AI System Design Essentials: What You Actually Need to Know
| Bryan Whiting

AI System Design Essentials: What You Actually Need to Know

ai system design architecture engineering

Building AI-powered applications doesn’t require mastering every system design concept. This guide cuts through the noise to show you what actually matters for real-world AI systems, using a CRM messaging platform as a practical example.

CRM System Design Blog Post Analysis

1. APIs

TLDR: APIs are bundles of code that take inputs and produce predictable outputs, enabling communication between applications without direct access to each other’s code or databases1.

What you need to know for CRM messaging: For your CRM, you’ll need REST APIs to:

  • Send messages via external services (email providers, SMS services)
  • Receive webhooks from messaging providers for delivery confirmations
  • Integrate with third-party communication tools (Slack, WhatsApp)
  • Implement authentication using JWT tokens
  • Handle user/contact management and message scheduling1

What’s esoteric: The deep technical details about different API communication methods (SOAP, gRPC) and complex authentication schemes beyond basic JWT implementation aren’t critical for a small CRM1.

2. API Gateways

TLDR: An API Gateway acts as a central server between clients and backend services, handling authentication, rate limiting, load balancing, and request routing2.

What you need to know for CRM messaging: You probably don’t need an API Gateway for a small CRM. It’s useful when you have multiple microservices. If you do implement one, it would handle:

  • Rate limiting for API calls to prevent abuse
  • Authentication for all incoming requests
  • Load balancing between multiple backend instances2

What’s esoteric: Complex features like circuit breaking, service discovery, and advanced monitoring are overkill for small-scale applications. API Gateways are more valuable in enterprise/microservices architectures2.

3. JWTs

TLDR: JSON Web Tokens are stateless authentication tokens that contain user claims and can be verified without server-side session storage3.

What you need to know for CRM messaging: JWTs are perfect for your CRM because they:

  • Enable stateless authentication (no server-side sessions to manage)
  • Include user permissions/roles in the token itself
  • Work well with API authentication for scheduling messages
  • Allow users to stay logged in across browser sessions
  • Support secure communication between frontend and backend3

What’s esoteric: Advanced JWT features like different signing algorithms (RS256 vs HS256), complex token rotation strategies, and detailed security considerations beyond basic implementation3.

4. Webhooks

TLDR: Webhooks allow external services to notify your application in real-time when events occur, instead of constantly polling for updates4.

What you need to know for CRM messaging: Webhooks are essential for your messaging CRM:

  • Email delivery status updates from providers like SendGrid/Mailgun
  • SMS delivery confirmations from Twilio
  • Bounce/unsubscribe notifications
  • Real-time message status updates without polling
  • Implement proper security verification and idempotency4

What’s esoteric: Complex webhook infrastructure with dead letter queues, retry mechanisms with exponential backoff, and sophisticated observability are beyond small-scale needs4.

5. Load Balancing

TLDR: Load balancing distributes incoming traffic across multiple servers using algorithms like round-robin, weighted distribution, or least connections5.

What you need to know for CRM messaging: For a small CRM, you likely won’t need load balancing initially. If you do scale up:

  • Round-robin for simple equal distribution
  • Health checks to avoid failed servers
  • Consider it when you have multiple server instances5

What’s esoteric: Complex algorithms like consistent hashing, geographic routing, and advanced health monitoring are unnecessary for small applications5.

6. Proxy vs Reverse Proxy

TLDR: Proxies act on behalf of clients (hiding client identity), while reverse proxies act on behalf of servers (hiding server details from clients)6.

What you need to know for CRM messaging: You might use a reverse proxy (like Nginx) for:

  • SSL termination for HTTPS
  • Basic load balancing if you scale
  • Serving static files efficiently
  • Simple caching of API responses6

What’s esoteric: Advanced proxy configurations, complex routing rules, and enterprise security features aren’t needed for small CRM systems6.

7. Scalability

TLDR: Scalability is a system’s ability to handle growing load by adding resources, achieved through vertical scaling (bigger servers) or horizontal scaling (more servers)7.

What you need to know for CRM messaging: Start simple and scale when needed:

  • Begin with vertical scaling (upgrade server specs)
  • Use caching for frequently accessed contact data
  • Consider horizontal scaling only when necessary
  • Implement asynchronous message processing with queues7

What’s esoteric: Complex distributed architectures, microservices patterns, and auto-scaling configurations are premature for small CRM applications7.

8. Availability

TLDR: Availability measures system uptime as a percentage, with strategies like redundancy, load balancing, and monitoring to improve reliability8.

What you need to know for CRM messaging: Focus on basic reliability:

  • Regular database backups
  • Basic health monitoring
  • Simple error handling and logging
  • Consider redundancy only as you grow8

What’s esoteric: Complex availability calculations (99.99% uptime), multi-region deployments, and sophisticated failover mechanisms aren’t priorities for small systems8.

9. SPOF (Single Point of Failure)

TLDR: SPOFs are components whose failure brings down the entire system. Avoid them through redundancy and proper architecture design9.

What you need to know for CRM messaging: Identify and minimize SPOFs in your CRM:

  • Database backups to prevent data loss
  • Multiple message delivery providers as fallbacks
  • Basic error handling for external API failures
  • Don’t over-engineer initially9

What’s esoteric: Complex redundancy patterns, sophisticated failover mechanisms, and chaos engineering are beyond small-scale requirements9.

10. CAP Theorem

TLDR: In distributed systems, you can only guarantee two of three properties: Consistency, Availability, and Partition tolerance10.

What you need to know for CRM messaging: For a small CRM:

  • Prioritize Consistency and Availability since you’ll likely start with a single database
  • CAP theorem becomes relevant only when you distribute your database
  • Focus on simpler reliability patterns first10

What’s esoteric: Complex distributed database theories, consensus algorithms, and advanced consistency models aren’t relevant until you have significant scale10.

11. SQL vs NoSQL

TLDR: SQL databases use structured tables with relationships and ACID properties, while NoSQL databases offer flexible schemas and horizontal scaling11.

What you need to know for CRM messaging: For a CRM, SQL databases (PostgreSQL/MySQL) are often better because:

  • Contact relationships are naturally relational
  • Message scheduling requires ACID transactions
  • Structured data fits well with SQL schemas
  • Strong consistency for user data and message logs11

What’s esoteric: Complex NoSQL data models, advanced sharding strategies, and detailed CAP theorem implications aren’t critical for typical CRM use cases11.

12. ACID Transactions

TLDR: ACID ensures database reliability through Atomicity (all-or-nothing), Consistency (valid states), Isolation (concurrent safety), and Durability (persistence)12.

What you need to know for CRM messaging: ACID is important for your CRM:

  • Ensures message scheduling is atomic (schedule or fail completely)
  • Maintains contact data consistency
  • Prevents race conditions in message sending
  • Most SQL databases provide ACID by default12

What’s esoteric: Advanced isolation levels, complex transaction management, and distributed transaction protocols are beyond basic CRM needs12.

13. Database Indexes

TLDR: Indexes are lookup tables that speed up database queries by creating efficient paths to find data, similar to a book’s index13.

What you need to know for CRM messaging: Essential indexes for your CRM:

  • Index contact email addresses for quick lookups
  • Index message timestamps for scheduling queries
  • Index user IDs for dashboard data
  • Index on message status for filtering13

What’s esoteric: Complex index types (bitmap, spatial), advanced optimization strategies, and detailed B-tree implementations aren’t necessary for small datasets13.

14. Database Sharding

TLDR: Sharding splits large databases across multiple servers horizontally, distributing data by user ID, date ranges, or other keys14.

What you need to know for CRM messaging: You likely won’t need sharding for a small CRM:

  • Start with a single database
  • Consider sharding only with millions of contacts
  • Vertical scaling is simpler initially14

What’s esoteric: Sharding strategies, rebalancing techniques, and distributed query coordination are complex topics you won’t need until significant scale14.

15. Consistent Hashing

TLDR: Consistent hashing distributes data across nodes in a way that minimizes redistribution when nodes are added or removed15.

What you need to know for CRM messaging: Not immediately relevant for a small CRM, but useful if you implement:

  • Distributed caching with multiple Redis instances
  • Load balancing across multiple servers
  • Generally overkill for small-scale applications15

What’s esoteric: Virtual nodes, hash ring implementation details, and complex distributed system coordination aren’t needed for basic CRM functionality15.

16. CDC (Change Data Capture)

TLDR: CDC tracks and captures database changes in real-time, streaming them to other systems without impacting the primary database16.

What you need to know for CRM messaging: CDC could be useful for:

  • Real-time sync between your CRM and external systems
  • Audit logs for contact data changes
  • Triggering message workflows when contact data updates
  • Generally complex for small systems16

What’s esoteric: Advanced CDC implementations, complex streaming architectures, and enterprise-grade data pipelines are beyond small CRM requirements16.

17. Caching

TLDR: Caching stores frequently accessed data in fast storage (memory) to reduce database load and improve response times17.

What you need to know for CRM messaging: Implement simple caching for:

  • User session data
  • Frequently accessed contact lists
  • Message templates
  • API rate limit counters
  • Start with simple in-memory caching, consider Redis later17

What’s esoteric: Complex multi-tier caching, sophisticated eviction policies, and distributed cache management are unnecessary for small-scale applications17.

18. Caching Strategies

TLDR: Different caching patterns include Cache Aside (lazy loading), Read Through (cache fetches), Write Through (sync writes), Write Around (bypass cache), and Write Back (async writes)18.

What you need to know for CRM messaging: For your CRM:

  • Use Cache Aside for contact data (simple and effective)
  • Write Through for critical user preferences
  • Keep it simple initially18

What’s esoteric: Complex caching strategies, cache invalidation patterns, and sophisticated consistency models are overkill for basic CRM needs18.

19. Cache Eviction Policies

TLDR: Eviction policies determine which data to remove when cache is full: LRU (least recently used), LFU (least frequently used), FIFO, TTL (time-based), etc.19.

What you need to know for CRM messaging: For your CRM caching:

  • LRU for general contact data (simple and effective)
  • TTL for temporary data like session tokens
  • Start simple with basic eviction policies19

What’s esoteric: Complex eviction algorithms, multi-tiered caching strategies, and advanced cache analytics aren’t necessary for small applications19.

20. CDN (Content Delivery Network)

TLDR: CDNs distribute static content globally through edge servers to reduce latency and improve load times for users worldwide20.

What you need to know for CRM messaging: For a small CRM:

  • CDN mainly useful for static assets (CSS, JS, images)
  • Not critical for core messaging functionality
  • Consider later for global reach20

What’s esoteric: Complex CDN configurations, advanced caching rules, and global distribution strategies aren’t priorities for small CRM applications20.

21. Rate Limiting Algorithms

TLDR: Rate limiting prevents abuse by controlling request frequency using algorithms like Token Bucket, Leaky Bucket, Fixed Window, Sliding Window, etc.21.

What you need to know for CRM messaging: Essential for your CRM:

  • Rate limit API calls to prevent abuse
  • Rate limit message sending to avoid spam
  • Token bucket algorithm is simple and effective
  • Protect against both internal and external abuse21

What’s esoteric: Complex sliding window implementations, sophisticated rate limiting across distributed systems, and advanced algorithmic details21.

22. Message Queues

TLDR: Message queues enable asynchronous communication between system components, decoupling producers and consumers for better scalability22.

What you need to know for CRM messaging: Perfect for your CRM’s messaging features:

  • Queue scheduled messages for future sending
  • Process email/SMS sending in background
  • Handle message delivery retries
  • Decouple message creation from sending
  • Redis or RabbitMQ are good starting options22

What’s esoteric: Complex queue topologies, advanced message routing, and enterprise messaging patterns aren’t needed for basic CRM messaging22.

23. Bloom Filters

TLDR: Bloom filters are space-efficient probabilistic data structures that quickly check if an element might be in a set, with possible false positives but no false negatives23.

What you need to know for CRM messaging: Potentially useful for:

  • Checking if email addresses are in blacklists
  • Deduplicating messages before sending
  • Generally overkill for small datasets23

What’s esoteric: Bloom filter implementation details, optimal parameter tuning, and advanced probabilistic data structures are beyond basic CRM needs23.

24. Idempotency

TLDR: Idempotent operations produce the same result when executed multiple times, essential for handling retries and ensuring system consistency24.

What you need to know for CRM messaging: Critical for your CRM:

  • Ensure message sending API calls are idempotent
  • Use unique request IDs for message operations
  • Prevent duplicate messages during retries
  • Essential for reliable messaging systems24

What’s esoteric: Complex distributed idempotency patterns, advanced conflict resolution, and sophisticated retry mechanisms24.

25. Concurrency vs Parallelism

TLDR: Concurrency manages multiple tasks simultaneously (task switching), while parallelism executes multiple tasks at the same time (multiple cores)25.

What you need to know for CRM messaging: For your CRM:

  • Use concurrency for handling multiple user requests
  • Parallel processing for bulk message sending
  • Async/await patterns for external API calls
  • Keep it simple with standard language features25

What’s esoteric: Complex parallel algorithms, advanced concurrency patterns, and sophisticated thread management are beyond basic CRM requirements25.

26. Stateful vs Stateless Architecture

TLDR: Stateful systems remember client data between requests, while stateless systems treat each request independently with all necessary information included26.

What you need to know for CRM messaging: For your CRM:

  • Use stateless APIs with JWT tokens for scalability
  • Maintain user sessions for web interface convenience
  • Store application state in database, not server memory
  • Hybrid approach often works best26

What’s esoteric: Complex state management patterns, distributed session handling, and advanced stateful/stateless trade-offs26.

27. Long Polling vs WebSockets

TLDR: Long polling keeps HTTP requests open until new data arrives, while WebSockets provide persistent bidirectional communication channels27.

What you need to know for CRM messaging: For real-time features in your CRM:

  • WebSockets for live message status updates in dashboard
  • Long polling for simpler notification systems
  • WebSockets better for real-time collaboration features
  • Start with simpler approaches unless real-time is critical27

What’s esoteric: Complex WebSocket scaling, advanced connection management, and sophisticated real-time architectures27.

28. Batch vs Stream Processing

TLDR: Batch processing handles large datasets at scheduled intervals, while stream processing handles data in real-time as it arrives28.

What you need to know for CRM messaging: For your CRM:

  • Batch processing for daily/weekly reports and analytics
  • Stream processing for real-time message delivery status
  • Start with batch processing for simplicity
  • Stream processing useful for real-time dashboards28

What’s esoteric: Complex stream processing frameworks, advanced windowing functions, and sophisticated data pipeline architectures28.

29. Strong vs Eventual Consistency

TLDR: Strong consistency ensures all reads return the latest write immediately, while eventual consistency allows temporary inconsistencies that resolve over time29.

What you need to know for CRM messaging: For your CRM:

  • Strong consistency for user authentication and message scheduling
  • Eventual consistency acceptable for analytics and reporting
  • Most single-database setups provide strong consistency by default29

What’s esoteric: Complex consistency models, distributed consensus algorithms, and advanced conflict resolution strategies aren’t needed for basic CRM systems29.

30. REST vs GraphQL

TLDR: REST uses fixed endpoints with HTTP methods for resource-based APIs, while GraphQL uses a single endpoint with flexible queries allowing clients to request exactly needed data.

What you need to know for CRM messaging: For your CRM API:

  • REST is simpler to implement and widely understood
  • GraphQL useful if you have multiple client types (web, mobile)
  • REST perfectly adequate for most CRM needs
  • GraphQL adds complexity that may not be worth it initially

What’s esoteric: Advanced GraphQL features like subscriptions, complex schema design, and sophisticated query optimization are beyond basic CRM requirements.

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Footnotes

  1. https://blog.algomaster.io/p/json-web-tokens ↩ ↩2 ↩3

  2. https://blog.algomaster.io/p/load-balancing-algorithms-explained-with-code ↩ ↩2 ↩3

  3. https://blog.algomaster.io/p/what-is-an-api-gateway ↩ ↩2 ↩3

  4. https://blog.algomaster.io/p/whats-an-api ↩ ↩2 ↩3

  5. https://blog.algomaster.io/p/what-are-webhooks ↩ ↩2 ↩3

  6. https://blog.algomaster.io/p/system-design-how-to-avoid-single-point-of-failures ↩ ↩2 ↩3

  7. https://blog.algomaster.io/p/cap-theorem-explained ↩ ↩2 ↩3

  8. https://blog.algomaster.io/p/scalability ↩ ↩2 ↩3

  9. https://blog.algomaster.io/p/proxy-vs-reverse-proxy-explained ↩ ↩2 ↩3

  10. https://blog.algomaster.io/p/system-design-what-is-availability ↩ ↩2 ↩3

  11. https://blog.algomaster.io/p/what-is-database-sharding ↩ ↩2 ↩3

  12. https://blog.algomaster.io/p/what-are-acid-transactions-in-databases ↩ ↩2 ↩3

  13. https://blog.algomaster.io/p/a-detailed-guide-on-database-indexes ↩ ↩2 ↩3

  14. https://blog.algomaster.io/p/sql-vs-nosql-7-key-differences ↩ ↩2 ↩3

  15. https://blog.algomaster.io/p/consistent-hashing-explained ↩ ↩2 ↩3

  16. https://blog.algomaster.io/p/content-delivery-networks ↩ ↩2 ↩3

  17. https://blog.algomaster.io/p/7-cache-eviction-strategies ↩ ↩2 ↩3

  18. https://blog.algomaster.io/p/change-data-capture-cdc ↩ ↩2 ↩3

  19. https://blog.algomaster.io/p/top-5-caching-strategies-explained ↩ ↩2 ↩3

  20. https://blog.algomaster.io/p/idempotency-in-distributed-systems ↩ ↩2 ↩3

  21. https://blog.algomaster.io/p/message-queues ↩ ↩2 ↩3

  22. https://blog.algomaster.io/p/bloom-filters ↩ ↩2 ↩3

  23. https://blog.algomaster.io/p/concurrency-vs-parallelism ↩ ↩2 ↩3

  24. https://blog.algomaster.io/p/rate-limiting-algorithms-explained-with-code ↩ ↩2 ↩3

  25. https://blog.algomaster.io/p/rest-vs-graphql ↩ ↩2 ↩3

  26. https://blog.algomaster.io/p/stateful-vs-stateless-architecture ↩ ↩2 ↩3

  27. https://blog.algomaster.io/p/strong-vs-eventual-consistency ↩ ↩2 ↩3

  28. https://blog.algomaster.io/p/long-polling-vs-websockets ↩ ↩2 ↩3

  29. https://blog.algomaster.io/p/batch-processing-vs-stream-processing ↩ ↩2 ↩3

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