Blog
Long-form articles, tutorials and deep dives into data engineering, AI, and robotics.
A Comparison of Leading Data Observability Tools
Okay, so your data pipelines are growing. More sources, more transformations, more consumers. It's awesome… until it isn't. When things break – and they *will* break – finding the root cause can feel…
Serverless Security Considerations: A Deep Dive
Serverless is awesome. It lets us focus on code, scales automatically, and can save a ton of money. But it doesn't mean security is magically solved. In fact, it *shifts* security concerns. We're no…
Interviewing for Generative AI Roles: A Comprehensive Guide
Okay, so you want to land a job in the GenAI space? Smart move. Demand is *high*, and frankly, a lot of people are trying to break in. But the interview process can be…weird. It’s not always about…
Frontend Engineering: Mastering React Server Components
React Server Components (RSCs) are a big deal. They represent a fundamental shift in how we build React applications, and understanding them is quickly becoming essential for frontend engineers.…
Cloud Engineering: Developing a Multi-Cloud Strategy
Okay, so you're hearing a lot about "multi-cloud" and wondering if it's right for your organization. Let's cut through the hype and talk about what it *actually* means, why you'd do it, and how to…
Data Engineering: DBT Testing Best Practices
Okay, let's talk dbt testing. You're building data pipelines, transforming data, and hopefully, making some good decisions based on that data. But what happens when the data is *wrong*? That's where…
Terraform Interview Questions: State, Modules, and Real-World Scenarios
Most Terraform interview guides will walk you through `terraform init`, `plan`, and `apply` — the stuff you'd find in a 10-minute getting-started tutorial. That's not what gets you hired at…
Platform Engineering Interview Guide: IDPs, Backstage, and Golden Paths
Platform Engineering roles are exploding right now, but interview prep content for them is almost nonexistent. Most candidates walk in prepared to talk about Kubernetes and CI/CD pipelines, then get…
How to Answer AI Agent System Design Questions in Interviews
AI agent system design questions are showing up constantly at companies like Anthropic, OpenAI, Cohere, and pretty much any startup building on top of LLMs. Yet almost nobody is preparing for them…
Building Real-Time Applications with GraphQL Subscriptions
If you're already using GraphQL for queries and mutations, adding real-time functionality feels like a natural next step. But a lot of developers hit a wall here — they know WebSockets exist, they…
Automating FinOps: Reducing Cloud Costs with Infrastructure as Code
Cloud bills are brutal. You spin up resources for a feature, forget to tear them down, and three months later finance is asking why AWS costs jumped 40%. Sound familiar? FinOps — the practice of…
Micro-Frontends: Best Practices for Scalable and Maintainable Applications
Your monolithic frontend is starting to hurt. Deployments take forever, five teams are stepping on each other's toes, and a bug fix in the checkout flow somehow breaks the navigation. Sound familiar?…
Evaluating and Mitigating Safety Risks in LLM Applications
You've built a slick LLM-powered feature. Users love it. Then one day it tells someone something harmful, confidently wrong, or just plain offensive. Suddenly you're the engineer explaining to your…
Building Real-Time Feature Stores for Machine Learning
Your fraud detection model is brilliant. It catches 94% of fraudulent transactions in offline evaluation. Then you deploy it and the performance tanks — not because the model is wrong, but because…
Advanced GraphQL Schema Design Patterns
If you've shipped a basic GraphQL API before, you know the honeymoon phase doesn't last long. Queries get complex, the schema grows organically (read: chaotically), and suddenly you're drowning in…
Data Engineering: Implementing Robust Data Validation Pipelines
Bad data is silent. It doesn't throw exceptions or crash your system — it just quietly corrupts your analytics, misleads your stakeholders, and eventually destroys trust in your entire data platform.…
Kubernetes Observability: Best Practices for Monitoring and Troubleshooting
Running Kubernetes without proper observability is like flying blind. When something breaks at 2 AM — and it will — you need to know *what* broke, *why* it broke, and *where* in your cluster it…
Rust Performance Optimization Techniques
Rust promises you systems-level performance without the footguns of C/C++. That promise is real — but it doesn't come for free. Writing *correct* Rust is one skill; writing *fast* Rust is another. If…
System Design: Implementing the Circuit Breaker Pattern
If you've ever had a single failing microservice take down your entire application, you already understand why the circuit breaker pattern exists. It's one of those patterns that feels obvious in…
Data Engineering: Implementing Data Contracts
Your analytics pipeline breaks at 2 AM. The upstream team changed a column name. Again. Sound…
Backend Engineering: Introduction to Event Sourcing
Event sourcing keeps coming up in system design interviews, and for good reason — it solves real problems that CRUD-based systems struggle with. If you've ever needed a full audit trail, wanted to…
LLM Engineering: Implementing Guardrails for Responsible AI
If you're building anything with LLMs right now, guardrails aren't optional — they're table stakes. Interviewers are asking about this. Production incidents are happening because of this. And…
Frontend Accessibility Best Practices for Inclusive Web Development
Accessibility is no longer optional. Lawsuits against companies for inaccessible websites have been climbing steadily, the ADA and WCAG guidelines carry real legal weight, and — more importantly —…
Modern Data Orchestration with Prefect
If you've spent any time in data engineering, you've probably wrestled with Airflow. It works, but it comes with a lot of ceremony — DAG files that have to live in specific directories, a scheduler…
Choosing the Right Vector Database for Your LLM Application
You’re building something cool with Large Language Models (LLMs). Maybe it’s Retrieval Augmented Generation (RAG), semantic search, or a recommendation engine. Whatever it is, you’ve probably hit a…
Understanding and Implementing Role-Based Access Control (RBAC)
Let's talk about security. Specifically, how to control *who* can do *what* in your applications. You’ve likely heard of authentication (verifying *who* a user is) and authorization (verifying *what*…
Building Real-Time Applications with WebSockets
Let's talk about WebSockets. You've probably encountered applications that feel *instant* – live chat, collaborative editors, real-time dashboards. That responsiveness isn't magic; it's often powered…
Beyond the Basics: Advanced dbt Techniques for Data Transformation
dbt (data build tool) has quickly become *the* standard for data transformation. You’ve probably already grasped the fundamentals – writing SELECT statements, defining models, and running them…
Ace the Data Science Interview: A Comprehensive Guide
Let's be real: landing a data science role is competitive. You can have the skills, the projects, and the degree, but if you stumble in the interview, you're likely out of the running. This isn't…
System Design: Implementing Rate Limiting
Rate limiting. It sounds simple, but it’s surprisingly complex when you need to do it *well* in a distributed system. It’s a frequent topic in system design interviews, and more importantly, it’s a…