Scalability
Table of Contents
1. Major Forks
1.1. Vertical Scaling (Scaling Up)
- Definition: Increasing the capacity of a single server or resource by adding more power (CPU, RAM, Disk).
- Advantages:
- Simpler architecture—requires no change in application logic.
- Immediate resource availability.
- Disadvantages:
- Limited by the capacity of the server.
- Higher risk of a single point of failure.
- Can be costly due to higher-specification hardware.
1.2. Horizontal Scaling (Scaling Out)
- Definition: Adding more servers or resources to distribute the load across multiple machines.
- Advantages:
- More resilient and fault-tolerant—failure of a single server does not affect the overall system.
- Can continue to add resources as demand grows.
- Typically uses commodity hardware, reducing costs.
- Disadvantages:
- More complex architecture—requires load balancing and potential application changes.
- Data consistency can be more challenging to manage across distributed systems.
1.3. Diff
| Aspect AsAaspect | Vertical Scaling | Horizontal Scaling |
|---|---|---|
| Definition | Increasing capacity of a single server | Adding more servers to distribute load |
| Architecture | Simpler, single-server focus | More complex, multi-server focus |
| Performance | Immediate performance gains | Performance improved as more servers are added |
| Fault Tolerance | Single point of failure | More resilient, can handle multiple failures |
| Cost | Higher cost for high-spec hardware | Typically cheaper, uses commodity hardware |
| Capacity Limitations | Limited by single server capacity | Can scale indefinitely as needed |
| Complexity | Easier implementation | Requires load balancing, synchronization |
| Use Cases | Predictable workloads | Unpredictable or growing workloads |
| Data Management | Easier to manage | More challenging to ensure consistency |
| Incremental Scaling | Limited; needs complete overhaul | Easy to add more servers as needed |