Premium Labs

Advanced caching, CDN, AI agent, and systems engineering content — free for everyone.

Each lab mixes architecture drawings, implementation checklists, and real interview angles so subscribers leave confident enough to discuss the topic in the next on-site.

Content updated weekly with new diagrams and prompts.

What you absorb

Lab blueprint

Launch-ready explanations with diagrams, ops checklists, and interview talking points. Treat it as your briefing before architecting in front of a panel.

  • Systems first

    Latency math, failure drills, and real SLIs. No fluffy marketing copy.

  • Hands-on guidance

    Exact commands, libraries, and monitoring hooks we use in production.

  • Interview leverage

    Each lab ends with questions real companies ask—plus what signals they listen for.

6

Architectures

18+

Deep sections

12

Interview prompts

∞

Reuse in projects

Use the material to brief yourself before interviews, stand up internal workshops, or spin up proof-of-concept side projects. The more you teach it, the better you remember it.

Caching & RedisPremium Lab

Redis-Powered Caching Playbook

Design write-through, write-back, and request coalescing layers that keep tail latency predictable even when upstream databases run hot.

✓Pick the right eviction strategy (LRU, LFU, TTL buckets) based on key churn.✓Model cache warming, fill retries, and cache stampede protection with Redis primitives.✓Instrument cache hit ratios by route and fall back smoothly when Redis is degraded.

Contrast application-local caches vs. shared Redis clusters and how to compose them.

Tiered caching strategies

  • Request-scoped memoization prevents redundant ORM hits inside a single request.
  • Near-cache (process memory) + Redis reduces cross-AZ latency, but requires explicit invalidation channels.
  • Global cache sits behind API gateways; pair with region-aware sharding to avoid noisy neighbors.

Estimate memory budgets and TTL design for interview prompts.

Eviction math & sizing drills

  • Translate QPS + payload size into Redis memory footprints with 20% overhead for metadata.
  • Use segmented TTLs: short-lived (minutes) for feeds, longer (hours) for reference data.
  • Run hit-rate sensitivity analysis: how many misses can the DB absorb during cache warmups?

Observability and fallback techniques the panel wants to hear.

Operational guardrails

  • Expose cache hit/miss, eviction, and saturation metrics per namespace.
  • Circuit-breaker to bypass Redis when latency > threshold; degrade features gracefully.
  • Automated keyspace scans with `SCAN` + sampling to validate TTL hygiene.

Interview Prompts

Signal check

Prompt

Design a cache for a product detail page with 10M items and 5% hot set.

Prompt

How do you prevent cache stampede after TTL expiry?

Tools & References

  • ↳Redis, KeyDB
  • ↳Envoy caching filter
  • ↳OpenTelemetry metrics

Pair the lab with your own code explorations: clone a starter repo, deploy to a sandbox, or rehearse the interview stories with a partner.