What should you do to handle rapid changes in request loads in a GKE application service?

When dealing with rapid changes in request loads in a Google Kubernetes Engine (GKE) application service, scaling the application horizontally is an effective strategy. Horizontal scaling involves adding more instances of your application, which allows the system to handle higher loads by distributing the incoming requests across multiple pods.

This approach is particularly advantageous in cloud environments like GKE, which supports automated scaling features. By implementing horizontal pod autoscaling, you can ensure that the number of pod replicas increases during peak load times and decreases when demand subsides. This elasticity is a key benefit of cloud-native architecture, enabling applications to efficiently utilize resources while maintaining performance and reliability.

Using horizontal scaling also enhances fault tolerance. If one pod fails or becomes unresponsive, the load can still be handled by other pods, thus improving the overall resilience of the application. Additionally, this strategy aligns with the microservices architecture principles, where services can independently scale based on their specific load requirements.

While other approaches, such as implementing health checks, increasing pod resources, or utilizing a cache, can be useful in specific scenarios, they do not directly address the need to manage fluctuating request loads in the same effective manner that horizontal scaling offers. For instance, health checks ensure that your application is running optimally but do not