What is Cloud Optimization & Why is It Important?

Last updated on March 22nd, 2022 at 10:12 pm

The cloud optimization process is choosing and assigning the right resources to a particular workload or application. When the workload’s performance, compliance, and costs are correctly and continuously weighed against the most efficient infrastructure, efficiency is attained.

Every workload and application’s infrastructure requirements are unique, and the needs change as time passes. The base performance of a system is typically accomplished by applying domain information when choosing the right resources for a particular workload.

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However, any workload that has been manually matched with cloud resources can gain from further optimization with machine intelligence.

Applications with their existing needs dynamically right  to the top cloud resource will run better, need less support infrastructure on premises, use less resources to manage, and as well as in the cloud, and provide the highest ROI on cloud-based dollars expense.

Why Companies Are Worried About Cloud Optimization

Cloud optimization can be a product for IT Operations teams–specifically CloudOps or DevOps according to the organization responsible for allocating resources.

They are trapped between the requirements set by finance departments who wish to control the cloud-based spending and app owners who don’t want to hear their app’s resources are being cut.

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To ensure that modern businesses are successful, it’s vital to make sure the IT Ops keep control over the decisions made by the stakeholder groups

Cloud optimization allows this by allowing CloudOps to increase the value of cloud services (soothing Finance Analysts and Finance Directors) and provide the best application performance and report on it (making the app’s owners and users satisfied).

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Services that aren’t compatible with requirements for the application create risks and unneeded cloud spending that companies can’t afford to endure.

Use Cases for Public Cloud Optimization

  • Risk reduction in the application by resizing instances based on the intraday work pattern.

  • Modernization and removal of infrastructure by resizing cloud instances.

  • Optimization of containers.

  • Better match by cloud comparison of providers.

  • Automatization through auto-aware cloud instances (application-aware cloud).

  • Automation via self-optimizing cloud apps.

  • Compliance and cost reduction via transparency of cloud-based billing in the public cloud.

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Hybrid Cloud Optimization Use Cases

  • Real-time optimization and proactive optimization for virtual infrastructure as well as cloud computing bare metal.

  • Reservation and routing of workloads.

  • Elastic cloud to support VMware infrastructure.

  • Digital transformation with effective cloud migration plans and models.

  • Optimization of licenses for software.

  • Optimization of storage resources.

  • Server analysis and refresh of transformation

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How Can Achieved of Cloud Optimization

Cloud Optimization, Service Matching And Workload Modeling Recommendations

Cloud optimization tools model and study what patterns are present in each workload, including the history of usage and operational costs.

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And combine this information with knowledge of cloud services, available configurations and provide recommendations for improving the match between workload and service. These tips will assist IT Operations develop best cloud option and boost the business development.

Cloud Cost Visibility & Optimization

Costs and complexity of cloud computing increase exponentially as infrastructure expands.

While the first generation of cloud optimization tools focuses on cost visibility for cloud services and spending optimization, they are a natural result of more sophisticated solutions designed to provide greater efficiencies, such as the performance of apps, and reduce the risk for companies.

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Workload Automation & Continuous Optimization

The latest generation of solutions goes beyond offering recommendations and allows companies to implement these suggestions to the degree they feel at ease.

This workload automation can be partially achieved by using the optimization recommendations to kick off workflows in IT service management platforms like ServiceNow or even made ongoing through optimization-as-code-driven  continuous optimization.

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This workload automation may  be partly execute through utilizing these tips to kick off workflows in IT service management platforms like even made ongoing through optimization-as-code-driven continuous optimization or  Service Now. 

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