](), [fine-tuning](), [gke](), [kubernetes](), [llms](), [open-source](), [orchestration](), [post-training](), [reinforcement-learning](), [reliability](), [rl](), [self-hosted](), [sft]() ### AI overview This article announces OpenRL, an open-source research preview from GKE Labs. OpenRL is a self-hosted training API for fine-tuning LLMs on a Kubernetes cluster, designed to separate post-training infrastructure from AI research workflows. The article describes potential benefits including concurrent reinforcement-learning jobs, improved GPU utilization, and simpler researcher workflows. ### Source excerpt by Sunil Arora, Shuby Mishra & Chuang Wang, GKE We are pleased to share a research preview of OpenRL, a new open-source project coming out of GKE Labs. OpenRL is a self-hosted training API for fine-tuning LLMs on your own Kubernetes cluster. Why we built it If you look at agentic RL on LLMs, it is incredibly easy to get bogged down in system complexity. To run a single RL loop, you have to coordinate a dozen different things: selecting and cleaning datasets, choosing RL environments, debugging training loops, managing reward signals, handling inference mismatches, allocating hardware, and managing infrastructure. Picture looks something like this: Figure shows an AI researcher and an infrastructure engineer staring at the hurdles in post training along the way to the summit. Each of these is a hard problem. But what makes it more complex is how tightly AI research and infrastructure concerns are mixed together in today's tooling and frameworks. We believe decoupling the infrastructure from AI research can make these problems more tractable so that infrastructure engineers and AI researchers can independently tackle them. We have seen this pattern with Kubernetes where Kubernetes abstracted out the infrastructure and made application developers and SREs life easier. So, can you abstract out post training infrastructure? We believe so and drew huge inspiration/validation from Tinker (from Thinking Machines). The Tinker APIs for post training hit that Goldilocks zone where it hides all the post training infrastructure behind four key APIs: Figure shows high level components and their interaction in a OpenRL based RL workflow So the end result of this abstraction is that AI Researchers get full flexibility on their RL loop and infrastructure engineers can focus on scaling, orchestration, and reliability. OpenRL allows you to run the same training APIs but on your own infrastructure. And this decoupling has other interesting benefits. Sharing GPUs Traditional RL loops ar ## Temporal Cloud and Datadog integration adds pre-built metrics dashboards and standard-metrics monitoring DevFeed: [Temporal Cloud and Datadog integration adds pre-built metrics dashboards and standard-metrics monitoring]() Original publisher: [Read original article]() Author: Dustin Cote Published: 2026-05-19T00:00:00Z Content type: release Language: en Sources: [Temporal Blog]() Topics: [datadog](), [observability](), [dashboards](), [monitor](), [Cloud](), [reliability](), [API](), [API keys](), [Latency](), [Replication]() Tags: [announcements](), [api](), [cloud](), [cost](), [dashboard](), [datadog](), [latency](), [metrics](), [monitoring](), [observability](), [reliability](), [replication](), [setup]() ### AI overview Temporal Cloud and Datadog now offer an integration with a pre-built metrics dashboard, simplified setup, and more than 30 metrics for monitoring workflow performance, system health, and reliability. The metrics are classified as standard metrics in Datadog, which may reduce costs compared with custom metrics ingestion. ### Source excerpt Monitor Temporal Cloud with Datadog metrics. Gain deeper visibility into workflow performance and reliability. ## How XY builds an AI agent orchestration platform for healthcare with Temporal DevFeed: [How XY builds an AI agent orchestration platform for healthcare with Temporal]() Original publisher: [Read original article]() Author: The XY Engineering Team Published: 2026-04-23T00:00:00Z Content type: article Language: en Sources: [Temporal Blog]() Topics: [agent orchestration](), [AI Agent](), [Orchestration](), [reliability](), [human review](), [sensitive data](), [Structured-data](), [YAML]() Tags: [agent](), [agent-orchestration](), [ai](), [ai-agent](), [automation](), [how-to](), [human-review](), [long-running](), [orchestration](), [reliability](), [sensitive-data](), [temporal](), [workflow]() ### AI overview XY describes using Temporal as a DSL-driven execution engine for an AI agent orchestration platform serving complex healthcare workflows. The approach uses a YAML-based workflow language and a generic Temporal workflow class to coordinate multiple systems, reliability features, human review, and sensitive healthcare data from prototype to production. ### Source excerpt One generic Temporal workflow class can provide infinite healthcare automation. See how XY built a DSL-driven AI agent orchestration platform that scales from prototype to production. ## Maintenance of Everything : A Review DevFeed: [Maintenance of Everything : A Review]() Original publisher: [Read original article]() Author: Phil Venables Published: 2026-04-18T10:45:19Z Content type: opinion Language: en Sources: [Risk and Cyber]() Topics: [maintenance](), [risk-management](), [reliability](), [Security]() Tags: [cybersecurity](), [maintenance](), [reliability](), [review](), [risk-management](), [security](), [technology]() ### AI overview A review of Stewart Brand's book Maintenance of Everything, discussing the importance of maintenance in technology risk management, security, and reliability. It also questions cybersecurity benchmarking that focuses on inputs such as budgets instead of outcomes such as control effectiveness. ### Source excerpt I haven't done a book review for a while and there's no better way to get back to this than a look at Stewart Brand's Maintenance of Everything . Stewart developed a lot of this book in an open editing process and so the final delivery of what is Part 1 of a forthcoming series was all the more anticipated. I've long been obsessed with the need for maintenance in the context of technology risk management, security and reliability. A big part of technical debt build up and the security... ## A quiz matches developers with Replay '26 conference sessions DevFeed: [A quiz matches developers with Replay '26 conference sessions]() Original publisher: [Read original article]() Author: Lauren Bennett Published: 2026-04-07T00:00:00Z Content type: opinion Language: en Sources: [Temporal Blog]() Topics: [legacy systems](), [AI Agent](), [migration](), [reliability]() Tags: [ai-agents](), [community](), [legacy-systems](), [migration](), [opinions](), [reliability]() ### AI overview This interactive quiz assigns developers a Replay '26 conference path based on their work and interests, including legacy-system modernization, AI workflows, reliability, migration, and architecture. ### Source excerpt Are you migrating haunted legacy systems, wrangling AI agents with opinions, or quietly keeping everything from falling apart? Take the quiz to find your Replay '26 path. [Next page]()