# Scalability A computing system's ability to handle varying workloads by adding or removing resources. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## How Khan Academy Scaled to 2.5x Traffic During the Coronavirus Pandemic DevFeed: [How Khan Academy Scaled to 2.5x Traffic During the Coronavirus Pandemic]() Original publisher: [Read original article]() Author: Khan Academy Published: 2020-05-09T22:00:00Z Content type: article Language: en Sources: [Khan Academy]() Topics: [Scalability](), [Architecture & Design](), [Serverless](), [Caching](), [Google Cloud Platform (GCP)](), [Load Balancing]() Tags: [architecture](), [caching](), [cdn](), [engineering](), [gcp](), [google-cloud](), [load-balancing](), [news](), [scalability](), [serverless](), [web]() ### AI overview Marta Kosarchyn explains how Khan Academy handled site usage reaching 2.5 times the previous year's level during the coronavirus pandemic. The article attributes the scalability to Google Cloud services, serverless infrastructure, Datastore, Memcache, Fastly CDN caching, and advance preparation. ### Source excerpt By Marta Kosarchyn Talk about rapid scaling... A few months ago I posted some thoughts on scaling and ... Read more ## ML based ranking using Nrtsearch DevFeed: [ML based ranking using Nrtsearch]() Original publisher: [Read original article]() Author: Mohammad Mohtasham (Software Engineer); Tao Yu (Software Engineer) Published: 2026-09-16T00:00:00Z Content type: article Language: en Sources: [Yelp]() Topics: [Inference](), [Scalability](), [Latency](), [recommendation systems](), [Open Source]() Tags: [bridge](), [inference](), [machine-learning](), [overhead](), [performance](), [pipeline](), [scalability](), [service]() ### AI overview Yelp's Nrtsearch Inference Plugin embeds machine-learning ranking directly in the search layer. The article explains the scoring workflow, including model configuration, feature extraction, candidate ranking, and application-specific business logic. It describes how co-locating feature storage and inference reduces network transfer, serialization overhead, and latency compared with a standalone inference service. ### Source excerpt We've extended Nrtsearch with the Inference Plugin, which embeds ML-based ranking directly in the search layer -- eliminating the need for a standalone scoring service. We use Nrtsearch (read more information on the blog post), a Lucene-based open-source search engine built by Yelp, to power a variety of applications such as business search, reviews search, ad delivery and photo search. In this blog post, we give a high-level overview of the Machine Learning (ML) based scoring workflow in Nrtsearch. We'll show how ML models are configured and loaded, and how different applications use custom business logic to develop, test, and... ## Performance improvements in Percona Server 8.4.11-11 DevFeed: [Performance improvements in Percona Server 8.4.11-11]() Original publisher: [Read original article]() Author: Bogdan Degtyariov Published: 2026-09-15T11:52:54Z Content type: article Language: en Sources: [Blog - Percona]() Topics: [Percona Server for MySQL](), [Percona](), [MySQL](), [Cache](), [Scalability](), [Database]() Tags: [benchmark](), [benchmarks](), [cache](), [io](), [mysql](), [percona](), [percona-server-for-mysql](), [performance](), [scalability]() ### AI overview This article describes performance and scalability improvements in Percona Server for MySQL 8.4.11-11, focusing on changes to the InnoDB buffer pool and page flushing. It explains how narrowing mutex coverage and using finer-grained latching allows physical reads to proceed more in parallel, particularly for read-heavy, I/O-bound workloads. ### Source excerpt Focusing on Percona Server 8.4.11-11 My previous post (Performance Progression of Percona Server for MySQL 8.4) did a brief review of the performance changes in Percona Server for MySQL 8.4 released in 2026. I recommend reading it first to better understand the material in this post. Version 8.4.11-11 includes patches that deliver significant improvements in ... Continued The post Performance improvements in Percona Server 8.4.11-11 appeared first on Percona. ## Evolving Pinterest's Embedding Retrieval Platform DevFeed: [Evolving Pinterest's Embedding Retrieval Platform]() Original publisher: [Read original article]() Author: Pinterest Engineering Published: 2026-09-11T15:01:03Z Content type: article Language: en Sources: [Pinterest Engineering Blog - Medium]() Topics: [Architecture & Design](), [Algorithms](), [Scalability](), [Latency](), [IO]() Tags: [ann](), [cost](), [embedding](), [embeddings](), [engineering](), [infrastructure](), [latency](), [memory](), [models](), [pinterest](), [platform](), [quantization](), [real-time](), [retrieval](), [scalability](), [search]() ### AI overview Pinterest describes evolving its Manas embedding-retrieval platform to address the cost, scale, and flexibility challenges of serving billions of embeddings. The excerpt covers ANN search, vector quantization, and SSD-based serving. ### Source excerpt Authors: Bowen Zhou | Staff Software Engineer; Shan Gao | Senior Software Engineer; Jingwen Hu | Software Engineer II; Wenjiang Chu | Staff Software Engineer The Billion-Embedding Challenge At Pinterest, the "signal" is our lifeblood. Whether it's a home decor enthusiast finding the perfect rug or a fashion seeker discovering a new aesthetic, our discovery engine relies on understanding deep semantic relationships to help our users find inspirations. Over the last few years, the explosive growth of embedding-based retrieval has fundamentally transformed how we surface these signals -- and at the heart of that transformation is Manas, Pinterest's in-house distributed search platform. Embedding Retrieval is one of the core capabilities of Manas, supporting multiple approximate nearest neighbor search algorithms, hybrid queries with both token and embedding clauses, as well as real-time updates to ensure fresh contents become searchable within seconds. Deployed on over 80 clusters and serving billions of embeddings, Manas embedding retrieval powers all major product surfaces at Pinterest including Home Feed, Search, Related Pins, Ads, and Notifications. However, as our corpus scales toward tens of billions of embeddings and our models capture increasingly complex interactions, we face mounting challenges around cost efficiency, scalability, and flexibility. On the infrastructure side, traditional ANN algorithms like HNSW are notoriously memory-hungry -- they require the entire index to reside in RAM to maintain low query latency, making cost grow linearly with corpus size. On the modeling side, the classic two-tower retrieval paradigm is too restrictive: it reduces each candidate to a single embedding and scores relevance through a simple dot product, leaving little room to express richer, context-dependent notions of similarity. To tackle these challenges, our team has been evolving Manas's embedding retrieval stack across three fronts: Quantization. We reduce the memor ## 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. ## Internal Developer Portals: Why Native CI/CD Drives Scale DevFeed: [Internal Developer Portals: Why Native CI/CD Drives Scale]() Original publisher: [Read original article]() Author: Rashmi Hegde Published: 2026-09-08T00:00:00Z Content type: article Language: en Sources: [Harness Blog]() Topics: [Platform Engineering](), [CI/CD](), [developer velocity](), [Automation](), [Scalability]() Tags: [automation](), [ci-cd](), [developer-velocity](), [idp](), [scalability](), [self-service](), [velocity]() ### AI overview This article argues that internal developer portals need native CI/CD integration to move beyond service catalogs and documentation. It explains that integrated pipelines can reduce context switching, support self-service workflows, help enforce standards, and improve developer velocity and scalability. ### Source excerpt Internal developer portals need native CI/CD integration to scale effectively. Learn how integrated pipelines improve velocity. Explore Harness IDP. | Blog ## Data Engineering Weekly #286 DevFeed: [Data Engineering Weekly #286]() Original publisher: [Read original article]() Author: Ananth Packkildurai Published: 2026-09-07T00:18:06Z Content type: article Language: en Sources: [Data Engineering Weekly]() Topics: [data-engineering](), [AI, ML & Data Engineering](), [agent observability](), [Large Language Model](), [data-modeling](), [Monitoring](), [Scalability](), [semantic-layer](), [parquet]() Tags: [ai](), [ai-agents](), [data-engineering](), [data-modeling](), [llm](), [monitoring](), [newsletter](), [observability](), [parquet](), [scalability](), [semantic-layer](), [weekly]() ### AI overview Data Engineering Weekly #286 is a curated newsletter covering data platform fundamentals, mathematics for machine learning, agentic machine learning at Instacart, Netflix's lifecycle for LLM-as-a-Judge systems, semantic layers and data modeling for AI analytics, and Apache Pinot scalability. ### Source excerpt The Weekly Data Engineering Newsletter ## How to Integrate an API Into a Website: A Step-by-Step Guide for Businesses (Sponsored) DevFeed: [How to Integrate an API Into a Website: A Step-by-Step Guide for Businesses (Sponsored)]() Original publisher: [Read original article]() Author: Sponsored Post Published: 2026-09-04T02:57:14Z Content type: tutorial Language: en Sources: [CNX Software - Embedded Systems News]() Topics: [API](), [Website](), [Development](), [Authentication](), [Security](), [Scalability]() Tags: [api](), [api-integration](), [authentication](), [guide](), [how-to](), [integration](), [security](), [software-management](), [sponsored](), [testing]() ### AI overview A sponsored guide explains how businesses can integrate third-party APIs into websites. It covers defining requirements, evaluating API documentation and support, configuring authentication, and testing data accuracy, error handling, performance, security, browser compatibility, and mobile functionality. ### Source excerpt Modern websites rarely work in isolation. They rely on third-party services to exchange data. API integration into website projects can improve user experience. From payment gateways to CRM platforms, almost every feature can be integrated. Build your successful API integration solutions today. What Is API Integration and Why Does Your Website Need It? An API allows two software applications to communicate with each other. They can exchange information securely to facilitate the production process. It is convenient because you don't have to develop every feature. You can simply connect your websites with specialized services. Common API integrations include: Payment gateways Social media integrations Customer relationship management (CRM) systems Supplier portals Email marketing platforms Weather services Maps and location tools For many businesses, API integrations are a way to: Save development time Utilize advanced applications at more affordable rates Provide a richer customer experience What Should Businesses Consider Before Integrating an [...] The post How to Integrate an API Into a Website: A Step-by-Step Guide for Businesses (Sponsored) appeared first on CNX Software - Embedded Systems News. ## How Every Team Can Build in Port at Scale, Without the Bottleneck DevFeed: [How Every Team Can Build in Port at Scale, Without the Bottleneck]() Original publisher: [Read original article]() Author: Guy Berman Published: 2026-09-03T14:39:07Z Content type: article Language: en Sources: [Developer Experience & Platform Engineering Blog | Port]() Topics: [Authorization](), [Scalability](), [sdlc](), [pull-requests](), [Security]() Tags: [agent](), [agentic](), [compliance](), [dashboards](), [development](), [production](), [pull-requests](), [scalability](), [scale](), [sdlc](), [security](), [workflow]() ### AI overview The article explains how every team can build and own a scoped part of Port at scale. It presents fine-grained permissions, role-based access controls, and controlled promotion across development, staging, and production environments as ways to reduce platform-team bottlenecks while limiting risk. ### Source excerpt How every team can build in Port at scale: scoped permissions, dynamic policies, and safe rollouts across environments. ## MCP Went Stateless: What Now? DevFeed: [MCP Went Stateless: What Now?]() Original publisher: [Read original article]() Author: Janet Wagner Published: 2026-09-03T07:00:00Z Content type: article Language: en Sources: [Nordic APIs]() Topics: [Model Context Protocol (MCP)](), [Scalability](), [MCP Server](), [Architecture & Design](), [Security](), [Tool]() Tags: [ai](), [ai-agents](), [api-gateway](), [api-security](), [api-standards](), [artificial-intelligence](), [blog](), [cloud-native](), [developers](), [http](), [llm](), [mcp](), [mcp-server](), [model-context-protocol](), [scalability](), [security](), [strategy]() ### AI overview The article examines the shift to stateless MCP and its implications for scalability, state management, security, gateways, and MCP server architecture. ### Source excerpt The latest release of the Model Context Protocol (MCP) specification has created a lot of buzz in tech circles. Why? Primarily because this AI communication protocol has now gone stateless! This shift from stateful to stateless impacts how developers of MCP servers and AI tools use the protocol moving forward. In addition, the change impacts ... ## Performance Progression of Percona Server for MySQL 8.4 DevFeed: [Performance Progression of Percona Server for MySQL 8.4]() Original publisher: [Read original article]() Author: Bogdan Degtyariov Published: 2026-08-27T13:07:20Z Content type: article Language: en Sources: [Blog - Percona]() Topics: [MySQL](), [benchmarking](), [Benchmark](), [Scalability](), [configuration](), [cpu](), [Hardware]() Tags: [2026](), [benchmark](), [benchmarking](), [benchmarks](), [concurrency](), [configuration](), [cpu](), [data](), [database](), [hardware](), [intel](), [latency](), [load](), [measurement](), [mysql](), [percona](), [percona-server-for-mysql](), [performance](), [processors](), [run]() ### AI overview This article investigates read/write performance changes across Percona Server for MySQL 8.4 versions released in 2026. It describes benchmark scope, database and buffer-size combinations, configuration, and CPU-frequency controls, while excluding features, security patches, latency percentiles, and resource-utilization measurements. ### Source excerpt 1. Purpose and scope This performance investigation aims to look into the read/write performance of Percona Server for MySQL 8.4 and how it changed between versions released in 2026: 8.4.8-8 released on 12 March 2026 8.4.10-10 released on 30 June 2026 8.4.11-11 released on 20 August 2026 We want to see if there are improvements ... Continued The post Performance Progression of Percona Server for MySQL 8.4 appeared first on Percona. ## Terraform Scalability: When IaC Outgrows Your Setup DevFeed: [Terraform Scalability: When IaC Outgrows Your Setup]() Original publisher: [Read original article]() Author: Mrinalini Sugosh Published: 2026-08-10T00:00:00Z Content type: article Language: en Sources: [Harness Blog]() Topics: [Terraform](), [Infrastructure as code](), [Scalability](), [iac-security]() Tags: [dynamodb](), [harness](), [iac](), [s3](), [scalability](), [security](), [terraform]() ### AI overview This article examines how Terraform scalability challenges emerge as infrastructure code and teams grow. It discusses bottlenecks involving state management, collaboration, governance, large state files, locking, plan times, module sprawl, and version drift, and introduces Harness IaCM as a management solution. ### Source excerpt Terraform scalability issues slow teams down. Learn how to overcome IaC bottlenecks with better management. See how Harness helps. | Blog ## Xen 4.22: Strengthening Open Source Virtualization for Cloud, Embedded, and Automotive Systems DevFeed: [Xen 4.22: Strengthening Open Source Virtualization for Cloud, Embedded, and Automotive Systems]() Original publisher: [Read original article]() Author: Cody Zuschlag Published: 2026-08-05T15:18:36Z Content type: article Language: en Sources: [Blog - Xen Project]() Topics: [virtualization](), [Open Source](), [Cloud](), [Hardware](), [Scalability](), [Arm](), [RISC-V]() Tags: [arm](), [automotive](), [cloud](), [developers](), [embedded](), [hardware](), [improvements](), [lifecycle](), [maintenance](), [open-source](), [performance](), [platform](), [release](), [releases](), [risc-v](), [safety](), [security](), [standards](), [systems](), [virtualization](), [xen-4-22]() ### AI overview Xen 4.22 is presented as the latest Xen hypervisor release, adding modern hardware support, Arm virtualization improvements, continued RISC-V progress, and Xenstore scalability updates. The Xen Project also introduces a consistent five-year security support lifecycle for Xen 4.20 and later releases. ### Source excerpt Xen 4.22 adds modern hardware support, Arm improvements, continued RISC-V progress, Xenstore scalability updates, and a five-year security support lifecycle. ## CockroachDB Kubernetes Operator launches with full lifecycle automation DevFeed: [CockroachDB Kubernetes Operator launches with full lifecycle automation]() Original publisher: [Read original article]() Author: Ethan Shmargad,Pritesh Lahoti Published: 2026-08-05T00:00:00Z Content type: release Language: en Sources: [Cockroach Labs]() Topics: [CockroachDB](), [Kubernetes](), [Deployment](), [Automation](), [migration](), [Scalability]() Tags: [automation](), [cockroach-labs](), [cockroachdb](), [database](), [deployment](), [kubernetes](), [migration](), [production](), [scalability]() ### AI overview Cockroach Labs announces the CockroachDB Kubernetes Operator, designed to connect CockroachDB-aware operations with Kubernetes. It provides lifecycle automation for deployment, upgrades, scaling, certificate rotation, and storage management, and supports multi-region deployments and workflows including Helm, GitOps, private registries, and air-gapped environments. ### Source excerpt The production-proven K8s operator is now available with full lifecycle automation, zero-downtime migration, as well as the flexibility and scalability to fit how your team actually works. ## DDIA 2nd Edition Excerpt: On Scalability DevFeed: [DDIA 2nd Edition Excerpt: On Scalability]() Original publisher: [Read original article]() Author: ScyllaDB Team Published: 2026-08-04T12:59:50Z Content type: article Language: en Sources: [ScyllaDB]() Topics: [Scalability](), [Architecture & Design](), [App](), [data](), [Database]() Tags: [applications](), [architecture](), [community](), [data](), [engineering](), [optimization](), [scalability](), [scale](), [systems]() ### AI overview An excerpt from the second edition of Designing Data-Intensive Applications explains scalability as a system's ability to cope with increased load. It discusses growth in users and data, trade-offs for early-stage products, architectural limits, resource expansion, and performance bottlenecks. ### Source excerpt Martin Kleppmann and Chris Riccomini's scalability considerations for designing data-intensive applications -- from the second edition of the Designing Data-Intensive Applications book ## Install Terraform: Secure & Scalable IaC Setup Guide DevFeed: [Install Terraform: Secure & Scalable IaC Setup Guide]() Original publisher: [Read original article]() Author: Mrinalini Sugosh Published: 2026-07-24T00:00:00Z Content type: tutorial Language: en Sources: [Harness Blog]() Topics: [Terraform](), [Infrastructure as code](), [iac-security](), [Scalability](), [Automation](), [Command-line interface]() Tags: [cli](), [guide](), [iac](), [infrastructure-as-code](), [install](), [scalability](), [security](), [terraform]() ### AI overview A guide to installing Terraform across platforms with security hardening and scalability in mind. It covers installation, configuration, state management, secret handling, version control, team workflows, and production-oriented infrastructure automation. ### Source excerpt Learn to install Terraform with security and scalability built in. Master IaC automation setup from start to finish. See how Harness helps. | Blog ## Week Ending July 19, 2026 DevFeed: [Week Ending July 19, 2026]() Original publisher: [Read original article]() Published: 2026-07-23T22:00:00Z Content type: news Language: en Sources: [Last Week in Kubernetes Development]() Topics: [Kubernetes](), [releases](), [Scalability](), [Streaming](), [x86]() Tags: [developer](), [kubernetes](), [news](), [releases](), [review](), [scalability](), [streaming]() ### AI overview This developer news roundup covers Kubernetes community and release updates, including Feature Discovery v0.19.0, Kubernetes v1.37 entering code freeze, patch releases, EtcdRangeStream becoming enabled by default, and ClusterTrustBundles reaching general availability. It also reports a watch cache initialization improvement on 5,000-node clusters and upcoming maintainer and steering committee activities. ### Source excerpt Developer News ## Alpha features in Kubernetes 1.36 DevFeed: [Alpha features in Kubernetes 1.36]() Original publisher: [Read original article]() Author: Nigel Douglas Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Kubernetes](), [AI Platform](), [Hardware](), [Scalability](), [Security](), [API](), [cpu](), [real-time]() Tags: [ai-ml](), [api](), [cpu](), [hardware](), [kubernetes](), [real-time](), [scalability](), [security]() ### AI overview An overview of selected Alpha-stage features planned for Kubernetes 1.36, focusing on five Dynamic Resource Allocation enhancements for AI/ML workloads. The article explains improved hardware discovery, real-time resource availability, list-typed device attributes, group-aware resource claims, and native resource requests. ### Source excerpt Explore the top 10 new Alpha features in Kubernetes 1.36. Learn about 5 DRA advancements for AI/ML workloads, workload-aware scheduling, new security policies, and major scalability gains ## The hyperscale blueprint: Why cloud giants prioritize VMs for Kubernetes over bare metal DevFeed: [The hyperscale blueprint: Why cloud giants prioritize VMs for Kubernetes over bare metal]() Original publisher: [Read original article]() Author: Jack Wallen Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [virtualization](), [Kubernetes](), [Containers](), [Scalability](), [Security](), [Amazon Web Services](), [Nitro System](), [Multi-tenancy]() Tags: [aws](), [containers](), [kubernetes](), [multi-tenancy](), [nitro-system](), [scalability](), [security](), [virtual-machines](), [virtualization]() ### AI overview Cloud providers generally run Kubernetes and other containerized workloads on virtual machines rather than bare metal because virtualization offers security, isolation, flexibility, scalability, and near-bare-metal performance. AWS Nitro and Firecracker help reduce virtualization overhead, while bare metal remains reserved for specialized performance or hardware-access requirements. ### Source excerpt Why do cloud giants use VMs for Kubernetes? Learn why AWS, Azure, and Google prioritize Virtual Machines for containerized workloads over bare metal, focusing on security and scalability. ## 5 most overlooked but critical considerations in container platform selection DevFeed: [5 most overlooked but critical considerations in container platform selection]() Original publisher: [Read original article]() Author: Pankaj Gupta Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Containers](), [Kubernetes](), [Cloud Native Ecosystem](), [Scalability](), [Security]() Tags: [cloud](), [containers](), [infrastructure](), [kubernetes](), [operations](), [performance](), [platforms](), [scalability](), [security](), [strategy](), [vks](), [vmware](), [vmware-cloud-foundation]() ### AI overview The article identifies five often-overlooked factors in container platform selection. It emphasizes rapid access to new CNCF-conformant Kubernetes versions, long standard support periods, the ability to run multiple Kubernetes versions on one host, and treating VMs and containers as first-class citizens. It presents VMware Cloud Foundation with vSphere Kubernetes Service as an example of a platform offering rapid Kubernetes access and a long support window. ### Source excerpt Choosing a container platform that's built for the future requires careful consideration. Learn more about critical factors such as long support lifecycles, multi-version flexibility, and first-class treatment for both VMs and containers. ## How NIIT helped Kyndryl certify more than 100 platform engineers DevFeed: [How NIIT helped Kyndryl certify more than 100 platform engineers]() Original publisher: [Read original article]() Author: Karolina Semiuk Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Platform Engineering](), [internal developer portal](), [Developer experience](), [Scalability](), [DevOps]() Tags: [best-practices](), [certifications](), [community](), [devops](), [efficiency](), [engineering](), [enterprise](), [organizational](), [platform](), [scalability](), [software-delivery]() ### AI overview The article describes how NIIT helped Kyndryl certify more than 100 platform engineers. It argues that team-scale certification creates shared language, reduces communication problems, standardizes best practices, and strengthens platform engineering capabilities across a distributed enterprise workforce. ### Source excerpt NIIT enabled Kyndryl to certify 100+ platform engineers, fostering shared language and organizational transformation through team-based certification programs ## How platform engineering plus VMs ease modernization DevFeed: [How platform engineering plus VMs ease modernization]() Original publisher: [Read original article]() Author: Jennifer Riggins Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Platform Engineering](), [virtualization](), [Containers](), [Cloud Native Ecosystem](), [Security](), [Scalability](), [Provisioning]() Tags: [architecture](), [cloud](), [cloud-native](), [containers](), [engineering](), [idp](), [infrastructure](), [operational](), [platform](), [platform-engineering](), [policy](), [provisioning](), [scalability](), [security](), [virtual-machines]() ### AI overview The article explains how combining containers in virtual machines with platform engineering and internal developer platforms can ease modernization. It argues that VMs provide stronger isolation, security boundaries, resource flexibility, and performance comparable to bare metal, while a policy-driven platform layer improves provisioning, utilization, compliance, and scalability. ### Source excerpt Explore why running containers in Virtual Machines (VMs) with a platform engineering strategy is essential for modern cloud environments. Learn how VMs deliver superior security, isolation, and resource management compared to bare metal, while achieving performance parity. ## How the Gradle Team Adopted Isolated Projects DevFeed: [How the Gradle Team Adopted Isolated Projects]() Original publisher: [Read original article]() Author: Alex Semin Published: 2026-07-22T04:00:00Z Content type: article Language: en Sources: [The Gradle Blog]() Topics: [Gradle](), [Scalability](), [Cache](), [configuration](), [Dependency management](), [ci](), [ide]() Tags: [cache](), [ci](), [configuration](), [dependency-management](), [gradle](), [ide](), [parallelism](), [performance]() ### AI overview The Gradle team describes adopting the experimental Isolated Projects feature in its own build. The article explains that Isolated Projects runs project configuration in parallel to improve scalability and performance, and outlines migration prerequisites, diagnostics, convention plugins, dependency management, and Shared Build Services. ### Source excerpt Isolated Projects is an experimental feature aimed at improving Gradle scalability and performance. It speeds up builds by running project configuration in parallel, which benefits practically every workflow, from CI builds to IDE sync. We want the feature to offer an excellent user experience, so we made it a goal to adopt Isolated Projects in our own build, even though it is still in active development. This lets us find and smooth out the rough spots early, though secretly, we were also looking forward to the productivity boost for our own team. With Isolated Projects, more build logic runs concurrently. To keep builds reliable under that parallelism, the feature introduces additional constraints, and adopting it means migrating your build to address the violations of those constraints. Migrating our build Isolated Projects builds directly on top of the Configuration Cache, so making the build Configuration Cache compatible is a prerequisite. Fortunately for us, we've been enjoying fast inner developer loops for many years now, so that box was already checked. The general approach to migrating against new constraints is to start with the simplest workflows, such as running the help task, and address the violations. Then proceed to more complex workflows, such as IDE sync or CI. Running in Diagnostics mode helps you see all violations at once in a single HTML report, and the guide describes the recommended migration path. For the Gradle build, we followed a similar path. What helped us the most and made the migration much smoother is following the best practices, especially the best practice of having convention plugins: each project applies the build logic it needs, and no project has to reach in and mutate another's state directly. We've leaned heavily on sharing artifacts between projects only via dependency management, which is inherently compatible with Isolated Projects by making each project define its "outputs", on which other projects can depend. For more ## AI on Kubernetes: Building the Cloud-Native Foundation for Intelligent Applications DevFeed: [AI on Kubernetes: Building the Cloud-Native Foundation for Intelligent Applications]() Original publisher: [Read original article]() Author: Urolime Technologies Published: 2026-07-20T12:54:45Z Content type: tutorial Language: en Sources: [Kubernetes Archives - Urolime Blogs]() Topics: [Artificial Intelligence](), [Kubernetes](), [Cloud](), [AI Platform](), [Scalability]() Tags: [ai](), [cloud](), [cloud-native](), [data-processing](), [inference](), [kubernetes](), [kubernetes-consulting-services](), [scalability]() ### AI overview This article explains why Kubernetes is useful as cloud-native infrastructure for deploying AI applications. It discusses dynamic workload scaling, GPU-based training, inference, CI/CD, large-scale data processing, and consistent management across on-premises, private-cloud, and public-cloud environments. ### Source excerpt Artificial Intelligence (AI) has grown past its experimental stage and is now becoming a strategic business enabler. With AI-powered customer experiences, predictions, and generative AI technologies, businesses have begun adopting AI solutions to stay ahead of the game. However, deploying AI at scale requires more than sophisticated AI models and algorithms. To use AI successfully [...] [Next page]()