Latest Articles

OpenTelemetry: The Standard for Distributed Tracing in 2026
Observability

OpenTelemetry: The Standard for Distributed Tracing in 2026

OpenTelemetry is the vendor-neutral standard for distributed tracing. Learn the OTel data model, auto-instrumentation, Collector pipelines, tail-based sampling, and how to choose between Jaeger, Tempo, Honeycomb, and Datadog.

9 min read·
Prometheus and Grafana: Setting Up Your First Monitoring Stack
Observability

Prometheus and Grafana: Setting Up Your First Monitoring Stack

Deploy Prometheus and Grafana on Kubernetes using Helm. Learn the pull-based scrape model, PromQL essentials (rate, histogram_quantile, aggregation), Grafana dashboard design, recording rules, and Alertmanager routing.

9 min read·
AI Observability: How to Monitor and Debug LLM Applications
AI/ML Engineering

AI Observability: How to Monitor and Debug LLM Applications

A practical guide to monitoring LLM applications in production -- input/output logging, cost tracking, quality metrics, and a comparison of LangSmith, Langfuse, and Arize.

10 min read·
Deploying ML Models in Production: From Notebook to Kubernetes
AI/ML Engineering

Deploying ML Models in Production: From Notebook to Kubernetes

End-to-end guide to deploying ML models -- from ONNX export and FastAPI serving to Kubernetes GPU workloads, canary deployments, and Prometheus monitoring.

9 min read·
Fine-Tuning vs Prompt Engineering: Choosing the Right Approach
AI/ML Engineering

Fine-Tuning vs Prompt Engineering: Choosing the Right Approach

A practical guide to choosing between prompt engineering and fine-tuning for LLMs -- techniques, costs, LoRA/QLoRA, and a decision framework for production systems.

10 min read·
Vector Databases: What They Are, How They Work, and When You Need One
AI/ML Engineering

Vector Databases: What They Are, How They Work, and When You Need One

A practical guide to vector databases -- how embeddings and ANN algorithms work, and an honest comparison of Pinecone, Weaviate, Qdrant, and pgvector.

9 min read·
RAG Explained: Building AI Applications That Know Your Data
AI/ML Engineering

RAG Explained: Building AI Applications That Know Your Data

A practical guide to building Retrieval-Augmented Generation pipelines -- from document chunking and embedding to hybrid retrieval and evaluation metrics.

9 min read·
Bash Scripting Best Practices for DevOps Engineers
Linux

Bash Scripting Best Practices for DevOps Engineers

Write reliable bash scripts with set -euo pipefail, proper quoting, [[ ]] tests, idempotent patterns, cleanup traps, ShellCheck, and knowing when to switch to Python.

10 min read·
The Linux Networking Stack: From Socket to NIC
Linux

The Linux Networking Stack: From Socket to NIC

Trace a packet through the entire Linux networking stack: socket buffers, the TCP state machine, IP routing, netfilter/iptables, traffic control, and NIC drivers with practical diagnostic tools.

10 min read·

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