Cloud Native CI/CD with GitLab
From Commit to Production Ready
Updates and recent posts about BigQuery.. Activity
@devopslinks added a new tool Lustre , 3 weeks ago.
Course
@eon01 published a course, 3 weeks, 1 day ago
Founder, FAUN.dev
Course 
@eon01 published a course, 3 weeks, 3 days ago
Founder, FAUN.dev
Observability with Prometheus and Grafana
A Complete Hands-On Guide to Operational Clarity in Cloud-Native Systems
Course 
@eon01 published a course, 3 weeks, 3 days ago
Founder, FAUN.dev
Cloud-Native Microservices With Kubernetes - 2nd Edition
A Comprehensive Guide to Building, Scaling, Deploying, Observing, and Managing Highly-Available Microservices in Kubernetes
Course
@eon01 published a course, 3 weeks, 3 days ago
Founder, FAUN.dev
Link
@anjali shared a link, 3 weeks, 3 days ago
Customer Marketing Manager, Last9
Instrument Jenkins With OpenTelemetry
Instrument Jenkins with OpenTelemetry to understand pipeline behavior, stage latency, and deploy steps using a single telemetry flow.
Activity
@devopslinks added a new tool Fleet , 3 weeks, 3 days ago.
Activity
@kaptain added a new tool Rancher Kubernetes Engine (RKE2) , 3 weeks, 3 days ago.
Course
@eon01 published a course, 3 weeks, 4 days ago
Founder, FAUN.dev
End-to-End Kubernetes with Rancher, RKE2, K3s, Fleet, Longhorn, and NeuVector
The full journey from nothing to production
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).
