Updates and recent posts about GPT-5.4..

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@faun shared a link, 9 months, 1 week ago

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The Art of Azure RBAC for Kubernetes: A Complete Guide to Access Control Mastery

This article dives into Azure RBAC for Kubernetes. It maps each persona to pinpoint roles per namespace. Permissions stay minimal from the get-go. It ties role bindings toAzure AD groups, splits dev and prod, and flips on audit logs. Quarterly reviews, crisp docs keep RBAC lean and current... read more

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@faun shared a link, 9 months, 1 week ago

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We Added Chaos to Our CI/CD Pipelines — It Made Everything More Stable.

Wix’sMREteam injectsAI-drivenchaosintoCI/CDpipelines. Mobile releases gain speed and rock-solid stability. They harness hackathon-born prompt tests to bulletproof builds and deployments. Signal: AI resilience trials in pipelines mark a shift from rigid builds to probabilistic validation... read more

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@faun shared a link, 9 months, 1 week ago

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Critical VMware Tools VGAuth Vulnerabilities Enable Full System Access for Attackers

Two CVE-2025 vulns in VMware Tools allow SYSTEM access via named pipe hijacking and path traversal. Upgrade to 12.5.1+ ASAP for fixes. Administrators must upgrade... read more

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@faun shared a link, 9 months, 1 week ago

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GitHub Spark in public preview for Copilot Pro+ subscribers

GitHub Spark spins natural-language prompts into full-stack AI apps in minutes. It tapsClaude Sonnet 4to scaffold UI and server logic. It hooks updata storage,LLM inference, hosting,GitHub Actions,Dependabot, plus multi-LLM smarts from OpenAI, Meta, DeepSeek and xAI—zero config. Trend to watch: AI .. read more

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@faun shared a link, 9 months, 1 week ago

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Kubernetes Image Builder Vulnerability Grants Root Access to Windows Nodes

A critical CVE-2025-7342 hauntsKubernetes Image Builder v0.1.44and earlier. It shipsNutanix/OVAimages with defaultWindows Administratorcreds intact. That slip-up invites root access on Windows nodes. Linux builds and other providers dodge this bullet. Mixed clusters run hot until images rebuild or p.. read more

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@faun shared a link, 9 months, 1 week ago

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Centralized Amazon ECS task logging with Amazon OpenSearch

Amazon ECS tasks fire logs through a FireLens sidecar. Fluent Bit ships them into a shared Amazon OpenSearch Serverless domain. Cross-account IAM roles lock down access. The pipeline centralizes logs, unlocks full-text search, SQL and PPL queries, and slashes storage costs with on-demand indexing. .. read more

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@faun shared a link, 9 months, 1 week ago

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Bare-Metal Kubernetes: The Performance Advantage Is Almost Gone

Benchmarks crack open the myth: VM-based Kubernetes rivals bare metal. It secures 99% throughput. It matches latency in netperf and MLPerf. Major clouds spin containers on VMs. They enforce hard resource caps, isolation, and central policy management. Bare metal shrinks to ultra-low-latency niches. .. read more

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@faun shared a link, 9 months, 1 week ago

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A Mid-Year Look at CNCF Project Momentum

Cloud Native Computing Foundation’s mid-year report drops.Kubernetescommands 3,500+ authors.OpenTelemetryrockets to 1,884 contributors, snagging second in PR velocity.Backstageclimbs to 649.Argo(860) andFlux(156) lock GitOps in place.Kubeflowbreaks into the top 30 with 302. Trend to watch:Internal .. read more

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Scaling beyond IPv4: integrating IPv6 Amazon EKS clusters into existing Istio Service Mesh

Amazon EKS now powers IPv6 dual-stack VPC clusters. It doles out /80 prefixes via the VPC CNI flagsENABLE_V6_EGRESSandENABLE_V4_EGRESS. AWS ships an Istio multi-cluster playbook—single-VPC to multi-VPC. It rigs remote reader secrets and east-west gateways, fusing IPv4 and IPv6 for service discovery.. read more

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Critical Container Registry Security Flaw: How Multi-Architecture Manifests Create Attack Vectors

ContainerHijack hijacksDocker Image Manifest V2 Schema 2. It taints images inDocker Hub,Amazon ECR,GCR. Scanners shrug. Signature checks buckle. Defenders deploypolicy-as-code admission controllers. They lock down Terraform ECR push policies.Falco rulesflag strange layers, ghost pushes, rogue proces.. read more

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.