System Design Template
Never dive directly into the design phase; it may raise red flags during the interview!.
1. Feature Expectations [5 mins]
(1) Use Cases
Understanding the primary and secondary functionalities of your system is essential. Clearly define the main features your system will provide and any additional features that support these primary functions.
(2) Scenarios That Will Not Be Covered
It's equally important to delineate what is out of scope for your system. This helps manage stakeholder expectations and focuses development efforts.
(3) Who Will Use
Identify the target users of your system. Knowing your audience helps tailor the design to meet their specific needs.
(4) How Many Will Use
Estimate the number of active users. This estimation informs various aspects of system design, including scalability and performance requirements.
(5) Usage Patterns
Describe typical usage patterns and frequency. Understanding how users interact with your system guides performance and capacity planning.
Limit the number of features discussed to one or two, as covering more can be time-consuming and may detract from explaining the most critical aspects of the design.
2. Estimations [5 mins]
(1) Throughput
Estimate the queries per second (QPS) for both read and write operations. This helps in designing the system's capacity and performance.
(2) Latency
Define expected latency for read and write queries. Low latency is often crucial for a good user experience.
(3) Read/Write Ratio
Determine the proportion of read to write queries. This ratio influences database design and caching strategies.
(4) Traffic Estimates
Estimate traffic in terms of QPS and data volume for both read and write operations. This guides infrastructure planning.
(5) Storage Estimates
Calculate total storage requirements. This includes database storage and any additional data storage needs.
(6) Memory Estimates
If using a cache, define the type of data to be cached, the amount of RAM required, and the number of machines needed. Also, estimate the amount of data to store on disk/SSD.
Clear estimations demonstrate planning and analytical skills crucial for system scalability and performance assessment.
3. Design Goals [5 mins]
(1) Latency and Throughput Requirements
Set specific targets for latency and throughput. These goals drive the design and optimization of your system.
(2) Consistency vs. Availability
Decide on the level of consistency (weak, strong, or eventual) and availability requirements. Plan for failover and replication strategies to ensure high availability.
Specify latency/throughput targets and decide on consistency/availability levels for robust system design
4. High-Level Design [5-8 mins]
(1) APIs for Read/Write Scenarios
Define key APIs for core functionalities. Ensure they are designed for efficiency and scalability.
(2) Database Schema
Outline the database schema. A well-designed schema is foundational to system performance and maintainability.
(3) Basic Algorithm
Describe core algorithms used in the system. These should be optimized for performance and scalability.
(4) High-Level Design for Read/Write Scenarios
Provide an overview of the architecture for handling read and write operations. Include key components and data flow.
5. Deep Dive [10-12 mins]
(1) Scaling the Algorithm
Detail strategies to scale your algorithms efficiently.
(2) Scaling Individual Components
Analyze and plan for scaling each component, including DNS, CDN, load balancers, reverse proxies, application layers, and databases. Address availability, consistency, and scalability for each.
(3) Components to Consider
DNS
CDN (Push vs. Pull)
Load Balancers (Active-Passive, Active-Active, Layer 4, Layer 7)
Reverse Proxy
Application Layer Scaling (Microservices, Service Discovery)
Database Options (RDBMS, NoSQL, Graph, NewSQL, Time Series, Vector databases)
Caches (Different caching strategies and eviction policies)
Asynchronism (Message queues, task queues, back pressure)
Communication (TCP, UDP, REST, RPC, WebSockets)
6. Justify [5 mins]
(1) Throughput of Each Layer
Analyze throughput for each system layer.
(2) Latency Caused Between Each Layer
Identify and justify latency at each layer.
(3) Overall Latency Justification
Explain overall system latency and its impact on user experience.
7. Key Metrics to Measure [3 mins]
(1) Identify Key Metrics
Define metrics for availability, latency, throttling, request patterns/volume, and customer experience.
(2) Metrics for Infrastructure and Resources
Utilize tools like Grafana with Prometheus, and AppDynamics to measure and monitor these metrics.
8. System Health Monitoring [2 mins]
(1) Measure App Index and Latency of Microservices
Use monitoring tools such as New Relic and AppDynamics.
(2) Canaries
Implement canaries to detect and address service degradation proactively.
9. Log Systems [2 mins]
(1) Implement Tools to Gather and Visualize Metrics
Use ELK (Elastic, Logstash, Kibana) or Splunk for log collection and analysis.
(2) Performance Monitoring
Discuss leveraging logs for performance monitoring and troubleshooting system bottlenecks.
(3) Compliance and Retention
Address compliance requirements and define log retention policies to meet regulatory standards.
10. Security [2 mins]
(1) Firewall, Encryptions at Rest and In Transit
Implement robust firewall policies and encryption to secure data.
(2) TLS
Ensure data encryption in transit with TLS.
(3) Authentication, Authorization (AuthN/Z)
Implement strong authentication and authorization mechanisms.
(4) Limited Egress/Ingress
Control data flow to enhance security.
(5) Principle of Least Privilege
Limit access to necessary permissions only to minimize security risks.
Cover only relevant security topics during the interview and ensure they are within the allotted time limit.