Updates and recent posts about BigQuery..

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News FAUN.dev() Team

@varbear shared an update, 3 months, 2 weeks ago

FAUN.dev()

New MCP Release v0.10.0 Supercharges AI-Assisted Web Development

#AI codi... #Model C... #perform... #Debuggi... #Chrome ...

Chrome DevTools MCP v0.10.0 unlocks deeper AI-powered debugging with new tools for DOM access, network request detection, page reload automation, performance insights, and snapshot saving.

Google Launches Chrome DevTools MCP Server Preview for AI-Driven Web Debugging

Activity

@varbear added a new tool chrome-devtools-mcp , 3 months, 2 weeks ago.

News FAUN.dev() Team

@varbear shared an update, 3 months, 2 weeks ago

FAUN.dev()

AWS Lambda Gets Python 3.14: Faster, Smarter, and More Serverless-Friendly

#aws #Python ... #Lambda@... #AWS Lam...

Python 3.14 is now available in AWS Lambda, enabling developers to leverage new Python features for serverless applications.

AWS Lambda Gets Python 3.14: Faster, Smarter, and More Serverless-Friendly

News FAUN.dev() Team

@kaptain shared an update, 3 months, 2 weeks ago

FAUN.dev()

The Most Absurd (and Brilliant) Kubernetes Cluster at KubeCon 2025

#kubecon #PETAFLO... #LattePa... #nvidia #kuberne...

Engineer Justin Garrison showcased a backpack-sized PETAFLOP Kubernetes cluster at KubeCon 2025, demonstrating localized AI capabilities without cloud reliance.

The Most Absurd (and Brilliant) Kubernetes Cluster at KubeCon 2025

Activity

@kaptain added a new tool Talos Linux , 3 months, 2 weeks ago.

News FAUN.dev() Team

@kaptain shared an update, 3 months, 2 weeks ago

FAUN.dev()

Google Breaks Kubernetes Limits Again: Inside the 130,000-Node GKE Cluster

#GKE #Google ... #Google #AI #kuberne...

Google successfully operates a 130,000-node Kubernetes cluster to enhance GKE's scalability for AI workloads.

Control plane throughput: Sustaining up to 1,000 operations per second for both Pod creation and Pod binding during intense scheduling phases.

Activity

@kaptain added a new tool kueue , 3 months, 2 weeks ago.

News FAUN.dev() Team

@devopslinks shared an update, 3 months, 2 weeks ago

FAUN.dev()

Inside Cloudflare's Worst Outage Since 2019: How a Single Config File Broke the Internet

#Feature... #DDoS #Postmor... #cloudfl... #outage

A database permissions change led to a Cloudflare outage by creating an oversized feature file, causing network failures initially mistaken for a DDoS attack.

Inside Cloudflare's Worst Outage Since 2019: How a Single Config File Broke the Internet

News FAUN.dev() Team

@devopslinks shared an update, 3 months, 2 weeks ago

FAUN.dev()

Valkey 9.0 Released: Faster Clusters, New TTL Controls, and Big Networking Gains

#scalabi... #Valkey #Valkey ... #Redis #open so...

Valkey 9.0 debuts with atomic slot migrations, hash field expiration, and improved cluster mode support, enhancing data management and scalability.

Valkey 9.0 Released: Faster Clusters, New TTL Controls, and Big Networking Gains

News FAUN.dev() Team

@devopslinks shared an update, 3 months, 2 weeks ago

FAUN.dev()

Grafana 12.3 Lands With New Learning Tools, Better Logs, and a Critical Security Fix

#Securit... #Grafana #observa... #monitor... #visuali...

Grafana 12.3 enhances user experience with interactive learning, improved logs visualization, and a critical security fix, alongside new features like dashboard image export and expanded data source support.

Grafana 12.3 Lands With New Learning Tools, Better Logs, and a Critical Security Fix

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).