Weekly Digest 5
Café IO's weekly digest to update you with awesome stuff written and published this week. This week, we discuss more about ML Model Deployment in Containers
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Links to the articles published this week:
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ML Model deployment in Containers: Part 3
Containers are only a small element of the large picture and require some tool to manage them. Such tools are called “Container Scheduler”. They help in interacting with Containers and managing them. One such scheduler is Kubernetes. Schedulers like Kubernetes have the following advantages:
It makes sure that resources are used efficiently and within constraints.
It makes sure that services are up and running.
We further learned few Kubernetes glossaries and demonstrated how to run Kubernetes on your local device & make the most of it.
Check out the complete article here
ML Model deployment in Containers: Part 1 & 2
In Part 1, We learned about Containers and container terminologies that are used. A Container is a standard unit of software that packages up code and all its dependencies so the application runs quickly and reliably from one computing environment to another. Containers offer a logical packaging mechanism in which applications can be abstracted from the environment in which they actually run.
We also discussed Virtualization and its comparison with Containers alongside an introduction to Docker & its workflow.
In Part 2, We saw how you can set up Docker on your machine and some basic commands to help you with it. We further illustrated Docker with a hands-on example by deploying an ML Model. We also learned what Container Orchestration is.
List of articles published previously at Cafe IO to help you more with Machine Learning:
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