What Are AI Guardrails
Learn the core concepts of AI guardrails and how they create safer, more reliable, and well-structured AI systems in production.
Updates and recent posts about BigQuery.. Link
Story
@laura_garcia shared a post, 1 month, 2 weeks ago
Software Developer, RELIANOID
🚨 AWS Outage Analysis: Lessons in Cloud Resilience
On October 20, 2025, AWS suffered a major disruption in its US-EAST-1 region, impacting over 140 services including EC2, Lambda, S3, and DynamoDB. The root cause? A DNS resolution failure that cascaded through dependent systems — showing how even the strongest cloud infrastructures can falter. At RE..
Story
@laura_garcia shared a post, 1 month, 2 weeks ago
Software Developer, RELIANOID
🚀 Deploy RELIANOID Load Balancer Enterprise Edition v8 with Terraform on AWS
Our latest quick guide shows you how to spin up the RELIANOID Enterprise Edition on AWS in just a few commands — using the official Terraform module from the Terraform Registry. You’ll automatically provision: ✅ VPC + Internet Gateway ✅ Public Subnet ✅ Security Group (SSH 22, Web GUI 444) ✅ EC2 Inst..
Link
@anjali shared a link, 1 month, 2 weeks ago
Customer Marketing Manager, Last9
Grafana Tempo: Setup, Configuration, and Best Practices
A practical guide to setting up Grafana Tempo, configuring key components, and understanding how to use tracing across your services.
Story
@laura_garcia shared a post, 1 month, 3 weeks ago
Software Developer, RELIANOID
🍺 Cyberattack on Asahi Group: A Wake-Up Call for Japan’s Industrial Sector
Just after Japan’s new Active Cyberdefence Law (ACD Law) came into effect — a major step toward reshaping the country’s cybersecurity posture — Japan’s largest brewer, Asahi Group, has suffered a ransomware attack that disrupted production and logistics nationwide. ⚠️ This incident starkly illustrat..
Link
@varbear shared a link, 1 month, 3 weeks ago
FAUN.dev()
Free software scares normal people
A developer rolled outMagicbrake- a no-fuss GUI forHandbrakeaimed at folks who don’t speak command line. One button. Drag, drop, convert. Done. It strips Handbrake down to the bones for anyone who just wants their video in a different format without decoding flags and presets... read more
Link
@varbear shared a link, 1 month, 3 weeks ago
FAUN.dev()
Kafka is fast -- I'll use Postgres
Postgres is pulling Kafka moves—without the Kafka. On a humble 3-node cluster, it held 5MB/s ingest and 25MB/s egress like a champ. Low latency. Rock-solid durability. Crank things up, andsingle-node Postgresflexed hard: 240 MiB/s in, 1.16 GiB/s out for pub/sub. Thousands of messages per second in q.. read more
Link
@varbear shared a link, 1 month, 3 weeks ago
FAUN.dev()
How Netflix Tudum Supports 20 Million Users With CQRS
Netflix gutted Tudum’s old read path—Kafka, Cassandra, layers of cache—and swapped inRAW Hollow, a compressed, distributed, in-memory object store baked right into each microservice. Result? Homepage renders dropped from 1.4s to 0.4s. Editors get near-instant previews. No more read caches. No extern.. read more
Link
@varbear shared a link, 1 month, 3 weeks ago
FAUN.dev()
Aggressive bots ruined my weekend
Bear Blog went dark after getting swarmed by scrapers. The reverse proxy choked first - too many requests, not enough heads-up. Downstream defenses didn’t catch it in time. So: fire, meet upgrades. What changed: Proxies scaled 5×. Upstream got strict with rate limits. Failover now has a pulse. Resta.. read more
Link
@varbear shared a link, 1 month, 3 weeks ago
FAUN.dev()
The bug that taught me more about PyTorch than years of using it
A sneaky bug inPyTorch’s MPS backendlet non-contiguous tensors silently ignore in-place ops likeaddcmul_. That’s optimizer-breaking stuff. The culprit? ThePlaceholder abstraction- meant to handle temp buffers under the hood - forgot to actually write results back to the original tensor... read more
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).
