Blogs¶
Overview¶
Engineering blogs publish postmortems, performance deep dives, and architecture retrospectives from production systems. They complement textbooks with current practice.
Why This Exists¶
You learn what teams actually ship, including mistakes and metrics rarely found in courses.
How It Works¶
Subscribe to a small set, read weekly, and file away patterns (caching incidents, DB migrations, rollout strategies).
Curated starting points¶
- High-scale product engineering: Netflix TechBlog, Uber Engineering, Meta Engineering
- Infra & cloud: AWS, GCP, Azure architecture blogs
- Databases: PostgreSQL planet, Cockroach Labs, PlanetScale
- AI: Google AI, OpenAI Research, Anthropic research
Independently operated
Listings are for education; no affiliation or endorsement implied.
Key Concepts¶
Prefer primary sources
Summaries help, but reading the original post preserves nuance and numbers.
Code Examples¶
Title:
Claim:
Evidence (metrics):
Applicable to my work:
Questions raised:
Interview Questions¶
How do blogs help system design interviews?
They provide realistic constraints, numbers, and failure stories you can cite when discussing trade-offs.
Practice Problems¶
- Write a one-page teardown of a postmortem and propose preventive controls
- Map three patterns from blogs to features in your past projects
Resources¶
- High Scalability — historical case studies
- ACM Queue — practitioner articles