AWS Savings Plan Details Test

Savings Plans offer a flexible pricing model that provides savings on AWS usage.

Savings Plans provide savings beyond On-Demand rates in exchange for a commitment of using a specified amount of compute power (measured per hour) for a one or three year period.

  • One year: 365 days

  • Three years: 1,095 days

To make informed decisions about right-sizing commitments, adjusting workloads, and optimizing future purchases to maintain maximum cost effectiveness and budget control in the AWS environment, it is essential to review the performance of the AWS savings plans from time to time. The AWS Savings Plan Details test helps administrators in this regard!

For each savings plan, this test reports the status, validity, utilization and net savings. Using this test, administrators can confirm that the committed spend aligns with the actual usage of the savings plan. This test proactively alerts administrators whenever the validity of the savings plan is about to expire.

Target of the test: Amazon Cloud

Agent deploying the test : A remote agent

Outputs of the test : One set of results for each AWS Regions on the target AWS Cloud being monitored.

Descriptor: AWS Region

Configurable parameters for the test
Parameter Description

Test Period

How often should the test be executed.

Host

The host for which the test is to be configured.

Access Type

eG Enterprise monitors the AWS cloud using AWS API. By default, the eG agent accesses the AWS API using a valid AWS account ID, which is assigned a special role that is specifically created for monitoring purposes. Accordingly, the Access Type parameter is set to Role by default. Furthermore, to enable the eG agent to use this default access approach, you will have to configure the eG tests with a valid AWS Account ID to Monitor and the special AWS Role Name you created for monitoring purposes.

Alternately, some AWS cloud environment administrators may not want to share their AWS Account ID. In this case, the eG agent can access the AWS API using a Managed Identity (trusted node) based approach. In this approach, you install the eG agent on a trusted node - i.e., an EC2 instance on the target AWS Cloud, assign IAM Roles to that EC2 instance for secure access, manage the AWS Cloud using the agent installed on that EC2 instance and collect the required metrics. To use this approach, you can change the Access Type to Managed Identity.

Some AWS cloud environments however, may not support the role-based approach or managed identity based approach. Instead, they may allow cloud API requests only if such requests are signed by a valid Access Key and Secret Key. When monitoring such a cloud environment therefore, you should change the Access Type to Secret. Then, you should configure the eG tests with a valid AWS Access Key and AWS Secret Key.

Note that the Secret option may not be ideal when monitoring high-security cloud environments. This is because, such environments may issue a security mandate, which would require administrators to change the Access Key and Secret Key, often. Because of the dynamicity of the key-based approach, Amazon recommends the Role-based approach for accessing the AWS API.

AWS Account ID to Monitor

This parameter appears only when the Access Type parameter is set to Role. Specify the AWS Account ID that the eG agent should use for connecting and making requests to the AWS API. To determine your AWS Account ID, follow the steps below:

  • Login to the AWS management console. with your credentials.

  • Click on your IAM user/role on the top right corner of the AWS Console. You will see a drop-down menu containing the Account ID (see Figure 1).

    Identifying AWS Account ID

    Figure 1 : Identifying the AWS Account ID

AWS Role Name

This parameter appears when the Access Type parameter is set to Role. Specify the name of the role that you have specifically created on the AWS cloud for monitoring purposes. The eG agent uses this role and the configured Account ID to connect to the AWS Cloud and pull the required metrics. To know how to create such a role, refer to Creating a New Role.

AWS Access Key, AWS Secret Key, Confirm AWS Access Key, Confirm AWS Secret Key

These parameters appear only when the Access Type parameter is set to Secret.To monitor an Amazon cloud instance using the Secret approach, the eG agent has to be configured with the access key and secret key of a user with a valid AWS account. For this purpose, we recommend that you create a special user on the AWS cloud, obtain the access and secret keys of this user, and configure this test with these keys. The procedure for this has been detailed in the Obtaining an Access key and Secret key topic. Make sure you reconfirm the access and secret keys you provide here by retyping it in the corresponding Confirm text boxes.

Proxy Host and Proxy Port

In some environments, all communication with the AWS cloud and its regions could be routed through a proxy server. In such environments, you should make sure that the eG agent connects to the cloud via the proxy server and collects metrics. To enable metrics collection via a proxy, specify the IP address of the proxy server and the port at which the server listens against the Proxy Host and Proxy Port parameters. By default, these parameters are set to none , indicating that the eG agent is not configured to communicate via a proxy, by default.

Proxy User Name, Proxy Password, and Confirm Password

If the proxy server requires authentication, then, specify a valid proxy user name and password in the Proxy User Name and Proxy Password parameters, respectively. Then, confirm the password by retyping it in the Confirm Password text box. By default, these parameters are set to none, indicating that the proxy sever does not require authentication by default.

Proxy Domain and Proxy Workstation

If a Windows NTLM proxy is to be configured for use, then additionally, you will have to configure the Windows domain name and the Windows workstation name required for the same against the Proxy Domain and Proxy Workstation parameters. If the environment does not support a Windows NTLM proxy, set these parameters to none.

Exclude Region

Here, you can provide a comma-separated list of region names or patterns of region names that you do not want to monitor. For instance, to exclude regions with names that contain 'east' and 'west' from monitoring, your specification should be: *east*,*west*

DD Frequency

Refers to the frequency with which detailed diagnosis measures are to be generated for this test. The default is 1:1. This indicates that, by default, detailed measures will be generated every time this test runs, and also every time the test detects a problem. You can modify this frequency, if you so desire. Also, if you intend to disable the detailed diagnosis capability for this test, you can do so by specifying none against DD frequency.

Detailed Diagnosis

To make diagnosis more efficient and accurate, the eG Enterprise embeds an optional detailed diagnostic capability. With this capability, the eG agents can be configured to run detailed, more elaborate tests as and when specific problems are detected. To enable the detailed diagnosis capability of this test for a particular server, choose the On option. To disable the capability, click on the Off option.

The option to selectively enable/disable the detailed diagnosis capability will be available only if the following conditions are fulfilled:

  • The eG manager license should allow the detailed diagnosis capability
  • Both the normal and abnormal frequencies configured for the detailed diagnosis measures should not be 0.
Measurements made by the test

Measurement

Description

Measurement Unit

Interpretation

Status

Indicates the current status of this savings plan.

 

The values that this measure reports and their corresponding numeric values are listed in the table below:

Measure Value Numeric Value
Inactive 0
Active 1

Note:

By default, this measure reports the Measure Values listed in the table above to indicate the current status of each savings plan. In the graph of this measure however, the same is represented using the numeric equivalents only.

The detailed diagnosis of this measure lists the Account ID, Account name, Savings plan type, Instance family, Purchase term, Start date time, End date time and Hourly commitment.

Remaining days

Indicates the number of days that are remaining for this savings plan to be valid.

Number

 

Utilization

Indicates the utilization of this savings plan.

Percent

 

Total commitment

Indicates the hourly amount (in USD/hour) that administrators agree to pay based on this savings plan.

US Dollars

By closely tracking this measure helps administrators obtain visibility into spending patterns, accuracy in budgeting and forecasting, and enable proactive adjustments as workloads change.

Unused commitment

Indicates the portion of hourly commitment amount that is already paid but remains unused based on this savings plan.

US Dollars

A value close to the Total commitment measure may indicate:

  • Reduced workload usage (e.g., scaled down EC2 or Fargate tasks)

  • Workloads moved to other services not covered by the Savings Plan

  • Incorrect commitment sizing (bought a plan larger than your typical usage)

  • Regional or instance family mismatch (for Compute vs EC2 Instance Savings Plans)

Used commitment

Indicates the portion of hourly commitment amount that is already used based on this savings plan.

US Dollars

A value close to Total commitment measure may indicate that the savings plan is being utilized efficiently.

A low value for this measure may indicate:

  • A low used commitment means:

  • You might be overcommitted (bought a plan too large).

  • Your workload pattern has changed (less compute usage).

  • Some workloads are ineligible (e.g., regions or instance types not covered).

Net savings

Indicates the total cost reduction or discount achieved by using this savings plan.

US Dollars

Net savings = On demand cost equivalent - Total amortized commitment.

By tracking Net savings, businesses can assess whether the savings plan is delivering the expected value, optimize future commitments, and ensure they are maximizing their return on investment. Essentially, Net savings helps confirm that the savings plan strategy is effectively reducing costs and improving long-term cloud spend management.

On demand cost equivalent

Indicates the amount that would have been paid if the same workloads were run without this savings plan.

US Dollars

Using this measure administrators can:

  • Quantify total cost avoidance due to Savings Plan

  • Compare different commitment levels or plan types.

  • Obtain insight into cost efficiency trends over time.

Total amortized commitment

Indicates the total cost of this savings plan commitment spread evenly (amortized) over a given period, such as a month.

US Dollars

By closely monitoring the value of this measure, administrators can:

  • Obtain a consistent monthly cost view for budgeting and forecasting.

  • Calculate Net savings (by comparing with On demand cost equivalent).

  • Obtain accurate cost allocation and performance tracking of savings plans.

Amortized upfront commitment

Indicates the portion of any upfront payment that is evenly distributed (amortized) over the duration of this savings plan.

US Dollars

This measure helps ensure that both upfront and recurring (hourly) costs are reflected proportionally over time.

Use the detailed diagnosis of the Status measure to view additional details of the Savings Plan such as Purchase term, Plan Type, etc.

Figure 2 : The detailed diagnosis of the Status measure