The latest News and Information on Containers, Kubernetes, Docker and related technologies.
Congratulations! You just put your 100th application into the cloud, marking the end of a highly successful project. As the senior leader tasked with driving transformation in your company, you are celebrating with the team. Your project manager buys the first round of drinks—they can afford it because their bonus was directly tied to hitting the target of 100 apps in the cloud and they are happy to spread the cheer.
With the emergence of new programming languages, libraries, packaging systems, and dependencies, the open source landscape has become more diverse. At the same time, companies are finding it more and more complex to package and deliver open source software. This creates a massive challenge for independent software vendors (ISVs), large enterprises, and other organizations that need to control their software supply chain lifecycles while adhering to industry standards and best practices.
In part two, I will cover: Microservices Architecture Overview: New Challenges for Monolithic Architecture As an application grows, so does the amount of code written. This can quickly overwhelm the development environment every time it needs to be opened and run. As you must deploy everything in one place, this approach means that the transition to another programming language, or other technologies becomes a big problem.
Modern Kubernetes environments are becoming increasingly complex. In 2021, Datadog analyzed real-world usage data from more than 1.5 billion containers and found that the average number of pods per organization had doubled over the course of two years. Organizations running containers also tend to deploy more monitors than companies that don’t leverage containers, pointing to the increased need for monitoring in these environments.
After months in development, we are thrilled to announce the launch of Cycle.io's support for NVIDIA GPUs (Beta). Combined with an already powerful platform that enables developers to focus on building, rather than managing, the addition of GPUs will further empower the development of accelerated applications which require a higher level of compute power.