On a $700 million budget, that gain is significant and can help build the business case
for a cloud native commitment.
Finally, it is a best practice to track your financial KPIs as you build your cloud program.
Your economic model gets better over time as you add more and more use cases.
#5 – Discover the Inner Workings of Your Application Estate
Cloud environments like AWS, Azure and Google are not fully backward compatible.
That means some of your applications will not be able to move to the cloud. Depending
on the importance of these applications, there will likely be a hybrid cloud whereby the
public cloud provider is connected with a private MPLS circuit. In this mode, cloud-based
applications can access legacy on-premises services, while still gaining the benefits of a
cost-efficient and agile infrastructure.
The challenges with hybrid cloud networks include latency issues, data gravity and the
volume of data being transmitted through the network. Simply put, you could cripple
your cloud program, without an understanding of the application mapping and data vol-
ume between application dependencies.
It is common for organizations to not fully know the inner workings of their application
estate. Rarely do CMDBs have this level of detail, and, more often than not, the team
members who did have this information are no longer working in your organization.
Companies have built data centers around application centers of gravity. Without a solid
understanding of what the connections are, and how much data travels between those
applications, there is little hope for program success.
Automation, Tools and Heroic Efforts
Application discovery is not easy. The good news is tools and automation make the job
far less painful.
Discovery Automation
Using automation to discover virtual machine profiles is nothing new. Most hypervisors
will give you this information, and there are numerous third-party tools that will sniff out
virtual and physical server details (such as RAM, cores, etc.). However, few hypervisors
will tell you the connections between VMs, the frequency between service calls and the
volume of data moving between the VMs.
There are agentless software tools that discover all the standard VM profile information,
and build a dependency map based on service calls. Over time, the tools provide a pro-
file of data flow between VMs. The dependency map is the critical first step in discovery
and forms the foundation for the rest of the process.
Profile Tools
We have developed custom processes and tools in our Right Mix Advisor which enables
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