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@kaptain shared a link, 4 weeks, 2 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, 4 weeks, 2 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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@kala shared a link, 4 weeks, 2 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, 4 weeks, 2 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, 4 weeks, 2 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, 4 weeks, 2 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, 4 weeks, 2 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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@devopslinks shared a link, 4 weeks, 2 days ago
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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  

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@devopslinks shared a link, 4 weeks, 2 days ago
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Why Serverless Compute Partners Are Now More Important Than Ever

The note saysAIworkloads are bursty. They spawn parallel tool calls, pull multi‑GB model weights into RAM, and endure long cold starts (e.g.,vLLM,SGLang). Companies wrestle with a fragmentedGPUmarket and poor peakGPU utilization. To hit latency, compliance, and cost targets they adoptmulti‑region/mu.. read more  

Why Serverless Compute Partners Are Now More Important Than Ever
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@devopslinks shared a link, 4 weeks, 2 days ago
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Amazon is back up after outage affecting tens of thousands of shoppers

Amazon faced an outage, affecting tens of thousands of shoppers globally on Thursday afternoon. Downdetector reported a surge in complaints, peaking at 20,000 by 3:49 p.m. ET. The outage involved checkout and pricing errors caused by a software code deployment... read more  

BigQuery is a cloud-native, serverless analytics platform designed to store, query, and analyze massive volumes of structured and semi-structured data using standard SQL. It separates storage from compute, automatically scales resources, and eliminates the need for infrastructure management, indexing, or capacity planning.

BigQuery is optimized for analytical workloads such as business intelligence, log analysis, data science, and machine learning. It supports real-time data ingestion via streaming, batch loading from cloud storage, and federated queries across external data sources like Cloud Storage, Bigtable, and Google Drive.

Query execution is distributed and highly parallel, enabling interactive performance even on petabyte-scale datasets. The platform integrates deeply with the Google Cloud ecosystem, including Looker for BI, Vertex AI for ML workflows, Dataflow for streaming pipelines, and BigQuery ML, which allows users to train and run machine learning models directly using SQL.

Built-in security features include fine-grained IAM controls, column- and row-level security, encryption by default, and audit logging. BigQuery follows a consumption-based pricing model, charging for storage and queries (on-demand or reserved capacity).