Updates and recent posts about BigQuery..

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@faun shared a link, 1 year ago

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AWS Introduces Extended Threat Detection for EKS via GuardDuty

AWSGuardDutycranks up EKS security using slickeBPFagents. These agents snag threats like reverse shells and crypto mining directly at the container level. No fuss with user-deployed agents needed. GuardDuty shrugs off traditional security headaches, nudging cloud giants like AWS toward smarter, hass.. read more

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How I Stopped Worrying About Costs and Learned to Love Kubernetes

Deploying a punyHello Worldapp on Kubernetes? Brace yourself. The meter's running even before your first visitor stumbles in—over$150/monthjust for the control plane. Solution? EnterRackspace Spot. Slash that tab by up to76%using bargain-basement servers that practically pay you at $0.001/hour, plus.. read more

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Containerizing AI: Hands-On Guide to Deploying ML Models With Docker and Kubernetes

Containerization bundles ML model code and dependencies for reproducibility and portability, easing scaling and isolating environments. Kubernetes automates management for seamless deployments and scalability, guaranteeing consistent performance... read more

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State of App Dev: AI

64% of users find AI tools actually lighten the workload, yet 59% roll their eyes at the hype—function outshines flash.But behind the curtain, data prep still plays villain, tripping up 24% of AI builders... read more

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Streamlining application deployment on Kubernetes at RBC Capital Markets: A journey with FluxCD

RBC FinSec Incubatorlaunched with Rogers Cybersecure Catalyst to support fintech and cybersecurity startups in meeting financial sector needs... read more

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Enforce admission policies with artifact attestations in Kubernetes using OPA Gatekeeper

OPA Gatekeeperups the ante on Kubernetes security. How? By enforcingGitHub Artifact Attestationswith the flair of a seasoned bouncer. Non-compliant images now get the boot before they even think about deployment... read more

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Kubernetes configuration as code – Gitea and ArgoCD

ArgoCDbrings serious application management chops to the table. But when it meets existingHelmsetups, chaos might ensue—junk those old secrets to clear the path... read more

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How To Run Kubernetes Commands in Go: Steps and Best Practices

Gocranks upKubernetesautomation, letting you tango directly with clusters at lightning speed. Forget clumsy shell scripts. Dive into Go's slick native libraries to conjure up CLI tools and seamless automation. Meanwhile, bask in rock-solid community support and run your masterpieces on any platform... read more

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What's New in ArcGIS Enterprise 11.5 on Kubernetes

ArcGIS Enterprise 11.5onKubernetesjust lifted its game. It's rolling out support forStreetMap Premium, cranking up the speed with GPU nodes forNotebooks, and cozying up to the cloud viaVMware Tanzu. Expect faster GIS ops. There's also a shiny new file management UI for Notebooks, custom-built for yo.. read more

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How MacOS Tahoe's killer new feature could make Docker feel obsolete

macOS Tahoerolls out nativeLinux containersupport. Goodbye, third-party hoop-jumping with Docker. Hello, secure coding paradise. Developers rejoice!.. 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).