# Integration Published articles for Integration. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Mem0 joins the Vercel Marketplace DevFeed: [Mem0 joins the Vercel Marketplace]() Original publisher: [Read original article]() Author: Tony Pan Published: 2026-09-16T17:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Vercel](), [Artificial Intelligence](), [App](), [context](), [API keys](), [Command-line interface](), [Environment Variables]() Tags: [ai](), [ai-agents](), [app](), [billing](), [cli](), [context](), [environment-variables](), [free](), [giving](), [install](), [integration](), [vercel](), [volume]() ### AI overview Mem0 is now a native integration on the Vercel Marketplace, providing long-term memory for AI agents and apps across sessions. The integration includes billing through Vercel, automatic provisioning of a scoped Mem0 project and API key, and environment-variable configuration. Mem0 offers a free plan with usage limits and a $20-per-month plan for higher volume. ### Source excerpt Mem0 is now available as a native integration on the Vercel Marketplace, giving your AI agents and apps long-term memory. Mem0 remembers user preferences, facts, and context across sessions, so your app stops starting from scratch. Install from the Marketplace with integrated billing on your Vercel invoice, no separate account or key management. A scoped Mem0 project and API key are provisioned automatically and added to your project as environment variables, including MEM0_API_KEY. Mem0 offers a free plan with usage limits and a $20 per month plan for higher volume. To see it end to end, deploy the eve Memory Agent template, an eve agent with long-term memory powered by Mem0. Get started with Mem0 on the Vercel Marketplace or through the Vercel CLI, available to customers on all plans. Read more ## Switching to Slack DevFeed: [Switching to Slack]() Original publisher: [Read original article]() Author: Khan Academy Published: 2015-11-09T23:00:00Z Content type: article Language: en Sources: [Khan Academy]() Topics: [Slack](), [migration](), [notifications](), [systems](), [Documentation]() Tags: [administration](), [chat](), [connectivity](), [delivery](), [documentation](), [engineering](), [infrastructure](), [integration](), [migrate](), [news](), [notifications](), [organization](), [remote](), [slack](), [switching](), [team]() ### AI overview Khan Academy describes its decision to migrate team chat from HipChat to Slack after connectivity, message delivery, and notification problems affected reliability, especially for remote workers. The article outlines cultural, administrative, organizational, and integration-related costs that make chat-platform migration difficult. ### Source excerpt By Benjamin Pollack Khan Academy recently made the decision to migrate our team chat from HipChat to Slack. ... Read more ## Optimizing cost and latency with Amazon Bedrock prompt caching DevFeed: [Optimizing cost and latency with Amazon Bedrock prompt caching]() Original publisher: [Read original article]() Author: Daniel Abib Published: 2026-09-15T16:18:19Z Content type: tutorial Language: en Sources: [Artificial Intelligence]() Topics: [Amazon Bedrock](), [Caching](), [Latency](), [API](), [foundation-models](), [LangChain](), [Multi-tenancy]() Tags: [advanced-300](), [amazon-bedrock](), [api](), [caching](), [foundation-models](), [integration](), [langchain](), [latency](), [pricing](), [technical-how-to](), [tokens]() ### AI overview This AWS post explains how Amazon Bedrock prompt caching can reduce repeated input-token costs by up to 90 percent and lower time to first token when requests reuse the same context. It presents six scenarios using the Converse API, including document, system prompt, tool definition, mixed TTL, tenant-isolated, and LangChain caching. ### Source excerpt Prompt caching in Amazon Bedrock can cut input token costs by up to 90% when you repeatedly send the same context to foundation models. This post walks through six practical prompt caching scenarios using the Converse API: message content, system prompt, tool definition, mixed TTL, tenant isolation, and LangChain integration. ## Thinking Like A Naturalist: An Interview with Claire Barrett DevFeed: [Thinking Like A Naturalist: An Interview with Claire Barrett]() Original publisher: [Read original article]() Author: J Simpson Published: 2026-09-15T07:00:00Z Content type: article Language: en Sources: [Nordic APIs]() Topics: [Artificial Intelligence](), [systems](), [Testing]() Tags: [2026](), [ai](), [ai-agents](), [ai-readiness](), [api-governance](), [api-integration](), [api-security](), [artificial-intelligence](), [awareness](), [blog](), [digital-transformation](), [driving](), [generative-ai](), [governance](), [integration](), [summit](), [systems](), [testing]() ### AI overview Claire Barrett discusses the mindset shift needed for AI-enabled strategies, emphasizing systems thinking, governance, testing, awareness, and attention to long-term risks. ### Source excerpt Ahead of Nordic APIs Summit 2026, we catch up with speaker Claire Barrett on the mindset shift needed for adopting AI-enabled strategies. "Imagine driving around an old town," responds Claire Barrett when asked to describe what it means to be AI-ready from an integration perspective. "Imagine a European city that's been inhabited for thousands of ... ## How to Use Differential Testing During a Legacy Migration DevFeed: [How to Use Differential Testing During a Legacy Migration]() Original publisher: [Read original article]() Author: Hugo Teijiz Published: 2026-09-14T16:25:50Z Content type: tutorial Language: en Sources: [freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More]() Topics: [migration](), [Testing](), [TypeScript](), [Integration testing](), [API](), [observability](), [Artificial Intelligence]() Tags: [ai](), [api](), [architecture](), [artificial-intelligence](), [code](), [how-to](), [integration](), [legacy-code](), [legacy-modernization](), [migration](), [modernization](), [observability](), [software-architecture](), [software-testing](), [testing](), [tests](), [tutorial](), [typescript]() ### AI overview This tutorial explains how to use differential testing during a legacy migration by running old and new implementations with identical inputs and comparing their behavior. It covers equivalence rules, output normalization, nondeterministic values, errors, side effects, automated testing, mismatch analysis, production shadow traffic, and using AI to classify divergences without allowing it to determine correctness. ### Source excerpt The most dangerous moment in a legacy migration isn't necessarily when you start writing the new implementation. It's when the new implementation looks finished. The code compiles, the tests pass, the ## 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. ## How to Connect to HMRC's Making Tax Digital API: A Beginner's Guide DevFeed: [How to Connect to HMRC's Making Tax Digital API: A Beginner's Guide]() Original publisher: [Read original article]() Author: Solomon Amos Published: 2026-09-11T22:10:33Z Content type: tutorial Language: en Sources: [freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More]() Topics: [API](), [Security, Privacy and Abuse Prevention]() Tags: [api](), [apis](), [code](), [guide](), [hmrc](), [hmrc-tax-filing](), [hmrc-tax-returns](), [how-to](), [integration](), [mtd](), [node](), [oauth](), [tax](), [tax-return](), [typescript]() ### AI overview A beginner-friendly guide to connecting software to HMRC's Making Tax Digital API. It explains the MTD context, sandbox setup, OAuth 2.0 authentication, fraud prevention headers, and authenticated API calls using Node and TypeScript. ### Source excerpt If you write software for anyone who pays UK tax, sooner or later you'll need to talk to HMRC. Making Tax Digital (MTD) for Income Tax went live on 6 April 2026, and it's already mandatory for self-em ## The hard part of an MCP gateway is auth DevFeed: [The hard part of an MCP gateway is auth]() Original publisher: [Read original article]() Author: WorkOS Published: 2026-09-11T15:22:28Z Content type: opinion Language: en Sources: [WorkOS Blog]() Topics: [MCP Server](), [Authorization](), [Model Context Protocol](), [Artificial Intelligence]() Tags: [audit](), [auth](), [github](), [integration](), [mcp](), [mcp-gateway](), [mcp-server](), [salesforce](), [scopes](), [slack](), [warehouse]() ### AI overview The article examines Sierra's internal MCP gateway and argues that its most difficult challenges are authentication, identity, per-tool scopes, consent, and audit rather than MCP protocol design. It also discusses integration work and the lack of standardized gateway behavior. ### Source excerpt Sierra's MCP gateway iceberg is a field report on agent auth: identity, per-tool scopes, consent, and audit are the submerged mass, and they ship off the shelf. ## Run DuckDB analytics on your Amazon DynamoDB data with zero-ETL DevFeed: [Run DuckDB analytics on your Amazon DynamoDB data with zero-ETL]() Original publisher: [Read original article]() Author: Lee Hannigan Published: 2026-09-11T14:53:57Z Content type: tutorial Language: en Sources: [AWS Database Blog]() Topics: [Databases](), [Amazon S3](), [Apache Iceberg](), [AWS Lambda](), [AWS IAM](), [Latency]() Tags: [advanced-300](), [amazon-dynamodb](), [amazon-s3-tables](), [analytics](), [apache-iceberg](), [aws-lambda](), [duckdb](), [how-to](), [iam](), [integration](), [sql](), [technical-how-to]() ### AI overview This tutorial explains how to run ad hoc SQL analytics on Amazon DynamoDB data with DuckDB through a zero-ETL replication flow. ### Source excerpt Run ad hoc SQL analytics on your Amazon DynamoDB data with DuckDB. A zero-ETL integration replicates your table into Apache Iceberg tables on Amazon S3 Tables, and an AWS Lambda function running DuckDB serves SQL queries through an IAM-authorized function URL. ## PayZephyr: One Payment API for Stripe, Paystack, and PayPal DevFeed: [PayZephyr: One Payment API for Stripe, Paystack, and PayPal]() Original publisher: [Read original article]() Author: Paul Redmond Published: 2026-09-11T01:46:25Z Content type: tutorial Language: en Sources: [Laravel]() Topics: [Laravel](), [API](), [stripe]() Tags: [api](), [checkout](), [failover](), [installation](), [integration](), [laravel](), [laravel-packages](), [payment](), [payments](), [production](), [protection](), [providers](), [stripe](), [subscription](), [webhooks]() ### AI overview PayZephyr is a Laravel payments package that provides one API for eight payment providers. It supports automatic failover, double-charge protection, signed webhooks, subscriptions, refunds, Composer installation, custom drivers, queue integration, and a playground. ### Source excerpt PayZephyr gives Laravel one payment API across Stripe, PayPal, Paystack, Flutterwave, and four more, with failover and double-charge protection. The post PayZephyr: One Payment API for Stripe, Paystack, and PayPal appeared first on Laravel News. Join the Laravel Newsletter to get Laravel articles like this directly in your inbox. ## How to calculate DevOps platform total cost of ownership DevFeed: [How to calculate DevOps platform total cost of ownership]() Original publisher: [Read original article]() Author: GitLab Published: 2026-09-11T00:00:00Z Content type: tutorial Language: en Sources: [GitLab]() Topics: [CI/CD]() Tags: [ai](), [ci-cd](), [complexity](), [compute](), [cost](), [devops](), [devsecops](), [devsecops-platform](), [drivers](), [how-to](), [infrastructure](), [integration](), [model](), [platform](), [reduce](), [software-delivery](), [tools]() ### AI overview A guide to modeling the total cost of ownership of a DevOps platform, including subscriptions, CI/CD compute, AI usage, infrastructure, tools, and internal labor. ### Source excerpt There's nothing like budget pressure to put your DevOps platform under a microscope. But subscription fees and license costs only tell one part of the story. The total cost of ownership (TCO) for a DevOps platform also includes variable costs like CI/CD compute and AI usage, along with the infrastructure, tools, and employee time required to keep software delivery moving. That wider view matters when you're tasked with defending platform spend or comparing options with a head of finance. Designing a useful TCO model can: Make those costs transparent for stakeholders Shine a light on the reasoning (or lack thereof) behind each cost Identify areas to reduce spend without negatively impacting software delivery What total cost of ownership really includes The core challenge of calculating TCO is that DevOps platforms package and price capabilities differently. For example, one platform may bundle CI/CD or AI capabilities into a per-seat subscription, while another could price usage separately. A third may appear less expensive upfront but require additional tools and ongoing integration work. That's why list prices or pricing tiers alone won't give you a useful comparison. Start with the capabilities and workloads your organization actually needs, then calculate what it takes to support them on each platform. Use the same scope and time period for every option -- often one year -- and define which teams, applications, environments, and delivery stages are included. Separate recurring costs from one-time expenses and external spend from internal labor, so finance can audit the assumptions and forecast future years. A useful TCO model, therefore, answers two questions: What does it cost to meet our requirements today? Which variables will cause that cost to rise or fall as our usage changes? The cost categories that drive your bill Most DevOps platform costs fit into the following categories: Cost categoryWhat it includesMain cost driverPlatform accessPaid seats, role-based ## Backblaze B2 and WEKA NeuralMesh Validated as a Two-Tier AI Storage Pipeline, With Snap-to-Object Checkpoints in B2 DevFeed: [Backblaze B2 and WEKA NeuralMesh Validated as a Two-Tier AI Storage Pipeline, With Snap-to-Object Checkpoints in B2]() Original publisher: [Read original article]() Author: Harold Fritts Published: 2026-09-10T20:40:57Z Content type: news Language: en Sources: [StorageReview.com]() Topics: [AI Infrastructure](), [cloud-infrastructure](), [Cloud](), [data-processing](), [model-deployment]() Tags: [accelerators](), [ai](), [ai-infrastructure](), [cloud](), [cloud-storage](), [data](), [datasets](), [enterprise](), [inference](), [infrastructure](), [integration](), [performance](), [snapshots](), [storage]() ### AI overview Backblaze and WEKA validated a two-tier AI storage pipeline that uses WEKA NeuralMesh as the high-performance tier for GPU workloads and Backblaze B2 Cloud Storage as the capacity tier. Raw data, training sets, media, source files, checkpoints, and other assets can move between the tiers according to access needs. NeuralMesh's Snap-to-Object feature was also tested with B2 for storing consistent filesystem snapshots and supporting recovery. ### Source excerpt Backblaze and WEKA have validated their two platforms together for AI pipelines, pairing WEKA NeuralMesh as the performance tier that feeds GPUs with Backblaze B2 Cloud Storage as the capacity tier that holds everything else. The integration, sizing, tuning, and testing are already done, so an AI infrastructure team can deploy a proven two-tier layout The post Backblaze B2 and WEKA NeuralMesh Validated as a Two-Tier AI Storage Pipeline, With Snap-to-Object Checkpoints in B2 appeared first on StorageReview.com. ## "Six tools, one harness": Salesforce loops together a six-pack of favorites DevFeed: ["Six tools, one harness": Salesforce loops together a six-pack of favorites]() Original publisher: [Read original article]() Author: Adrian Bridgwater Published: 2026-09-10T20:03:25Z Content type: article Language: en Sources: [The New Stack]() Topics: [Architecture & Design](), [Orchestration](), [data-architecture](), [Vibe coding](), [Claude](), [SDKs]() Tags: [agent](), [ai](), [ai-agents](), [api](), [claude](), [data](), [enterprise](), [integration](), [orchestration](), [salesforce](), [security](), [vibe-coding]() ### AI overview Salesforce introduced an Enterprise AI Harness that combines platform capabilities through a common, composable architecture and an AI control plane. The article describes its use of data, integration, APIs, agent orchestration, analytics, security and compliance to reduce siloed enterprise automation. ### Source excerpt Salesforce introduced its Salesforce Enterprise AI Harness on Thursday as a formalized amalgamation of the AI harness concepts and infrastructure The post "Six tools, one harness": Salesforce loops together a six-pack of favorites appeared first on The New Stack. ## High-Throughput Structure Prediction with BioNeMo Inference Runtime DevFeed: [High-Throughput Structure Prediction with BioNeMo Inference Runtime]() Original publisher: [Read original article]() Author: Elizabeth Goodman Published: 2026-09-10T15:00:00Z Content type: tutorial Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [AI, ML & Data Engineering]() Tags: [bionemo](), [cuda](), [cuda-graphs](), [data-center-cloud](), [data-science](), [drug-discovery](), [gpu](), [healthcare-life-sciences](), [how-to](), [hpc-scientific-computing](), [inference](), [integration](), [kernels](), [model](), [models](), [node](), [nvidia](), [python](), [pytorch](), [resource](), [scale](), [simulation-modeling-design](), [tokenization](), [torch](), [tutorial](), [workflow]() ### AI overview A tutorial on using NVIDIA BioNeMo Inference Runtime to accelerate biomolecular structure-prediction models on GPUs. It covers the end-to-end Boltz2 workflow, PyTorch integration, input requirements, and Ray-based single-node throughput scaling. ### Source excerpt Biomolecular structure prediction is now often run at proteome scale, where the goal is to move an entire worklist through the pipeline efficiently. NVIDIA... ## Honoring #IconsOfQuality: Keith Klain DevFeed: [Honoring #IconsOfQuality: Keith Klain]() Original publisher: [Read original article]() Author: Rajrupa Roychowdhury Published: 2026-09-10T11:56:43Z Content type: article Language: en Sources: [BrowserStack Blog]() Topics: [Testing](), [Artificial Intelligence](), [systems](), [Software]() Tags: [ai](), [community](), [enterprise](), [financial-services](), [icons-of-quality](), [infrastructure](), [insights](), [integration](), [keynote](), [leadership](), [operational](), [quality-engineering](), [systems](), [technology](), [testing](), [thought-leadership](), [uk]() ### AI overview BrowserStack profiles Keith Klain as an influential figure in software quality and testing. The article highlights his work in AI assurance, quality engineering, operational risk, systems thinking, and strategic enterprise transformation, along with his contributions to the testing community and thought leadership. ### Source excerpt To celebrate the relentless passion and invaluable contributions of leaders in software quality, BrowserStack is proud to honour Icons of Quality. ## Tako Search is free on AI Gateway through September 30 DevFeed: [Tako Search is free on AI Gateway through September 30]() Original publisher: [Read original article]() Author: Jerilyn Zheng Published: 2026-09-10T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [vercel ai sdk](), [SDKs](), [API](), [Web](), [data]() Tags: [ai](), [ai-gateway](), [api](), [configuration](), [documentation](), [free](), [integration](), [playground](), [sdk](), [search](), [tools](), [web]() ### AI overview This changelog announces that Tako Search is free on AI Gateway through September 30. It enables AI models to search curated data and the live web, filter results, and provide current answers with citations and visualizations. Tako Search works with any model on AI Gateway and does not require a separate Tako account or API key. ### Source excerpt Tako Search is free exclusively on AI Gateway through September 30. It lets AI models search Tako's curated data and the live web, filter web results by domain or publication date, and use the results to answer questions with current information, citations, and visualizations. After September 30, searches are billed at standard rates. The same integration works with any model on AI Gateway, so you can switch models without changing your search setup. You also don't need a separate Tako account or API key. To use Tako Search with the AI SDK, add gateway.tools.takoSearch() to a generateText or streamText request. The model can then call it when it needs current information: Try Tako Search in the AI Gateway playground. See the web search documentation for configuration and search options. Read more ## Build with OpenAI Agents API on Vercel DevFeed: [Build with OpenAI Agents API on Vercel]() Original publisher: [Read original article]() Author: Allen Zhou Published: 2026-09-10T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [AI Bots]() Tags: [agent](), [agents](), [api](), [architecture](), [code](), [guide](), [integration](), [openai](), [sandbox](), [scale](), [tool](), [vercel]() ### AI overview Vercel now supports building and deploying long-running, tool-using agents with the OpenAI Agents API. OpenAI manages agent loops and session state, while Vercel provides hosted applications, Sandbox execution, persistent workspaces, webhook and queue integration, and scale-to-zero operation. ### Source excerpt You can now build and deploy long-running, tool-using agents with the OpenAI Agents API on Vercel. OpenAI manages the agent loop and session state, while Vercel hosts the application and connects each session to Vercel Sandbox for code execution and file access. With this integration, you get: An OpenAI-managed agent loop and session state Reliable Sandbox creation and reconnection through signed OpenAI webhooks and Vercel Queues An isolated execution environment for every agent session A persistent workspace that retains files across follow-up instructions A scale-to-zero architecture without an always-on worker Follow the step-by-step guide to build and deploy an agent, or explore the sample application. Read more ## Cisco and Axis Communications: Greater visibility, scalability, and incident management DevFeed: [Cisco and Axis Communications: Greater visibility, scalability, and incident management]() Original publisher: [Read original article]() Author: Jonathan Cohn Published: 2026-09-09T15:00:31Z Content type: news Language: en Sources: [Cisco Blogs]() Topics: [incident management](), [dashboards](), [interoperability](), [Security](), [Scalability](), [Cloud]() Tags: [boot](), [cisco-networking](), [cloud](), [encryption](), [incident-management](), [integration](), [interoperability](), [networking](), [security]() ### AI overview Cisco and Axis Communications are integrating Axis devices with Cisco Cloud Control through the Meraki dashboard. The integration gives IT and physical security teams centralized visibility into device health, firmware, patches, and connectivity while supporting secure, privacy-focused management across connected locations. ### Source excerpt Cisco and Axis Communications now allow managing Axis devices directly via the Meraki dashboard. This integration unifies IT and physical security, providing centralized visibility and simplified operations on a single, scalable platform. ## Introducing Consort: Test-driven development on a branching database DevFeed: [Introducing Consort: Test-driven development on a branching database]() Original publisher: [Read original article]() Author: Kevin Hartman Published: 2026-09-09T13:41:25Z Content type: article Language: en Sources: [Databricks]() Topics: [Test-driven development](), [Database](), [Integration testing](), [Software Engineering](), [Refactoring](), [Continuous Delivery (CD)](), [Pull Request](), [Reverse Engineering]() Tags: [code](), [continuous-delivery](), [database](), [development](), [integration](), [partners](), [platform](), [postgres](), [pull-request](), [refactoring](), [reverse-engineering](), [software](), [software-development](), [testing]() ### AI overview The article introduces Consort, a workflow for applying test-driven development to a branching database. It argues that copy-on-write branches of a real database can replace mocks, bring integration testing into the inner development loop, and let engineers run destructive tests in isolation. Versioned schema migrations can move with the dependent code, enabling what the article calls Data CD and helping catch production database problems during pull requests and merges. ### Source excerpt For 25 years I built software on the practices I grew up with: Kent Beck's TDD, Martin... ## v0 adds one-click integrations for email, auth, search, and databases DevFeed: [v0 adds one-click integrations for email, auth, search, and databases]() Original publisher: [Read original article]() Author: Jathin Singaraju Published: 2026-09-09T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [AI Chat]() Tags: [agent-skills](), [auth](), [code](), [databases](), [integration](), [react](), [search](), [skills](), [vercel]() ### AI overview Vercel's v0 adds inline Marketplace integrations for providers including Resend, Amazon OpenSearch, MongoDB Atlas, Algolia, and Clerk. Connected providers can be configured automatically, and provider skills can guide generated code. ### Source excerpt We're working toward bringing parity across Vercel integration and v0, starting with Resend, Amazon OpenSearch, MongoDB Atlas, Algolia and Clerk. Prompt v0 with what you want to build, and when your prompt requires a provider, v0 renders a connect card in the chat. With Marketplace integrations in v0, you get: Connect as you build: Prompt v0 with what you want to create, and connect the required provider inline. Automatic setup: Once connected, v0 handles the required environment variables and configuration. Provider skills loaded automatically: When you connect a provider that publishes agent skills, v0 loads them and generates code that follows the provider's recommended patterns. Provider-specific capabilities: Resend, for example, adds transactional email with React Email components. To get started, open a v0 chat and prompt what you want to add to your stack. Read more ## From AI Agent to Human Agent: ElevenLabs Call Handoffs with Twilio DevFeed: [From AI Agent to Human Agent: ElevenLabs Call Handoffs with Twilio]() Original publisher: [Read original article]() Author: Ricardo Bangueses Published: 2026-09-09T00:00:00Z Content type: tutorial Language: en Sources: [Twilio Blog]() Topics: [Conversational AI](), [voice ai](), [interoperability]() Tags: [ai-agent](), [developer-insights](), [how-to](), [integration](), [interoperability](), [voice]() ### AI overview This tutorial explains how to integrate an ElevenLabs voice agent with Twilio Programmable Voice so the agent can escalate an active call to human-agent routing while preserving call control and useful context. The example uses Twilio Flex as the destination. ### Source excerpt Learn how to integrate an ElevenLabs voice agent with Twilio Programmable Voice for seamless AI-to-human call handoffs, preserving context and call control. ## Kubernetes v1.37: Advancing Workload-Aware Scheduling DevFeed: [Kubernetes v1.37: Advancing Workload-Aware Scheduling]() Original publisher: [Read original article]() Published: 2026-09-08T18:30:00Z Content type: release Language: en Sources: [Kubernetes Blog]() Topics: [releases]() Tags: [api](), [batch](), [go](), [integration](), [kubernetes](), [release]() ### AI overview Kubernetes v1.37 advances workload-aware scheduling by promoting Workload and PodGroup APIs, gang scheduling, workload-aware preemption, and shared DRA ResourceClaims for PodGroups to Beta. It also introduces CompositePodGroup and controller integration APIs for complex distributed and batch workloads. ### Source excerpt AI/ML and complex batch workloads continue to push the boundaries of Kubernetes scheduling. Following the foundational workload-centric enhancements introduced in previous releases, Kubernetes v1.37 delivers the next major milestone in the Workload-Aware Scheduling (WAS) journey. In this release, the core Workload and PodGroup APIs--enabling gang scheduling--along with Workload-Aware Preemption (WAP) and shared DRA ResourceClaims for PodGroups, all graduate to Beta, solidifying their role in the Kubernetes ecosystem. To address the hierarchical scheduling requirements of modern high-performance distributed workloads, v1.37 introduces the new CompositePodGroup API. This new API allows expressing multi-level topology constraints, gang scheduling, and preemption policies for complex, heterogeneous groups of Pods. Crucially, this architectural expansion unlocks native scheduling support for advanced workload structures commonly managed by higher-order extension APIs such as JobSet and LeaderWorkerSet (LWS). Alongside these API additions, v1.37 focuses on streamlining adoption by introducing a new set of controller integration APIs and the workloadbuilder Go library. These provide standardized building blocks that significantly simplify how out-of-tree controllers can integrate with WAS capabilities. Utilizing these new tools, the native Job controller integration has been upgraded to fully consume the expanded WAS APIs--enabling advanced scheduling policies, flexible disruption modes, and topology-aware scheduling for standard batch workloads. Gang scheduling and Workload / PodGroup APIs Kubernetes v1.37 delivers a major milestone: Workload / PodGroup APIs and gang scheduling are officially graduating to Beta. This graduation signals that native, "all-or-nothing" scheduling for workloads is solidifying for wider adoption. Key updates to the API and gang scheduling algorithm in this release include: Beta graduation and API versioning changes The core Workload and PodGroup A ## Build custom workflows with Cypress Cloud Webhooks DevFeed: [Build custom workflows with Cypress Cloud Webhooks]() Original publisher: [Read original article]() Published: 2026-09-08T17:17:31Z Content type: tutorial Language: en Sources: [Cypress Blog]() Topics: [Cypress](), [Cloud](), [Automation](), [Messaging](), [GitHub](), [Google Chat](), [Slack]() Tags: [automation](), [cypress](), [github](), [how-to](), [integration](), [integrations](), [mcp](), [slack]() ### AI overview This tutorial introduces Cypress Cloud webhooks for building custom automation workflows. It explains how webhooks can deliver run results and metadata to external systems, trigger actions based on test outcomes, customize notifications, and reduce routine CLI or MCP requests when analyzing runs with AI tools. ### Source excerpt Webhooks are a new addition to Cypress Cloud, supporting more flexible automation workflows beyond what is built into the platform itself. Learn why we've added them and how to get started using them in your project. Integration support in Cypress Cloud Cypress Cloud supports a wide range of integrations out of the box. If you need a GitHub status check for every group of tests in your test run, we've got you covered. Slack and Teams messages when a run fails? That's there, along with deskto ## Kubernetes access via an identity provider: Public client, not confidential DevFeed: [Kubernetes access via an identity provider: Public client, not confidential]() Original publisher: [Read original article]() Author: Kolawole Olowoporoku | CNCF Ambassador and Senior Platform Engineer Published: 2026-09-08T11:30:00Z Content type: tutorial Language: en Sources: [Cloud Native Computing Foundation]() Topics: [Kubernetes](), [Authorization](), [client]() Tags: [api](), [architecture](), [authentication](), [blog](), [browser](), [iam](), [identity](), [integration](), [kubernetes](), [on-prem](), [operations]() ### AI overview The article explains how to replace static Kubernetes credentials with identity-provider login using a public OIDC client and PKCE. It describes kubectl with kubelogin, Keycloak, kube-apiserver token validation, and RBAC-based access decisions. ### Source excerpt Access control belongs on the same day-zero checklist as networking and storage. On most on-prem clusters, it never makes the list. The Identity Gap Managed cloud Kubernetes ships IAM or SSO integration out of the box.... [Next page]()