What is Cloud Cost Optimization?
Cloud cost optimization is the process of reducing your overall cloud spend by identifying mismanaged resources, eliminating waste, reserving capacity for higher discounts, and Right Sizing computing services to scale.
The cloud offers organizations unlimited scalability and lower IT costs by only charging for the resources you use. But the truth about Amazon Web Services (AWS) pricing and Microsoft Azure pricing is that cloud customers pay for the resources they order, whether they use them or not. In their recent report, How to Identify Solutions for Managing Costs in Public Cloud IaaS, Gartner analysts Brandon Medford and Craig Lowery estimate that as much as 70% of cloud costs are wasted.
Fortunately, there are many best practices for cloud cost optimization. Here are seven simple ways that you can optimize your cloud costs.
7 Cloud Cost Optimization Best Practices
1. Find Unused or Unattached Resources
The easiest way to optimize cloud costs is to look for unused or unattached resources. Often an administrator or developer might “spin up” a temporary server to perform a function, and forget to turn it off when the job finishes. In another common use case, the administrator may forget to remove storage attached to instances they terminate. This happens frequently in IT departments across the company.
The result is that an organization’s AWS bills and Azure bills will include charges for resources they once purchased, but are no longer using. A cloud cost optimization strategy should start by identifying unused and completely unattached resources and removing them.
2. Identify and Consolidate Idle Resources
The next step in optimizing cloud computing costs is to address idle resources. An idle computing instance might have a CPU utilization level of 1-5%. When an enterprise receives a bill for 100% of that computing instance, it is a significant waste. A key cloud cost optimization strategy would be to identify such instances and consolidate computing jobs onto fewer instances.
In the days of data centers, administrators often wanted to operate at low utilization, so they would have headroom for a spike in traffic or a busy season. It’s difficult, expensive and inefficient to add new resources in the data center. Instead, the cloud offers autoscaling, load balancing, and on-demand capabilities that allow you to scale up your computing power at any time.
3. Utilize Heat Maps
Heat maps are important mechanisms for cloud cost optimization. A heat map is a visual tool showing peaks and valleys in computing demand. This information can be valuable in establishing start and stop times to reduce costs. For example, heat maps can indicate whether development servers can safely shut down on weekends.
While administrators can shut down servers manually, a better option is to leverage automation to schedule instances to start and stop, thereby optimizing costs.
4. Right Size Computing Services
Right Sizing is the process of analyzing computing services and modifying them to the most efficient size. According to Gartner’s Nik Simpson, in his Picking the Right AWS EC2 Instance for Your Workload Migration report, it’s difficult to size instances correctly when cloud administrators have more than 1.7 million possible combinations to choose from. In addition to server sizes, you can optimize servers for memory, database, computing, graphics, storage capacity, throughput, and more.
Right Sizing tools can also recommend changes across instance families if necessary. Right Sizing does more than simply reducing cloud costs, it also helps with cloud optimization, which means achieving peak performance from the resources you are paying for.
5. Invest in AWS Reserved Instances (RIs) or Azure Reserved VM Instances (RIs)
Enterprises committed to the cloud for the long-term should invest in reserved instances. These are larger discounts based on upfront payment and time commitment. RI savings can reach up to 75%, so this is a must for cloud cost optimization.
Since you can purchase RIs for one or three years, it is important to analyze your past usage and properly prepare for the future. To purchase RIs, see Microsoft’s Azure Reserved VM Instances (RIs) purchasing guide or follow instructions in the AWS Management Console.
6. Take Advantage of Spot Instances
Spot Instances are very different than RIs, but they can help you save more on your AWS spend or Azure spend. Spot Instances are available for auction and, if the price is right, can be purchased for immediate use.
However, opportunities to buy Spot Instances can go away quickly. That means they are best suited for particular computing cases like batch jobs and jobs that can be terminated quickly. Jobs like this are common in large organizations, so Spot Instances should be part of all cloud cost optimization strategies.
7. Consider Multi-Cloud vs. Single Cloud
Some enterprises deliberately seek out multi-cloud solutions to avoid vendor lock-in. While this is a valid strategy for increasing availability and uptime, these organizations may risk losing potential volume discounts by a single cloud vendor.
For example, if a company spends $500,000 on AWS + $300,000 on Azure + $200,000 on Google Cloud Platform, they could miss out on reaching a $1 million tier with one vendor. The value of that $1 million tier may be substantial discounts on overall cloud spend, as well as preferred status with that particular vendor. Additionally, the administrative hassles of switching between platforms, paying for network traffic between clouds, and training staff on multiple clouds could outweigh the ability to save money with a multi-cloud strategy.
Cloud Cost Optimization in Action
The cloud holds great potential. You can achieve cost savings in the cloud, as long as you pay attention to cloud cost optimization.
CloudCheckr helps enterprises manage and allocate costs, optimize spend, and save money on your cloud bills. With more than 600 Best Practice Checks for security, compliance, and cost management, CloudCheckr CMx can help optimize your workloads, identify idle and unused resources, and alert you of any vulnerabilities in your cloud environment.
Using CloudCheckr’s cost management features, Leaf Group’s Information Security Engineer Kevin Kang identified problems with the company’s object lifecycle management policy. The solution — changing storage types — resulted in a 25% decrease in S3 costs year over year. Kang explained:
“One important thing to note is that Society6 has seen a significant increase in traffic compared to last year. Under the old S3 policy, our costs would likely have increased accordingly. However, the cost has remained remarkably steady throughout 2020.”
Learn how Leaf Group managed cloud costs across multiple accounts and drove greater operational efficiency with CloudCheckr.