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News FAUN.dev() Team
@kala shared an update, 2 months, 1 week ago
FAUN.dev()

Google’s Cloud APIs Become Agent-Ready with Official MCP Support

Apigee Google Cloud Platform Google Kubernetes Engine (GKE) BigQuery

Google supports the Model Context Protocol to enhance AI interactions across its services, introducing managed servers and enterprise capabilities through Apigee.

 Activity
@devopslinks added a new tool BigQuery , 2 months, 1 week ago.
News FAUN.dev() Team
@devopslinks shared an update, 2 months, 1 week ago
FAUN.dev()

AWS Previews DevOps Agent to Automate Incident Investigation Across Cloud Environments

Datadog Amazon CloudWatch Dynatrace New Relic Amazon Web Services

AWS introduces an autonomous AI DevOps Agent to enhance incident response and system reliability, integrating with tools like Amazon CloudWatch and ServiceNow for proactive recommendations.

AWS Previews DevOps Agent to Automate Incident Investigation Across Cloud Environments
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@devopslinks added a new tool ServiceNow , 2 months, 1 week ago.
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@laura_garcia shared a post, 2 months, 1 week ago
Software Developer, RELIANOID

The UK raises the bar on digital security

With cyberattacks on the rise, the Product Security and Telecommunications Infrastructure (PSTI) Act marks a major step toward making connected technology secure by design. In our latest article, we explain: What the PSTI Act requires Why it matters beyond consumer IoT How it signals a global sh..

Story Palark Team
@shurup shared a post, 2 months, 1 week ago
@palark

New CNCF Sandbox projects in 2025: From Podman to CloudNativePG

Kubernetes

Each year, 25-30 new Open Source projects related to the Cloud Native ecosystem are accepted to the CNCF Sandbox. In January 2025, there were 13 additions, with four of them donated by Red Hat. Here's the list of these newly added CNCF projects: - Podman Container Tools (security-focused Docker alte..

CNCF Sandbox projects in January 2025
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@sancharini shared a post, 2 months, 1 week ago

CI Testing Best Practices for Reliable and Fast Builds

As software teams adopt continuous integration, build speed and reliability become critical success factors. CI testing plays a central role in ensuring that every code change is validated quickly and consistently before it moves further down the delivery pipeline. Without clear practices, however, ..

Story FAUN.dev() Team
@eon01 shared a post, 2 months, 2 weeks ago
Founder, FAUN.dev

Announcing FAUN.sensei() — Self-paced guides to grow fast — even when tech moves faster.

Docker GitLab CI/CD Helm Kubernetes GitHub Copilot

After months of hard work, FAUN.sensei() is finally alive!

FAUN.sensei()
Story
@laura_garcia shared a post, 2 months, 2 weeks ago
Software Developer, RELIANOID

🌟 𝗪𝗲’𝗿𝗲 𝗛𝗶𝗿𝗶𝗻𝗴! 𝗝𝗼𝗶𝗻 𝘁𝗵𝗲 𝗥𝗘𝗟𝗜𝗔𝗡𝗢𝗜𝗗 𝗧𝗲𝗮𝗺 🌟

Are you passionate about technology, networking, and innovation? At RELIANOID, we’re building cutting-edge solutions that power secure, scalable, and reliable infrastructures — and we’re looking for talented people to join us on this journey! 🚀 Whether you’re an experienced professional or just star..

careers RELIANOID hiring
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).