Shared Resources and Forecasting
For your application containers to run together on arbitrary computers, they need an agreement about what they're allowed to do. Container clusters establish a declarative contract between resource needs and resource availability. We don’t recommend that you use containers as secure trust boundaries, but running trusted containers together and relying on VMs let’s you get the most utilization within your existing VM boundaries.
Another problem you may face is how to forecast capacity across multiple people and applications. Your team can use Kubernetes to share machines while being protected from noisy neighbors via resource isolation in the kernel. Now you can see resources across your teams and apps, aggregating numerous usage signals that might be misleading on their own. You can forecast this aggregate trend into the future for more cost effective use of hardware resources.
Conclusion
The decoupling of applications from the container cluster separates the operational tasks of managing applications and the underlying machines. Modular applications are easier to scale and maintain. Building container images before deployment reduces the risk that you’ll discover installation problems when it’s too late. And sharing resources leads to better utilization and forecasting, making your cloud smarter.
If you’d like to
take container clusters for a spin yourself, sign up for a
free trial and head on over to
Google Container Engine.
-Posted by Brendan Burns, Software Engineer
Follow