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Queryiest
QueryiestEnlightened
Asked: March 8, 20232023-03-08T00:34:10-05:00 2023-03-08T00:34:10-05:00In: AWS

On an EC2 instance, an application of yours is active. Once the CPU usage on your instance hits 80%, you must reduce the load on it. What strategy do you use to complete the task?

When the CPU usage on an EC2 instance hits 80% and the load needs to be reduced, there are several strategies that can be used to complete the task:

  • Add more instances: One way to reduce the load on an EC2 instance is to add more instances to the environment. This can be done by creating new instances and load-balancing traffic across them, which distributes the load and reduces the CPU usage on each instance.
  • Use auto-scaling: Auto-scaling can be used to automatically add or remove EC2 instances based on predefined conditions. This can be set up to add more instances when the CPU usage on existing instances reaches a certain threshold, reducing the load on each instance.
  • Use throttling: Throttling can be used to limit the rate of incoming requests to the application. This can reduce the load on the EC2 instance and prevent it from reaching 80% CPU usage. Throttling can be done using a variety of tools, such as load balancers, proxy servers, and application-level rate limiting.
  • Optimize the application: The application running on the EC2 instance can be optimized to reduce its CPU usage. This can be done by identifying and fixing slow or inefficient code, reducing unnecessary processing or disk I/O, and optimizing queries.
  • Use caching: Caching can be used to store frequently accessed data in memory or on disk, reducing the load on the EC2 instance and improving performance. Caching can be done using a variety of tools, such as in-memory caches, distributed caches, and content delivery networks (CDNs).
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  1. Queryiest
    Queryiest Enlightened
    2023-03-08T00:34:34-05:00Added an answer on March 8, 2023 at 12:34 am

    To reduce the load on an EC2 instance when its CPU usage hits 80%, one can add more instances, use auto-scaling, use throttling, optimize the application, or use caching. The strategy used will depend on the specific requirements and constraints of the application and environment.

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