🧰 How it Works
Cheapest, most Secure, and Greenest cloud asset is the one that doesn’t exist.
The foundation of our unutilized resource detection algorithm lies in analyzing CloudWatch metrics, and last activity data
🗯 Integrate with tools you already use
Our reports are delivered directly to your team’s preferred communication channels:
- Microsoft Teams
Save up to 15% on AWS
🔄 Scan, Turn off, Save Money, Repeat
We offer a powerful solution for waste detection on AWS. Our product supports multiple AWS services, including EC2, RDS, CloudWatch, Snapshots, IAM, Glue, Redshift, SageMaker, EBS, and Elastic IPs.
With unusd.cloud, you can easily identify and eliminate any unused resources, saving you time and money on your AWS bill and reducing your attack surface.
What our Client says
Previously, we had been caught off guard by unexpected high AWS bills caused by forgotten dev resources that had been left running.
Thanks to unusd.cloud, we now receive notifications when an RDS database or other serverful dev resource has been left on, giving us peace of mind that our bills are being monitored and helping us make more cost-effective decisions
At Formance (YC S21), our engineering team is always pushing the boundaries of innovation which leads to accumulation of unused assets over time. Due to this, we often forget to turn them off or delete them.
To tackle this issue, we use unusd.cloud, which helps us keep track of our AWS assets and sends us a reminder via Slack before the end of the month invoice, thus reducing our AWS bills and lowering our attack surface.
Our primary focus at Mangrove.ai is to develop Machine Learning models using an optimized Data-ML architecture. Our data science teams heavily depend on SageMaker Notebooks and Redshift Clusters for their daily tasks.
Over time, we accumulated hundreds of unused notebooks and multiple Redshift clusters in our development, sandbox, and training AWS accounts, resulting in wasted OPEX budget.
With unusd.cloud, we can now easily track and reclaim these unused assets and share this information with our data science teams via Microsoft Teams integration or a simple daily email.