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@kaptain shared a link, 1 week, 5 days ago
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How WebAssembly plugins simplify Kubernetes extensibility

Helm 4runsWebAssembly (Wasm)plugins to executeWASImodules insideOCIcontainers and VMs.Helmtemplates standardize module lifecycle. The Wasm plugin adds instruction-level sandboxing and Kubernetes segmentation.Helm 4preserves portability acrossx86/ARM. Compared withHelm 3plugins, it shows up to a 40% .. read more  

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@kaptain shared a link, 1 week, 5 days ago
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pg_plan_alternatives: Tracing PostgreSQL’s Query Plan Alternatives using eBPF

The tracer hooks PostgreSQL's optimizer via eBPF. It captures every alternative plan path with cost estimates and flags the chosen plan. A kernel-space eBPF program reads planner structs using DWARF-derived offsets. A user-space collector gathers the data and a visualizer renders plan graphs. eBPF p.. read more  

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@kaptain shared a link, 1 week, 5 days ago
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The great migration: Why every AI platform is converging on Kubernetes

The CNCF survey finds82%of container users runKubernetesin production.66%of GenAI hosts use it for inference. Kubernetes now stitches data processing, distributed training, LLM inference, and autonomous agents viaSpark,Kubeflow,Kueue,KServe, andArmada. GPU sharing and scheduling advanced withMIG, ti.. read more  

The great migration: Why every AI platform is converging on Kubernetes
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@kaptain shared a link, 1 week, 5 days ago
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How Does Kubernetes Self-Healing Work? Understand Self-Healing By Breaking a Real Cluster

KubeLab boots a three-nodeKubernetescluster and runs seven failure simulations. It deploysNode.js,Postgres,Prometheus, andGrafana. Then it deletes pods, forcesOOMKill, throttles CPU, drains nodes, and scales aStatefulSetto zero. Each scenario surfaces fixes:readiness probes,PodDisruptionBudget, anti.. read more  

How Does Kubernetes Self-Healing Work? Understand Self-Healing By Breaking a Real Cluster
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@kala shared a link, 1 week, 5 days ago
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Reasoning models struggle to control their chains of thought, and that’s good

OpenAI's paper unveilsCoT-Control: an open-source suite of 13,000+ tasks fromGPQA, MMLU-Pro, HLE, BFCLthat measuresCoTcontrollability. Evaluations on 13 models show compliance at 0.1%-15.4%. Compliance is tiny. Controllability improves with model size. It drops as reasoning chains lengthen and after.. read more  

Reasoning models struggle to control their chains of thought, and that’s good
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@kala shared a link, 1 week, 5 days ago
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The L in "LLM" Stands for Lying

The author arguesLLMschurn out fast, generic answers by remixing low-quality source material. They seed brittle, repetitive code viavibe-coding. The remedy: requiresource attributionand auditable inference to separate originals from forgeries and to reshape model training and deployment. Requiringso.. read more  

The L in "LLM" Stands for Lying
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@kala shared a link, 1 week, 5 days ago
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AI as tradecraft: How threat actors operationalize AI

Microsoft observes threat actors operationalizeAIandLLMsacross the cyberattack lifecycle. They accelerate reconnaissance, phishing, malware development, and post‑compromise triage. Actors abusejailbreakingtechniques andGANs. They craft personas, generate look‑alike domains, embed runtime‑adaptive pa.. read more  

AI as tradecraft: How threat actors operationalize AI
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@kala shared a link, 1 week, 5 days ago
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LLMs are getting better at unmasking people online

Researchers at ETH Zurich show LLMs can stitch anonymous bios to public web data and reidentify users across platforms. Fine-tuned models and agent chains parse unstructured text and automate deanonymization in minutes at penny-level inference costs... read more  

LLMs are getting better at unmasking people online
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@kala shared a link, 1 week, 5 days ago
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The reason big tech is giving away AI agent frameworks

A catalog of majoragent frameworks: LangGraph, CrewAI, Google ADK, AWS Strands, Microsoft Agent Framework, OpenAI Agents SDK, Mastra, Pydantic AI, Agno. Hyperscalers co-design free SDKs (e.g.,Strands,ADK). They tie those SDKs to metered runtimes -Bedrock,Vertex AI. Revenue shifts to inference and de.. read more  

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AWS Cost Optimization Best Practices: A Maturity-Based Guide [2026]

The guide maps a five-stagematurity model— fromVisibilitytoFinOps Culture. It prescribes staged actions before commitment purchases. It recommends turning onCost ExplorerandAWS Budgets, enforcingtag policies, runningCompute Optimizer, testingGraviton, and usingCloudBurn/Amazon Qfor pre-deploy estima.. read more  

Rancher is a Kubernetes management platform originally created by Rancher Labs and now maintained by SUSE. It is designed to simplify the deployment, operation, and security of Kubernetes clusters at scale, whether they run on public cloud, private cloud, on-premises data centers, or at the edge.

At its core, Rancher provides a centralized control plane that allows teams to create, import, and manage multiple Kubernetes clusters from a single UI and API. It supports a wide range of Kubernetes distributions, including upstream Kubernetes, RKE / RKE2, K3s, and managed cloud services like EKS, GKE, and AKS.

Rancher focuses heavily on enterprise needs such as multi-cluster management, role-based access control (RBAC), authentication integration (LDAP, Active Directory, OIDC), policy enforcement, and cluster lifecycle management. It enables platform teams to enforce consistent configurations and security policies while allowing application teams to self-serve Kubernetes resources safely.

The platform also integrates tightly with the broader cloud-native ecosystem. Rancher provides built-in support for Helm, monitoring (Prometheus, Grafana), logging, and GitOps workflows, and works well alongside tools like Argo CD, Fleet, and Longhorn for storage.

Rancher is often used as the foundation for platform engineering initiatives, helping organizations standardize Kubernetes operations, reduce operational complexity, and safely scale containerized workloads across environments.