In the wake of Broadcom’s acquisition of VMware, the world of virtualization is in flux. Customers, especially those reliant on VMware’s Pivotal Cloud Foundry (PCF), are feeling uncertain about the future. This blog post is designed to guide customers through the specific hurdles they now face due to the acquisition, explore Kubernetes (K8s) as an alternative to PCF, and discuss how Komodor can help with a K8s migration.

In the ever-evolving DevOps and site reliability engineering (SRE) landscape, Kubernetes stands out as a pivotal technology, revolutionizing how we deploy, scale, and manage containerized applications. K8s offers powerful orchestration capabilities, ensuring our applications are resilient and can scale seamlessly to meet varying demands. However, as robust as Kubernetes is, managing it efficiently requires significant expertise and effort.

For years, AI in operations was plagued by noise—overwhelming alerts, false positives, and a lack of actionable insights. The tools available promised much, but often delivered little, leading to a loss of trust. However, with the groundbreaking work by platforms like OpenAI and the emergence of trustworthy AI tools like Copilot, the potential of AI in operations has never been nearer and clearer.

Komodor, the company that automates Kubernetes management, today announced Klaudia, the first Generative AI (GenAI) agent for troubleshooting and remediating operational issues, as well as optimizing Kubernetes environments. Integrated within the Komodor Kubernetes Management Platform, Klaudia simplifies and accelerates root-cause analysis, empowering both platform and application teams with precise diagnostics to resolve issues with unprecedented speed and precision.

GitOps is a framework that combines the principles of software development and continuous integration, continuous delivery (CI/CD) to automate and manage application configurations and infrastructure using Git.

Handling resource allocation within Kubernetes clusters is of paramount importance. Proper resource allocation in Kubernetes ensures optimal performance and efficient utilization of the underlying infrastructure, safeguarding against capacity issues and application downtime. In contrast, improper resource allocation can lead to a plethora of challenges, from wasted resources to compromised application performance.

In today’s rapidly evolving technology landscape, Kubernetes has become essential for deploying and managing containerized applications. As organizations increasingly rely on Kubernetes to scale their operations, the need for robust guardrails becomes paramount. In this context, guardrails refer to the policies and mechanisms that ensure the safe and efficient operation of Kubernetes environments.

The current landscape of open-source software (OSS) in enterprises is characterized by a strategic shift towards open-source solutions for critical infrastructure and development needs. Enterprises increasingly rely on OSS to power their applications, manage data, and automate their deployment pipelines, making OSS an integral part of the software development lifecycle.

In recent months, AWS has announced significant changes to its Amazon Elastic Kubernetes Service (EKS) pricing structure, particularly concerning extended support for older K8s versions. This change is a crucial development for organizations that rely on AWS for their Kubernetes clusters, as it introduces potential cost increases for maintaining outdated versions.

In this multi-part series, we are taking a deep dive into everything from the technical review and assessment required to make the correct decision around substantial infrastructure migrations, through the practical hands-on work of migrating from legacy systems to Kubernetes and cloud-native environments.