# Deployment Published articles for Deployment. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## WSO2 Releases Agent Manager as Enterprises Look to Control Growing AI Agent Sprawl DevFeed: [WSO2 Releases Agent Manager as Enterprises Look to Control Growing AI Agent Sprawl]() Original publisher: [Read original article]() Author: Craig Risi Published: 2026-09-18T12:00:00Z Content type: news Language: en Sources: [InfoQ]() Topics: [AI Agent](), [Artificial Intelligence](), [Authorization](), [Security](), [Deployment](), [Kubernetes](), [Model Context Protocol](), [OpenTelemetry]() Tags: [agent-identity](), [agentic-ai-architecture](), [ai](), [ai-agent](), [ai-agents](), [ai-development](), [ai-ml-data-engineering](), [aiops](), [authorization](), [deployment](), [devops](), [governance](), [kubernetes](), [ml-data-engineering](), [model-context-protocol](), [news](), [opentelemetry](), [ws02-agent-manager](), [ws02-stratos]() ### AI overview WSO2 has released Agent Manager, an open-source platform for governing AI agents across models, frameworks, and deployment environments. The general availability release adds agent identity and authorization, MCP governance, lifecycle controls, a Kubernetes-native sandboxed runtime, and OpenTelemetry-based tracing and evaluation. ### Source excerpt WSO2 has announced the general availability of WSO2 Agent Manager, an open-source platform designed to provide centralized governance, identity management, security controls, and operational oversight for AI agents running across different models, frameworks, and deployment environments. By Craig Risi ## Turbo build machines can now be enabled per deployment DevFeed: [Turbo build machines can now be enabled per deployment]() Original publisher: [Read original article]() Author: Mehul Kar Published: 2026-09-17T20:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Deployment](), [Vercel](), [Command-line interface](), [REST API](), [GitHub](), [builds]() Tags: [build](), [cli](), [deploy](), [deployment](), [github](), [rest-api](), [vercel]() ### AI overview Vercel now allows Turbo build machines to be enabled for individual deployments. Developers can opt in through a Git commit message, Vercel CLI 59.20.0 or later, or the REST API without changing project settings. ### Source excerpt You can now opt into Turbo build machines on any individual deployment. This is useful when you need to increase resources temporarily without changing project settings. You can do this in three ways: Include #VERCEL_BUILD_MACHINE=TURBO in your Git commit message before pushing to GitHub Use vc deploy --turbo (Vercel CLI 59.20.0 or later) Set buildMachine to turbo when creating a deployment with the REST API Learn more in the managing builds documentation. Read more ## AWS Elastic Beanstalk introduces Cluster Mode DevFeed: [AWS Elastic Beanstalk introduces Cluster Mode]() Original publisher: [Read original article]() Author: Channy Yun (윤석찬) Published: 2026-09-17T19:20:21Z Content type: release Language: en Sources: [AWS News Blog]() Topics: [Amazon Web Services](), [Deployment](), [Amazon EKS](), [autoscaling](), [Monitoring](), [observability](), [Provisioning](), [Secrets Management](), [AWS Certificate Manager](), [CI/CD]() Tags: [amazon-eks](), [amazon-elastic-kubernetes-service](), [application](), [autoscaling](), [aws](), [aws-certificate-manager](), [aws-elastic-beanstalk](), [ci-cd](), [cluster](), [code](), [compute](), [container](), [deployment](), [dockerfiles](), [https](), [infrastructure](), [kubernetes](), [launch](), [monitoring](), [news](), [provisioning]() ### AI overview AWS Elastic Beanstalk introduces a fully managed Cluster Mode that runs multiple applications on shared infrastructure powered by Amazon EKS. It also highlights AI-assisted environment analysis, GitHub Actions deployment, observability, traffic-splitting deployments with rollback, autoscaling, secrets management, and HTTPS by default. ### Source excerpt Run an application on AWS Elastic Beanstalk Cluster Mode without provisioning or operating the compute underneath it. You provide a container image or source code; Elastic Beanstalk with service-operated compute creates and operates the environment that runs it. ## Multi-modal autoscaling with Amazon EC2 Auto Scaling: adding signals for faster, more reliable scaling DevFeed: [Multi-modal autoscaling with Amazon EC2 Auto Scaling: adding signals for faster, more reliable scaling]() Original publisher: [Read original article]() Author: Shubhendu Dubey Published: 2026-09-17T18:18:38Z Content type: tutorial Language: en Sources: [AWS Compute Blog]() Topics: [autoscaling](), [Amazon EC2](), [scaling](), [Amazon CloudWatch](), [Amazon Web Services](), [AWS CloudFormation](), [Deployment](), [dashboards]() Tags: [advanced-300](), [amazon-cloudwatch](), [amazon-ec2](), [api](), [auto-scaling](), [autoscaling](), [aws](), [aws-cloudformation](), [deployment](), [forecasting](), [latency](), [load](), [load-balancer](), [scaling](), [technical-how-to]() ### AI overview This tutorial explains multi-modal autoscaling with Amazon EC2 Auto Scaling by combining CPU, request-count, application-level, and predictive signals. It describes a controlled test in which application metrics avoided rejected checkout sessions and reduced p99 latency compared with CPU-only scaling. ### Source excerpt Multi-modal autoscaling with Amazon EC2 Auto Scaling combines infrastructure metrics like CPU with application-level signals, so a group scales on the demand its users create. In this post, we show you how to implement it, with code samples and results from a controlled test. ## How Equinix cut operational overhead with a shared services architecture on Amazon EKS DevFeed: [How Equinix cut operational overhead with a shared services architecture on Amazon EKS]() Original publisher: [Read original article]() Author: Chhavi Kaushik Published: 2026-09-17T18:00:56Z Content type: article Language: en Sources: [AWS Architecture Blog]() Topics: [Amazon EKS](), [Kubernetes](), [Architecture & Design](), [Cloud](), [Deployment](), [Provisioning](), [observability](), [Security](), [CI/CD](), [Open Source]() Tags: [amazon-eks](), [amazon-elastic-kubernetes-service](), [architecture](), [customer-solutions](), [deployment](), [infrastructure](), [kubernetes](), [observability](), [pipelines](), [provisioning](), [security]() ### AI overview Equinix moved from independently managed Kubernetes clusters on Amazon EC2 to a shared services architecture on Amazon EKS. The approach centralizes governance and common infrastructure services while addressing operational sprawl, lifecycle complexity, security, networking, observability, and deployment consistency. ### Source excerpt Equinix, the world's digital infrastructure company, built a shared services architecture on Amazon EKS to eliminate the operational sprawl of its self-managed Kubernetes environment. Learn how a multi-account North Star architecture centralized governance and shared services, delivering 4x faster deployments and 40% less operational overhead. ## Zero-touch deployment requirements for Mac fleet backup DevFeed: [Zero-touch deployment requirements for Mac fleet backup]() Original publisher: [Read original article]() Author: Kari Wilson Published: 2026-09-17T16:51:35Z Content type: article Language: en Sources: [Backblaze Blog | Cloud Storage & Cloud Backup]() Topics: [Deployment](), [Automation](), [Software]() Tags: [agent](), [automation](), [backing-up](), [backup](), [businessbackup](), [deployment](), [featured](), [featured-backing-up](), [fleet](), [mac]() ### AI overview The article argues that zero-touch deployment has become essential for Mac fleets, especially for lean IT teams managing devices through MDM platforms such as Jamf Pro, Kandji, and Addigy. It explains how interactive installers, permission prompts, and registration failures create support work and can leave machines unprotected. ### Source excerpt For lean IT teams, zero-touch Mac backup deployment is no longer optional. Learn what truly silent installation requires and how Backblaze helps admins protect every device across Jamf, Kandji, Addigy, and other MDM-managed fleets without user interaction or follow-up work. The post Zero-Touch or It Doesn't Scale: The New Standard for Mac Fleet Backup appeared first on Backblaze Blog | Cloud Storage & Cloud Backup ## Lenovo ThinkAgile VX850 V4 Takes On In-Memory Virtualization With New Deploy Tiers and Four-Hypervisor Express Bundles DevFeed: [Lenovo ThinkAgile VX850 V4 Takes On In-Memory Virtualization With New Deploy Tiers and Four-Hypervisor Express Bundles]() Original publisher: [Read original article]() Author: Harold Fritts Published: 2026-09-17T16:43:22Z Content type: news Language: en Sources: [StorageReview.com]() Topics: [virtualization](), [Hardware](), [Deployment](), [hyper-v](), [Windows](), [Microsoft](), [Azure](), [nutanix](), [intel]() Tags: [azure](), [capacity](), [deployment](), [enterprise](), [hardware](), [hyper-v](), [intel](), [microsoft](), [nutanix](), [nvme](), [pcie](), [server](), [virtualization]() ### AI overview Lenovo added the four-socket ThinkAgile VX850 V4 to its virtualization lineup for demanding in-memory workloads. The launch also introduces three Infrastructure Deployment Services tiers and pre-validated Top Choice Express bundles covering Microsoft, Red Hat, SUSE, and Nutanix. Lenovo has not yet published the VX850 V4's own product specifications. ### Source excerpt Lenovo has added the ThinkAgile VX850 V4 to its virtualization lineup, a four-socket node it describes as purpose-built for highly virtualized and demanding in-memory workloads, and paired the launch with a three-tier deployment service framework and a set of pre-validated Top Choice Express bundles spanning Microsoft, Red Hat, SUSE, and Nutanix. The announcement follows Lenovo's The post Lenovo ThinkAgile VX850 V4 Takes On In-Memory Virtualization With New Deploy Tiers and Four-Hypervisor Express Bundles appeared first on StorageReview.com. ## Microsoft configuration change leaves SharePoint pages drawing a blank DevFeed: [Microsoft configuration change leaves SharePoint pages drawing a blank]() Original publisher: [Read original article]() Author: Richard Speed Published: 2026-09-17T15:17:00Z Content type: news Language: en Sources: [www.theregister.com - Articles]() Topics: [configuration](), [Microsoft](), [Deployment]() Tags: [configuration](), [deployment](), [microsoft](), [microsoft-365](), [saas]() ### AI overview The document reports that a Microsoft configuration change caused SharePoint pages to display blank, with validation apparently occurring after deployment. ### Source excerpt Validation? Apparently that comes after deployment ## From hours to minutes: Optimizing Red Hat Developer Hub performance testing with immutable LDAP images DevFeed: [From hours to minutes: Optimizing Red Hat Developer Hub performance testing with immutable LDAP images]() Original publisher: [Read original article]() Author: Shashank Kestwal Published: 2026-09-17T13:16:48Z Content type: article Language: en Sources: [Red Hat](), [Red Hat Developer]() Topics: [Performance Testing](), [LDAP](), [Keycloak](), [CI/CD](), [Concurrency](), [Deployment](), [rbac]() Tags: [ci-cd](), [concurrency](), [deployment](), [keycloak](), [ldap](), [migration](), [performance-testing](), [testing]() ### AI overview This Red Hat developer article describes a performance-testing bottleneck in Red Hat Developer Hub caused by generating users and groups at runtime through the Keycloak Admin REST API and synchronizing them over HTTP. It introduces pre-built LDAP container images as immutable infrastructure to reduce environment setup complexity and improve testing feedback loops. ### Source excerpt At Red Hat, our CI/CD pipelines are the heartbeat of our development process. However, as we scaled the Red Hat Developer Hub performance testing framework, we hit a wall. Our environment setup time was ballooning, turning what should have been a seamless verification step into a long waiting game. For performance engineering in catalog-dependent applications, deployment and catalog population speed directly dictate your feedback loops. The post From hours to minutes: Optimizing Red Hat Developer Hub performance testing with immutable LDAP images appeared first on Red Hat Developer. ## Catching poor LLM performance and accuracy before deployment DevFeed: [Catching poor LLM performance and accuracy before deployment]() Original publisher: [Read original article]() Author: Christopher Miyai Published: 2026-09-17T13:16:47Z Content type: article Language: en Sources: [Red Hat](), [Red Hat Developer]() Topics: [vllm](), [Inference Performance](), [LLM evaluation / benchmarking](), [benchmarking](), [CI/CD](), [model-deployment](), [Open Source](), [container]() Tags: [ai-inference](), [benchmarking](), [benchmarks](), [ci-cd](), [container-images](), [deployment](), [developer-tools](), [llm](), [open-source](), [performance](), [vllm]() ### AI overview This article describes a regression-testing system for Red Hat AI Inference that compares upstream and midstream vLLM builds. It benchmarks LLM performance and accuracy across hardware variants and uses CI/CD to detect regressions before release. ### Source excerpt vLLM is the leading open source inference and serving engine for LLMs. Averaging 64 commits a day with bi-weekly releases, the open source project goes through a significant amount of code changes rapidly. Red Hat AI Inference offers an integrated inference platform powered by vLLM, llm-d and vLLM's llm-compressor. The post Catching poor LLM performance and accuracy before deployment appeared first on Red Hat Developer. ## New Hampshire software freedom bill hearing scheduled for 21 February 2023 DevFeed: [New Hampshire software freedom bill hearing scheduled for 21 February 2023]() Original publisher: [Read original article]() Author: Leah Rowe Published: 2026-09-17T04:32:50.666044Z Content type: news Language: en Sources: [News about Libreboot releases and development]() Topics: [Software](), [Deployment](), [Deployment Strategies](), [systems]() Tags: [article](), [bios](), [canoeboot](), [coreboot](), [deployment](), [deployment-strategies](), [free-software](), [information-technology](), [libre](), [libreboot](), [mastodon](), [news](), [opensource](), [uefi]() ### AI overview The article reports on an upcoming New Hampshire House Bill 556-FN hearing concerning software freedom. It describes provisions that would require the New Hampshire Information Technology Council to study promoting libre software and reducing citizens' reliance on proprietary software in state interactions. ### Source excerpt Article: NEW New Hampshire software freedom bill hearing on 21 February 2023 needs your support! Web link: https://libreboot.org/news/usa-libre-part3.html ## Native Marketplace integrations now support custom environments DevFeed: [Native Marketplace integrations now support custom environments]() Original publisher: [Read original article]() Author: Tony Pan Published: 2026-09-17T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Vercel](), [Deployment](), [Environment Variables](), [Command-line interface](), [REST API]() Tags: [cli](), [deployment](), [environment-variables](), [environments](), [rest-api](), [vercel]() ### AI overview Vercel now lets users connect native Marketplace resources to custom environments through the dashboard, CLI, or REST API. The resulting environment variables can be scoped to the selected environments, while existing deployments remain unchanged. ### Source excerpt You can now connect native Marketplace resources to custom environments. Previously, resource connections could only target production, preview, and development environments. Choose custom environments when connecting a resource from the Vercel dashboard, Vercel CLI, or REST API. Vercel scopes the environment variables created by the connection to the selected environments. For example, from the CLI: Existing deployments do not change. Create a new deployment after connecting a resource or changing its environment scope. Custom environments are available on Pro and Enterprise plans. Read the docs for connecting from the dashboard, the CLI --environment flag, and the REST API envVarEnvironments field. Read more ## Beyond the sync: Argo CD needs an Enterprise Control Plane DevFeed: [Beyond the sync: Argo CD needs an Enterprise Control Plane]() Original publisher: [Read original article]() Author: Eric Minick Sudarshan Purohit Published: 2026-09-16T20:28:57.610955Z Content type: opinion Language: en Sources: [Harness Blog]() Topics: [argo-cd](), [GitOps](), [Orchestration](), [DevOps](), [Platform Engineering](), [Deployment](), [Artificial Intelligence]() Tags: [argo-cd](), [deployment](), [gitops](), [governance](), [orchestration](), [platform-engineering](), [verification]() ### AI overview This article argues that Argo CD's manifest synchronization is only one part of enterprise software delivery. It describes how scaling GitOps can create operational toil and Argo sprawl, and proposes an enterprise control plane with workflow orchestration, governance, and deployment verification. ### Source excerpt Scaling GitOps? Argo CD is great for syncing manifests, but enterprise delivery requires workflow orchestration, governance, and AI verification. | Blog ## Platform Engineering in the Age of AI DevFeed: [Platform Engineering in the Age of AI]() Original publisher: [Read original article]() Author: Nicole Morgan Published: 2026-09-16T20:28:57.610955Z Content type: opinion Language: en Sources: [Harness Blog]() Topics: [Platform Engineering](), [Artificial Intelligence](), [AI Agent](), [internal developer portal](), [API](), [Deployment](), [sdlc]() Tags: [agent](), [ai](), [api](), [deployment](), [developer-experience](), [engineering](), [metrics](), [platform](), [sdlc]() ### AI overview This commentary examines how platform engineering is adapting as AI coding tools and agents become part of software delivery. It discusses the build-versus-provide decisions facing platform teams, how agents may consume internal developer platforms through APIs, the need for guardrails, and the challenge of measuring the results of AI investment. ### Source excerpt 94% of engineering leaders say their AI metrics are missing. Here's how platform engineering is changing to close that gap. | Blog ## AI Agent Governance: Why It Belongs in Your Platform DevFeed: [AI Agent Governance: Why It Belongs in Your Platform]() Original publisher: [Read original article]() Author: Prateek Mittal Published: 2026-09-16T20:28:57.610955Z Content type: article Language: en Sources: [Harness Blog]() Topics: [AI Agent](), [Artificial Intelligence](), [observability](), [audit](), [test](), [Deployment](), [Monitoring](), [pull-requests]() Tags: [ai](), [ai-agent](), [audit](), [deployment](), [governance](), [monitoring](), [observability](), [pull-requests](), [test]() ### AI overview Engineering leaders from Yelp, Platformable, and Harness argue that AI agent governance must be automated, continuously enforced, and built into the platform rather than left to policy documents. The article discusses audit trails, agent-to-agent access controls, experiment tracking, testing, latency monitoring, rollback paths, and observability for agent-driven changes. ### Source excerpt Engineering leaders from Yelp, Platformable, and Harness explain why AI agent governance has to be built into the platform, not a policy doc. | Blog ## Constraining AI agents with Red Hat AI: Containment, identity, and governance DevFeed: [Constraining AI agents with Red Hat AI: Containment, identity, and governance]() Original publisher: [Read original article]() Author: Grace Ableidinger Published: 2026-09-16T13:01:59Z Content type: tutorial Language: en Sources: [Red Hat](), [Red Hat Developer]() Topics: [Artificial Intelligence](), [Security](), [Zero Trust](), [Containers](), [Kubernetes](), [Architecture & Design]() Tags: [ai](), [ai-agents](), [containers](), [deployment](), [kubernetes](), [prompt-injection](), [security](), [trust]() ### AI overview This tutorial explains how to secure AI agents running on Red Hat OpenShift using containment, verifiable identity, and governance. It covers namespace isolation, quotas, sandboxing, workload identity, and admission control, with OpenClaw used in the demo. ### Source excerpt When an agent process runs on your laptop, it typically inherits anything your user has access to. Often this includes the full network stack, the file system, and the credentials sitting in memory. When integrating with GitHub, Slack, or a cloud provider, you could be one faulty permission or well-crafted prompt injection away from a security incident. The post Constraining AI agents with Red Hat AI: Containment, identity, and governance appeared first on Red Hat Developer. ## Lyft Moves Streaming Fleet to Apache Flink Kubernetes Operator DevFeed: [Lyft Moves Streaming Fleet to Apache Flink Kubernetes Operator]() Original publisher: [Read original article]() Author: Mark Silvester Published: 2026-09-16T11:00:00Z Content type: news Language: en Sources: [InfoQ]() Topics: [flink](), [apache-flink](), [Kubernetes](), [autoscaling](), [Deployment](), [legacy](), [Testing]() Tags: [apache-flink](), [architecture-design](), [autoscaling](), [deployment](), [development](), [devops](), [flink](), [kubernetes](), [kubernetes-operator](), [legacy](), [lyft-flink-k8s-operator](), [news](), [testing](), [upgrade]() ### AI overview Lyft moved hundreds of production Apache Flink jobs from its in-house Kubernetes operator to the Apache Flink Kubernetes Operator. The change enabled last-state upgrades, in-place autoscaling, and resource autotuning, while Lyft adapted legacy deployment specifications through its deploy API and contributed a fix for a configuration-renaming bug. ### Source excerpt Lyft has moved hundreds of production Flink jobs from a 2020 in-house Kubernetes operator to the Apache Flink Kubernetes Operator, unlocking last-state upgrades, in-place autoscaling and resource autotuning across the fleet. By Mark Silvester ## How to upgrade hundreds of React components without breaking production DevFeed: [How to upgrade hundreds of React components without breaking production]() Original publisher: [Read original article]() Author: Khan Academy Published: 2019-09-23T22:00:00Z Content type: tutorial Language: en Sources: [Khan Academy]() Topics: [React](), [Design system](), [upgrade](), [Accessibility](), [consistency](), [test](), [Deployment](), [Code]() Tags: [accessibility](), [components](), [consistency](), [deployment](), [design-system](), [engineering](), [how-to](), [news](), [production](), [react](), [test](), [upgrade](), [web-frontend]() ### AI overview This article explains how Khan Academy upgraded hundreds of React buttons and links to components from its Wonder Blocks design system. It describes using a prop-conversion guide, organizing small team-owned changes, deploying often, and validating the migration with detailed test plans and responsive screenshots. ### Source excerpt By Jangmi Jo Background In 2018, we started renewing our color system using our new shared design system, ... Read more ## Google tag gateway: Now on Webflow DevFeed: [Google tag gateway: Now on Webflow]() Original publisher: [Read original article]() Author: Webflow Team Published: 2026-09-16T00:00:00Z Content type: release Language: en Sources: [Webflow Blog]() Topics: [gateway](), [webflow](), [Google](), [Confidential Computing](), [data](), [configuration](), [Deployment]() Tags: [confidential-computing](), [configuration](), [conversion](), [data](), [deployment](), [development](), [gateway](), [google](), [measurement](), [webflow]() ### AI overview Webflow announces Google tag gateway, which routes conversion data through a site's first-party infrastructure. Existing native Google tag integration users can activate it by republishing their site, while new users can follow a code-free setup workflow. ### Source excerpt When you build on Webflow, you're creating experiences designed to help your business stand out and grow. Underpinning those experiences with a strong measurement foundation can help you understand what's driving results and make more informed marketing decisions. Now, Webflow makes it easier to strengthen your measurement foundation. ## Support the well-known change password URL with Appwrite Auth DevFeed: [Support the well-known change password URL with Appwrite Auth]() Original publisher: [Read original article]() Author: Atharva Deosthale Published: 2026-09-16T00:00:00Z Content type: tutorial Language: en Sources: [Appwrite Blog]() Topics: [passwords](), [Appwrite](), [Application Security](), [web applications](), [W3C]() Tags: [bitwarden](), [deployment](), [passwords](), [security](), [tutorial](), [tutorials](), [w3c]() ### AI overview This tutorial shows how to support the well-known change password URL in a TanStack Start app using Appwrite Auth. It explains the redirect, the change-password form for signed-out visitors, autocomplete hints, and deployment to Appwrite Sites. ### Source excerpt Password managers open /.well-known/change-password when they find a leaked or weak password. Add the redirect and a change password page backed by Appwrite Auth. ## Automate Docker Registry Creation with Harness and Terraform DevFeed: [Automate Docker Registry Creation with Harness and Terraform]() Original publisher: [Read original article]() Author: Shibam Dhar Published: 2026-09-16T00:00:00Z Content type: tutorial Language: en Sources: [Harness Blog]() Topics: [docker registry](), [Kubernetes](), [Provisioning](), [Terraform](), [Infrastructure as code](), [CI/CD](), [Dockerfile]() Tags: [ci-cd](), [container-image](), [deployment](), [docker-registry](), [infrastructure-as-code](), [kubernetes](), [registry](), [terraform]() ### AI overview A tutorial shows how to use Harness Pipelines and the Harness Terraform Provider to provision a uniquely named Docker Registry, build and push a container image, and deploy it to Kubernetes. It covers Terraform execution in a CI step, passing output variables between stages, and rolling updates with automatic rollback. ### Source excerpt Provision a fresh Docker Registry with Terraform, build your container image into it, and deploy to Kubernetes in one | Blog ## Dense vs. MoE Models: Active Parameters, Throughput, and When to Choose Each DevFeed: [Dense vs. MoE Models: Active Parameters, Throughput, and When to Choose Each]() Original publisher: [Read original article]() Author: Elizabeth Goodman Published: 2026-09-15T17:00:11Z Content type: article Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [Mixture of Experts (MoE)](), [Nemotron](), [Routing (disambiguation)]() Tags: [agentic-ai-generative-ai](), [ai-inference](), [architecture](), [cost](), [data-center-cloud](), [deployment](), [llms](), [memory](), [mixture-of-experts-moe](), [models](), [moe](), [nemo](), [nemotron](), [performance](), [router](), [routing](), [tokens]() ### AI overview This article explains how dense and Mixture-of-Experts models activate parameters, compares their effects on throughput, memory cost, and serving complexity, and discusses when each architecture fits different deployment constraints. It uses Nemotron 3.5 Lightning as an example of an MoE model. ### Source excerpt How can a 30B-parameter model activate only 3B parameters per token, and still use the capacity of the larger model? Nemotron 3.5 Lightning illustrates the... ## Agents operate, humans govern: Scale your operations and reduce toil with Azure SRE Agent DevFeed: [Agents operate, humans govern: Scale your operations and reduce toil with Azure SRE Agent]() Original publisher: [Read original article]() Author: TNS Staff Published: 2026-09-15T16:21:45Z Content type: article Language: en Sources: [The New Stack]() Topics: [SRE](), [incident](), [Azure](), [observability](), [DevOps](), [Redis]() Tags: [agent](), [ai-agents](), [ai-operations](), [azure](), [code-review](), [deployment](), [devops](), [incident](), [microsoft-azure](), [monitoring](), [observability](), [post](), [redis](), [sponsor-microsoft-azure](), [sponsored](), [sponsored-post](), [sre](), [telemetry]() ### AI overview The article describes Azure SRE Agent as a system that analyzes telemetry, correlates deployment and monitoring data, investigates incidents, identifies root causes, recommends or prepares fixes, and supports mitigation and other operational tasks under human approval. It cites examples involving Microsoft service teams and InEight, including a recommendation to scale Redis. ### Source excerpt What if engineers could spend their time building and optimizing systems rather than maintaining them? It's 3 a.m., and the The post Agents operate, humans govern: Scale your operations and reduce toil with Azure SRE Agent appeared first on The New Stack. ## Scaling Federated Learning Across Docker, Kubernetes, and Slurm with NVIDIA FLARE DevFeed: [Scaling Federated Learning Across Docker, Kubernetes, and Slurm with NVIDIA FLARE]() Original publisher: [Read original article]() Author: Elizabeth Goodman Published: 2026-09-15T15:00:00Z Content type: article Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [Federated Learning](), [Docker](), [Kubernetes](), [Nvidia](), [Server](), [dataset](), [Deployment]() Tags: [architecture](), [compute](), [configuration](), [container](), [data-analytics-processing](), [data-science](), [dataset](), [deployment](), [docker](), [docker-container](), [federated-learning](), [gpu](), [job](), [kubernetes](), [nvidia](), [nvidia-flare](), [server]() ### AI overview This article explains how NVIDIA FLARE scales federated learning across sites with different infrastructure, including Docker, Kubernetes, and Slurm. Its two-layer architecture separates persistent federation services from on-demand job execution, while allowing each site to retain local control over compute, data, secrets, and scheduling. ### Source excerpt Federated learning (FL) projects often begin with a straightforward setup: one server, a few clients, and one dataset at each site. As those projects grow, the... [Next page]()