𝟭. 𝗦𝗰𝗮𝗹𝗮𝗯𝗹𝗲 𝗗𝗮𝘁𝗮 𝗦𝘁𝗼𝗿𝗮𝗴𝗲
• Relational vs. NoSQL: Know when to use SQL vs. NoSQL databases.
• Partitioning: Vertical and horizontal partitioning (sharding). Understand trade-offs.
• Indexing: Covering indexes, primary vs. secondary indexes.
• Consistency Models: Strong, eventual, causal.

𝟐. 𝐂𝐚𝐜𝐡𝐢𝐧𝐠
• Client-side vs. Server-side Cache: Understand where caching should happen.
• Caching Strategies: Write-through, write-back, write-around.
• Distributed Cache: Redis, Memcached.
• Cache Eviction Policies: LRU, LFU, etc.

𝟑. 𝐋𝐨𝐚𝐝 𝐁𝐚𝐥𝐚𝐧𝐜𝐢𝐧𝐠
• Horizontal Scaling: Why and how to horizontally scale services.
• Load Balancing Techniques: Round-robin, consistent hashing.
• Reverse Proxy: Understand how to use Nginx, HAProxy.

𝟒. 𝐀𝐬𝐲𝐧𝐜𝐡𝐫𝐨𝐧𝐨𝐮𝐬 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠
• Message Brokers: Kafka, RabbitMQ. When to use queues vs. streams.
• Event-Driven Architecture: Benefits of decoupling and event sourcing.
• Task Queues: For delayed jobs or retries.

𝟓. 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞 𝐑𝐞𝐚𝐝 𝐚𝐧𝐝 𝐖𝐫𝐢𝐭𝐞 𝐒𝐜𝐚𝐥𝐢𝐧𝐠
• Read Scaling: Master replication, read replicas.
• Write Scaling: Challenges with partitioning for writes, leader-election.
• CAP Theorem: Consistency, Availability, or Partition tolerance may be compromised.

𝟲. 𝗗𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗲𝗱 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀
• Consensus Algorithms: Paxos, Raft.
• Conflict Resolution: Last Write Wins, CRDTs, vector clocks for data reconciliation.

𝟳. 𝗥𝗲𝗹𝗶𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗮𝗻𝗱 𝗙𝗮𝗶𝗹𝗼𝘃𝗲𝗿
• Redundancy: Active-passive vs. active-active configurations.
• Health Checks.
• Retries and Circuit Breakers: How to protect systems from cascading failures.

𝟴. 𝗖𝗗𝗡𝘀 (𝗖𝗼𝗻𝘁𝗲𝗻𝘁 𝗗𝗲𝗹𝗶𝘃𝗲𝗿𝘆 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝘀)
• Static Content Delivery: Why use a CDN, how does it work?
• Caching at the Edge: How CDNs improve latency for end users.

𝟵. 𝗔𝗣𝗜 𝗗𝗲𝘀𝗶𝗴𝗻 𝗮𝗻𝗱 𝗥𝗮𝘁𝗲 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁
• REST vs. GraphQL: Difference and practical use-cases for each.
• Pagination and Filtering: Strategies for efficiently fetching data.
• API Versioning: Best practices for evolving APIs.
• Throttle Requests: Why rate limiting is essential, algorithms like token bucket, leaky bucket.

𝟭𝟬. 𝗦𝗲𝗮𝗿𝗰𝗵 𝗦𝘆𝘀𝘁𝗲𝗺𝘀
• Indexing: Building and maintaining indexes for fast search.
• Full-Text Search Engines: ElasticSearch, Azure AI Search.
• Ranking and Relevance: Basic understanding of how scoring works.

𝟭𝟭. 𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴 𝗮𝗻𝗱 𝗢𝗯𝘀𝗲𝗿𝘃𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗮𝗻𝗱 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆
• Metrics Collection: Prometheus, Grafana.
• Distributed Tracing: OpenTelemetry, Sentry.
• Centralized Logging.
• Authentication and Authorization: OAuth, JWT.
• Encryption: Data in transit vs. data at rest.

If you master these 11 areas, you’ll be ready for most system design interviews thrown at you.