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 LangChain.. Link
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@laura_garcia shared a post, 2 months, 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..
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@laura_garcia shared a post, 2 months, 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..
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@anjali shared a link, 2 months, 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.
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@laura_garcia shared a post, 2 months, 2 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..
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@varbear shared a link, 2 months, 2 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
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@varbear shared a link, 2 months, 2 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
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@varbear shared a link, 2 months, 2 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
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@varbear shared a link, 2 months, 2 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
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@varbear shared a link, 2 months, 2 weeks ago
FAUN.dev()
uv is the best thing to happen to the Python ecosystem in a decade
uvis a new Rust-powered CLI from Astral that tosses Python versioning, virtualenvs, and dependency syncing into one blisteringly fast tool. It handles yourpyproject.tomllike a grown-up—auto-generates it, updates it, keeps your environments identical across machines. Need to run a tool once without t.. read more
LangChain supports retrieval-augmented generation (RAG) pipelines through integrations with vector databases, enabling models to access and reason over large external knowledge bases efficiently. It also provides utilities for handling long-term context via memory management and supports multiple backends like OpenAI, Anthropic, and local models.
Technically, LangChain simplifies building LLM-driven architectures such as chatbots, document Q&A systems, and autonomous agents. Its ecosystem includes components for caching, tracing, evaluation, and deployment, allowing seamless movement from prototype to production. It serves as a foundational layer for developers who need tight control over how language models interact with data and external systems.
