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AWS ARCHITECTURE BLOG


OPTIMIZING YOUR AWS INFRASTRUCTURE FOR SUSTAINABILITY, PART I: COMPUTE

by Katja Philipp, Aleena Yunus, Otis Antoniou, and Ceren Tahtasiz | on 10 AUG
2021 | in Amazon CloudWatch, Graviton, Sustainability | Permalink | Comments |
 Share
 * 
 * 
 * 
 * 
 * 

As organizations align their business with sustainable practices, it is
important to review every functional area. If you’re building, deploying, and
maintaining an IT stack, improving its environmental impact requires informed
decision making.

This three-part blog series provides strategies to optimize your AWS
architecture within compute, storage, and networking.

In Part I, we provide success criteria and metrics for IT executives and
practical guidance for architects/developers on how to adjust the compute layer
of your AWS infrastructure for sustainability. To help you achieve this goal, we
provide key metrics, show commonly used services and tools, provide insights
into analyzing them with Amazon CloudWatch, and provide steps for improving
them.


OUR COMMITMENT TO SUSTAINABLE PRACTICES

At AWS, we are committed to running our business in the most environmentally
friendly way possible. We also work to enable our customers to use the benefits
of the cloud to better monitor and optimize their IT infrastructure. As reported
in The Carbon Reduction Opportunity of Moving to Amazon Web Services, our
infrastructure is 3.6 times more energy efficient than the median US enterprise
data center, and moving to AWS can lower your workload’s carbon footprint by 88%
for the same task.

That said, sustainability is a shared responsibility between AWS and our
customers. As shown in Figure 1, we optimize for sustainability of the cloud,
while customers are responsible for sustainability in the cloud, meaning they
must optimize their workloads and resource utilization.

Figure 1. Shared responsibility model for sustainability

To reduce the amount of energy spent by your workload, you must use your
resources efficiently. “The greenest energy is the energy we don’t use” as Peter
DeSantis, VP of AWS Global Infrastructure, has said. But when we have to, using
the fewest number of resources possible, and using these to the fullest will
result in the lowest impact on the environment. Translating this to your
architectural decisions means that the more efficient your architecture is, the
more sustainable it will be.

We acknowledge that every AWS architecture is different and there is no one size
fits all solution. Therefore, keep in mind that you should assess first if the
proposed recommendations adhere to your specific requirements.


OPTIMIZING THE COMPUTE LAYER OF YOUR AWS INFRASTRUCTURE

Compute services make up the foundation of many customers’ workloads, which
brings great potential for optimization. When you look at the energy
proportionality of hardware (the ratio between consumed power and utilization),
an idle server still consumes power, as shown in The Case for
Energy-Proportional Computing. Thus, you can improve the efficiency of your
workload by using the fewest number of compute resources and achieving a high
utilization. Implementing the recommendations in the following sections will
help you use resources more efficiently and save costs.


REDUCING IDLE RESOURCES AND MAXIMIZING UTILIZATION

Energy-Proportional Computing: A New Definition reports that compute resources
should be maximized, on average 70-80%. This is because energy efficiency
quickly decreases as performance drops. The following table shows you the most
widely used compute services, the metrics they measure, and their associated
user guides.

Service Metric Source Amazon Elastic Compute Cloud (Amazon EC2) CPUUtilization
List of the available CloudWatch metrics for your instances Total Number of
vCPUs Monitor metrics with CloudWatch Amazon Elastic Container Service (Amazon
ECS) CPUUtilization Available metrics and dimensions Amazon EMR IsIdle Monitor
metrics with Cloudwatch

You can monitor these metrics with the architecture shown in Figure 2.
CloudWatch provides a unified view of your resource metrics.

Figure 2. CloudWatch monitors your compute resources

With an AWS Cost & Usage Report, you can understand your resource usage. AWS
Usage Queries, as shown in Figure 3, is a sample solution that provides an AWS
Cloud Development Kit (AWS CDK) template to create, store, query, and visualize
your AWS Cost & Usage Report.

Figure 3. AWS Cost & Usage Report for monitoring your compute resources

We recommend the following services and tools to reduce idle resources and
maximize utilization.

 * Integrate Amazon EC2 Auto Scaling. Setting up Amazon EC2 Auto Scaling allows
   your workload to automatically scale up and down based on demand.
   * Set up scheduled or dynamic scaling policies based on metrics such as
     average CPU utilization or average network in or out.
   * Integrate AWS Instance Scheduler and Scheduled scaling for Amazon EC2 Auto
     Scaling to schedule shut downs and terminate resources that run only during
     business hours or on weekdays.
 * Right-size resources with AWS Cost Explorer and AWS Graviton2. When you
   decide on an instance type, you should consider the requirements of your
   workload.
   * Consider using T instances, which come with burstable performance, if your
     workload has several unpredictable spikes. This reduces the need to
     over-provision capacity.
   * Use AWS Cost Explorer to see right-sizing recommendations for your
     workload. It highlights opportunities to reduce cost and improve resource
     efficiency by downsizing instances where possible.
   * Improve the power efficiency of your compute workload by switching to
     Graviton2-based instances. Graviton2 is our most power-efficient processor.
     It delivers 2-3.5 times better CPU performance per watt than any other
     processor in AWS. Additionally, Graviton2 provides up to 40% better price
     performance over comparable current generation x86-based instances for
     various workloads.
 * Adopt a serverless, event-driven architecture. Consider adopting a
   serverless, event-driven architecture to maximize overall resource
   utilization. Serverless architecture removes the need for you to run and
   maintain physical servers, because it is abstracted by AWS services. Because
   the cost of serverless architectures generally correlates with the level of
   usage, your workload’s cost efficiency will improve.
   * For asynchronous workloads, use an event-driven architecture so that
     compute is only used as needed and not in an idle state while waiting.


SHAPE DEMAND TO EXISTING SUPPLY

In contrast to matching supply to demand through methods such as automatic
scaling, you can shape demand to match existing supply. This strategy makes
sense especially for flexible workloads where the exact time to run a certain
operation is not relevant. This could include a recurring scheduled task that
runs overnight or a workload that can be interrupted.

We recommend the following services and tools to shape demand to existing
supply:

 * Use Amazon EC2 Spot Instances. Spot Instances take advantage of unused EC2
   capacity in the AWS Cloud. By shaping your demand to the existing supply of
   EC2 instance capacity, you will improve your overall resource efficiency and
   reduce idle capacity.
   * Spot Instances save you up to 90% in cost compared to On-Demand Instances.
   * Use Spot Instances for fault-tolerant, flexible, and stateless workloads
     that can be interrupted.
 * Apply jitter to scheduled tasks. Avoid load spikes by applying jitter to
   scheduled tasks and shift time-flexible workloads.
   * Assess if your scheduled tasks can be distributed to run at a random time
     during the hour.
   * Avoid using 0 as the start minute of scheduled tasks. This is the common
     default value. Rather, use a number between 2 and 58 to define the start
     minute for scheduled tasks.


CONCLUSION

In this blog post, we discussed key metrics and recommended actions you can take
to optimize your AWS infrastructure for resource efficiency. This will in turn
improve the sustainability of your compute resources.

As your business grows, it is natural that metrics like “Total vCPUs hours” will
increase. This is why it is important to track these metrics per unit of work,
such as number of vCPUs per 100 users or transactions. This way, the KPIs you
measure are independent of your business growth.

In the next part of this blog post series, we show you how to optimize the
storage part of your IT infrastructure for sustainability in the cloud!


KATJA PHILIPP

Katja Philipp is an Associate Solutions Architect based in Munich, Germany. With
a background in M. Sc. Information Systems, she joined AWS in September 2020
with the TechU Graduate program. She enables her customers in the Power &
Utilities vertical with best practices around their cloud journey. Katja is
passionate about sustainability and how technology can be leveraged to solve
current challenges for a better future.


ALEENA YUNUS

Aleena Yunus is an Associate Startup Solutions Architect in DACH. She has a
Masters in Computer Science majoring in distributed systems and network
security. She enjoys developing, helping her customers innovate on the cloud,
and apply architectural best practices. Aleena is an avid reader and her
favorite author is John Steinbeck.


OTIS ANTONIOU

Otis Antoniou is an Associate Solutions Architect based in London. He is part of
the UK and Ireland SMB team and he enjoys helping customers innovate and solve
business problems using AWS Services. Outside of work, Otis enjoys playing team
sports, racket sports, and he is passionate about music.


CEREN TAHTASIZ

Ceren Tahtasiz is a Startup Solutions Architect based in London. She helps
startups grow by understanding their goals and challenges, and guiding them on
how they can get started on AWS. She’s passionate about enabling customers to
launch cloud-native products that are resilient and scalable. Her core focus
areas are serverless technologies and sustainability in cloud.

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