System Design

 What is system Design?
System Design is the process of designing the system, or process , defining its architecture and components and classes so that it meets the need of the end users.


System Design Life Cycle is defined as the complete journey of a System from planning to deployment. The System Design Life Cycle is divided into 7 Phases or Stages, which are:
1. Planning Stage
2. Feasibility Study Stage
3. System Design Stage
4. Implementation Stage
5. Testing Stage
6. Deployment Stage
7. Maintenance and Support

Importance of Scalability in System Design

Scalability is an important factor in system design, which offers many benefits such as:

  • Managing Growth: When a system is scalable, it can handle more users, data, and traffic without sacrificing speed or reliability. Businesses that want to grow over time and draw in more customers need to do this.
  • Increasing Performance: By dividing up the load among several servers or resources, a scalable system increases overall performance. This leads to faster processing speeds, faster reaction times, and an intuitive user interface.
  • Ensuring Availability: By guaranteeing that systems continue to operate even in the event of unexpected spikes in traffic or component failures, scalability ensures availability. This is particularly crucial for mission-critical systems, which must always be operational to guarantee that clients can get the services they require.
  • Cost-effectiveness: Scalable systems are able to adjust their resources to meet demand variations by adding or subtracting resources as needed. This flexibility helps avoid oversupply and leads to significant cost savings by using just the resources that are required.
  • Encouraging Innovation: Scalability encourages the development of new features or services by lowering infrastructure obstacles. Because of this flexibility, businesses can swiftly adapt to changes in the market and keep a competitive edge.
  • What is Scalability and How to achieve it?

  • How to achieve Scalability?

    Now scalability is achieved via two methods in systems.

    1. Vertical Scaling

    Vertical scaling, also known as scaling up, refers to the process of increasing the capacity or capabilities of an individual hardware or software component within a system.

    • You can add more power to your machine by adding better processors, increasing RAM, or other power-increasing adjustments.
    • Vertical scaling aims to improve the performance and capacity of the system to handle higher loads or more complex tasks without changing the fundamental architecture or adding additional servers.

    What is Scalability and How to achieve it?

    Example of Vertical Scaling

    Let’s say you have a web application running on a server with 4 CPU cores and 8GB of RAM.

    As the application grows in popularity and starts receiving more traffic, you notice that the server is starting to struggle to handle the increased load. To address this, you decide to vertically scale your server by upgrading it to a new server with 8 CPU cores and 16GB of RAM.

    Advantages of Vertical Scaling

    • Increased Capacity: You can greatly improve a server’s performance and capacity to handle more requests by improving its hardware, for as by installing more RAM or a faster CPU.
    • Simplified Management: Since vertical scaling concentrates on improving a single server, it is simple to implement. This can be less complicated and more user-friendly to handle than managing several servers.

    Disadvantages of Vertical Scaling

    • Limited Scalability: The maximum hardware capacity of a single server places restrictions on vertical scaling. Physical bounds are reached at a certain point in the vertical scaling process.
    • Increased Costs: Compared to adding many, less expensive servers, upgrading server hardware, particularly with high-end components, might be more expensive. Because of this, choosing vertical scaling may end up costing more in the long term.
    • Single Point of Failure: When one server is used, any incoming requests are impacted by its failure, which causes downtime. Because of this, vertical scaling is more sensitive than horizontal scaling, which spreads the load over a number of servers to lower the chance of a complete failure.

    2. Horizontal Scaling

    Horizontal scaling, also known as scaling out, refers to the process of increasing the capacity or performance of a system by adding more machines or servers to distribute the workload across a larger number of individual units.

    • In this approach, there is no need to change the capacity of the server or replace the server.
    • Also, like vertical scaling, there is no downtime while adding more servers to the network

    What is Scalability and How to achieve it?

    Example of Horizontal Scaling

    Imagine you own a small delivery service company that initially operates with a single delivery van. As your business grows, you start receiving more orders and delivering to a larger area. However, you quickly realize that the single van is not sufficient to handle the increasing demand efficiently.

    • To address this issue, you decide to horizontally scale your delivery operation by adding more delivery vehicles to your fleet. Instead of relying on just one van, you purchase several additional vans and hire more drivers.
    • By doing so, you’re able to distribute the workload across multiple vehicles, enabling your company to handle a greater volume of packages and serve a larger customer base.

    Advantages of Horizontal Scaling

    1. Expanded Capacity: By adding more servers or instances, horizontal scaling allows your system to handle a larger number of incoming requests. This helps accommodate growing traffic and demand without compromising performance.
    2. Enhanced Performance: With multiple servers, the workload can be distributed evenly using load balancing. This prevents any single server from becoming overloaded, ensuring smooth and efficient performance across the system.
    3. Greater Fault Tolerance: Horizontal scaling improves system reliability. If one server goes down, other servers can take over the load, minimizing the risk of downtime and maintaining service availability.

    Disadvantages of Horizontal Scaling

    1. Increased Complexity: Managing a network of multiple servers or instances can be more challenging compared to handling a single server. This requires robust infrastructure and management tools to ensure everything runs smoothly.
    2. Higher Costs: Adding more servers or instances generally increases the overall cost of the system. This includes not just the hardware or cloud costs but also the expenses related to maintenance and management of the additional resources.

    Vertical Scaling vs. Horizontal Scaling

    Now that we have looked into the details of each type of scaling, let us compare them with respect to different parameters:

    What is Scalability and How to achieve it?

    Vertical Scaling vs. Horizontal Scaling

    Aspect

    Vertical Scaling (Scale-Up)

    Horizontal Scaling (Scale-Out)

    Definition

    Increasing the capacity of a single server (CPU, RAM, storage)

    Adding more servers or machines to the system

    Cost

    Higher, as larger and more powerful hardware is expensive

    Lower per server, but cost increases with more servers

    Complexity

    Easier to implement, as it involves upgrading a single machine

    More complex, as it requires managing multiple machines

    Limitations

    Limited by the hardware capabilities of a single server

    Can be scaled infinitely by adding more servers

    Performance Impact

    Performance improves by adding resources to a single server

    Performance improves through distribution of load across servers

    Downtime

    May require downtime for upgrades or maintenance

    Can be scaled without downtime (if properly configured)

    Use Case

    Suitable for small applications with less traffic

    Suitable for large-scale systems and high-traffic applications

    Elasticity

    Less elastic, harder to quickly add/remove capacity

    Highly elastic, capacity can be adjusted easily by adding/removing servers



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