Software development, agility and efficiency are paramount. Continuous Integration and Continuous Deployment (CI/CD) practices have revolutionised the way we build, test, and deploy software. When coupled with the power of Kubernetes, an open-source container orchestration platform, organisations can achieve a level of deployment excellence that was once only a dream.

The rise of containerization has precipitated an unprecedented shift in the software development landscape, with Kubernetes emerging as the de facto standard for managing large-scale containerized applications. One of the more nuanced aspects of Kubernetes that is gaining attention is multi-cluster orchestration. This approach to cluster management offers several compelling advantages that reshape how businesses operate and innovate in a cloud-native context.

Success in the cloud continues to be elusive for many organizations. A recent Forbes article describes how financial services firms are struggling to succeed in the cloud, citing Accenture Research that found that only 40% of banks and less than half of insurers fully achieved their expected outcomes from migrating to cloud. Similarly, a 2022 KPMG Technology Survey found that 67% of organizations said they had failed to receive a return on investment in the cloud.

Kubernetes has become the de facto standard for container orchestration, offering powerful features for managing and scaling containerized applications. In this guide, we will explore the various aspects of Kubernetes scaling and explain how to effectively scale your applications using Kubernetes. From understanding the scaling concepts to practical implementation techniques, this guide aims to equip you with the knowledge to leverage Kubernetes scaling capabilities efficiently.

Containers have gained significant popularity due to their ability to isolate applications from the diverse computing environments they operate in. They offer developers a streamlined approach, enabling them to concentrate on the core application logic and its associated dependencies, all encapsulated within a unified unit.

Memory (or RAM, short for random-access memory) is a finite and critical computing resource. The amount of RAM in a system dictates the number and complexity of processes that can run on the system, and running out of RAM can cause significant problems, including: This problem can be mitigated using clustered platforms like Kubernetes, where you can add or remove RAM capacity by adding or removing nodes on-demand.

We recently covered some of the complex decisions and architecture behind Cycle’s brand new interface. In this final installment, we’ll peer into our crystal ball and glimpse into the future of the Cycle portal. Cycle already is a production-ready DevOps platform capable of running even the most demanding websites and applications. But, that doesn’t mean we can’t make the platform even more functional, and make DevOps even simpler to manage.