Scalability & Performance
Techniques for handling more load, reducing latency, and optimizing resource utilization — from caching and sharding to rate limiting and connection pooling.
Horizontal Scaling
Adding more nodes or instances to distribute workload when traffic can be partitioned.
Vertical Scaling
Increasing the resources of a single node — when and when not to scale up.
Sharding Strategies
Splitting data or traffic across multiple buckets when a single node is no longer sufficient.
Partitioning Patterns
Range, hash, and list partitioning — choosing the right data distribution strategy.
Hot Partition Mitigation
Preventing one key or partition from overwhelming the system with skewed traffic.
Read Replicas
Offloading read traffic to replica nodes to scale read-heavy workloads.
Caching Strategies
Storing reused data closer to the consumer — cache-aside, read-through, write-through, and write-back.
Cache Invalidation
Removing stale cached data — the notoriously hard problem and practical strategies to solve it.
CDN Architecture
Distributing static and dynamic content globally to reduce latency for end users.
Rate Limiting
Capping request volume per identity or tenant to protect fairness, cost, and capacity.
Request Throttling
Controlling the flow of requests to protect downstream systems from overload.
Connection Pooling
Reusing database and service connections to reduce connection overhead and latency.
Lazy Loading
Deferring expensive data retrieval until it is actually needed.
Materialized Views
Precomputing and storing derived query results for fast reads at the cost of write overhead.