Resource Automation for Cloud Computing – an Overview


The Resource Automation Series is finished so far – but it will continue once there is new exciting content. There is still a lot to be covered regarding resource automation. With this post, I want to give an Overview of what was discussed.

In the first post, I discussed if and how Cloud Computing will change the datacenter design. We were talking about standardisation in the datacenter and how Cloud Computing affects this. The next post was about how automations in datacenters. Cloud Computing needs us to think different since we don’t talk about 10 or 100 servers but rather tens of thousands. This also leads to various problems, which are discussed in this blog post.

Resource Automation also requires a cooperation between Developer Teams and Operation Teams. This is often referenced as “DevOps“. How deployment can be done, requires different strategies. Resource Automation leads to several problems that need to be addressed. One approach is to apply Datacenter Event Lifecycle Management. Resource Automation should lead to self Service IT, or also called “Software defined Datacenter” (VMware). Monitoring is an important task for resource automation in the Cloud. With Resource Automation, we have several possibilities to automate processes. How to identify processes, we discuss datacenter automation and integration in this post.

I hope you liked this tutorial on Cloud Computing and resource automation. Should you have any ideas, feel free to comment below. Our next series will be about Software Architectures for the Cloud so stay tuned ;).

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Published by

Mario Meir-Huber

I work as Big Data Architect for Microsoft. With this role, I support my customers in applying Big Data technologies - mainly Hadoop/Spark - for their use-cases. I also teach this topic at various universities and frequently speak at various Conferences. In 2010 I wrote a book about Cloud Computing, which is often used at German & Austrian Universities. In my home country (Austria) I am part of several organisations on Big Data.

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