Link - <a href="https://youtu.be/GMvbDCUEegs" target="_blank" rel="noopener nofollow">https://youtu.be/GMvbDCUEegs</a>
When dealing with system performance and scalability, two primary strategies exist: horizontal scaling and vertical scaling. Each has its advantages and trade-offs depending on the requirements of your application
<ol>
<li>Horizontal Scaling (Scaling Out)</li>
</ol>
✅ Increases capacity by adding more instances
✅ Load balancers distribute traffic across nodes
✅ More fault-tolerant (if one node fails, others continue)
✅ More complex setup and management
✅ Common in distributed systems and cloud environments
<ol start="2">
<li>Vertical Scaling (Scaling Up)
Vertical scaling means upgrading the existing machine by adding more resources (CPU, RAM, disk, etc.). Instead of adding more nodes, you make a single server more powerful.</li>
</ol>
✅ Simpler to implement (no need for multiple nodes)
✅ Suitable for applications that cannot be distributed
✅ Limited by the maximum hardware capacity
✅ Single point of failure (if the server crashes, everything stops)
✅ More expensive hardware upgrades
Link - <a href="https://youtu.be/GMvbDCUEegs" target="_blank" rel="noopener nofollow">https://youtu.be/GMvbDCUEegs</a>
#HorizontalScaling #VerticalScaling #Scalability #PerformanceOptimization #CloudComputing #LoadBalancing #HighAvailability #DistributedSystems #Microservices #AutoScaling #CloudInfrastructure #ServerScaling #BigData #WebApplications #SystemArchitecture

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Two primary strategies for system performance and scalability are horizontal scaling and vertical scaling. Horizontal scaling involves adding more instances and distributing traffic across nodes, suitable for distributed systems, and is more fault-tolerant. Vertical scaling upgrades existing machines with more resources, simpler to implement but is limited by hardware capacity and has a single point of failure.

Horizontal vs Vertical Scaling: Key Differences