35 practical thoughts on system design: trade-offs, databases, reliability, architecture, observability, performance, cost, people, and process.

Operations First Design: Ever heard of this pattern? Neither did I. But I have seen this in action. The development phase of any Application is a fraction of the total life span of that application. All design patterns are oriented towards easier maintainability as one of their goals. But not all patterns would give the same benefits given different enterprise policies, business nature and team culture. In my experience (as recent as last year), we built a shinny new app, but it was blocked by the operations team to go to prod because they did not have the right mechanism to observe, change or report in production environment. In another extreme experience, we built a SaaS application and the SME knoew exactly how customer workflow changes are done. So he added a feature of inserting VB scripts as config files which would be changed for each client deployment based on their needs. This was of course a security risk, which was mitigated by making sure no one has access to the folder :). But just due to this feature 100s of client deployments were a no brainer for us. To explain lets take a simple example of "Configuration values". Developers have built a application which is fully controllable using config attributes. But where to keep this attributes so that it can be easily and safely modified, and once modified how will the application mange the change in its behaviour? An Operations led approach would help decide this: - Should the config file be in a external ASCII files (JSON/YML/CSV) in a shared location? This may be a problem for SaaS like application where accidental changes can lead to chaos. - Should it be in a database? Many enterprises have a very strong control on access to production DB. Also Audit trail would become difficult as a system users is usually used for all access. - Should it be an internal part of the application with a UI to edit it? This can increase dev time. Actual answer depends on what is the Enterprises production access policy, Audit requirements, impact of the change to the application and much more. Other examples could be reconciliations, transaction back tracking, health reports etc. That is why it is important to consider the Operations framework of the enterprise while designing applications. Most of the time Operations is either a second thought OR a by product of SME knowing the process very well. Instead, Operations led Design would enforce deliberate Enterprise Operations framework consideration just like performance and security considerations. This would lead to applications that are easier to maintain, observe and change in Production. P.S. no ai used, excuse the rawness.

𝐒𝐲𝐬𝐭𝐞𝐦 𝐃𝐞𝐬𝐢𝐠𝐧 𝐌𝐚𝐝𝐞 𝐒𝐢𝐦𝐩𝐥𝐞: 𝐋𝐋𝐃 & 𝐇𝐋𝐃 𝐄𝐬𝐬𝐞𝐧𝐭𝐢𝐚𝐥𝐬 𝐟𝐨𝐫 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐬 System Design can feel overwhelming, but the secret is knowing what truly matters. Whether you’re prepping for interviews or aiming to build scalable systems, here’s a clear roadmap: 1️⃣ Low-Level Design (LLD) – Implementation Details 1) 𝐂𝐥𝐚𝐬𝐬 & 𝐎𝐛𝐣𝐞𝐜𝐭 𝐃𝐞𝐬𝐢𝐠𝐧 - Designing modular, reusable, and maintainable classes. - Proper encapsulation, abstraction, and responsibility assignment. 2) 𝐃𝐞𝐬𝐢𝐠𝐧 𝐏𝐚𝐭𝐭𝐞𝐫𝐧𝐬 - Singleton, Factory, Observer, Strategy, Decorator, and more. - Helps solve recurring problems efficiently in software design. 3) 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞 𝐒𝐜𝐡𝐞𝐦𝐚 & 𝐑𝐞𝐥𝐚𝐭𝐢𝐨𝐧𝐬𝐡𝐢𝐩𝐬 - Normalization to avoid redundancy. - Efficient indexing, foreign keys, and query optimization. 4) 𝐀𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐬 & 𝐃𝐚𝐭𝐚 𝐒𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞𝐬 - Choosing the right structures for fast retrieval and storage. - Arrays, Linked Lists, Trees, Graphs, Heaps, Hashmaps, etc. 5) 𝐂𝐨𝐦𝐩𝐨𝐧𝐞𝐧𝐭 𝐈𝐧𝐭𝐞𝐫𝐚𝐜𝐭𝐢𝐨𝐧 & 𝐒𝐞𝐪𝐮𝐞𝐧𝐜𝐞 𝐃𝐢𝐚𝐠𝐫𝐚𝐦𝐬 - How different modules or classes communicate internally. - Visualizing method calls, event flows, and dependencies. 6) 𝐄𝐫𝐫𝐨𝐫 𝐇𝐚𝐧𝐝𝐥𝐢𝐧𝐠 & 𝐋𝐨𝐠𝐠𝐢𝐧𝐠 - Designing systems to handle exceptions gracefully. - Proper logging to track and debug issues efficiently. 2️⃣ High-Level Design (HLD) – Architecture Overview 1) 𝐂𝐥𝐢𝐞𝐧𝐭-𝐒𝐞𝐫𝐯𝐞𝐫 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 - Understanding request-response flow. - Load distribution between clients and servers. 2) 𝐋𝐨𝐚𝐝 𝐁𝐚𝐥𝐚𝐧𝐜𝐢𝐧𝐠 & 𝐂𝐚𝐜𝐡𝐢𝐧𝐠 - Distributing incoming traffic to multiple servers. - Reducing response times with caching strategies. 3) 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞 𝐒𝐜𝐚𝐥𝐢𝐧𝐠 - Choosing SQL vs NoSQL based on use case. - Replication, sharding, and partitioning for high performance. 4) 𝐌𝐢𝐜𝐫𝐨𝐬𝐞𝐫𝐯𝐢𝐜𝐞𝐬 𝐯𝐬 𝐌𝐨𝐧𝐨𝐥𝐢𝐭𝐡 - Designing modular services for scalability. - Comparing with monolithic approaches for simpler systems. 5) 𝐀𝐏𝐈 𝐃𝐞𝐬𝐢𝐠𝐧 & 𝐑𝐚𝐭𝐞 𝐋𝐢𝐦𝐢𝐭𝐢𝐧𝐠 - Building secure, scalable, and consistent APIs. - Preventing system overload using rate limiting strategies. 6) 𝐌𝐞𝐬𝐬𝐚𝐠𝐞 𝐐𝐮𝐞𝐮𝐞𝐬 & 𝐄𝐯𝐞𝐧𝐭-𝐃𝐫𝐢𝐯𝐞𝐧 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 - Decoupling services for asynchronous processing. - Ensuring reliable communication between components. 7) 𝐇𝐢𝐠𝐡 𝐀𝐯𝐚𝐢𝐥𝐚𝐛𝐢𝐥𝐢𝐭𝐲 & 𝐅𝐚𝐮𝐥𝐭 𝐓𝐨𝐥𝐞𝐫𝐚𝐧𝐜𝐞 - Ensuring system uptime during failures. - Designing redundant systems, failover strategies, and disaster recovery. 𝐏𝐫𝐨 𝐓𝐢𝐩: - Start with LLD to master internal design. - Then move to HLD for scalability and reliability. - Focus on concepts that actually impact system performance and maintainability. Credit: Original PDF owner. For more technical insights and structured content, follow Anil Rathod. #SystemDesign #LLD #HLD #SoftwareArchitecture #TechInterviews #Engineering #ScalableSystems

🚀 Day 42 of System Design — Architecture of a System Architecture is the blueprint of any system — it defines how components interact, how data flows, and how the system scales, performs, and evolves over time. 🏗️ A well-thought-out architecture ensures clarity, scalability, maintainability, and security, serving as the foundation for robust and future-proof systems. ⚙️ Key Components of System Architecture Hardware Platform 🖥️ → Servers, storage, and networking. Software Platform 💻 → OS, frameworks, and application servers. Interfaces 🔗 → APIs and user interfaces. System Structure 🧩 → Organization and interaction of components. Security 🔒 → Safeguards against unauthorized access and attacks. 🏗️ Popular Architectural Styles 1️⃣ Monolithic Architecture — All components tightly coupled into one unit. 2️⃣ Microservices Architecture — Independent, scalable services communicating via APIs. 3️⃣ Event-Driven Architecture — Components react to and emit events asynchronously. 4️⃣ Serverless Architecture — Run code without managing servers; let the cloud handle scaling. Each comes with trade-offs — the choice depends on your project’s scalability, performance, and complexity needs. 🛒 Example: Online Retail System Frontend → Displays products, categories, and user interactions. Backend → Processes requests, manages logic, and handles APIs. Database → Stores products, users, and orders. APIs → Connects payment, shipping, and inventory services. Security → SSL, authentication, and firewalls. Monitoring → Tracks performance and user activity. 🧠 Architecture Diagrams — The Visual Backbone Diagrams like Conceptual, Component, Deployment, Sequence, and Data Flow Diagrams (DFDs) simplify complexity and enhance collaboration. They help with: ✅ Clear visualization of system structure ✅ Better communication between teams ✅ Easier debugging, scalability planning, and documentation 🧰 Top Tools for Creating Architecture Diagrams Lucidchart — Cloud-based, collaborative diagramming. Draw.io (diagrams.net) — Free, simple, and effective. Microsoft Visio — Enterprise-grade detailing. Visual Paradigm — Great for UML and system modeling. OmniGraffle — Perfect for macOS users. 💡 Takeaway: A system’s architecture is its DNA — the design decisions you make today shape its stability, scalability, and success tomorrow. Build thoughtfully. 🏗️✨ 📸 Screenshot of my progress 🔗 Course: https://lnkd.in/dzba7VuX 🙏 Thanks: GeeksforGeeks #skillupwithgfg #nationskillup #SystemDesign #SoftwareArchitecture #Microservices #EngineeringDesign

Monolithic Architecture Types 💡Monolithic architecture refers to a software design approach where all components of an application are interconnected and interdependent, often deployed as a single unit. However, within the broader category of monolithic architectures, there are variations that address different needs and complexities in application development. 1. Monolith 🔎Definition: In a traditional monolithic architecture, the application is built as a single, indivisible unit. All components (UI, business logic, database access, etc.) are tightly coupled and run as a single process. 📌Characteristics: 🕯️Single Codebase: All functionalities reside in one codebase. 🕯️Tightly Coupled: Components are interdependent, making changes in one part potentially affect others. 🕯️Deployment: The entire application is deployed at once, which can complicate updates and scaling. 🕯️Development: Easier to develop for smaller teams, but can become unwieldy as the application grows. 2. Modular Monolith 🔎Definition: A modular monolith is a more structured version of a traditional monolith. The application is still a single deployable unit, but it is organized into distinct, self-contained modules or components. 📌Characteristics: 🕯️Decoupled Modules: Each module has its own responsibilities and can be developed, tested, and maintained separately, promoting separation of concerns. 🕯️Single Deployment: Despite the modular structure, it is still deployed as one unit, which simplifies deployment but maintains some of the challenges of traditional monoliths. 🕯️Easier Maintenance: Changes can be made in individual modules without affecting the entire application as severely as in a traditional monolith. 🕯️Potential for Future Microservices: The modular structure can serve as a stepping stone to transitioning to microservices if needed. 3. Distributed Monolith 🔎Definition: A distributed monolith is an architectural style that appears to be distributed (like microservices) but still has tight coupling between its components, which makes it behave like a monolith. 📌Characteristics: 🕯️Multiple Services: The application is divided into multiple services or components that are deployed separately. 🕯️Tight Coupling: Despite the separation, these services are often interdependent, leading to complexities similar to those found in a traditional monolith (e.g., needing to coordinate multiple services for a single transaction). 🕯️Deployment Challenges: While services can be deployed independently, the tight coupling may still lead to deployment challenges, as changes in one service can require changes in others. 🕯️Performance Overhead: Inter-service communication can introduce additional latency and performance bottlenecks. Want to know more? Follow me or connect🥂 Please don't forget to like❤️ and comment💭 and repost♻️ x.com/sina_riyahi medium.com/@Sina-Riyahi Instagram.com/Cna_Riyahi github.com/sinariyahi

Monolithic Architecture - System Design : Monolithic architecture is a software design methodology that combines all of an application's components into a single, inseparable unit. Under this architecture, the user interface, business logic, and data access layers are all created, put into use, and maintained as one, unified unit. A traditional approach in system design, which contains all application components into a single codebase. It was preferred for its simplicity and ease of initial setup. In contrast, alternative architectural approaches, like microservices, divide the application into smaller, separately deployable services. Because of its rigidity, it is difficult to scale and maintain, which makes it difficult to adjust to changing needs. لو المحتوى مفيد سيب تعليق وحابب تشوف مقارنة بالعربي بين Monolithic و Microservices، اكتبلي في الكومنت وأنا أجهزه ليك 

Architectural Styles 💡Architectural styles are essential frameworks that guide the structure and organization of software systems. 1. Monolithic Architecture 🔎Definition: A monolithic architecture is a traditional model where all components of an application are integrated into a single, unified codebase. This includes the user interface, business logic, and data access layers. 🔦Characteristics: ✅Single Codebase: All functionalities are encapsulated in one codebase, making deployment simple. ✅Tight Coupling: Components are highly interdependent, making it difficult to isolate and update parts of the application. ✅Scalability Challenges: Scaling often requires duplicating the entire application rather than specific components. ✅Development Speed: Initially, it can be faster to develop as everything is in one place, but this can lead to challenges as the application grows. 🕯️Use Cases: Small to medium-sized applications, startups, or projects with straightforward requirements. 2. N-Tier Architecture 🔎Definition: N-Tier architecture, also known as multi-tier architecture, organizes an application into layers, each with specific responsibilities. Typically, this includes presentation, business logic, and data access layers. 🔦Characteristics: ✅Separation of Concerns: Each layer is responsible for a specific aspect of the application, promoting modularity and easier maintenance. ✅Scalability: Different layers can be scaled independently depending on demand. ✅Interoperability: Layers can communicate through well-defined interfaces, which can facilitate integration with other systems or services. ✅Flexibility: Changes to one layer can be made with minimal impact on others, allowing for easier updates and enhancements. 🕯️Use Cases: Web applications, enterprise applications, and systems that require clear separation of responsibilities. 3. Microservices Architecture 🔎Definition: Microservices architecture is a modern approach that structures an application as a collection of small, loosely coupled services. Each service is independently deployable and focuses on a specific business capability. 🔦Characteristics: ✅Decentralized Data Management: Each microservice can manage its own database, allowing for flexibility in technology choices. ✅Independent Deployment: Services can be deployed and scaled independently, enabling faster delivery and updates. ✅Resilience: The failure of one service does not necessarily impact the entire system, enhancing overall reliability. ✅Polyglot Programming: Different services can be built using different programming languages or technologies best suited for their tasks. 🕯️Use Cases: Large applications, cloud-native systems, and organizations that prioritize continuous delivery and scalability. Want to know more? Follow me or connect🥂 Please don't forget to like❤️ and comment💭repost♻️ x.com/sina_riyahi medium.com/@Sina-Riyahi Instagram.com/Cna_Riyahi github.com/sinariyahi

Architectural Styles 💡Architectural styles are essential frameworks that guide the structure and organization of software systems. 1. Monolithic Architecture 🔎Definition: A monolithic architecture is a traditional model where all components of an application are integrated into a single, unified codebase. This includes the user interface, business logic, and data access layers. 🔦Characteristics: ✅Single Codebase: All functionalities are encapsulated in one codebase, making deployment simple. ✅Tight Coupling: Components are highly interdependent, making it difficult to isolate and update parts of the application. ✅Scalability Challenges: Scaling often requires duplicating the entire application rather than specific components. ✅Development Speed: Initially, it can be faster to develop as everything is in one place, but this can lead to challenges as the application grows. 🕯️Use Cases: Small to medium-sized applications, startups, or projects with straightforward requirements. 2. N-Tier Architecture 🔎Definition: N-Tier architecture, also known as multi-tier architecture, organizes an application into layers, each with specific responsibilities. Typically, this includes presentation, business logic, and data access layers. 🔦Characteristics: ✅Separation of Concerns: Each layer is responsible for a specific aspect of the application, promoting modularity and easier maintenance. ✅Scalability: Different layers can be scaled independently depending on demand. ✅Interoperability: Layers can communicate through well-defined interfaces, which can facilitate integration with other systems or services. ✅Flexibility: Changes to one layer can be made with minimal impact on others, allowing for easier updates and enhancements. 🕯️Use Cases: Web applications, enterprise applications, and systems that require clear separation of responsibilities. 3. Microservices Architecture 🔎Definition: Microservices architecture is a modern approach that structures an application as a collection of small, loosely coupled services. Each service is independently deployable and focuses on a specific business capability. 🔦Characteristics: ✅Decentralized Data Management: Each microservice can manage its own database, allowing for flexibility in technology choices. ✅Independent Deployment: Services can be deployed and scaled independently, enabling faster delivery and updates. ✅Resilience: The failure of one service does not necessarily impact the entire system, enhancing overall reliability. ✅Polyglot Programming: Different services can be built using different programming languages or technologies best suited for their tasks. 🕯️Use Cases: Large applications, cloud-native systems, and organizations that prioritize continuous delivery and scalability. Want to know more? Follow me or connect🥂 Please don't forget to like❤️ and comment💭repost♻️

Layered Architecture: Building Organized Software Ever wondered how big software programs stay organized and manageable? One of the oldest and most trusted ways is called Layered Architecture. It's like building a cake, where each layer has a specific job and only talks to the layers directly above or below it. WHAT IS LAYERED ARCHITECTURE? ---------------------------- Layered Architecture is a way of structuring software into distinct, separate layers. Each layer focuses on a specific set of concerns, making the system easier to understand, develop, and maintain. The key idea is that a layer can only directly use services from the layer immediately below it. COMMON LAYERS YOU MIGHT SEE: - **Presentation Layer:** This is what users see and interact with (e.g., a website's UI, a mobile app screen). It handles how data is displayed and user input. - **Application Layer:** This orchestrates tasks and defines how the application works. It tells the lower layers what to do based on user requests from the presentation layer. - **Domain/Business Logic Layer:** This is the core of your application, containing the rules and logic that solve your business problems. It defines "what" the software actually does. - **Data Access Layer:** This layer handles talking to the database or other data sources. It's responsible for storing and retrieving information without the upper layers needing to know the technical details of the database. BENEFITS OF LAYERS ------------------ - **Clear Separation of Concerns:** Each layer has a clear responsibility, reducing complexity. - **Easier Maintenance:** Changes in one layer (like a database switch) often don't require changes in higher layers. - **Improved Testability:** You can test individual layers in isolation. - **Enhanced Reusability:** Components within layers can often be reused in different parts of the system or even other projects. - **Better Scalability:** You can scale specific layers independently if needed, though this is more prominent in microservices. CONCLUSION ---------- Layered Architecture is a fundamental concept for building robust and maintainable software. By understanding how to separate concerns into logical layers, developers can create systems that are easier to build, debug, and evolve over time. It's a blueprint for order in the complex world of software development.

Modular Architecture Overview → An architectural style where the system is divided into self-contained modules → Each module represents a feature or plugin that can be added, removed, or updated independently → Promotes flexibility, maintainability, and scalability in large systems Types of Modular Architecture 1. Plugin-Based Modular Architecture → Core system provides a foundation (framework or host application) → Features are implemented as plugins that can be loaded or unloaded at runtime → Plugins extend functionality without modifying the core system Example: → Web browser (core) + plugins/extensions (ad-blocker, translator, password manager) 2. Feature-Based Modular Architecture → Modules are grouped by business features rather than technical layers → Each feature module may include its own UI, business logic, and data handling → Promotes separation of concerns by focusing on complete features Example: → E-commerce system with independent modules: Products, Cart, Checkout, Payments, User Accounts Components → Core System → Provides common services and infrastructure → Modules (Plugins or Features) → Independent units that add specific functionality → Module Interfaces → Defined contracts/APIs between core and modules → Module Loader/Registry → Mechanism to discover, load, and manage modules Flow → User interacts with the core → Core delegates tasks to the appropriate module → Module executes and returns result Benefits → High flexibility — modules can be added, removed, or updated independently → Easier maintenance — smaller, focused codebases → Parallel development — teams can work on modules without blocking each other → Reusability — modules can be reused across projects → Scalability — only critical modules need to be optimized or scaled Drawbacks → More complex design compared to monoliths → Requires careful management of module dependencies → Versioning and compatibility issues may arise between core and plugins → Slight performance overhead due to modular boundaries Best Practices → Define clear APIs/contracts for module interaction → Keep modules loosely coupled and independent → Use dependency injection for flexibility → Apply versioning and module governance → Organize feature-based modules around business domains → Ensure the core system remains stable and minimal When to Use → Applications that require extensibility (e.g., IDEs, CMS, browsers) → Large systems with multiple independent features → Teams working in parallel on different business areas → Products expected to evolve with new functionalities over time

1. Monolithic Architecture : A monolithic architecture means the entire application is built as a single, unified unit. All features — user interface, business logic and data access — are bundled together and deployed as one codebase. Characteristics: Single codebase, single deployment file (like .war, .jar, .exe). All modules (e.g., login, orders, payments) run in the same process. Single database shared by all modules. Easier to develop initially, but harder to scale as it grows. If one module fails, it can affect the whole system. Updating or scaling requires redeploying the entire application. Example: An e-commerce app where UI, order, payment, product, and inventory logic are all part of one big application and deployed together. Pros: Simple to develop and deploy initially. Easy debugging and testing when the app is small. Straightforward performance monitoring. Cons: Hard to scale individual features. Slower deployment for large applications. Difficult to adopt new technologies. Any small change requires full redeployment. _________________________________________________ ⚙️ 2. Microservices Architecture A microservices architecture breaks down the application into smaller, independent services — each responsible for one business function (like Order Service, Payment Service, etc.). Characteristics: Each service runs in its own process. Services communicate via APIs (REST, gRPC, messaging queues). Each has its own database (data independence). Can be developed, deployed, and scaled independently. Teams can work in parallel on different services. Example: In an e-commerce system: User Service handles user profiles and login. Product Service manages product catalog. Order Service handles orders. Payment Service manages transactions. Each one runs independently and communicates via APIs. Pros: Independent scaling and deployment. Easier to adopt new technologies per service. Better fault isolation — one service failure doesn’t crash everything. Enables faster development cycles. Cons: More complex to manage (network calls, distributed logging, monitoring). Requires robust DevOps setup (CI/CD, service discovery). Communication overhead and latency between services.