In today’s ever-changing business landscape, those that operate using a software-driven model will be the most successful. These businesses recognize the power of transforming enormous volumes of data generated by digital operations into real-time insights that propel further success. The ability to do this in real-time, all the time, across multiple functional disciplines, lies at the heart of continuous intelligence.
Automation is a key component in the management of the entire software release lifecycle. While we know it is critical to the Continuous Integration/Continuous Delivery process, it is now becoming equally essential to the underlying infrastructure you depend on. As automation has increased, a new principle for managing infrastructure has emerged to prevent environment drift and ensure your infrastructure is consistently and reliably provisioned.
Kubernetes is an extremely intelligent technology, but without the right direction it can respond in unwanted or unexpected ways. As is true with most “smart” technologies, it is only as smart as the operator. In order to set teams up for peak success with Kubernetes, it is vital they have a pulse on their Kubernetes clusters. Here are 5 ways that engineers can best identify any loose ends when setting up a Kubernetes cluster and ensure the healthiest workloads possible.
The last fifteen years have seen huge increases in developer productivity for several reasons, including the arrival of open source into the mainstream and the ability to better emulate target environments. In addition, the process of resetting a development environment back to the last known stable version has been vastly improved by Vagrant and then Docker.
How do you migrate a production system to Kubernetes with confidence? Lior Mechlovich is an SRE for a cloud platform made up of dozens of microservices spanning 10+ teams and 5+ countries. Migration is difficult and risky. In this talk Lior shares his experience and lessons learned migrating to Kubernetes; how they trained teams, gained visibility, and triple checked each phase of the migration.
Kubernetes has several key differences that push the limits of traditional application monitoring. Due to the distributed ephemeral nature of Kubernetes, most existing solutions fail to give the visibility we might expect, resulting in longer resolution times. Looking at these potential pitfalls can help guide us as we take a fresh look at Kubernetes management and monitoring.