Infrastructure optimization

Cloud optimization is the process of analyzing and configuring the allocation of cloud resources that power applications, infrastructures, and workloads to maximize performance and minimize waste due to over-provisioning. 

Each workload has specific requirements that change over time and with differing load profiles. However, all these workloads have to be manually connected to cloud resources.Humans are not capable of continuous cloud optimization. As it is too complex a task to manually tune trillions of configurations at lightning speed, round the clock.By leveraging machine learning, enhanced optimization can be achieved.

Apps perform exceptionally well when their continuously changing requirements are constantly addressed and paired with the optimal cloud resources. Optimal configurations consume surprisingly lower resources and deliver notably higher performance at lower costs, yielding greater value to user and app owners alike.

Should you be implementing cloud infrastructure optimization?

So, who exactly in your enterprise should be looking into cloud optimization? The simple answer is all teams because cloud optimization is in everyone’s interest. What team wouldn’t benefit from lower cost and better performance of their apps? However,  IT Operations Teams, which could be either DevOps or CloudOps, have the task of cloud optimization because they divide and assign your cloud resources.

In order for present-day enterprises to thrive, it is imperative that they have some control over cloud cost. When implemented, cloud optimization is a win for everyone. Costs are reduced, which is thrilling for financial administration. Simultaneously, performance is dramatically enhanced, making the lives of the end-user easier. 

Uncontrolled, mismanaged cloud spend causes more money trouble for business than most realize.

 

Types of Cloud Infrastructure Optimization, Uses, and Benefits 

Public Cloud Optimization

Public cloud infrastructure optimization can decrease error rates by allocating instances proportionately in relation to workloads. Right-sizing instance allocations enable infrastructure footprint to be condensed. Streamlined cloud deployments are easier to understand which makes invoices more transparent, resulting in visibility into the costs and subsequent reductions. Continuous optimization technology delivers these benefits in an automated, ongoing process to every application and service within the cloud.

How is Optimization Done?

To achieve cloud infrastructure optimization, workloads are observed using a combination of AI, machine learning, and prediction technology. Factors such as costs and past performances are thoroughly analyzed. Results and deep insights derived from the analysis are then used to craft recommendations and suggest optimal configurations of resources and parameters to further improve cost and performance. These recommendations give IT Operations a deeper understanding of how the cloud works to enhance performance and improve their overall business efficiency. 

Technology Generations

As applications mature, infrastructure needs grow, costs rise, systems grow more complex, and understanding it all becomes more complicated. Even though the first-generation cloud optimization solutions center on transparency and optimization, these are a deep-rooted spin-off of complex next-generation solutions that are created to secure extensive capabilities including reducing risk and enhancing performance.

Consistent and Automated Optimization

Next-generation technologies go far beyond the simple generation of recommendations. Optimization engines such as Opsani weave optimization into the fabric of day to day development and release processes by integrating into the continuous delivery pipeline and connecting with the tools orchestrating the cloud deployment. Machine learning and deep ecosystem integration enable businesses to manage the complexity inherent to cloud-native environments and apply optimizations on an automated, ongoing basis.