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Accelerating application development with the Amazon EKS MCP server

TheEKS MCP serverhands AI code assistants, likeQ Developer CLI, the keys to a streamlined Kubernetes kingdom. App development? Now lightning fast. WithLLMstapping into real-time context, AI flexes its muscles in the wild world of Kubernetes ops and troubleshooting... read more  

Accelerating application development with the Amazon EKS MCP server
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Introducing MCP Catalog and Toolkit: The Simple and Secure Way to Power AI Agents with MCP

Docker's MCP Catalog and Toolkit bust myths and solve setup headaches, smoothing out AI agent development with snug, secure containers.With heavy-hitter partners likeStripe,Elastic, andHerokuon board, developers now revel in one-click connections through Docker Desktop. Integration nightmares and se.. read more  

Introducing MCP Catalog and Toolkit: The Simple and Secure Way to Power AI Agents with MCP
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Secrets Management in CI/CD Pipeline: Best Practices & Tools

Hardcoding secrets is a ticking time bomb. Instead, reach for centralized tools like HashiCorp Vault; they'll guard your secrets like a vault should. Automate secret rotation so your credentials don't gather dust, and log everything to keep tabs on who does what. Devtron makes it a breeze with its K.. read more  

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Kubernetes CRD Abstraction Risks in kro

Orca Research Pod discovered two bugs in kro that could allow an attacker to introduce a malicious CustomResourceDefinition (CRD). Kro is an open-source project enabling custom Kubernetes APIs using ResourceGraphDefinition resources. These vulnerabilities could lead to a confused deputy scenario whe.. read more  

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Upgrading ECK Operator: A Side-by-Side Kubernetes Operator Upgrade Approach

Abhishek Munagekar from the Search Infrastructure Team at Mercari manages several Elasticsearch clusters on Kubernetes using the Elastic Cloud on Kubernetes (ECK) Operator. The team embarked on an upgrade project to leverage advancements in newer ECK operator versions. By implementing a custom side-.. read more  

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Open Source KubeVirt: VM Management With Kubernetes Is a Work in Progress

KubeVirtpromises the glitzy dream: running VMs in Kubernetes. With Red Hat and friends fanning the flame, it seems poised for greatness. But hold your applause—it's not yet a production powerhouse. Advanced VM management features? Missing in action. Switching to KubeVirt isn't just a hop; it's a lea.. read more  

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Why Kubernetes 1.33 Is a Turning Point for MLOps — and Platform Engineering

Kubernetes v1.33crushes it for AI/ML workloads with slickDynamic Resource Allocation.Your GPU headaches? Gone. It's nimble, modular, and ready to scale. Plus, with topology-aware routing now in the spotlight, Kubernetes slashes network latency and trims cloud expenses by favoring the nearest options.. read more  

Why Kubernetes 1.33 Is a Turning Point for MLOps — and Platform Engineering
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Kubernetes at Google Cloud: AI, containers and open source scale

Kubernetestransformed from an obscure tech into a backbone for cloud-native AI projects. Today,Google Cloudtakes the crown for effortlessly scaling AI models withGKE. Together,Cloud RunandKubernetescurb AI inference expenses. The secret sauce? On-the-fly GPU access and serverless wizardry that let e.. read more  

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10 Open Source Kubernetes Security Tools 2025

A wild440%spike in Kubernetes vulnerabilities over five years calls for open-source security tools that actually get the job done. Still, half of the organizations feel like they're playing catch-up trying to lock it down. Enter tools likeFalcoandIstio. Falco sniffs out runtime anomalies while Istio.. read more  

10 Open Source Kubernetes Security Tools 2025
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High Available Mosquitto MQTT on Kubernetes

Running a Kubernetes-nativeMQTT brokerwith Eclipse Mosquitto cuts downtime to a mere5 seconds. Compare that to the usual 5-minute snooze. This feat involves Traefik sorcery and a custom failover rig. Uninterrupted message flow? Check. Real-time state? Handled with message bridges that practically da.. read more  

High Available Mosquitto MQTT on Kubernetes
GPT-5.4 is OpenAI’s latest frontier AI model designed to perform complex professional and technical work more reliably. It combines advances in reasoning, coding, tool use, and long-context understanding into a single system capable of handling multi-step workflows across software environments. The model builds on earlier GPT-5 releases while integrating the strong coding capabilities previously introduced with GPT-5.3-Codex.

One of the defining features of GPT-5.4 is its ability to operate as part of agent-style workflows. The model can interact with tools, APIs, and external systems to complete tasks that extend beyond simple text generation. It also introduces native computer-use capabilities, allowing AI agents to operate applications using keyboard and mouse commands, screenshots, and browser automation frameworks such as Playwright.

GPT-5.4 supports context windows of up to one million tokens, enabling it to process and reason over very large documents, long conversations, or complex project contexts. This makes it suitable for tasks such as analyzing codebases, generating technical documentation, working with large spreadsheets, or coordinating long-running workflows. The model also introduces a feature called tool search, which allows it to dynamically retrieve tool definitions only when needed. This reduces token usage and makes it more efficient to work with large ecosystems of tools, including environments with dozens of APIs or MCP servers.

In addition to improved reasoning and automation capabilities, GPT-5.4 focuses on real-world productivity tasks. It performs better at generating and editing spreadsheets, presentations, and documents, and it is designed to maintain stronger context across longer reasoning processes. The model also improves factual accuracy and reduces hallucinations compared with previous versions.

GPT-5.4 is available across OpenAI’s ecosystem, including ChatGPT, the OpenAI API, and Codex. A higher-performance variant, GPT-5.4 Pro, is also available for users and developers who require maximum performance for complex tasks such as advanced research, large-scale automation, and demanding engineering workflows. Together, these capabilities position GPT-5.4 as a model aimed not just at conversation, but at executing real work across software systems.