# Provisioning Provisioning is the process of configuring a physical or virtual machine into a ready-to-use operating system. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## 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. ## 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. ## 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 ## How to attach an owner to every cloud resource you find DevFeed: [How to attach an owner to every cloud resource you find]() Original publisher: [Read original article]() Author: Zeen Rachidi Published: 2026-09-15T14:00:00Z Content type: tutorial Language: en Sources: [The New Stack]() Topics: [Cloud](), [Provisioning](), [Open Policy Agent](), [audit trail]() Tags: [audit-trail](), [cloud](), [cloud-services](), [devops](), [env-zero](), [how-to](), [logs](), [open-policy-agent](), [platform-engineering](), [policy](), [post-contributed](), [provisioning](), [sponsor-env-zero](), [sponsored-post-contributed]() ### AI overview This tutorial explains how to identify cloud resources without assigned owners and prevent new ownerless resources. It presents continuously synced inventory queries, Open Policy Agent policies requiring owner tags, and logs or audit trails for resource governance. ### Source excerpt The engineer who knew why that cloud instance existed has left the company. The instance is still running, the bill The post How to attach an owner to every cloud resource you find appeared first on The New Stack. ## Inside LuBot's database-per-tenant architecture DevFeed: [Inside LuBot's database-per-tenant architecture]() Original publisher: [Read original article]() Author: Carlota Soto Published: 2026-09-14T12:00:00Z Content type: article Language: en Sources: [Blog -- Neon Docs]() Topics: [Database](), [Software as a service](), [Supabase](), [Provisioning](), [stripe](), [API]() Tags: [api](), [architecture](), [billing](), [case-studies](), [checkout](), [database](), [infrastructure](), [product](), [provisioning](), [saas](), [scale](), [stripe]() ### AI overview This article explains LuBot's database-per-tenant architecture. LuBot uses Supabase for shared administrative data such as organizations, users, and billing state, while each paying customer receives an isolated Postgres database. Stripe checkout triggers a webhook that provisions a Neon branch through the Neon API, with deterministic naming to prevent duplicate tenants. Neon branches provide independent compute and can scale idle tenants to zero. ### Source excerpt It took six days to go from zero to isolated Postgres per tenant, provisioned the moment someone pays. A traditional Postgres setup would have been a full quarter of work. ## Article: Implementing Durable Workflows on Postgres Without an External Orchestrator DevFeed: [Article: Implementing Durable Workflows on Postgres Without an External Orchestrator]() Original publisher: [Read original article]() Author: Raman Varma Published: 2026-09-14T11:00:00Z Content type: article Language: en Sources: [InfoQ]() Topics: [Databases](), [SQL](), [Provisioning](), [incident](), [CI/CD](), [Kubernetes](), [AWS Step Functions](), [Artificial Intelligence]() Tags: [ai](), [ai-ml-data-engineering](), [architecture-design](), [article](), [automation](), [aws-step-functions](), [database](), [durable-workflows-postgres](), [incident-response](), [infrastructure](), [kubernetes](), [ml-data-engineering](), [orchestration](), [postgres](), [queue](), [relational-databases](), [sql](), [workflows]() ### AI overview This article explains how to implement durable workflows on Postgres without an external orchestrator. It describes using row-level locking as a concurrent work queue, primary-key checkpoints for idempotency, and leases with a sweeper for crash recovery. Workflow state, sleeps, and human approvals can persist in the database and survive process restarts. ### Source excerpt Postgres can serve as the durable state store and coordination layer for workflows, eliminating the need for an external orchestrator. SKIP LOCKED enables concurrent work processing, primary-key checkpoints enforce idempotency, and leases support crash recovery. Workflow sleeps and human approvals can also be persisted as database state and survive restarts. By Raman Varma ## KCP: How to Migrate to Confluent Cloud in Days, Not Weeks DevFeed: [KCP: How to Migrate to Confluent Cloud in Days, Not Weeks]() Original publisher: [Read original article]() Author: Ahmed Saef Zamzam Published: 2026-09-14T07:00:00Z Content type: tutorial Language: en Sources: [Confluent: Data in motion]() Topics: [Kafka](), [migration](), [Confluent Cloud](), [Replication](), [Infrastructure as code](), [Provisioning](), [Access Control](), [Structured-data]() Tags: [access-control](), [confluent](), [confluent-cloud](), [data-replication](), [infrastructure-as-code-iac](), [kafka](), [migration](), [open-source](), [provisioning](), [replication](), [schema]() ### AI overview The article explains how Confluent's open source KCP tool automates migration from Amazon MSK to Confluent Cloud. KCP supports discovery, infrastructure provisioning, ACL and schema mapping, and migration, while Cluster Linking provides offset-preserving data replication. Support for self-managed Kafka migrations is described as coming soon. ### Source excerpt Use Kafka Copy Paste (KCP) to automate Kafka migration with infrastructure generation, ACL and schema mapping, and offset-preserving data replication. ## How to answer the identity questions on an enterprise security questionnaire DevFeed: [How to answer the identity questions on an enterprise security questionnaire]() Original publisher: [Read original article]() Author: WorkOS Published: 2026-09-14T00:00:00Z Content type: article Language: en Sources: [WorkOS Blog]() Topics: [Security](), [Single sign-on (SSO)](), [Provisioning](), [OpenID connect (OIDC)](), [App]() Tags: [configuration](), [enterprise](), [how-to](), [identity](), [integration](), [oidc](), [okta](), [provisioning](), [saml](), [security](), [sign-in](), [sso]() ### AI overview A practical guide to answering identity-related questions in enterprise security questionnaires. It explains what reviewers are really assessing behind SAML single sign-on and SCIM provisioning questions, including implementation details such as per-organization configuration, certificate rotation, and reliable deprovisioning. ### Source excerpt Every line has a literal answer and a real question behind it. Here is what the buyer is actually checking, which answers you can buy, and the three you cannot fake. ## Now generally available: See how Stack Automation by Quali cuts deployment time DevFeed: [Now generally available: See how Stack Automation by Quali cuts deployment time]() Original publisher: [Read original article]() Author: Carlos Campos Torres Published: 2026-09-09T15:00:14Z Content type: article Language: en Sources: [Cisco Blogs]() Topics: [Automation](), [Deployment](), [Provisioning](), [configuration](), [cloud-infrastructure](), [Cloud]() Tags: [agenticops](), [automation](), [cloud](), [data-center](), [deployment](), [documentation](), [infrastructure](), [infrastructure-as-code-iac](), [platform](), [software](), [ubuntu](), [windows]() ### AI overview Stack Automation by Quali, co-developed with Cisco, is generally available as a deployment automation platform for validated Cisco and third-party infrastructure solutions. Its Solutions Hub supports planning, modeling, bill of materials generation, and automated deployment across on-premises and public-cloud services, reducing deployment cycles from weeks to hours or minutes. ### Source excerpt Still burning weeks on manual infrastructure deployment? Stack Automation by Quali, co-developed with Cisco, is now available--turning that grind into an automated, cloud-like experience that takes minutes. ## See How Organizations Achieved 137% ROI with VMware Cloud Foundation 9 DevFeed: [See How Organizations Achieved 137% ROI with VMware Cloud Foundation 9]() Original publisher: [Read original article]() Author: vmwareblogs Published: 2026-09-08T15:00:00Z Content type: article Language: en Sources: [VMware Blogs]() Topics: [Cloud](), [Provisioning](), [systems](), [Security]() Tags: [cloud](), [cloud-infrastructure](), [compliance](), [cost](), [efficiency](), [financial](), [home-page](), [infrastructure](), [legacy](), [private-cloud](), [provisioning](), [survey](), [vcf-9-0](), [vcf-9-1](), [vmware](), [vmware-cloud-foundation](), [webinar]() ### AI overview The article presents a commissioned Forrester Consulting Total Economic Impact study of VMware Cloud Foundation 9. Based on interviews with eight customers and a survey of 55 customers over a modeled three-year period, it describes projected financial and operational benefits for large enterprises running VCF 9 in production, including lower infrastructure costs, reduced operational effort, less downtime, faster delivery, tool consolidation, and improved security and compliance. The title reports 137% ROI. ### Source excerpt Enterprises running private cloud face a common question: what does the investment actually deliver? To answer it, we commissioned Forrester Consulting to conduct an independent New Technology Total Economic Impact (TEI) study on VMware Cloud Foundation 9 (VCF 9). Forrester interviewed decision-makers at organizations running VCF 9 and surveyed additional customers to develop a composite ... Continued The post See How Organizations Achieved 137% ROI with VMware Cloud Foundation 9 appeared first on VMware Blogs. ## Vespa Newsletter, September 2026 DevFeed: [Vespa Newsletter, September 2026]() Original publisher: [Read original article]() Author: Bonnie Chase Published: 2026-09-08T00:00:00Z Content type: news Language: en Sources: [Vespa Blog]() Topics: [ann](), [Latency](), [Provisioning](), [Algorithm](), [telemetry](), [Graphs]() Tags: [2026](), [algorithm](), [cloud](), [features](), [graph](), [latency](), [newsletter](), [product](), [provisioning](), [ranking](), [retrieval](), [september-2026](), [telemetry](), [updates]() ### AI overview The September 2026 Vespa newsletter announces updates including time-constrained ANN search, sub-query ranking support, flexible provisioning, new rank features, and telemetry export. It also introduces Vespa.ai Live, an in-person community meetup focused on retrieval and ranking systems. ### Source excerpt Advances in Vespa include time-constrained ANN search, sub-query ranking support, flexible provisioning, new rank features and telemetry export ## Nuxt co-creator Alexandre Chopin joins Encore DevFeed: [Nuxt co-creator Alexandre Chopin joins Encore]() Original publisher: [Read original article]() Author: Marcus Kohlberg Published: 2026-09-07T00:00:00Z Content type: news Language: en Sources: [Encore Updates]() Topics: [Provisioning](), [Cloud](), [Vue.js](), [Command-line interface](), [GitHub](), [Open Source](), [SDKs](), [AI-assisted coding]() Tags: [agentic-development](), [ai-agents](), [cli](), [developer](), [developer-relations](), [github](), [infrastructure](), [open-source](), [provisioning](), [sdk](), [teams](), [vue]() ### AI overview Encore announces that Alexandre Chopin, co-creator of Nuxt, has joined the company as Head of Developer Relations. He will work with developers and engineering teams and help shape Encore's roadmap around automated infrastructure. ### Source excerpt Alexandre joins as Head of Developer Relations to help bring automated infrastructure to more developers and teams. ## AgentOps: How to build AI agents at scale DevFeed: [AgentOps: How to build AI agents at scale]() Original publisher: [Read original article]() Author: Matar Peles Published: 2026-09-06T18:44:36Z Content type: tutorial Language: en Sources: [Developer Experience & Platform Engineering Blog | Port]() Topics: [AI Agent](), [Artificial Intelligence](), [Provisioning](), [Authorization](), [Cloud]() Tags: [agents](), [ai](), [ai-agents](), [best-practices](), [build-ai-agents](), [developer](), [how-to](), [platform](), [provisioning](), [workflow]() ### AI overview This article presents AgentOps as the practice of creating, running, and operating AI agents reliably in production and at scale. It recommends governing agents throughout their lifecycle, starting with an agent registry and a standardized golden-path workflow for creating new agents. The proposed workflow captures an agent's purpose and dependencies, obtains approval for sensitive access, creates scoped service accounts with minimum permissions, provisions the agent on a selected platform, and registers it. ### Source excerpt AgentOps is the practice of running AI agents reliably at scale. See what it covers, which teams own it, and where to start. ## From Bottleneck to Breakthrough: Centralizing GitOps at Enterprise Scale with VCF 9.1.1 DevFeed: [From Bottleneck to Breakthrough: Centralizing GitOps at Enterprise Scale with VCF 9.1.1]() Original publisher: [Read original article]() Author: vmwareblogs Published: 2026-09-03T14:03:46Z Content type: article Language: en Sources: [VMware Blogs]() Topics: [GitOps](), [Platform Engineering](), [CI/CD](), [Automation](), [Cloud](), [Provisioning](), [Tooling]() Tags: [argo-cd](), [automation](), [cloud-infrastructure](), [cloud-native](), [continuous-delivery](), [deployment](), [gitops](), [home-page](), [platform](), [platform-engineering](), [provisioning](), [self-service](), [vcf-9-1](), [vcf-automation](), [vmware](), [vmware-cloud-foundation]() ### AI overview This VMware article announces VCF 9.1.1, which introduces a native GitOps service for VCF Automation Org users in Tech Preview. By integrating Argo CD, the update aims to centralize declarative application delivery, continuous delivery pipelines, and lifecycle management at enterprise scale, reducing manual work and operational friction for platform engineering teams. ### Source excerpt In today's fast-paced digital economy, where AI-driven innovation demands unprecedented agility, IT leaders are tasked with more than just provisioning infrastructure; they are expected to deliver a frictionless, self-service platform that accelerates software delivery. For platform engineers, cloud architects, and IT executives, the goal is to bridge the gap between robust infrastructure and modern application ... Continued The post From Bottleneck to Breakthrough: Centralizing GitOps at Enterprise Scale with VCF 9.1.1 appeared first on VMware Blogs. ## Announcing native MySQL databases: Bring your MySQL workloads to Appwrite DevFeed: [Announcing native MySQL databases: Bring your MySQL workloads to Appwrite]() Original publisher: [Read original article]() Author: Jake Barnby Published: 2026-09-02T00:00:00Z Content type: release Language: en Sources: [Appwrite Blog]() Topics: [Appwrite](), [MySQL](), [Databases](), [Provisioning](), [Availability](), [Replication](), [autoscaling](), [TLS (Transport Layer Security)]() Tags: [announcements](), [autoscaling](), [availability](), [database](), [databases](), [mysql](), [provisioning](), [replication](), [tls]() ### AI overview Appwrite announces native managed MySQL databases that can run inside the same project as an application's existing backend. The service supports MySQL 8.4 and 8.0, standard drivers and ORMs, TLS, backups and point-in-time recovery, replicas with automatic failover, database branches, scaling, and connection pooling. ### Source excerpt Provision a managed MySQL 8.4 instance inside your Appwrite project and keep using the drivers, ORMs, and tools your applications already depend on. ## Compute that takes any shape DevFeed: [Compute that takes any shape]() Original publisher: [Read original article]() Author: Luke Phillips-Sheard Published: 2026-09-01T07:00:00Z Content type: article Language: en Sources: [Vercel News]() Topics: [Cloud](), [Provisioning](), [cloud-infrastructure](), [Vercel](), [cpu](), [IO](), [DRIVE]() Tags: [agent](), [cloud](), [code](), [compute](), [cpu](), [image](), [infrastructure](), [io](), [memory](), [pricing](), [real-time](), [sandbox](), [storage](), [vercel]() ### AI overview Vercel presents Fluid as a unified compute system that assembles machines for different workloads, changes configuration dynamically, and absorbs burst capacity in real time. It supports builds, sandboxes, and functions, using isolated virtual machines, custom images, and separate storage connections. ### Source excerpt Workloads differ in how long they run, how much memory they take, and how much of the environment they control. That previously meant a different compute primitive for each job, so product iterations required provisioning infrastructure, not just working on a feature. We built Vercel so that none of this has to be your problem. The compute layer is a single system with a simple job. Take any workload, assemble the machine it needs, swap configuration on the fly, and absorb burst capacity in real time. We call this Fluid. Builds ran on it first, then sandboxes, and now functions. If you've shipped on Vercel, you've been on Fluid without knowing it. Fluid compute now runs over 15 million builds a day, 25 million sandboxes a week, and a trillion requests a month. A history of compute Changing a machine used to mean changing it by hand. You went down to the computer store, bought a hard drive or a stick of RAM, and swapped it in yourself. Then you could rent bare metal when you needed it, and use it to serve a website, host a database, or send email. Then the cloud let you request a machine in any configuration you wanted, choose its operating system, use it, and throw it away when you were done. For agents, even the cloud is too slow. A standard VM can't provision fast enough to keep up with how they work, but this is where Fluid excels. How a workload runs on Fluid When a workload comes in, Fluid assembles a machine to fit its shape. If an agent needs to run code, Hive provides an isolated VM, usually one already warm, so it's ready instantly. Your own image boots on top as the environment. A Drive connects, and your files are right where you left them, because storage was never tied to the machine. Each workload needs something different. A build is compute-bound, so it wants a beefy machine, heavy on CPU and memory. A function is IO-bound, loading specific code to run the instant a request lands, usually on a small VM. A sandbox is flexibility-bound, taking whatever ## A new getting started experience for ClickHouse Managed Postgres DevFeed: [A new getting started experience for ClickHouse Managed Postgres]() Original publisher: [Read original article]() Author: Cristina Albu; Yashpreet Bathla Published: 2026-08-28T12:55:15Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [data](), [Provisioning](), [real-time](), [Replication](), [Databases](), [Command-line interface]() Tags: [analytics](), [cli](), [clickhouse](), [cloud](), [data](), [docs](), [getting-started](), [guide](), [onboarding](), [postgres](), [real-time](), [replication]() ### AI overview ClickHouse Managed Postgres introduces a four-step onboarding experience that guides users from provisioning a Postgres service to loading data, querying it, and replicating it to ClickHouse for real-time analytics. ### Source excerpt See how a four-step onboarding flow helps users move from provisioning ClickHouse Managed Postgres to querying operational data and running real-time analytics with ClickHouse. ## Closing the AI agent trust gap with graduated autonomy DevFeed: [Closing the AI agent trust gap with graduated autonomy]() Original publisher: [Read original article]() Author: Dev Arora Published: 2026-08-26T17:33:03Z Content type: article Language: en Sources: [AWS Architecture Blog]() Topics: [Artificial Intelligence](), [AI Agent](), [Authorization](), [Amazon Bedrock](), [Amazon Web Services](), [Large Language Model](), [tracing](), [configuration](), [Provisioning]() Tags: [agent](), [agents](), [ai](), [ai-agent](), [ai-agents](), [amazon](), [amazon-bedrock](), [amazon-bedrock-agentcore](), [api](), [aws](), [compliance](), [evaluation](), [infrastructure](), [large-language-model](), [logs](), [model](), [policy](), [production](), [thought-leadership](), [tracing]() ### AI overview This article presents graduated autonomy as an architectural pattern for closing the trust gap in AI agents. Agents gain permissions through sustained reliability and lose them when performance degrades, using trust scoring, autonomy tiers, pre- and post-execution controls, policy enforcement, provenance, reversibility, and delivery gates. The design uses Amazon Bedrock AgentCore, Amazon DynamoDB, and AWS CodePipeline. ### Source excerpt Most teams give AI agents either full access or read-only, leaving value unused or risk unmanaged. This post describes graduated autonomy, an architectural pattern in which agents earn expanded permissions through sustained reliability and lose them when performance degrades, built on Amazon Bedrock AgentCore, Amazon DynamoDB, and AWS CodePipeline. ## 9 things to consider before choosing an IaC platform in 2026 DevFeed: [9 things to consider before choosing an IaC platform in 2026]() Original publisher: [Read original article]() Author: Jonah Kowall Published: 2026-08-26T14:33:56Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Infrastructure as code](), [Architecture & Design](), [Provisioning](), [Cloud](), [Terraform]() Tags: [2026](), [ci](), [cloud](), [evaluation](), [iac](), [infrastructure](), [infrastructure-as-code](), [opentofu](), [policy](), [terraform](), [workflows]() ### AI overview This 2026 article presents nine considerations for evaluating an infrastructure as code platform. It emphasizes that mature IaC now involves coordinating changes, managing access, enforcing policies, reviewing infrastructure changes, and keeping environments synchronized--not only provisioning cloud resources. It recommends assessing whether a platform is necessary, examining its execution layer and scalability, testing it under concurrent workloads and failures, and ensuring that engineers beyond the platform builder can use it effectively. ### Source excerpt IaC platform evaluation in 2026: nine things to test, from execution and dependency handling to policy enforcement, support quality and AI workflows. ## Developer Self-Service Pipelines with Harness IDP DevFeed: [Developer Self-Service Pipelines with Harness IDP]() Original publisher: [Read original article]() Author: Rashmi Hegde Published: 2026-08-26T00:00:00Z Content type: article Language: en Sources: [Harness Blog]() Topics: [CI/CD](), [Deployment](), [Provisioning](), [Microservice]() Tags: [ci-cd](), [deployment](), [developer](), [idp](), [platform](), [provisioning](), [self-service]() ### AI overview This article explains how platform teams can connect Harness IDP self-service workflows to CI/CD and deployment pipelines. It covers triggering deployments, provisioning infrastructure, and managing promotion logic while preserving governance and operational consistency. ### Source excerpt Connect developer self-service to production with Harness IDP's pipeline integration. Automate deployments and boost velocity. Learn more. | Blog ## Fewer lockouts, less manual work: What's new for 1Password EPM admins DevFeed: [Fewer lockouts, less manual work: What's new for 1Password EPM admins]() Original publisher: [Read original article]() Author: info@1password.com (Jairo Camacho) Published: 2026-08-26T00:00:00Z Content type: release Language: en Sources: [Blog on 1Password Blog]() Topics: [Provisioning](), [Multi-tenancy](), [Entra ID](), [releases](), [Single sign-on (SSO)]() Tags: [documentation](), [entra-id](), [identity](), [integration](), [multi-tenancy](), [news](), [outage](), [releases](), [scale](), [security]() ### AI overview 1Password announces releases for EPM admins focused on reducing lockouts and automating provisioning at scale. The updates include Entra ID secret-expiration tracking with reminders and guided rotation, integration between Multi-Tenancy and Automated Provisioning, and Vault Migrations for populating shared vaults in linked accounts. ### Source excerpt As a company grows, more employees join, but the size of the IT team overseeing critical systems often doesn't grow at the same pace. Admins have to be intentional about prioritizing their efforts to meet the needs of a growing organization. That's why we're excited to announce several releases aimed at helping admins optimize their organization's use of 1Password in two important areas: reducing lockouts and automating provisioning at scale. Preventing avoidable lockouts Entra ID Secret Expiration Most 1Password Business accounts sign in via SSO through an identity provider like Microsoft Entra ID. Admins rely on a secret provisioned by Entra to establish connectivity with 1Password. However, it comes with an expiration date. Once it expires, the connection breaks, preventing anyone from signing in. This was one of the most common and disruptive patterns we'd observe with customers. Entra ID Secret Expiration now tracks it for you. Simply record the expiration date, and 1Password will send escalating reminders across in-app banners, emails, and login prompts at a fixed cadence (e.g., 90/60/30 days). Once it's time to rotate the secret, follow the guided flow in the Admin Console, confirm it's working as intended, and the countdown resets automatically. A predictable secret expiration date should never become an outage, and now it doesn't have to. Standing up new parts of the business quickly Multi-Tenancy and Automated Provisioning integration Earlier this year we released Multi-Tenancy and Automated Provisioning, hosted by 1Password, two critical features for admins to manage provisioning, deprovisioning, and parent/child accounts at scale. Now admins can use these features in tandem, so enterprises with multi-tenant setups can take advantage of Automated Provisioning. To get started, check out our detailed documentation for setting up the Multi-Tenancy and Automated Provisioning integration To get started, check out our detailed documentation for setting up the M ## Golden Paths for AI agents: What changes when platform users aren't human? DevFeed: [Golden Paths for AI agents: What changes when platform users aren't human?]() Original publisher: [Read original article]() Author: Candace Shamieh; Shlomo Benyaminov; James Eastham Published: 2026-08-25T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [Artificial Intelligence](), [Software Engineering](), [API](), [Low Latency](), [Provisioning](), [real-time]() Tags: [agent-observability](), [agentic](), [agents](), [ai](), [ai-agents](), [ai-security](), [api](), [autonomous](), [developers](), [engineering](), [how-to](), [latency](), [low-latency](), [platform](), [platform-engineering](), [real-time](), [sandbox](), [software-engineering](), [workflow](), [workflows]() ### AI overview Golden Paths for AI agents must evolve beyond human-oriented development workflows. The article explains how platform teams can design agent-facing paths around workload requirements, machine-consumable and enforceable platform capabilities, execution patterns, and controlled workflow dispatch. ### Source excerpt Golden Paths for AI agents require intentional execution patterns, machine-consumable contracts, and dispatch controls. Here's how to build them. ## Scale software delivery pipelines in isolation without owning the runner fleet DevFeed: [Scale software delivery pipelines in isolation without owning the runner fleet]() Original publisher: [Read original article]() Author: Kyurim Rhee Published: 2026-08-25T00:00:00Z Content type: article Language: en Sources: [GitLab]() Topics: [ci](), [GitLab](), [Software as a service](), [Security](), [cloud-infrastructure](), [Provisioning]() Tags: [agentic](), [ci](), [compliance](), [cost](), [developers](), [devsecops-platform](), [infrastructure](), [operations](), [platform](), [product](), [saas](), [scale](), [security](), [software-delivery](), [workflows]() ### AI overview GitLab presents Hosted Runners for GitLab Dedicated, a fully managed CI execution SaaS offering with isolated runner infrastructure. Each job runs in a newly provisioned VM that is deleted after completion, helping enterprises address security, compliance, scalability, reliability, and runner-operations demands without owning the runner fleet. ### Source excerpt Many enterprises choose GitLab Dedicated for a clear reason: a secure and compliant, single-tenant GitLab instance, managed by GitLab. As agentic workflows drive more pipeline volume, full data isolation and runner infrastructure operational burden become a challenge. This leads to the question, "Does owning the runner fleet still make sense?" With GitLab Dedicated, there is no more need to provision, patch, build, and scale your own runner fleet. Hosted Runners for GitLab Dedicated handles the heavy lifting and delivers a seamless experience across the entire software development lifecycle so your team can focus on shipping. Hosted Runners for GitLab Dedicated provides a runner fleet isolated from other customers. To support job-level security, each job runs in a newly provisioned, isolated VM that is deleted after the job completes. We provide a scalable and highly reliable runner fleet to support your bursty CI demands and resiliency needs. Creating and managing runners is self-serviceable through Switchboard (GitLab Dedicated management console). The runner ownership trade-off: Cost vs. user experience Pipeline load can be unpredictable. To account for this, runner infrastructure can be over-provisioned to give developers the best experience and maintain low wait times. But this drives up the infrastructure cost. Conversely, under-provisioning can save on infrastructure cost, but your developers will waste time waiting for their CI jobs to be picked up. Efforts to fine-tune this balance can monopolize your platform team's time. Shift runner operations to GitLab while maintaining control Hosted Runners for GitLab Dedicated is a fully managed CI execution SaaS offering. It's backed by a high-performing and reliable runner infrastructure. Key benefits include: Supports compliance: Full isolation/single-tenant runners with same data residency as GitLab Dedicated. Job level security: "One runner for one job" -- hosted runners run every job in a standalone, short-lived ## Maximizing AI Factory Performance per Watt with NVIDIA DSX MaxLPS DevFeed: [Maximizing AI Factory Performance per Watt with NVIDIA DSX MaxLPS]() Original publisher: [Read original article]() Author: Tanya Lenz Published: 2026-08-24T15:00:00Z Content type: article Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [AI Factory](), [Artificial Intelligence](), [Optimization](), [datacenter](), [GPU](), [Inference](), [Nvidia](), [Provisioning](), [systems]() Tags: [ai](), [ai-factory](), [ai-inference](), [compute](), [data-center](), [data-center-cloud](), [dsx](), [efficiency](), [gpu](), [inference](), [infrastructure](), [nvidia](), [nvidia-dsx](), [optimization](), [performance](), [scale](), [tokens](), [vera-rubin-nvl72]() ### AI overview NVIDIA DSX MaxLPS is presented as a suite of chip, thermal, system, and software technologies for increasing AI factory throughput within a fixed power budget. The article emphasizes application-level performance per watt, dynamic power allocation, software power optimization, and warm-water liquid cooling as ways to convert more site power into AI inference output. ### Source excerpt AI factories are power-constrained industrial systems. The question is no longer how many GPUs fit in a data center, but how much AI output each available... [Next page]()