// Topics / Scaling

Scaling

Definition

Scaling coverage in this archive spans 3 posts from Nov 2016 to Mar 2020 and deals with structural tradeoffs: coupling, failure boundaries, and long-term change cost. The strongest adjacent threads are engineering, video, and infrastructure. Recurring title motifs include scaling, video, infrastructure, and ready.

What the archive argues

  • Most pieces recommend choosing the simplest architecture that can be operated confidently.
  • The consistent theme from 2016 to 2020 is disciplined execution over hype cycles.
  • This topic repeatedly intersects with engineering, video, and infrastructure, so design choices here rarely stand alone.

Execution checklist

  • Define failure domains and data boundaries before introducing additional services or protocols.
  • Start with the newest post to calibrate current constraints, then backtrack to older entries for first principles.
  • When boundary questions appear, cross-read engineering and video before committing implementation details.

Common failure modes

  • Breaking systems into many parts without clear ownership of cross-service behavior.
  • Choosing architecture for trend alignment rather than workload constraints.
  • Applying guidance from 2016 to 2020 without revisiting assumptions as context changed.

Suggested reading path

References

3 entries tagged “Scaling”

    Your Video Infrastructure Isn't Ready for What's Coming · 6 min Most companies building video calling right now are making the same three architecture mistakes. Here's what I keep seeing and how to fix it before your SFUs fall over. video infrastructure scaling What I Learned Scaling an Engineering Team · 6 min Lessons from growing an engineering org at the fintech startup -- what breaks, what works, and why clarity beats process every time. engineering management teams The Economics of State: Why Scaling Up Beats Sharding (Until It Doesn't) · 8 min A production-grounded case for exhausting single-server headroom with pooling, replicas, and partitioning before taking on sharding complexity. postgresql databases scaling
All topics →