cloud-custodian
cfn_nag
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cloud-custodian | cfn_nag | |
---|---|---|
32 | 14 | |
5,180 | 1,218 | |
1.4% | 0.4% | |
9.5 | 0.0 | |
5 days ago | 7 months ago | |
Python | Ruby | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
cloud-custodian
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Cutting down AWS cost by $150k per year simply by shutting things off
> The best optimization is simply shutting things off
This is the way.
A similar idea has been bouncing around in my mind for a while now. An ideal, turnkey system would do the following:
- Execute via Lambda (serverless).
- Support automated startup and shutdown of various AWS resources on a schedule influenced by specially formatted tags.
- Enable resources to be brought back up out of schedule when demand dictates.
- Operate as a TCP/HTTP proxy that can delay clients so that a given service can be started when it is dormant or, even better, the service isn't serverless but you want it to be. This can't work for everything, but perhaps enough things such that the need to run always on services is reduced.
Cloud Custodian [1] can purportedly do some of this, but I've been reluctant to learn yet another YAML-based DSL to use it.
So this is my "make things designed to be always-on serverless instead" project and the work AWS has done to make Java apps function on Lambda keeps me thinking about the potential to take things that 1) have a relatively long startup time and 2) are designed to be long running service loops, and find a way to force them into the serverless execution model.
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Optimizing cost on an app which is not used 24/7
Use a tool like this https://cloudcustodian.io/ to manage instance on/off hours or go fargate.
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EC2 start and stop via Lambda
I'd use a combination of Cloudcustodian for start/stop scheduling and Apprise for notifications.
- Enforce tagging on everything that can be tagged
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cloud-custodian VS cloudquery - a user suggested alternative
2 projects | 2 Feb 2022
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Common avenues for reducing waste in AWS (Specifically EC2)
You can try Cloudcustodian. Very good tool to help you make a list of all underutilized instances. This also helps you do a lot more than that. https://cloudcustodian.io/
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Favorite Resources of 2021
Cloud Custodian; rules engine for cloud security, cost optimization, and governance, DSL in yaml for policies to query, filter, and take actions on resources
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I added AWS CIS 1.2 compliance checks to GraphQL API for AWS!
Another alternative that I personally would use is CloudCustodian. It is a widely used tool for continuous cloud governance, detection and remediation. There is a CIS pack for it.
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Implementing Cloud Governance as a Code using Cloud Custodian
Note: Cloud Custodian kubernetes resources still work in progress. We can check the status of the plugin here.
cfn_nag
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Setting up my own landing zone on AWS
.pre-commit-config.yaml – contains the cfn-lint and cfn_nag pre-commit hooks.
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Guide to Serverless & Lambda Testing — Part 2 — Testing Pyramid
For generic CloudFormation templates, check CFN-NAG.
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AWS Serverless Production Readiness Checklist
If you use CDK, you should implement CDK nag; otherwise, use cfn-nag.
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Make your life easier using Makefiles
cfn_nag
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Creating a Multi-Account CI/CD Pipeline with AWS CodePipeline
CodeBuild will run a linting check against the CloudFormation Template using cfn-lint and will then run cfn-nag to check for patterns that indicate insecure resources within the CloudFormation template.
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App with self-contained infrastructure on AWS
Security checks for the Cloudformation stack using cfn-nag
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Mastering AWS CDK Aspects
cdk-nag contains several Aspects to check your applications for best practices. It is especially useful if you need to be HIPAA-compliant or have other compliance requirements. It is inspired by cfn_nag which is a a tool checking for patterns in your CloudFormation templates.
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how did you get good at iac-cloudformation
cfn-lint and cfn_nag or other tools of that nature to check as you write so you don't need to continually try to deploy only to find that you've done something dumb.
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Source Control your AWS CloudFormation templates with GitHub
There is another tool called cfn_nag that can check your code for potentially any insecure infrastructure. When you read the documentation around this tool, the author says it can check for things such as:
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Static Analysis for Cloud Formation
cfn-nag: Verify that there is no code that poses a security risk.
What are some alternatives?
checkov - Prevent cloud misconfigurations and find vulnerabilities during build-time in infrastructure as code, container images and open source packages with Checkov by Bridgecrew.
terraform - Terraform enables you to safely and predictably create, change, and improve infrastructure. It is a source-available tool that codifies APIs into declarative configuration files that can be shared amongst team members, treated as code, edited, reviewed, and versioned.
cfn-python-lint - CloudFormation Linter
ScoutSuite - Multi-Cloud Security Auditing Tool
gatekeeper - 🐊 Gatekeeper - Policy Controller for Kubernetes
steampipe - Zero-ETL, infinite possibilities. Live query APIs, code & more with SQL. No DB required.
fixinventory - Fix Inventory consolidates user, resource, and configuration data from your cloud environments into a unified, graph-based asset inventory.
cloudquery - The open source high performance data integration platform built for developers.
SonarQube - Continuous Inspection
cloud-guardrails - Rapidly apply hundreds of security controls in Azure
aws-secure-environment-accelerator - The AWS Secure Environment Accelerator is a tool designed to help deploy and operate secure multi-account, multi-region AWS environments on an ongoing basis. The power of the solution is the configuration file which enables the completely automated deployment of customizable architectures within AWS without changing a single line of code.