Subject: System Design
Learning Objectives:
- Understanding Computer Architecture
- Understanding High-Level Architecture of Production-Ready Apps
- Understanding the Pillars of System Design
- Understanding Networking Basics
- Understanding API Design
- Understanding Caching and Content Delivery Networks (CDNs)
- Understanding Proxy Servers
- Understanding Databases
A) Understanding Computer Architecture
Question 1: How does the principle of locality relate to the different levels of cache memory (L1, L2, L3) and their impact on CPU performance?
Answer 1: The principle of locality states that data and instructions accessed recently are more likely to be accessed again soon. This is exploited in cache design, with smaller and faster L1 caches holding the most recently used data, followed by larger but slower L2 and L3 caches. When a CPU request hits in a cache level, it’s faster than accessing main memory, improving performance.
Question 2: In a multi-core CPU environment, how do the cores share access to the RAM and cache memory, and what are the potential performance implications of different sharing mechanisms?
Answer 2: Cores share access to RAM through a shared memory bus, often using a cache coherency protocol (e.g., MESI) to manage consistency. Cache can be shared (all cores access one cache), private (each core has its own), or a mix. Shared caches are simple but prone to contention, while private caches reduce contention but increase complexity for maintaining data consistency.
Question 3: Explain how the architecture of a computer, specifically the interaction between the CPU, RAM, and disk storage, affects the execution time of a complex program.
Answer 3: A program’s execution time is affected by the speed at which the CPU can access instructions and data. The CPU first looks for instructions and data in its cache. If not found, it fetches them from RAM, which is slower. Disk storage is accessed if data is not in RAM, which is even slower. This hierarchy of access speeds, with CPU cache being the fastest and disk storage being the slowest, significantly impacts the overall execution time of a complex program.
B) Understanding High-Level Architecture of Production-Ready Apps
Question 1: Discuss the advantages and disadvantages of storing logs on external services versus the primary production server. What factors would influence this decision in a system design context?
Answer 1: Storing logs on external services offers advantages such as centralized log management, scalability, and vendor-provided analysis tools. However, it introduces network dependency and potential security concerns. Conversely, storing logs on the primary server offers more control and potentially faster access but can impact server performance and storage limits. Factors influencing this decision include log volume, security requirements, budget constraints, and the need for specialized log analysis features.
Question 2: Explain how a load balancer might integrate with a service discovery mechanism in a microservices architecture to ensure requests are routed to available instances of a service.
Answer 2: In a microservices architecture, a service discovery mechanism keeps track of the available service instances and their network locations. When a request arrives at the load balancer, it queries the service discovery mechanism (e.g., Consul, Eureka) to get an updated list of healthy instances for the target service. The load balancer then distributes incoming requests among these instances based on its configured algorithm (e.g., round-robin, least connections), ensuring requests are routed to available services even in dynamic environments.
Question 3: In the context of the alerting service described, how can you design the system to avoid alert fatigue for developers? What strategies would you implement to ensure alerts are meaningful and actionable?
Answer 3: To avoid alert fatigue, prioritize clarity and relevance: (1) Define clear alert thresholds based on meaningful metrics, not just noise. (2) Group related alerts intelligently to prevent notification storms. (3) Implement alert escalation procedures so the right person is contacted. (4) Include actionable information in alerts, such as relevant logs or dashboards, to aid in quick diagnosis and resolution. Regularly review and adjust the system based on feedback and evolving needs.
C) Understanding the Pillars of System Design
Question 1: Imagine you’re designing a social media platform for a global audience. How would you prioritize the CAP theorem’s elements (Consistency, Availability, Partition Tolerance) based on different use cases, such as posting updates, sending messages, or viewing trending topics?
Answer 1: In a global social media platform: – For posting updates, prioritize Availability and Partition Tolerance over strong Consistency, as users expect posts to go through even with network issues. Eventual consistency is acceptable. – For sending messages, prioritize Consistency and Partition Tolerance. Users expect messages to be delivered reliably, even if some delay is incurred due to network partitions. – For viewing trending topics, prioritize Availability and Partition Tolerance. Stale data is acceptable, as trends change over time.
Question 2: Discuss the trade-offs between using a message queue for asynchronous communication and directly invoking an API endpoint for synchronous communication in a distributed system. When would you choose one over the other?
Answer 2: Message queues (asynchronous) offer decoupling, fault tolerance, and better handling of traffic spikes but introduce latency and complexity. Direct API invocation (synchronous) is simpler and provides immediate feedback but is tightly coupled, sensitive to failures, and can lead to cascading failures. Choose queues when decoupling, reliability, and handling bursts are crucial, like order processing. Choose direct invocation when simplicity and immediate feedback are key, like real-time dashboards.
Question 3: You’re tasked with designing a system with high availability requirements. Discuss various techniques, including load balancing, redundancy, and failover mechanisms, that you would implement to achieve your availability goals.
Answer 3: To achieve high availability: – Load balancing: Distribute traffic across multiple servers to prevent overload and single points of failure. – Redundancy: Implement redundant servers, databases, and other infrastructure components so the system can tolerate the loss of any single element. – Failover mechanisms: Set up automated processes to detect failures and switch to redundant instances. This can involve using heartbeats, monitoring services, and failover scripts or tools. Additional techniques include using geographically distributed infrastructure, implementing proper capacity planning, and having robust disaster recovery plans.
D) Understanding Networking Basics
Question 1: Explain how DNS resolution works, from the initial request in a user’s browser to receiving the IP address of a website. What are the different types of DNS servers involved in this process?
Answer 1: DNS resolution starts with a user’s browser requesting a website. If the IP isn’t cached locally, it contacts a Recursive DNS server (often from the ISP). This server queries the Root DNS servers for the top-level domain (.com, .org, etc.). The Root servers direct it to the TLD name server. The Recursive server then asks the TLD server for the authoritative name server for the specific domain (e.g., google.com). Finally, the Recursive server gets the IP address from the Authoritative server, caches it, and provides it to the browser.
Question 2: Compare and contrast TCP and UDP protocols. Provide examples of applications where one is preferred over the other and explain why.
Answer 2: TCP and UDP are transport layer protocols with key differences. TCP is connection-oriented, ensuring reliable, ordered data delivery with error checking and flow control. It’s suitable for applications like web browsing (HTTP), email (SMTP), and file transfer (FTP) where reliability is crucial. UDP is connectionless, offering speed and efficiency but without delivery guarantees. It’s preferred for applications like video streaming (RTP) and DNS queries, where speed outweighs reliability and some data loss is tolerable.
Question 3: Describe how firewalls use port numbers to control network traffic. What are the security implications of leaving unnecessary ports open on a server, and how can you mitigate these risks?
Answer 3: Firewalls act as network gatekeepers, examining incoming and outgoing traffic and filtering based on rules. One key rule set involves port numbers. Each port is associated with a specific service. Firewalls can block or allow traffic on specific ports. Leaving unnecessary ports open increases the attack surface, as malicious actors can exploit open ports for unauthorized access or attacks. Mitigate risks by: closing unused ports, using port forwarding to hide internal services, regularly scanning for vulnerabilities, and employing intrusion detection/prevention systems.
E) Understanding API Design
Question 1: Explain the concept of idempotency in HTTP methods. Why is it crucial to design idempotent APIs, and how can you ensure idempotency for methods like POST, PUT, and DELETE?
Answer 1: Idempotency in HTTP means that making the same request multiple times has the same effect as making it once. This is crucial for handling errors and retries gracefully, especially in distributed systems. – POST is not inherently idempotent. To ensure idempotency, use unique request identifiers or implement a mechanism to detect and discard duplicate requests. – PUT is idempotent. Updating a resource with the same data multiple times results in the same state. – DELETE is idempotent. Deleting a resource multiple times has the same effect as deleting it once.
Question 2: Discuss the differences between RESTful APIs, GraphQL APIs, and gRPC. Provide examples of scenarios where each API paradigm would be the most suitable choice.
Answer 2: – RESTful APIs use HTTP verbs (GET, POST, PUT, DELETE) and focus on resources. They are widely adopted, simple, and cacheable. Suitable for: resource-based CRUD operations, e.g., e-commerce product listings. – GraphQL APIs allow clients to query for specific data, reducing over-fetching and under-fetching. They are efficient and flexible but can be complex to implement. Suitable for: data-intensive applications, e.g., social media feeds. – gRPC uses Protocol Buffers for serialization and is designed for performance-critical, inter-service communication. It is fast and efficient but less widely supported. Suitable for: microservices communication, internal APIs.
Question 3: Explain how rate limiting and CORS settings can be used to secure an API. What are the potential drawbacks of overly strict rate limiting, and how can you find a balance between security and usability?
Answer 3: Rate limiting restricts the number of requests an API client can make in a given timeframe, preventing abuse and DoS attacks. CORS (Cross-Origin Resource Sharing) controls which origins (domains) can access API resources, mitigating cross-site scripting attacks. Overly strict rate limiting can hinder legitimate users, especially during peak usage or for applications with high request rates. Balance security by: implementing tiered rate limits based on user roles, using clear error messages and retry mechanisms, offering rate limit information in API responses, and providing mechanisms for legitimate users to request rate limit increases.
F) Understanding Caching and Content Delivery Networks (CDNs)
Question 1: Explain how caching can improve web application performance. Discuss the different types of caching, such as browser caching, server-side caching, and CDN caching, and their respective advantages and disadvantages.
Answer 1: Caching improves web application performance by storing copies of frequently accessed data closer to users, reducing latency and server load: – Browser caching stores data locally on the user’s browser, offering the fastest retrieval but limited storage capacity. – Server-side caching stores data on the server, enabling faster responses for subsequent requests but requires server resources. – CDN caching distributes cached data across geographically dispersed servers, reducing latency for global users but can be complex to manage. Each caching type offers a trade-off between speed, storage capacity, and management complexity, depending on the specific application requirements.
Question 2: What are the key differences between “push-based” and “pull-based” CDNs? Discuss the scenarios where one approach might be more advantageous than the other.
Answer 2: Push-based CDNs proactively push content to edge servers based on anticipated demand, reducing latency for popular content but potentially wasting storage and bandwidth for less frequently accessed data. Pull-based CDNs cache content on edge servers only when requested by users, optimizing for cache utilization but potentially resulting in higher latency for first-time requests. Choose push-based for: known popular content, predictable traffic patterns. Choose pull-based for: dynamic content, unpredictable traffic, limited storage/bandwidth.
Question 3: Imagine you’re designing a system that serves a mix of static and dynamic content. How would you leverage caching and CDNs to optimize the delivery of both content types and ensure a fast user experience?
Answer 3: For a system serving mixed content: – Static content (images, CSS, JS): Cache aggressively on CDNs with long expiration times. Use cache busting techniques (versioning, query parameters) when changes occur. – Dynamic content (personalized data, API responses): Employ server-side caching with shorter expiration times or use CDNs with edge computing capabilities to cache personalized responses closer to users. Additionally, implement cache control headers for fine-grained control over caching behavior, use a CDN with origin shield to reduce origin server load, and monitor cache hit ratios to optimize performance.
G) Understanding Proxy Servers
Question 1: What are the security implications of using public or open proxy servers? How do forward proxies, particularly those used for anonymization, mitigate or exacerbate these concerns?
Answer 1: Using public/open proxies risks: – Data interception: Traffic passes through unknown servers, potentially exposing sensitive data. – Malicious activity: Some proxies are run by malicious actors for data theft or malware injection. – Lack of control: Users rely on the proxy’s security measures, which may be inadequate. Forward proxies for anonymization can mitigate by masking the user’s IP address but exacerbate concerns if the proxy itself is compromised. Always prioritize reputable, security-focused proxies, preferably paid ones with strong logging and auditing practices.
Question 2: Explain how a reverse proxy can be utilized to implement a security measure like a Web Application Firewall (WAF). What are the benefits of placing a WAF at the reverse proxy level rather than directly on the application server?
Answer 2: A reverse proxy sits in front of application servers, acting as an intermediary for incoming requests. A WAF, integrated into the reverse proxy, analyzes HTTP/HTTPS traffic for malicious patterns, blocking attacks before they reach the server: – Benefits over server-level WAF: Centralized protection for multiple servers, reduced load on application servers, simplified security management, potential performance improvements due to caching and other proxy features. This layered approach enhances security by providing a dedicated line of defense against web application attacks.
Question 3: Compare and contrast the use of hardware load balancers, software load balancers, and cloud-based load balancing services. Discuss the factors that would influence the choice of one over the others in a specific system design scenario.
Answer 3: – Hardware load balancers: Dedicated physical devices, offer high performance and advanced features but are expensive and less flexible. – Software load balancers: Run on commodity hardware, more affordable and customizable but require server resources and management. – Cloud-based load balancing: Provided as a service, scalable and easy to deploy but vendor-dependent and may have limitations. Choice factors: Budget, scalability needs, technical expertise, desired features (e.g., SSL offloading, session persistence), and integration with existing infrastructure or cloud providers.
H) Understanding Databases
Question 1: Explain the ACID properties of a database transaction. Why are these properties crucial for maintaining data integrity, particularly in financial or e-commerce applications?
Answer 1: ACID properties guarantee reliable transaction processing: – Atomicity: All operations in a transaction succeed or fail together, preventing partial updates. – Consistency: Transactions move the database from one valid state to another, preserving data integrity. – Isolation: Concurrent transactions appear to execute in isolation, preventing data corruption from interleaving operations. – Durability: Once a transaction commits, changes are permanently stored and survive system failures. These properties are crucial in finance and e-commerce to prevent data loss, inconsistencies (like double-spending), and ensure accurate financial records.
Question 2: Discuss the trade-offs between choosing a relational (SQL) database and a NoSQL database for a new application. Consider factors like data structure, scalability, consistency, and query flexibility in your analysis.
Answer 2: SQL databases offer structured data, ACID properties, and powerful querying capabilities (joins, aggregations), making them suitable for applications requiring data consistency and complex relationships, like financial systems. NoSQL databases provide flexibility, scalability, and performance for unstructured data, but often with weaker consistency guarantees. They are suitable for applications handling large volumes of rapidly changing data, like social media or sensor data, where scalability and availability are paramount.
Question 3: Describe various database sharding strategies, such as range-based sharding, directory-based sharding, and geographical sharding. Explain the rationale behind choosing one strategy over another based on the application’s data access patterns and scalability requirements.
Answer 3: Sharding distributes data across multiple database servers to improve performance and scalability. – Range-based sharding: Data is divided based on key ranges, suitable for sequential data access but can lead to uneven load distribution. – Directory-based sharding: A central directory maps shards to servers, offering flexibility but introducing a single point of failure. – Geographical sharding: Data is distributed based on geographical regions, reducing latency for users in different locations but adding complexity. The choice depends on access patterns and scalability needs: consistent key ranges favor range-based, flexible mapping favors directory-based, and geographically distributed users favor geographical sharding.
About the Author
Joshua Makuru Nomwesigwa is a seasoned Telecommunications Engineer with vast experience in IP Technologies; he eats, drinks, and dreams IP packets. He is a passionate evangelist of the forth industrial revolution (4IR) a.k.a Industry 4.0 and all the technologies that it brings; 5G, Cloud Computing, BigData, Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT), Quantum Computing, etc. Basically, anything techie because a normal life is boring.
