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Overview of Intel Cloud Optimization Modules

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Part 2 of a 4-part series: Unlocking Cloud Automation with Intel’s Cloud Optimization Modules for Terraform

Cloud computing has revolutionized the way businesses operate by providing scalable and flexible infrastructure solutions. However, managing and optimizing cloud resources can be challenging without the right tools and frameworks. One of the biggest challenges facing Intel’s customers is that there is no EASY BUTTON for all the optimizations that can provide immense benefits. The Intel Cloud Optimizations Modules (OCM) for Terraform is Intel’s solution to this challenge.

Intel’s OCM aims to automate your CI/CD pipeline by codifying Intel instance selection and “optimizing” the software (when possible). For example, for AWS RDS MySQL, you set 3rd gen Intel Xeon Scalable processor instance as defaults and optimize InnoDB parameters beyond the AWS default (using the Xeon tuning guide). This is not where Intel stops! – They have thought about management and governance at scale - Sentinel Policies are being developed that allow us to overtime monitor and alert during pipeline runs. e.g., once a new Intel Instance Generation is out for customers using the solution, a simple policy update would alert customers that new (possibly more performant instances) are available. All this is being wrapped with the Terraform Cloud platform, which enhances and simplifies this type of implementation and usage at scale.

Benefits of Using Intel Cloud Optimization Modules

Automated Best Practices:  Intel's cloud optimization modules encapsulate industry best practices for infrastructure deployment and management, allowing organizations to benefit from Intel's deep expertise without having to configure and look for different optimizations. The modules will be a one-place store that captures all of Intel's goodness (e.g., Instance Selection, Workload Tunning Parameters, etc.). With the use of HashiCorp products like Terraform Cloud – you will be able to integrate and automate these best practices in your CI/CD pipeline in a matter of minutes.

Performance Optimization:  By leveraging Intel's cloud optimization modules, organizations can ensure that their workloads will be optimized. For example, Databricks clusters provisioned using Intel OCM come with the optimal combination of compute resources and configurations, leading to enhanced performance and faster processing times. Intel’s Databricks Cluster Module launches the cluster, which lands on 3rd Generation Intel Xeon Processor i4i Instances. With Databricks Photon Engine enabled, the benchmarking report shows 5.3x performance speed up in query processing!



Cost Efficiency: According to the 2023 Flexera State of Cloud Report, one of the biggest concerns for enterprises is managing cloud spend. Intel’s cloud optimization modules help organizations minimize the wastage of cloud resources, leading to optimized cost management. By provisioning resources based on workload demands, businesses can align their infrastructure costs with actual usage, resulting in significant cost savings over time. Again, let’s look at the Databricks Workload, according to benchmarking reports, using the module provides 3x price/performance benefits which lead to faster insights and lower costs.



Scalability and Flexibility: With Intel's cloud optimization modules, organizations can easily scale their infrastructure based on workload requirements. The flexibility provided by these modules enables businesses to adjust resource allocations dynamically, ensuring optimal performance during peak usage periods.

In the next blog installment on this theme, Intel Cloud Optimization Modules for Databricks, I will go over an overview of the Intel Cloud Optimization Modules for Databricks and then go over implementation and usage details to deploy Databricks Workspace and Cluster.


Here are some useful links if you'd like to learn more: