One engineering graph. Multiple ways to go deeper.
Search across what we teach, what we help architect and troubleshoot, representative engineering scenarios, technical diagrams, practical articles and reusable production resources.
AAOS Architecture Fundamentals
A systems-level view of Android Automotive OS, vehicle integration and the engineering boundaries that matter.
AAOS Platform Readiness Checklist
A compact review checklist for AAOS platform integration, diagnostics, security and production readiness.
AAOS Vehicle Signal Path
Trace a vehicle property from an ECU boundary through VHAL and Car Service to an Android Automotive application.
Agentic AI Control Loop
See planning, tool use, memory, policy and evaluation as a controlled loop around the language model.
AI Engineering
Move beyond AI demos into engineered systems: machine-learning fundamentals, LLM applications, retrieval, agents, evaluation, observability, security and production deployment.
AI Engineering
Move AI, LLM, RAG and agentic applications from prototype behavior toward measurable, secure and operable production systems.
Android Automotive OS (AAOS)
Understand Android Automotive as a vehicle platform: architecture, services, vehicle integration, HAL/VHAL, security, diagnostics and engineering workflows.
Apache Spark for Production Data Engineering
A practical engineering guide to Spark architecture, PySpark pipelines, partitioning, performance, streaming and production operations.
Apache Spark Production Readiness Checklist
A compact review checklist for Spark and PySpark workloads before they become production data pipelines.
Architecture & Technical Advisory
Independent engineering guidance for organizations making architecture, platform, modernization or technology-selection decisions across connected systems.
Assessing Kubernetes production readiness
A representative architecture-review scenario for a Kubernetes platform that works functionally but needs stronger production resilience, security and operability.
Automotive & AAOS
Architecture, integration and troubleshooting support for Android Automotive OS and connected vehicle-platform engineering.
Cloud & Platform Architecture
Architecture and modernization guidance for cloud infrastructure, platform services, networking, observability and workload migration.
Data Engineering & Big Data
Understand distributed data systems and build practical batch, streaming and lakehouse pipelines with production-oriented performance and operability.
Data Engineering & Big Data
Architect, modernize and troubleshoot distributed data platforms spanning Apache Spark, Kafka, Trino, orchestration and lakehouse technologies.
Data Platform Architecture Review Checklist
A practical checklist for reviewing batch, streaming, Spark, Kafka, lakehouse and distributed-SQL architectures.
Defense-in-Depth Control Plane
Visualize security as overlapping identity, edge, workload, data and telemetry controls rather than one perimeter.
DevOps & Platform Engineering
Connect source control, CI/CD, infrastructure automation, containers, Kubernetes and observability into a coherent engineering delivery system.
DevOps & Platform Engineering
Improve software delivery and platform engineering by connecting CI/CD, automation, containerization, Kubernetes and observability into an operable system.
DevSecOps Software Supply Chain
Follow a change from developer commit through verification, artifact creation, deployment and runtime controls.
Diagnosing an AAOS / VHAL integration boundary
A representative automotive-platform scenario where application, Car Service, VHAL and vehicle integration boundaries need to be understood systematically.
Embedded Linux Boot Chain
See the handoff from immutable boot code to bootloader, kernel, device tree, userspace and the final application.
Embedded Linux Production Basics
A practical introduction to the layers that turn Linux into a reliable embedded platform.
Embedded Systems
Engineering support for embedded Linux platforms, BSP and device integration, system interfaces, performance and low-level troubleshooting.
Embedded Systems Engineering
Connect software to hardware behavior through embedded C/C++, Embedded Linux, BSP concepts, drivers, interfaces, debugging and product-level engineering practices.
Hardening a Linux production baseline
A representative security-review scenario for a Linux estate that needs a consistent, explainable hardening baseline without breaking operational requirements.
Kubernetes Production Architecture: From Cluster to Platform
A practical reference for designing Kubernetes as an operable production platform rather than a collection of nodes.
Kubernetes Production Readiness Checklist
A compact field checklist for reviewing a Kubernetes platform before production workloads depend on it.
Kubernetes Production Traffic Flow
Follow a production request from the public edge to a workload and back through the observability plane.
Linux & Open Infrastructure
Design, review and troubleshoot Linux and open infrastructure with emphasis on reliability, security, performance and operational clarity.
Linux & Open Source Engineering
Build a durable Linux mental model, then progress into administration, networking, security, performance, troubleshooting and production operations.
Linux Incident Command Sheet
A concise first-response command reference for Linux availability and performance incidents.
Linux Performance Troubleshooting: A Layered Method
A practical workflow for moving from symptoms to evidence across CPU, memory, storage, network and application layers.
Linux Security Review Checklist
A practical first-pass checklist for reviewing Linux hosts used in production services.
Linux Service Incident Path
Move from user-visible failure through sockets, processes, systemd, logs and kernel resources in a disciplined diagnostic sequence.
Modern Data Platforms: Batch, Streaming and the Lakehouse
How Spark, Kafka, Trino, Airflow and open table formats can fit together in a modern data-engineering platform.
Production RAG System
See retrieval, reranking, generation and evaluation as one production path rather than a single LLM call.
Programming & Systems Engineering
Develop programming skill with an engineering focus: data structures, memory, concurrency, networking, APIs, debugging and system-level behavior.
RAG in Production: Retrieval Is an Engineering System
Why production RAG depends on ingestion, chunking, retrieval, evaluation, security and observability—not only an LLM prompt.
Recovering a slow Spark data pipeline
A representative performance-engineering scenario for a Spark/PySpark workload that becomes slower and less predictable as data volume and transformation complexity grow.
Security Engineering
Build security understanding across Linux, networks, applications, DevSecOps, containers, Kubernetes and AI systems with practical engineering controls.
Security Engineering
Engineering-focused security assessment and hardening across Linux, delivery pipelines, containers, Kubernetes, applications, APIs and AI systems.
Security Engineering: Defense in Depth
A practical way to reason about security across hosts, networks, applications, containers and delivery pipelines.
Spark Lakehouse Data Flow
Connect batch and streaming ingestion to Spark processing, lakehouse storage and analytical consumption.
Strengthening security inside a CI/CD pipeline
A representative DevSecOps scenario for a delivery pipeline that needs security controls without turning every build into an unmanageable collection of scanners.
Taking a RAG system from demo to production
A representative AI-engineering scenario for a RAG prototype that produces promising demos but lacks measurable retrieval quality, evaluation and production controls.