Earlier this week, AWS announced the launch of AWS resource optimization recommendations within their cost management portal. AWS claims that this will “identify opportunities for cost efficiency and act on them by terminating idle instances and rightsizing under-used instances.” Here’s what that actually means, and what functionality AWS still does not provide that users need in order to automate cost control.

AWS Recommendations Overview

AWS Recommendations are an enhancement to the existing cost optimization functionality covered by AWS Cost Explorer and AWS Trusted Advisor. Cost Explorer allows users to examine usage patterns over time. Trusted Advisor alerts users about resources with low utilization. These new recommendations actually suggest instances that may be a better fit. 

AWS Resource Optimization provides two types of recommendations for EC2 instances:

    • Terminate idle instances
    • Rightsize underutilized instances

These recommendations are generated based on 14 days of usage data. It considers “idle” instances to be those with lower than 1%  peak CPU utilization, and “underutilized” instances to be those with maximum CPU utilization between 1% and 40%. 

While any native functionality to control costs is certainly an improvement, users often express that they wish AWS would just have less complex billing in the first place. 

AWS Resource Optimization Tool vs. ParkMyCloud

ParkMyCloud offers cloud cost optimization through RightSizing for AWS, as well as Azure and Google Cloud, in addition to our automated scheduling to shut down resources when they are idle. Note that AWS’s new functionality does not include on/off schedule recommendations.

Here’s how the new AWS resource optimization tool stacks up against ParkMyCloud.

Types of Recommendations Generated

The AWS Resource Optimization tool will provide up to three recommendations for size changes within the same instance family, with the most conservative recommendation listed as the primary recommendation. Putting it another way, the top recommendation will be one size down from the current instance, the second recommendation will be two sizes down, etc. ParkMyCloud recommends the optimal instance type and size for the workload, regardless of the existing instance’s configuration. This includes instance modernization recommendations, which AWS does not offer.

The AWS tool generates recommendations for EC2 instances only, while ParkMyCloud recommends scheduling and RightSizing recommendations for EC2 and RDS. AWS also does not support GPU-based instances in its recommendations, while ParkMyCloud does. 

AWS customers must explicitly enable generation of recommendations in the AWS Cost Management tools. In ParkMyCloud, recommendations are generated automatically (with some access limitations based on subscription tier).  

ParkMyCloud allows you to manage resources across a multi-cloud environment including AWS, Azure, Google Cloud, and Alibaba Cloud. AWS’s tool, of course, only allows you to manage AWS resources.

Recommendation Quality

When you start to dig in, you’ll notice several limitations of the recommendations provided by AWS. The recommendations are based on utilization data from the last 14 days, a range that is not configurable. ParkMyCloud’s recommendations, on the other hand, can be based on a configurable range of 1-24 weeks of data, configurable by the customer by team, cloud provider, and resource type. 

Another important aspect of “optimization” that AWS does not allow the user to configure are the utilization thresholds. AWS assumes that any instance at less than 1% CPU utilization is idle, and assumes any instance between 1-40% CPU utilization is undersized. While these are reasonable rules of thumb, users need the ability to customize such thresholds to best suit their own environment and use cases, and AWS does not allow you to customize these parameters. AWS also assumes an “all or nothing” approach – they recommend that any instance detected as idle simply be terminated. ParkMyCloud does not assume that low utilization means the instance should be terminated, but suggests sizing and/or scheduling solutions with specificity to the utilization patterns.  ParkMyCloud allows users to select between Conservative, Balanced, or Aggressive schedule recommendations with customizable thresholds.

AWS also only evaluates “maximum CPU utilization” to determine idle resources. However, for resource schedule recommendations, ParkMyCloud uses both Peak and Average CPU plus network utilization for all instances, and memory utilization for instances with the CloudWatch agent installed. For sizing recommendations, ParkMyCloud uses maximum Average CPU plus memory utilization data if available. 

Perhaps the most dangerous aspect of the AWS Recommendation is they will recommend an instance size change based on CPU alone, even if they do not have memory metrics. Without cross-family recommendation, this means each size down typically cuts the memory in half.  ParkMyCloud Rightsizing Recommendations do not assume this is OK. In the absence of memory metrics, we make downsizing recommendations that keep memory constant. For a concrete example of this, here is an AWS recommendation to downsize from m5.xlarge to m5.large, cutting both CPU and memory, and resulting in a net savings of $60 per month.

In contrast, here is the ParkMyCloud Rightsizing Recommendation for the same instance:

You can see that while the AWS recommendation can save $60 per month by downsizing from m5.xlarge to m5.large, the top ParkMyCloud recommendation saves a very similar $57.67 by allowing the transition from m5.xlarge to r5a.large, keeping memory constant. While the savings are off by $2.33, this a far less risky transition and probably worth the difference. In both cases, of course, memory data from the CloudWatch Agent would likely result in better recommendations.

As shown in the AWS recommendation above, AWS provides the “RI hours” for the preceding 14 days, giving better visibility into the impact of resizing on your reserved instance usage, and uses this data for the cost and savings calculations. ParkMyCloud does not yet provide correlation of the size to RI usage, though that is planned for a future release.  That said, the AWS documentation also states “Rightsizing recommendations don’t capture second-order effects of rightsizing, such as the resulting RI hour’s availability and how they will apply to other instances. Potential savings based on reallocation of the RI hours aren’t included in the calculation.”  So the RI visibility on the AWS side has minimal impact on the quality of their recommendations.  

If the user is viewing the AWS Recommendation from within the same account as the target EC2 instance, a “Go to the Amazon EC2 Console” button appears on the recommendation details, but it leads to the EC2 console for whatever your last-used region was, and without an automatic filter for the specific instance ID. This means you need to do your own navigation to the right region (perhaps also requiring a new console login if the recommendation is for a different account in the Organization), and then find the instance to see the details. ParkMyCloud provides better ease-of-use in that you can jump directly from the recommendation into the instance details, regardless of your AWS Organization account structure.  ParkMyCloud: 1 click. AWS: At least five, plus copy/paste of the instance ID and plus possibly a login.

ParkMyCloud also shows utilization data for the recommendation below the recommendation text, giving excellent context. AWS again requires navigation the right account, EC2 and then region, or to CloudWatch and the right metrics using the instance ID. 

AWS Resource Optimization also ignores instances that have not been run for the past three days. ParkMyCloud takes this lack of utilization into consideration and does not discard these instances from recommendations. 

AWS regenerates recommendations every 24 hours. ParkMyCloud regenerates recommendations based on the calculation window set by the customer. 

Automation & Ease of Use

While AWS’s new recommendations are generated automatically, they all must be applied manually. ParkMyCloud allows users to accept and apply scheduling recommendations automatically, via a Policy Engine based on resource tagging and other criteria. RightSizing changes can be “applied now”, or scheduled to occur in the future, such as during a designated maintenance window. 

There is also the question of visibility and access across team members. In AWS, users will need access to billing, which most users will not have. In ParkMyCloud, Team Leads have access to view and execute recommendations for resources assigned to their respective teams. Additionally, recommendations can be easily exported, so business units or teams can share and review recommendations before they’re accepted if required by their management process. 

AWS’s management console and user interface are often cited as confusing and difficult to use, a trend that has unfortunately carried forward to this feature. On the other hand, ParkMyCloud makes resource management straightforward with a user-friendly UI. 

Get Started

Want to see what ParkMyCloud will recommend for your environment? Try it out with a free trial, which gives you 14-day access to our entire feature set, and you can see what cost optimization recommendations we have for you.

About Bill Supernor

Bill Supernor is the CTO at ParkMyCloud. Bill is a software and network engineering professional with over 20 years of engineering and management experience in enterprise-grade software products, security, and networking. Prior to joining ParkMyCloud in 2017, Bill served as the CTO at KoolSpan, where he led the development of a globally deployed secure voice communication system for smartphones. Prior to KoolSpan, Bill served in security software engineering management positions at TrustDigital, Cognio, Symantec, and McAfee/Network Associates. He also was an officer in the United States Navy. Bill has the AWS Certified Advanced Networking - Specialty, is an AWS Certified Solutions Architect – Associate and holds the CISSP and CSSLP security certifications from ISC2.

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