Using ServiceNow & Jira Service Desk to Action Resource Optimization Analytics
Start by provisioning new products from a service catalog hosted through an ITSM platform like ServiceNow or Jira. This triggers a deployment process through an infrastructure as code technology like AWS CloudFormation or HashiCorp Terraform to deploy the necessary services required by the product.
The consumption of cloud resources by these services is monitored by SaaS services like Densify to analyze and derive recommendations for optimizing supply allocations like memory, CPI, and more. As these recommendations become available, they are distributed to a parameter repository, typically situated within your DevOps CI/CD pipeline. The example technology we are using here is AWS Parameter Store.
The delivery of these rightsizing recommendations triggers an ITSM collaboration process to acquire both an approval to execute from application owners, as well as a maintenance window from Cloud Operations.
We finally come full circle when the maintenance window is triggered to perform the necessary optimizations using the same IaC technology used to initially deploy the services.
Demonstration of Continuous Cloud Optimization via ServiceNow
In practice, within ServiceNow ITOM, you start bu navigating to the AWS service catalog in the ServiceNow GUI. You can order the continuously-optimizing product you are interested in.
At some point in the future when sufficient resource utilization data has been collected, Densify will analyze these services and generate recommendations to optimize supply allocations.
In this example, you are seeing various recommendations to modernize, downsize, upsize or even change family for Amazon EC2 instances.
Recommendations are continuously distributed by Densify to your parameter repo. Here, we are using AWS Parameter Store, where each parameter is storing not only the optimal supply allocation, but also storing the historical context and recommendation details.
Again within ServiceNow, you can see a change management request with the complete recommendation context. Approvals to execute the recommendation can be provided by application owners directly within the request.
Upon approval, Cloud Operations will receive a work order to execute the approved changes. This request is delivered through AWS Systems Manager OpsCenter, which can be used to manage the complete lifecycle of the work order. Your Ops team begins by scheduling a maintenance window.
Finally, AWS CloudFormation will be triggered automatically within the maintenance window. The changes will be performed with a notification sent to all stakeholders.
This cycle repeats continuously, keeping your cloud infrastructure optimized.