Join us

ContentUpdates and recent posts about BigQuery..
 Activity
@ishanupadhyay started using tool Docker , 2 weeks, 2 days ago.
 Activity
@ishanupadhyay started using tool Argo CD , 2 weeks, 2 days ago.
 Activity
@ishanupadhyay started using tool Amazon Web Services , 2 weeks, 2 days ago.
News FAUN.dev() Team Trending
@kala shared an update, 2 weeks, 2 days ago
FAUN.dev()

NanoClaw + Docker Sandboxes: Secure Agent Execution Without the Overhead

NanoClaw Claude Code Docker

NanoClaw integrates with Docker Sandboxes to enhance AI agent security through strong isolation and transparency. This collaboration focuses on enabling secure and autonomous operations for AI agents within enterprise environments.

Link
@varbear shared a link, 2 weeks, 2 days ago
FAUN.dev()

Interview with Thomas Wouters - release Manager for Python

The interview traces Python's core evolution. It starts with addingaugmented assignment(+=) and thePEP 203debates. Arguments followed. Nested scopeslanded viafuture imports. Maintainers repackagedelementtree/xmlplususingpath. asynciorose and supplantedTwisted. Python moved toyearly releases... read more  

Link
@varbear shared a link, 2 weeks, 2 days ago
FAUN.dev()

The real cost of random I/O

Therandom_page_costwas introduced ~25 years ago, and its default value has remained at 4.0 since then. Recent experiments suggest that the actual cost of reading a random page may be significantly higher than the default value, especially on SSDs. Lowering therandom_page_costmay not always be the be.. read more  

The real cost of random I/O
Link
@varbear shared a link, 2 weeks, 2 days ago
FAUN.dev()

Things I miss about Spring Boot after switching to Go

The author migrated fromJava/Spring BoottoGolang. Spring bundlesSecurity,Data,Actuator, and auto-wiring. Go prefers minimalist libraries and explicit wiring. It produces static binaries, instant startup, lower memory use, and nativegoroutineconcurrency. Spring needs JVM startup and GC tuning... read more  

Things I miss about Spring Boot after switching to Go
Link
@varbear shared a link, 2 weeks, 2 days ago
FAUN.dev()

Why is WebAssembly a second-class language on the web?

The post catalogs recentWebAssemblyextensions:shared memory,SIMD,exceptions,tail calls,64-bit memory,GC,bulk memory,multiple returns, andreference types. It arguesWebAssemblyremains a second-class web language. MessyJS glueand arcane loading keep it there. The post pushes theWebAssembly Component Mo.. read more  

Link
@varbear shared a link, 2 weeks, 2 days ago
FAUN.dev()

How to steal npm publish tokens by opening GitHub issues

Attackers pushed a poisonedcline@2.3.0to npm using a stolen publish token. ItspostinstallinstalledOpenClawglobally. An AI triage bot let a malicious issue title trickClaudeinto running commands on a GitHub Actions runner. It wrote a poisonedactions/cacheentry. The nightly release restored the poison.. read more  

Link
@kaptain shared a link, 2 weeks, 2 days ago
FAUN.dev()

When Kubernetes Is the Wrong Default

The guide mapsteam size,workload shape, andtime-to-valueto three tiers:managed platforms,VMs, andKubernetes. It calls outKubernetesbluntly: expect a 1–3 month delay to production. Expect ongoing consumption of 30–50% of one engineer. It only pays off for multi-region setups, complex networking, or t.. read more  

When Kubernetes Is the Wrong Default
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).