Search results
20 resultsDiagnostic RAG for heavy equipment
Indexed 4M+ pages across PDFs & manuals; latency < 400ms; 32% fewer escalations.
Observability — Logs, Metrics, and Traces
Implementing the three pillars with OpenTelemetry and making them actionable.
What is Retrieval-Augmented Generation (RAG)?
A plain-English explanation of RAG: why it beats pure LLM memory for production knowledge systems.
Applied AI & ML — Service Overview
Everything included in our Applied AI engagements: RAG, agents, fine-tuning, evals, and guardrails.
Introduction to Data Pipelines
What a data pipeline is, the core stages, and when to build vs buy.
Progressive Delivery — Feature Flags, Canary, and Dark Launching
Techniques for releasing software confidently at any scale.
Fine-tuning LLMs: when, why, and how
A practical guide to LoRA, QLoRA, and full fine-tuning for production use cases.
Load Testing with k6
Script a realistic load test, interpret results, and find bottlenecks before they find users.
Airflow Best Practices for Production Pipelines
Idempotency, backfilling, SLA misses, and common pitfalls to avoid.
API Gateway — Responsibilities and Implementation Patterns
Authentication, rate limiting, routing, request aggregation, and when not to use a gateway.
Our observability stack for production services
Logs, metrics, traces — how we instrument every service we ship.
HTTP Caching Strategies for APIs and Web Applications
Cache-Control headers, ETags, CDN caching, and cache invalidation.
Batch vs Streaming Pipelines — Choosing the Right Pattern
Lambda architecture, Kappa architecture, and practical guidance for choosing.
ETL vs ELT — Which Pattern Should You Use?
Understand the difference between Extract-Transform-Load and Extract-Load-Transform and when each fits.
Real-Time Analytics Architecture Patterns
Lambda, Kappa, HTAP, and choosing the right pattern for sub-second analytics.
Serverless Architecture — When Functions Work and When They Don't
Cold starts, event-driven patterns, cost model, and the right use cases.
Stream Processing with Apache Flink
Event time vs processing time, windows, stateful operators, and production deployment.
CDN and Edge Caching Strategy
Origin offload, cache key design, purging, and choosing a CDN.
Change Data Capture (CDC) — Debezium and Log-Based CDC
How CDC works, why it beats polling, and how to implement it with Debezium.
Feature Stores — Bridging Data Engineering and ML
What a feature store is, online vs offline stores, and when to build vs buy.