Cloud Cost Optimization is one of most important initiative on which organization are focusing nowadays . As more and more organizations are moving to the cloud. According to Flexera’s RightScale 2019 Cloud Status Report, 84% of organizations are adopting a multi-cloud strategy, and multi-cloud adoption is becoming the norm. In addition, 2019 enterprises will spend 24% more on the public cloud than in 2018. It’s not hard to see why. According to a recent Gartner report, organizations have realized 14% savings by moving to the cloud through reductions in capital spending, software licensing, IT staff reductions, and usage-based billing. Until 2020, Gartner will overshoot cloud infrastructure by 80% as a service budget due to a lack of cost optimization approaches. Forty-five percent of organizations that lift and shift to cloud IaaS without optimization will over provision as much as 55. It’s a percentage and will spend 70 percent during the first 18 months. Obviously, adopting cloud services offers powerful agility benefits. However, without a cloud cost management plan, you can quickly get out of control. Wildrun is rampant as an example of cloud costs.
Consider the example reported in Information:
Business grows rapidly as Adobe Adobe migrates its core software products to the cloud in 2013 and makes them available only to users through subscriptions. However, Adobe’s development team inadvertently charged $ 80,000 daily for computing jobs that weren’t discovered for more than a week.
Pinterest predicts IT capacity and prepays your instances at a lower rate. They, however, did not anticipate the popularity of that online scrapbook, but were too enthusiastic for any user to use. Pinterest then had to buy additional capacity at a much higher rate, so they had to spend $ 20 million more than originally estimated.
To reduce real estate in the Capital One data center and become a more agile next-generation company, Capital One has ordered the workload to move to the cloud, moving with the risk-averse financial services industry and odds. When legacy applications were migrated and determined to be stable, developers rushed to modernize them for resiliency. As a result of this strategic change, Capital One’s cloud costs increased by 73% between 2017 and 2018. I’m not sure if Capital One expects a significant surge in cloud costs, but these examples show how quickly capital ones can go out of control without proper management.
According to the Flexera / RightScale report, cloud cost optimization remains a top-class concern no matter where you are in your organization on the cloud journey. Indeed, as more workloads move to the cloud, it’s easier to lose track of the big picture and associated costs. While the pay-as-you-go model of cloud computing offers great opportunities for cost savings, IT also needs new approaches to minimize waste and optimize spending. Here are some steps you can take to manage your cloud costs. Avoid cloud-first or cloud-only thinking. Not all workloads are designed for the public hyper-scale cloud.
Cloud Cost Optimization
|Types of Orphaned Resources||Contents|
|Orphaned Snapshots||Snapshots of expired data|
|Orphaned Volumes||Amazon EBS, Azure Virtual Disks and Block Storage in GCP, etc.|
|Unassociated IPs||Elastic IPs in AWS, Static Public IPs in Azure and Static external IP addresses in GCP|
|Load Balancers||Load balancers with no instances|
|Unused Machine Images||AMIs in AWS and images in GCP|
|Orphaned Object Storage||S3 buckets in AWS, Azure Block Bobs and Google Cloud Storage|
Type of unwanted cost incurring resources
The easiest way to optimize your cloud costs is to look for unused or unconnected resources. Administrators or developers often forget to start a temporary server to perform a function and turn off IT when the job completes. In another common use case, the administrator may forget to remove the storage attach to the terminated instance. This often happens in his IT department throughout the enterprise. As a result, his AWS and Azure invoices for the organization include charges for resources that they have purchased but are not using.
So cloud cost optimization strategy should start by identifying unused and completely unattached resources and removing them. The next step in optimizing cloud computing costs is to deal with idle resources. The CPU utilization level for idle computing instances is 1-5%. If a company bills 100% of its compute instances, the IT department is a huge waste. The main strategy for cloud cost optimization is to identify such instances and consolidate compute jobs into fewer instances.
During the days of the data center, administrators often want to operate at low utilization, resulting in spikes in traffic and headroom during busy periods. Adding new resources to the data center is difficult, costly, and inefficient. Instead, the cloud offers auto-scaling, load balancing, and on-demand capabilities. This allows you to scale up your computing power at any time. Heatmaps are an important mechanism for cloud cost optimization. Heatmap is a visual tool that shows peaks and valleys in computing demand. This information can help you set start and stop times to reduce costs. For example, a heatmap can show if you can safely shut down your development server over the weekend. You can do this manually, but it’s better to take advantage of automation to schedule instance ups and downs to optimize costs. Proper sizing is the process of analyzing computing services and resizing them to the most efficient size.
According to Gartners Nik Simpson, his AWS EC2 instance selection report for workload migration shows that if a cloud administrator can choose her over 17,000 combinations, it’s not possible to size the instance correctly. It Is difficult. In addition to server size, there are options for servers optimized for memory, database, compute, graphics, storage capacity, throughput, and more. Appropriate sizing tools can also recommend changes between instance families, if desired. Proper sizing not only reduces cloud costs, but also helps optimize the cloud. This means achieving peak performance from the resources you are paying for.
Companies that have invested in AWS Reserved Instances or Azure Reserved VM Instances and have long-term commitment to the cloud should invest in RI. These are big discounts based on prepayment and time commitment. RI savings can reach up to 75%, which is essential for optimizing cloud costs. RIs can be purchased for one or three years, so it is important to analyze past usage and prepare for the future. To purchase an RI, refer to the Microsoft Azure Reserved VM Instance Purchasing Guide or follow the instructions in the AWS Management Console.
|Types of Overprovisioned Resources||Contents|
|Instances||Amazon EC2, Azure Virtual Machines, Google Compute Engine|
|Volumes||Amazon EBS, Azure Virtual Disks and Block Storage in GCP|
|Database Warehouses||Amazon Redshift, Google Cloud Datastore and Microsoft Azure SQL Data Warehouse|
|Relational Databases||Amazon RDS, Azure SQL and Google Cloud SQL|
|Types of Idle Resources||Contents|
|Instances||Amazon EC2, Azure Virtual Machines and Google Compute Engine|
|Load Balancers||Identify load balancers with no instances or instances that run 24X7 unnecessarily|
|Relational Databases||Amazon RDS, Azure SQL and Google Cloud SQL|
|Scale Groups||Auto Scaling Groups in AWS, Azure Scale Sets and Google Scale Groups|
|Types of RIs||Solution|
|Expired RIs||Renew and review RIs regularly|
|Unused RIs||Track RI usage and sell the unused at the vendor marketplace|
Accelerate cloud adoption by optimizing costs
By 2024, almost all legacy applications will be migrated to public cloud infrastructure as optimizations are needed to make services cost-effective. Cloud providers continue to enhance their native optimization capabilities to help you choose the most cost-effective architecture that can provide the performance you need. The market for third-party cost optimization tools is expanding, especially in multi-cloud environments. Its value focuses on high-quality analytics that maximize savings without sacrificing performance, provide independence from cloud providers, and provide consistency in multi-cloud management. Recognize the need for optimization as an integral part of your cloud migration project. Develop skills and processes early, use tools to analyze operational data, and find cost optimization opportunities. Maximize cost savings by leveraging what cloud providers natively offer to enhance IT with third-party solutions