Published on Aug 16, 2022
Organisations are constantly looking for ways to increase innovation speed and agility while simultaneously maximising operational and economic efficiency to keep up with the competition. Consequently, they have been migrating their applications to multi-cloud and hybrid cloud environments for quite some time.
Originally, these monolithic applications were moved to the cloud using a “lift-and-shift” approach. Monolithic applications, however, cannot fully utilize the benefits of the cloud, such as elasticity and distributed computing, and are difficult to maintain and scale.
As a result, organizations are redesigning their existing monolithic applications or developing new ones as containerised ones as the next evolutionary step.
In contrast, deploying and containerizing applications is a complex task, which is where Kubernetes comes in. It has become the platform of choice for deploying containerised applications in public and private clouds thanks to Kubernetes (also known as K8s).
In public and private clouds, organisations have successfully deployed and managed containerised applications using K8s. As a result, they have struggled with the subsequent steps, such as ensuring secure and reliable access to Kubernetes applications externally.
As a result, legacy load balancers, which make these applications accessible to end users, were designed for monolithic applications and cannot keep up with the agile way these Kubernetes applications are deployed due to the fact that they were designed with monolithic applications in mind.
In order to deploy these load balancers, network and security teams must manually provision network resources for the applications, which may take days if not weeks. The load balancers will then need to be manually configured. As a result, this process becomes a bottleneck in the overall deployment process of Kubernetes applications.
This problem is further compounded by the fact that each public cloud provider has its own load balancer and management system.
Microsoft’s Azure Load Balancer is different from Amazon Web Services’ Elastic Load Balancing solution. This complicates and prolongs the process of automating application deployment. Since each load balancer has its own configuration and operation, it makes applying consistent policies across different cloud environments difficult.
