Auto-scaling is possible through the use of cloud environments and the containerization of applications. With auto-scaling, an application can always keep the required processing capacity. This reduces costs by avoiding the need to configure to the maximum required resources from the beginning. It also prevents manual scaling and eliminates operational errors.
For many applications, auto-scaling means an increase in resource requirements, as the number of requests (number of processes) increases. For this reason, scale-out (horizontal scaling) comes to play as an effective solution. Specific implementations are: increasing the number of cloud instances, increasing the pod of K8s, or a combination of both.
Our experts not only design auto-scaling triggers based on your application characteristics, but also an architecture that takes availability and disaster recovery into account. This will ensure that auto-scaling is meaningful to your business. Please feel free to contact us.

1. Design Auto-scaling on the Cloud

Our experts will consider the characteristics of your application, adapt best practices to be cost-optimal, and design auto-scaling. In addition, with their background in application development, they can understand non-functional requirements that your application should guarantee.

2. Design Auto-scaling with K8s

If you already have K8s (Kubernetes) environment, our experts can help you design the metrics for auto-scaling. On the other hand, if you have not yet adopted K8s, we provide the Kubernetes consulting service.

3. Design Auto-scaling by Combining K8s and the Cloud

Most of the architectures that adopted K8s could be assumed to be cloud-based. Our experts will design K8s pod and node auto-scaling (Horizontal Pod Autoscaler and Cluster Autoscaler). Because of their expertise in both K8s and application development, they can design scaling that works well as part of the overall architecture. For example, when scaling APs or services, they consider the increased load on the DB.