Running platforms that handle ~1M TPS and serve billions of users requires far more than just “good infrastructure.” At that scale, success depends on how systems behave under stress, failure, and unpredictable traffic patterns.

This post intentionally stays high-level, and I’m happy to deep dive into any topic below.

At a Nutshell

At scale, resilient systems emerge from the combination of:

  • Edge computing
  • Async, event-driven pipelines
  • Fanout and backpressure control
  • In-memory caching
  • Strong operational discipline

Key operational principles:

  • Explicit state machines
  • Idempotency everywhere
  • Load shedding (not just rate limiting)
  • Traffic prioritization
  • Retry budgets
  • Reconnect storm protection

Design for eventual consistency where possible, strong consistency where required, and continuously validate resilience through chaos engineering in a multi-region active-active setup.

Core System Primitives

Most large-scale applications rely on these fundamentals:

  • Edge compute (Akamai / CDN proximity)
  • Rate limiting & circuit breakers
  • Multi-layer caching
  • Pub/Sub pipelines (Kafka)
  • Async writes & batching (Cassandra, tunable consistency)
  • Async views / materialized projections
  • In-memory data grids (Redis / Hazelcast)
  • Fanout control & backpressure
  • WebSockets vs SSE split
  • Horizontal + vertical scaling
  • Monitoring & observability
  • Multi-region deployments & DR

What Truly Differentiates Systems at Scale

  • Idempotency & Deduplication Idempotency keys · Dedup caches · Monotonic sequence IDs
  • Load Shedding (Beyond Rate Limiting) Drop typing indicators · Degrade location accuracy · Skip ranking features under load
  • Traffic Classification & Priority Queues Protect critical user flows · Prevent cascading failures
  • Retry Budgeting Per-request retry budgets · Exponential backoff + jitter · Global retry caps
  • Reconnect Storm Protection Staggered reconnect windows · Token-based reconnect delays · Edge-side buffering
  • Consistency Model Awareness Writes at QUORUM · Reads at ONE · Eventual consistency for UI · Strong consistency for billing
  • Schema & Data Evolution Strategy Versioned schemas · Feature flags · Temporary dual writes
  • Chaos Engineering (Non-Optional) Kill Kafka brokers · Kill Redis shards · Simulate full region loss
  • Security at Scale Token rotation · Regional key isolation · Blast-radius control · Replay attack prevention

If you’d like to discuss any of these topics in more detail, feel free to DM me on LinkedIn or Twitter. Always happy to exchange notes with fellow engineers building at scale.