Data centers are only getting more complex, but you can get a handle on them with the combined use of data center analytics and automation.
If you're not familiar with IT operations analytics or data center analytics platforms, it's easy to get overwhelmed. All too often, information regarding data center analytics platforms focuses on how and what to implement, as opposed to why. In this article, we're going to take a step back to explain the purpose of adopting data center analytics and point out specific challenges you can overcome using purpose-built algorithms and infrastructure automation.
For those of us that work in the enterprise IT space, it's no secret that data centers are becoming increasingly complex. The added layers of virtualization and distributed services blur a once clear data flow map. Additionally, the continued expansion of hybrid and multi-cloud environments creates borderless networks that are a challenge to manage and suffer from a loss of end-to-end visibility. Yet, the added complexity being designed into modern data centers is absolutely necessary.
Today's business world requires a data center that allows for application flexibility and scalability. So, while complexities do indeed create new challenges in the data center, IT operations managers must learn to adapt to those challenges. And one way to solve these types of challenges is through the combined use of data center analytics and automation.
Solving the problems of increasing layers of virtualization, distributed workflows, and a need to easily move data and applications around at will largely revolves around two pieces of information. First, there is the need to understand application dependencies. These are the resources that a single application requires to make the application function. This includes virtual machines, containers, and microservices, as well as storage, networking and any other physical or virtualized infrastructure components that are necessary for it to work.
The second component is to understand the data flows between these application-specific dependencies and how end users of the application interact. With theinformation that can be mined using IT ops collection tools, one can automate the process of creating a real-time application dependency map of the entire data center landscape, both private and public.
With the power of an application dependency map, the layers of virtualization, lack of visibility and distribution of application resources simply melt away. And what we're left with is an easy to grasp layout of how an application truly functions on your network.
