CostGuard is part of Finout’s cost optimization suite that is responsible for generating cost-saving recommendations by continuously scanning your resources and your entire MegaBill, allowing you to identify and leverage potential cost-saving opportunities across various use cases.

CostGuard recommendations are divided into three different use cases:

When you select a CostGuard scan, you will find the query prominently displayed in the top right corner of the screen. This query is customized to your selection, reflecting the specific criteria and filters you have chosen. It serves as a concise summary of the scan's parameters, allowing you to review and verify that the scan aligns with your objectives.

Moreover, the query provides you with valuable insights by presenting all relevant resources identified within the past 7 days. By focusing on recent data, CostGuard ensures that you have access to the most up-to-date information when making informed decisions about cost optimization.

EC2 Instance Savings Plans unlock savings of up to 72% off on-demand prices by committing to a specific instance family in an AWS Region, regardless of instance size (e.g., m5.xlarge, m5.2xlarge, etc.), operating system (e.g., Windows, Linux, etc.), and tenancy type (Host, Dedicated, Default) within the chosen family and region.

With an EC2 Instance Savings Plan, you retain the flexibility to resize your instances within the selected family (e.g., from c5.xlarge to c5.2xlarge) or switch operating systems (e.g., from Windows to Linux). Even transitioning from dedicated tenancy to default does not affect the discounted rate provided by your EC2 Instance Savings Plan.

As part of CostGuard for EC2 Savings plans, our platform conducts scans across all EC2 instances within your account. We prioritize optimizing EC2-compute and on-demand filters, as these areas are vital in cost optimization. The resource names in the platform will include the respective regions to provide accurate insights and optimization recommendations.

For each region type, we have an analysis model that includes a simulator for savings plans.

To use the savings simulator:

Once the simulator is set based on your scan type, a summary is displayed. It includes the current on-demand spend, estimated monthly spend, and potential savings based on the chosen payment option.

The simulator provides an hourly level comparison with the on-demand rate, indicating the coverage provided by each commitment.

Using the simulator, we recommend the price of an hourly commitment based on the analysis.

We provide the user with the ability to understand the RIs for each one of the instances; how many resources are in each instance (Resources Count), how much of the instances are currently covered by any plan (Current Coverage), the optimal coverage and we provide a recommendation of how many instances, what type of instance family you should purchase and the annual potential savings if you go by the recommendation.

This instance is analyzed on a time frame of the last 30 days.

Compute Savings Plans can lead to savings of up to 66% relative to on-demand prices by committing to specific hourly compute costs. These plans offer maximum flexibility, regardless of the instance family, region, operating system (e.g., Windows, Linux), tenancy type (such as Host, Dedicated, or Default), or product type (EC2, Fargate, Lambda).

Finout’s CostGuard feature conducts scans across EC2, Fargate, and Lambda compute. Based on your hourly usage, it recommends the best $/hour rate for you.

Scan Breakdown:

From these options, 6 different combination scans are created, each showing how much you could save annually by choosing any one of these options.

For each combination including the payment option and saving plan term, we have an analysis model which includes a simulator for each savings plan.

To use the savings simulator:

This model is based on the historical behavior of your environment. In this scan, Finout assigns a dollar value to CPU and Memory usage based on the associated costs of the pods.

To propose recommended and new Memory and CPU requests, Finout offers a dynamic calculator. This tool enables the manual discovery of various CPU and Memory scenarios, based on the percentile CPU and Memory usage of the samples.

For instance, at the 100th percentile, recommendations are based on the maximum CPU and Memory usage within the selected period. At the 85th percentile, recommendations are based on the CPU and Memory levels where 85% of the samples met the criteria during the chosen period.

Finout provides two types of graphs to observe historical behavior:

To understand how Finout calculates K8s costs, please refer to the relevant documentation.

As Amazon encourages more people to transition to gp3, an advanced resource offering potential savings, Finout offers recommendations to users regarding the resources they should migrate from gp2 to gp3. By making this transition, users can potentially save a significant amount, denoted as "X."

Finout identifies underused RDS instances that can be downsized to a cost-effective alternative. The aim is to select the optimal instance for migration to maximize yearly savings, taking into account metrics like CPU usage and RDS connection count.

In this scan, Finout identifies underutilized instances that should not be shut down but rather moved to a more cost-effective alternative. The objective is to determine the most suitable instance to migrate to achieve the maximum potential savings on an annual basis.

During the VM rightsizing process, Finout analyzes VM CPU utilization data to suggest the most economical machine for optimal cost reduction. Within the calculations, CPU usage is constrained to a maximum of 80%. For predefined machines, we evaluate both standard and custom options. However, with custom machines, we specifically assess the custom configurations.

Still need help? Please feel free to reach out to our team at [email protected].