# Amazon EKS Fully managed Kubernetes service for building, securing, and maintaining Kubernetes clusters. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Automate proxy injection for Amazon EKS on AWS Fargate using Kyverno DevFeed: [Automate proxy injection for Amazon EKS on AWS Fargate using Kyverno]() Original publisher: [Read original article]() Author: Himanshu Bansal Published: 2026-09-01T15:59:57Z Content type: tutorial Language: en Sources: [Containers]() Topics: [Amazon EKS](), [Kubernetes](), [Containers](), [Amazon EC2]() Tags: [advanced-300](), [amazon-eks](), [amazon-elastic-kubernetes-service](), [aws-fargate](), [compliance](), [containers](), [how-to](), [kubernetes](), [policy]() ### AI overview This tutorial shows how to use a Kyverno mutating admission policy to inject corporate HTTP/HTTPS proxy environment variables into Amazon EKS pods running on AWS Fargate. It targets labeled namespaces, avoids per-application manifest changes, and covers validation and proxy bypasses for Fluent Bit and AWS endpoints. ### Source excerpt Learn how to use a Kyverno mutating admission policy to automatically inject corporate proxy environment variables into Amazon EKS on AWS Fargate pods at admission time, delivering consistent egress compliance without modifying application deployment manifests. ## Hybrid cloud orchestration: Modernizing on-premises infrastructure management with AWS DevFeed: [Hybrid cloud orchestration: Modernizing on-premises infrastructure management with AWS]() Original publisher: [Read original article]() Author: Sandeep Singh Published: 2026-09-01T14:01:10Z Content type: tutorial Language: en Sources: [AWS Architecture Blog]() Topics: [Orchestration](), [Kubernetes](), [Amazon EKS](), [AWS Lambda](), [Server](), [Hardware]() Tags: [amazon-dynamodb](), [amazon-eks](), [aws](), [aws-lambda](), [aws-step-functions](), [data-centers](), [deployment](), [event-driven](), [hardware](), [kubernetes](), [observability](), [orchestration](), [server](), [serverless](), [thought-leadership]() ### AI overview Tutorial on designing an AWS-based hybrid cloud orchestration system for centralized lifecycle management of distributed on-premises servers and EKS Anywhere clusters. ### Source excerpt Learn how to build a hybrid cloud orchestration solution that manages distributed on-premises infrastructure at scale using AWS serverless technologies and Amazon EKS Anywhere. Part 1 covers the core event-driven architecture patterns for automating server lifecycle and cluster management across hundreds of sites. ## Break-glass access for Amazon EKS when federated identity fails DevFeed: [Break-glass access for Amazon EKS when federated identity fails]() Original publisher: [Read original article]() Author: Sam Mukherjee Published: 2026-08-26T16:20:28Z Content type: article Language: en Sources: [Containers]() Topics: [Amazon EKS](), [AWS Identity and Access Management (IAM)](), [Infrastructure as code](), [MFA](), [Authorization](), [iac-security](), [migration]() Tags: [advanced-300](), [amazon-eks](), [amazon-elastic-kubernetes-service](), [aws-iam](), [best-practices](), [identity-and-access-management](), [infrastructure-as-code](), [mfa](), [migration](), [technical-how-to]() ### AI overview This post presents a break-glass access pattern for Amazon EKS clusters when a federated identity provider fails. It describes a dedicated cross-account IAM role with enforced, recency-aware MFA, infrastructure-as-code templates, validation tests, and post-incident recovery procedures. ### Source excerpt Implementing break-glass access for Amazon EKS clusters removes the circular dependency where a federated identity provider outage locks you out of the clusters you need to reach to fix it. This post supplies a cross-account IAM role with enforced MFA, infrastructure-as-code templates, validation tests, and a post-incident recovery procedure. ## Deep dive into Amazon EKS certificate authority rotation DevFeed: [Deep dive into Amazon EKS certificate authority rotation]() Original publisher: [Read original article]() Author: Micah Hausler Published: 2026-08-19T20:55:49Z Content type: article Language: en Sources: [Containers]() Topics: [Amazon EKS](), [TLS (Transport Layer Security)](), [Availability](), [AWS Fargate](), [CI/CD](), [Security]() Tags: [advanced-300](), [amazon-eks](), [amazon-elastic-kubernetes-service](), [announcements](), [availability](), [aws](), [aws-fargate](), [ci-cd](), [deep-dive](), [security](), [technical-how-to](), [tls]() ### AI overview This deep dive explains Amazon EKS certificate authority rotation. It describes the managed lifecycle, automated safeguards, rollback, AWS-managed components, and the customer responsibilities needed to preserve connectivity during the transition. ### Source excerpt Amazon EKS now provides a managed, non-disruptive lifecycle for rotating your cluster's certificate authority (CA), with automated safeguards and rollback. This deep dive explains how CA rotation works, what AWS handles versus what you must update, and how to walk through the rotation lifecycle on your own timeline. ## Amazon EKS is replacing the deprecated aws-auth ConfigMap for IAM-to-cluster permission mapping DevFeed: [Amazon EKS is replacing the deprecated aws-auth ConfigMap for IAM-to-cluster permission mapping]() Original publisher: [Read original article]() Author: Yannick Struyf Published: 2026-08-19T18:59:54Z Content type: article Language: en Sources: [Kubernetes Overview, News and Trends | The New Stack]() Topics: [Amazon EKS](), [Kubernetes](), [AWS IAM](), [Access Control](), [Amazon Web Services](), [Cloud](), [migration]() Tags: [access-control](), [amazon-eks](), [aws](), [cloud](), [cloud-native](), [deprecated](), [iam](), [kubernetes](), [migration](), [nutanix](), [platform-engineering](), [post](), [report](), [security](), [sponsor-nutanix](), [sponsored](), [sponsored-post]() ### AI overview The article examines security challenges in Kubernetes and cloud-native infrastructure, focusing on Amazon EKS's replacement of the deprecated aws-auth ConfigMap with an API-driven method for mapping IAM identities to cluster permissions. It also explains how Kubernetes security spans code, containers, clusters, and cloud infrastructure. ### Source excerpt The migration to Kubernetes and cloud native infrastructure has been one of the defining IT trends of the past decade. The post AWS deprecated this EKS auth method. 81% of clusters still run it. appeared first on The New Stack. ## Best Kubernetes Infrastructure as Code Tools in 2026 DevFeed: [Best Kubernetes Infrastructure as Code Tools in 2026]() Original publisher: [Read original article]() Author: Pulumi Content Team Published: 2026-08-14T00:00:00Z Content type: comparison Language: en Sources: [Pulumi]() Topics: [Infrastructure as code](), [Kubernetes](), [Terraform](), [argo-cd](), [Helm charts](), [GitOps](), [flux](), [opentofu](), [Amazon EKS](), [AWS CloudFormation](), [VPC](), [AWS IAM]() Tags: [argo-cd](), [cloudformation](), [code](), [comparisons](), [devops](), [flux](), [general](), [gitops](), [helm](), [helm-charts](), [iam](), [infrastructure](), [infrastructure-as-code](), [kubernetes](), [opentofu](), [platform-engineering](), [terraform](), [vpc]() ### AI overview This comparison explains that Kubernetes infrastructure as code spans cluster and cloud provisioning, in-cluster workload definition, and continuous delivery and reconciliation. It presents Pulumi and Terraform or OpenTofu as general-purpose provisioning options, Helm and Kustomize for workload templating, and Argo CD and Flux for GitOps reconciliation. ### Source excerpt There is no single best Kubernetes infrastructure as code tool, because "Kubernetes IaC" actually spans three different jobs. For provisioning the cluster and its cloud dependencies, Pulumi and Terraform (or OpenTofu) are the strongest general-purpose options. For templating and packaging workloads, Helm and Kustomize dominate. For continuous reconciliation once things are running, Argo CD and Flux lead the GitOps category. The right stack usually combines one tool from each layer, not a single tool that claims to do all three. What counts as infrastructure as code for Kubernetes? Kubernetes infrastructure as code work splits into three layers that get conflated constantly, and the confusion is where most tool comparisons go wrong. The cluster and cloud layer provisions the things Kubernetes itself sits on top of: the managed control plane (EKS, GKE, AKS), node pools, the VPC and subnets, IAM roles, load balancers, and cluster add-ons. Terraform, Pulumi, and cloud-native tools like CloudFormation operate here. The in-cluster workload layer defines what runs on the cluster once it exists: Deployments, Services, ConfigMaps, CustomResourceDefinitions, and the Helm charts or Kustomize overlays that template them. This is where Helm, Kustomize, and Crossplane's custom resources live. The delivery and reconciliation layer keeps what's declared in Git in sync with what's actually running on the cluster, continuously, rather than as a one-shot apply. Argo CD and Flux own this layer, and they consume the output of the other two rather than replacing them. Most real Kubernetes platforms use tools from at least two of these layers together. A team might provision EKS with Terraform, package its application with Helm, and let Argo CD reconcile it continuously. Knowing which layer a tool actually addresses, rather than treating "Kubernetes IaC" as one shopping list, is the first decision that matters. Pulumi provisions the cluster and the workloads on it in the same language Pul ## Adobe Firefly: Simplified observability with Amazon Managed Prometheus DevFeed: [Adobe Firefly: Simplified observability with Amazon Managed Prometheus]() Original publisher: [Read original article]() Author: Dev Arora Published: 2026-08-13T00:14:19Z Content type: article Language: en Sources: [AWS Architecture Blog]() Topics: [observability](), [GPU](), [Amazon EKS](), [Amazon Web Services](), [Monitoring](), [telemetry](), [migration](), [Training AI Models]() Tags: [adobe](), [amazon](), [amazon-eks](), [amazon-elastic-kubernetes-service](), [amazon-managed-service-for-prometheus](), [amazon-web-services-aws](), [aws](), [compute](), [cpu](), [customer-solutions](), [data](), [deployment](), [efficiency](), [gpu](), [infrastructure](), [jobs](), [kubernetes](), [metrics](), [observability](), [performance](), [prometheus]() ### AI overview Adobe Firefly migrated critical GPU infrastructure metrics from self-managed Prometheus to Amazon Managed Service for Prometheus. The article describes the observability challenges of large-scale model training on Amazon EKS, including high-cardinality GPU, compute, memory, and network telemetry, and reports 28x faster GPU metric queries with improved reliability and operational efficiency. ### Source excerpt Learn how Adobe Firefly achieved 28x faster GPU metric queries by migrating from self-managed Prometheus to Amazon Managed Service for Prometheus, with improvements in query performance, infrastructure reliability, and operational efficiency. ## Introducing advanced Kubernetes control plane configuration in Amazon EKS DevFeed: [Introducing advanced Kubernetes control plane configuration in Amazon EKS]() Original publisher: [Read original article]() Author: Ashok Srirama Published: 2026-08-12T17:23:45Z Content type: article Language: en Sources: [Containers]() Topics: [Amazon EKS](), [Kubernetes](), [configuration](), [API](), [Availability](), [Provisioning]() Tags: [advanced-300](), [ai-ml](), [amazon-eks](), [amazon-elastic-kubernetes-service](), [announcements](), [api](), [availability](), [ci-cd](), [kubernetes](), [packing](), [retention](), [storage]() ### AI overview Amazon EKS introduces advanced Kubernetes control plane configuration, allowing users to set API server, scheduler, and controller manager parameters directly. The article covers pod placement scoring, event retention, and HPA synchronization settings through feature explanations and hands-on walkthroughs. ### Source excerpt With Amazon EKS, you can now configure Kubernetes control plane components (the API server, scheduler, and controller manager) directly through EKS APIs. This post explains what's configurable and includes two hands-on walkthroughs: enabling MostAllocated bin-packing to optimize pod placement, and tuning event retention duration. ## Under the hood: how Amazon EKS Auto Mode detects, repairs, and diagnoses node failures DevFeed: [Under the hood: how Amazon EKS Auto Mode detects, repairs, and diagnoses node failures]() Original publisher: [Read original article]() Author: Sajjan Gundapuneedi Published: 2026-08-05T18:48:18Z Content type: article Language: en Sources: [Containers]() Topics: [Amazon EKS](), [Kubernetes](), [Monitoring](), [systemd](), [Cloud]() Tags: [advanced-300](), [amazon-eks](), [amazon-elastic-kubernetes-service](), [cloud](), [diagnostics](), [kubernetes](), [monitoring](), [systemd](), [technical-how-to]() ### AI overview This article explains how Amazon EKS Auto Mode detects, diagnoses, drains, and replaces failed Kubernetes nodes. It describes the collaboration between the Node Monitoring Agent and Karpenter, including system-level fault detection, repair policies, safety thresholds, and node diagnostics without SSH. ### Source excerpt On Amazon EKS Auto Mode, node failures are detected, drained, and replaced automatically before anyone reaches for a laptop. This post shows how the Node Monitoring Agent and Karpenter form a detect-and-replace cycle that runs by default, why specific faults trigger node replacement, and how to collect node diagnostics without SSH. ## Data Engineering Weekly #279 DevFeed: [Data Engineering Weekly #279]() Original publisher: [Read original article]() Author: Ananth Packkildurai Published: 2026-07-20T04:07:20Z Content type: article Language: en Sources: [Data Engineering Weekly]() Topics: [data-engineering](), [Data Quality](), [semantic-layer](), [Kafka](), [observability](), [knowledge-engineering](), [Embeddings](), [Databases](), [Amazon EKS](), [Amazon EC2](), [Availability]() Tags: [availability](), [data-engineering](), [data-quality](), [database](), [embeddings](), [engineering](), [kafka](), [knowledge-engineering](), [observability](), [semantic-layer]() ### AI overview Data Engineering Weekly #279 is a newsletter covering data platform fundamentals, data management for generative AI, semantic-layer portability, knowledge-base construction with Postgres and embeddings, Kafka migration, and Apache Pinot high availability. The supplied text includes sponsored material and ends mid-item. ### Source excerpt The Weekly Data Engineering Newsletter ## Self-healing GPU nodes in Kubernetes: What we learned building the EKS node monitoring agent DevFeed: [Self-healing GPU nodes in Kubernetes: What we learned building the EKS node monitoring agent]() Original publisher: [Read original article]() Author: Sajjan Gundapuneedi Published: 2026-07-19T13:00:00Z Content type: article Language: en Sources: [Kubernetes Overview, News and Trends | The New Stack]() Topics: [Kubernetes](), [Amazon EKS](), [GPU](), [Monitoring]() Tags: [ai-infrastructure](), [amazon-eks](), [aws-marketplace](), [gpu](), [kubernetes](), [monitoring](), [open-source](), [pcie](), [post-contributed](), [self-healing](), [sponsor-aws-marketplace](), [sponsored-post-contributed]() ### AI overview The article describes how the EKS Node Monitoring Agent detects Kubernetes node failures, writes NodeConditions, and works with Karpenter to replace affected nodes. It explains design lessons from operating automatic repair at GPU scale and places the agent within EKS Auto Mode. ### Source excerpt When you run Kubernetes at the scale we do on Amazon EKS, nodes break constantly. GPUs fall off the PCIe The post Self-healing GPU nodes in Kubernetes: What we learned building the EKS node monitoring agent appeared first on The New Stack. ## What running Kubernetes across millions of clusters taught AWS about zonal failures DevFeed: [What running Kubernetes across millions of clusters taught AWS about zonal failures]() Original publisher: [Read original article]() Author: Raghav Tripathi Published: 2026-07-10T15:00:00Z Content type: article Language: en Sources: [Kubernetes Overview, News and Trends | The New Stack]() Topics: [Amazon EKS](), [Kubernetes](), [Amazon Web Services](), [Resilience](), [Availability]() Tags: [amazon-eks](), [api](), [availability](), [aws](), [aws-marketplace](), [cloud-services](), [health-checks](), [kubectl](), [kubernetes](), [networking](), [operations](), [outage](), [post-contributed](), [resilience](), [sponsor-aws-marketplace](), [sponsored-post-contributed]() ### AI overview AWS describes how years of engineering on Amazon EKS addressed zonal failures, including gray failures where a zone is degraded but still passes some health checks. The approach emphasizes static stability, preserving capacity, and routing around the impaired Availability Zone. ### Source excerpt Handling the obvious failures is the easy part: a server goes down, you spin up another. The failures that actually The post What running Kubernetes across millions of clusters taught AWS about zonal failures appeared first on The New Stack. ## Operating Kubernetes at scale: a few stories from running Amazon EKS DevFeed: [Operating Kubernetes at scale: a few stories from running Amazon EKS]() Original publisher: [Read original article]() Author: Neelendra Bhandari Published: 2026-06-30T13:00:00Z Content type: article Language: en Sources: [Kubernetes Overview, News and Trends | The New Stack]() Topics: [Amazon EKS](), [Kubernetes](), [Availability](), [systems](), [Apache Spark](), [AI Platform]() Tags: [agentic-ai](), [ai-infrastructure](), [amazon-eks](), [apache-spark](), [availability](), [aws-marketplace](), [cloud-services](), [data](), [gpu](), [kubernetes](), [post-contributed](), [real-time](), [sponsor-aws-marketplace](), [sponsored-post-contributed](), [systems]() ### AI overview This article describes how operating Amazon EKS at very large scale shaped approaches to Kubernetes control-plane resilience. It argues that availability problems often arise when components amplify faults, and explains how changing workload patterns--including foundation-model training, real-time inference, Apache Spark analytics, and agentic AI--create extremely rapid state transitions that challenge traditional Kubernetes operating assumptions. ### Source excerpt Amazon EKS runs hundreds of thousands of Kubernetes clusters across more than thirty AWS regions. Operating at that scale has The post Operating Kubernetes at scale: a few stories from running Amazon EKS appeared first on The New Stack. ## Building a Stateful IT Service Desk Agent with LangGraph on Amazon EKS DevFeed: [Building a Stateful IT Service Desk Agent with LangGraph on Amazon EKS]() Original publisher: [Read original article]() Author: Sunil Ramachandra Published: 2026-06-26T14:16:08Z Content type: tutorial Language: en Sources: [AWS Open Source Blog]() Topics: [AI Agent](), [Amazon EKS](), [Kubernetes](), [Amazon DynamoDB](), [Persistence](), [FastAPI](), [OpenTelemetry](), [Orchestration](), [autoscaling](), [Graphs](), [tracing](), [Open Source]() Tags: [ai-agent](), [amazon-dynamodb](), [amazon-eks](), [amazon-elastic-kubernetes-service](), [autoscaling](), [backend](), [graphs](), [kubernetes](), [open-source](), [opentelemetry](), [orchestration](), [persistence](), [tracing]() ### AI overview This article presents a stateful IT service desk AI agent built with LangGraph. It autonomously handles routine Level 1 support requests, escalates complex issues with context, persists state in Amazon DynamoDB, and uses Amazon EKS, FastAPI, OpenTelemetry, and Kubernetes autoscaling. ### Source excerpt IT support teams face a persistent challenge: employees expect instant answers to common questions (VPN setup, single sign-on troubleshooting, new-hire onboarding), but novel or complex issues still require human expertise. An AI agent that confidently answers, "How do I reset my VPN?" but hallucinates a response to "My IAM Identity Center session keeps expiring after [...] ## Build an EKS Environment Factory with Pulumi and vCluster DevFeed: [Build an EKS Environment Factory with Pulumi and vCluster]() Original publisher: [Read original article]() Author: Pablo Seibelt Published: 2026-06-04T00:00:00Z Content type: tutorial Language: en Sources: [Pulumi]() Topics: [Amazon EKS](), [Multitenancy](), [Kubernetes](), [Provisioning](), [Architecture & Design](), [Amazon Web Services](), [CI/CD]() Tags: [amazon-eks](), [architecture](), [aws](), [ci-cd](), [infrastructure](), [kubernetes](), [multi-tenancy](), [platform-engineering](), [provisioning](), [pulumi](), [tutorials]() ### AI overview A tutorial shows how to build an ephemeral Kubernetes environment factory with Pulumi, Amazon EKS Auto Mode, and vCluster. It uses a shared host cluster with virtual tenant clusters to reduce environment sprawl, provisioning delays, and operational overhead while preserving tenant isolation controls. ### Source excerpt AWS reports in an AWS Architecture Blog case study that Deloitte's move to a virtual cluster model on Amazon EKS resulted in 89% faster testing environment provisioning. By consolidating dozens of disparate clusters into a single host cluster with over 50 vCluster instances, the case study says Deloitte saved about 500 QA hours per year. This "Environment Factory" pattern allows platform teams to provide isolated, ephemeral Kubernetes environments on demand without the cost or lag of full cluster provisioning. This post adapts that general architecture with Pulumi to orchestrate Amazon EKS Auto Mode and vCluster. The problem: environment sprawl and provisioning lag Traditional development workflows often rely on one full EKS cluster per developer or feature branch. While this provides strong isolation, it introduces major pain points. Provisioning a full cluster can take 15 minutes or more, which slows down CI/CD pipelines. Managing dozens of clusters also leads to high costs and significant operational overhead. Platform teams need a "soft multi-tenancy" model. This model should feel like a dedicated cluster to the developer but run on shared infrastructure to keep costs low and startup times fast. Architecture overview: the host and the tenants The environment factory architecture consists of two main layers. Host cluster: A single, reliable EKS cluster managed with EKS Auto Mode. This cluster provides the underlying compute, networking, and storage. Tenant environments: Virtual clusters (vCluster) running as pods within host namespaces. According to the vCluster architecture, the virtual control plane handles API requests while a syncer maps virtual resources to the host cluster. This separation allows tenants to manage their own CRDs, namespaces, and RBAC while platform teams use quotas, NetworkPolicies, pod security, IAM boundaries, and node isolation controls to protect the host and other tenants. Implementation: the EKS Auto Mode host EKS Auto Mode simplifies ## Chainguard EKS add-ons are now available in the AWS Marketplace DevFeed: [Chainguard EKS add-ons are now available in the AWS Marketplace]() Original publisher: [Read original article]() Published: 2026-04-30T00:00:00Z Content type: release Language: en Sources: [Chainguard: Unchained]() Topics: [Amazon EKS](), [aws-marketplace](), [chainguard](), [Security](), [supply-chain-security](), [Image](), [Containers]() Tags: [aws-eks-add-ons](), [aws-marketplace](), [chainguard](), [chainguard-aws](), [chainguard-containers](), [chainguard-eks-add-ons](), [compliance](), [eks-add-ons](), [fips](), [fips-140-3](), [kubernetes](), [security](), [software-supply-chain]() ### AI overview Chainguard announces that its EKS add-ons are available in AWS Marketplace. The five add-ons provide networking, DNS, storage, and traffic-management components, with zero-known-CVE images and FIPS 140-3 validation for organizations that need greater control over security and compliance. ### Source excerpt Chainguard delivers zero-CVE, FIPS 140-3 EKS add-ons on AWS Marketplace, simplifying secure Kubernetes for regulated environments with full control. ## Improving DNS performance with NodeLocalDNS DevFeed: [Improving DNS performance with NodeLocalDNS]() Original publisher: [Read original article]() Author: Luca Cittadini Published: 2025-12-01T16:36:27Z Content type: article Language: en Sources: [Blog -- Neon Docs]() Topics: [Kubernetes](), [Caching](), [Latency](), [Amazon EKS](), [Network](), [Databases](), [Process]() Tags: [aws](), [caching](), [clusters](), [database](), [dns](), [engineering](), [kubernetes](), [latency](), [network](), [performance](), [postgres](), [systems]() ### AI overview Neon describes deploying node-local-dns across its Kubernetes fleet to reduce DNS latency for ephemeral Postgres databases. Local caching moves most cache-hit DNS traffic off the network and avoids round trips to CoreDNS, while trading additional node memory for lower latency. ### Source excerpt At Neon, we run hundreds of thousands of Postgres databases as ephemeral Kubernetes pods. Because of our scale-to-zero feature, every time a user connects to their database, there's a chance that we need to spin up a new Postgres process to serve that connection. The newly spun P... ## Transforming Customer Experience with DevOps and Cloud Practices DevFeed: [Transforming Customer Experience with DevOps and Cloud Practices]() Original publisher: [Read original article]() Author: Urolime Technologies Published: 2025-11-11T12:34:32Z Content type: article Language: en Sources: [Kubernetes Archives - Urolime Blogs]() Topics: [Cloud](), [DevOps](), [Deployment](), [CI/CD](), [Infrastructure as code](), [Scalability](), [Monitoring](), [Amazon EKS](), [personalization](), [Amazon Web Services]() Tags: [aws](), [aws-cloud-consulting](), [aws-consulting](), [ci-cd](), [cloud](), [deployment](), [devops](), [infrastructure-as-code](), [kubernetes](), [kubernetes-consulting](), [monitoring](), [scalability]() ### AI overview This article explains how cloud and DevOps practices can improve customer experience through faster delivery, greater reliability, resilience, scalability, and personalization. It discusses AWS and Kubernetes consultation, CI/CD pipelines, Infrastructure as Code, monitoring, failover, and cloud-native architecture. ### Source excerpt Irrespective of the ask, as the user journey on digital ecosystem is in full swing, customer requirements are being completely transformed. They expect ubiquity with seamless interaction platforms, always-on availability, greater reliability, and personalization. Businesses have to adopt new patterns of software development, deployment, and operation if they wish to be at their optimum game. [...] ## Kubernetes Production Topologies: EKS vs GKE vs AKS DevFeed: [Kubernetes Production Topologies: EKS vs GKE vs AKS]() Original publisher: [Read original article]() Author: Abhimanyu Saharan Published: 2025-07-19T00:00:00Z Content type: comparison Language: en Sources: [Abhimanyu Saharan]() Topics: [Kubernetes](), [Amazon EKS](), [Amazon Web Services](), [Azure](), [Google]() Tags: [aks](), [aws](), [azure](), [clusters](), [design](), [how-to](), [kubernetes]() ### AI overview A comparison of Kubernetes production topologies across AWS EKS, Google GKE, and Azure AKS, focused on designing resilient, production-grade clusters. ### Source excerpt Compare Kubernetes topologies across AWS EKS, Google GKE, and Azure AKS. Learn how to design resilient, production-grade clusters the right way. ## Cut AWS costs 40% while scaling faster with EKS, Karpenter, and Spot Instances DevFeed: [Cut AWS costs 40% while scaling faster with EKS, Karpenter, and Spot Instances]() Original publisher: [Read original article]() Author: Luis Rodríguez Published: 2025-06-27T10:00:00Z Content type: article Language: en Sources: [Tinybird]() Topics: [Amazon EKS](), [Amazon Web Services]() Tags: [aws](), [scalable-analytics-architecture]() ### AI overview The article explains changes that cut AWS costs by 40% while improving scaling speed with EKS, Karpenter, and Spot Instances. ### Source excerpt We cut AWS costs 40% while scaling faster using EKS, Karpenter, and Spot Instances. Here's exactly what we changed. ## How to use Teleport Machine ID to provide database access to applications running on EKS without passwords DevFeed: [How to use Teleport Machine ID to provide database access to applications running on EKS without passwords]() Original publisher: [Read original article]() Author: info@goteleport.com (Gavin Frazar) Published: 2024-12-03T00:00:00Z Content type: tutorial Language: en Sources: [Teleport]() Topics: [Amazon EKS](), [Kubernetes](), [PostgreSQL](), [Authorization](), [AWS Fargate](), [certificates](), [Access Control](), [Amazon Elastic Container Service](), [TLS (Transport Layer Security)](), [AWS IAM](), [container](), [VPC]() Tags: [access-control](), [api-keys](), [aws-fargate](), [aws-iam](), [certificates](), [container](), [ecs](), [how-to](), [kubernetes](), [passwords](), [postgresql](), [secrets](), [tls](), [vpc]() ### AI overview A tutorial on deploying Temporal on Amazon EKS so it can connect to an AWS RDS PostgreSQL database without passwords or other shared secrets. It uses Teleport Machine & Workload Identity, a sidecar, short-lived X.509 certificates, PostgreSQL role provisioning, and a Teleport Database Service deployed on AWS Fargate. ### Source excerpt Discover how to secure database access in Kubernetes workloads. Eliminate secrets, keep databases in private networks, and improve audit logging with Teleport. ## Snyk and AWS announce native Amazon EKS support directly from the AWS Management Console DevFeed: [Snyk and AWS announce native Amazon EKS support directly from the AWS Management Console]() Original publisher: [Read original article]() Author: David Lugo Published: 2024-06-12T05:00:00Z Content type: release Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Amazon EKS](), [aws-marketplace](), [AWS Management Console](), [Deployment](), [Command-line interface]() Tags: [add-ons](), [amazon](), [amazon-eks](), [application-security](), [awareness](), [aws](), [aws-management-console](), [aws-marketplace](), [blog](), [cli](), [deployment](), [devops](), [executive](), [getting-started](), [installation](), [integration](), [interest](), [kubernetes](), [related-content](), [security](), [snyk]() ### AI overview Snyk has introduced an AWS Marketplace add-on for Amazon EKS, embedded in the AWS Management Console. Customers can deploy the Snyk Runtime Sensor to existing or new EKS clusters through the console or AWS CLI, subject to AWS Marketplace subscription and a Snyk license. ### Source excerpt Snyk has now developed an AWS Marketplace add-on for Amazon Elastic Kubernetes Service (Amazon EKS) embedded directly into the AWS Management Console. ## A behind-the-scenes look at building interactive analysis capabilities in Benchling DevFeed: [A behind-the-scenes look at building interactive analysis capabilities in Benchling]() Original publisher: [Read original article]() Author: Wonja Fairbrother Published: 2024-06-11T13:01:25Z Content type: article Language: en Sources: [Benchling]() Topics: [data-processing](), [web applications](), [Amazon EKS](), [Amazon S3](), [API](), [Back end](), [Front end](), [JSON]() Tags: [apache-arrow](), [apache-parquet](), [api](), [architecture](), [backend](), [data](), [data-analysis](), [data-transformation](), [data-visualization](), [duckdb](), [frontend](), [json](), [real-time](), [s3](), [storage](), [systems]() ### AI overview This article explains the architecture and design decisions behind Benchling's Interactive Analysis capabilities. The system lets scientists select data from multiple sources, transform and analyze it in real time, and visualize results within Benchling. Its architecture uses the Benchling web application, a stateless service running on EKS, temporary S3 storage, and a JSON-based transformation API. ### Source excerpt Authors: Wonja Fairbrother and Eli Levine Science is iterative. To design the next experiment, scientists need to analyze the results of previous ones. Interactive Analysis in Benchling allows scientists to perform real-time data transformation, visualization, and analysis without having to transfer it into other systems. In this post we will describe the architecture behind interactive analysis capabilities in Benchling and give a peek into the decision journey we took along the way¹. Interactive Analysis allows scientists to: 1. Select data from many sources: Benchling entity and results data Instrument data Notebook tables Data upload via both API and UI 2. Transform, visualize, and analyze data in real time, without leaving Benchling: Data transformations: filtering, aggregations, window functions, etc. Visualizations: line chart, bar chart, scatter plot, etc. Scientific analysis methods: IC50 and various curve fitting functions Overall architecture The architecture backing Interactive Analysis consists of: The Benchling web application An auto-scaling stateless internal service running on EKS that performs the transformations Temporary S3 storage locations for input and output data, shared between the web app and the service The frontend of the application is responsible for taking in input datasets and transformation configurations from users. The backend of the web application collects all the input data from the appropriate sources, serializes and uploads the data to S3, and sends a synchronous transformation request to the service. The service's API consists of one main endpoint that takes in a JSON payload of transformation parameters. The service can accept a single transformation, or a list of many transformations to perform. In this endpoint, the service downloads and deserializes the input data, performs the transformation with an analysis engine, and serializes and uploads the resulting data to S3. Each request spins up its own self-contained in-memor ## How to ensure your Kubernetess cluster can tolerate lost nodes DevFeed: [How to ensure your Kubernetess cluster can tolerate lost nodes]() Original publisher: [Read original article]() Author: Andre Newman Published: 2024-04-12T00:00:00Z Content type: article Language: en Sources: [Gremlin Blog]() Topics: [Kubernetes](), [Resilience](), [Amazon EKS](), [DevOps](), [hosting]() Tags: [availability](), [cloud](), [gremlin](), [hosting](), [how-to](), [kubernetes](), [resilience]() ### AI overview This article explains how Kubernetes redundancy helps applications tolerate failed Pods, deployments, and worker nodes. It covers replica management, failure detection, traffic rerouting, replica recovery, and the role of managed Kubernetes services such as Amazon Elastic Kubernetes Service in adding or removing worker nodes. It also introduces Gremlin's Recommended Scenarios for verifying cluster resilience. ### Source excerpt Kubernetes is known for its redundancy features, but that doesn't make it infallible. Learn what the risks are of having a Kubernetes node fail, and how you can prepare for them using Gremlin. [Next page]()