https://github.com/converged-computing/check-aws-costs
Simple script to generate single interface of daily costs for inspection
https://github.com/converged-computing/check-aws-costs
Last synced: 5 months ago
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Simple script to generate single interface of daily costs for inspection
- Host: GitHub
- URL: https://github.com/converged-computing/check-aws-costs
- Owner: converged-computing
- License: mit
- Created: 2023-09-11T18:26:49.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2023-09-11T22:33:42.000Z (almost 3 years ago)
- Last Synced: 2025-09-10T05:37:02.436Z (9 months ago)
- Language: Python
- Size: 10.7 KB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# AWS Cost Check
We need an automated means to check for cases that can lead to bad times with billing.
- Instances left on (and forgotten)
- Storage / Volumes attached to off-instances
Likely the way we monitor these will depend on the project. For example, a project that regularly runs long analyses would not want an alert for an instance up a day. Much of the analysis would come down to looking for either patterns or outliers. Since outliers require some kind of model and historical data, I'm going to (at first) go for more of a logical approach - identifying the patterns to be concerned about, and then assessing:
- total lump sums of things
- big rates of change between timepoints
- going above some threshold
I want to start by reading about some of these patterns and taking notes, and asking:
1. What is the pattern?
2. What are we looking for?
A third idea I'm also thinking is that it might be easy enough to just plot everything we have, over time, and send an email (or similar) to a human to look at it. I might just start with this because it's simple and easy.
## Usage
```bash
pip install -r requirements.txt
# See what you can customize
python check-aws-costs.py --help
# Run the default, looking at DAILY (granularity) AmortizedCost (metric) SERVICE (dimension) for 90 days over 4 regions (us-east-1/2 and us-west-1/2).
python check-aws-costs.py
```
```console
Querying for daily cost by service for us-east-1
Querying for daily cost by service for us-east-2
Querying for daily cost by service for us-west-1
Querying for daily cost by service for us-west-2
Saving raw results to cache/spending-2023-09-11.json
Saving raw results to cache/spending-latest.json
Adding us-east-1 to the data frame...
Adding us-east-2 to the data frame...
Adding us-west-1 to the data frame...
Adding us-west-2 to the data frame...
Saving formatted results to cache/spending-2023-09-11.csv
Saving formatted results to cache/spending-latest.csv
```
This generates the files mentioned above.
Note that we save based on the day, but also "latest" to make it easy to find the latest
to plot. Hey, if "latest" works poorly for container tags it can work here too! How to plot?
```bash
python plot-aws-costs.py
```
This will generate a pdf in your present working directory. We don't generate plots if the total is under $5.
```console
Skipping amazon-simple-notification-service, total across regions is < $5
Skipping amazon-simple-queue-service, total across regions is < $5
Skipping amazon-simple-storage-service, total across regions is < $5
Skipping amazoncloudwatch, total across regions is < $5
Skipping amazon-elastic-container-service-for-kubernetes, total across regions is < $5
Skipping amazon-ec2-container-registry-(ecr), total across regions is < $5
Skipping amazon-route-53, total across regions is < $5
Skipping amazon-virtual-private-cloud, total across regions is < $5
Skipping aws-systems-manager, total across regions is < $5
Skipping amazon-elastic-container-registry-public, total across regions is < $5
Skipping aws-lambda, total across regions is < $5
Skipping tax, total across regions is < $5
Skipping aws-cost-explorer, total across regions is < $5
```
The data is fairly generic and we could have other output types/formats too.
## References
- [AWS Cost-Saving Gotchas](https://medium.com/@matt_weingarten/aws-cost-saving-gotchas-f0f883c34c69)