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Autoscaling

Definition​

Autoscaling is a process in cloud computing that automatically adjusts the number of compute resources (such as virtual machines or containers) allocated to an application or service based on its current demand. The goal of autoscaling is to ensure optimal performance, availability, and cost efficiency by dynamically scaling resources up or down as needed.

Types​

  1. Vertical Autoscaling (Up and Down):
    • Vertical autoscaling involves adjusting the capacity of an individual resource, such as increasing or decreasing the number of CPUs, memory, or storage on a single machine.
    • Also known as "scaling up" and "scaling down," this approach involves making an existing resource more powerful or reducing its capacity based on the application's needs.
    • Vertical autoscaling is suitable for applications that may benefit from increased resources on a single machine, but it has limitations in terms of scalability compared to horizontal autoscaling.
  2. Horizontal Autoscaling (Out and In):
    • Horizontal autoscaling involves adjusting the number of instances or nodes in a distributed system. It is achieved by adding or removing entire machines (or instances) from a resource pool.
    • Also known as "scaling out" and "scaling in," this approach is more suitable for applications that can benefit from parallel processing and distributing the workload across multiple instances.
    • Horizontal autoscaling is generally more flexible and scalable than vertical autoscaling because it can handle a larger number of requests by adding more machines to the resource pool.

Differences​

  • Vertical Autoscaling:
    • Involves adjusting the capacity of individual resources.
    • Typically requires downtime during the scaling process.
    • Suitable for applications that may benefit from increased resources on a single machine.
  • Horizontal Autoscaling:
    • Involves adjusting the number of instances or nodes.
    • Can be done without downtime, as new instances can be added to the pool seamlessly.
    • Offers better scalability for handling a large number of requests by distributing the workload.

Considerations​

Both vertical and horizontal autoscaling have their use cases, and in some scenarios, a combination of both approaches may be employed to meet specific performance and scalability requirements.