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Usage.ai is an automated cloud cost optimization platform designed to help companies reduce infrastructure spending across AWS environments. The platform focuses on optimizing commitment-based pricing such as AWS Savings Plans and Reserved Instances.
Instead of manually forecasting infrastructure usage and purchasing commitments, Usage.ai continuously analyzes real-time cloud consumption and automatically manages commitments to maximize savings while minimizing the risk of unused capacity.
Engineering and FinOps teams use Usage.ai to improve their effective savings rate, reduce manual cloud cost management work, and gain better visibility into infrastructure efficiency.
By automating commitment purchasing and optimization, Usage.ai helps organizations achieve predictable cloud savings while allowing engineering teams to focus on building products instead of managing cloud pricing complexity.
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Usage AI's answer:
Usage.ai automates cloud commitment management with AI, continuously optimizes savings across AWS, Azure, and GCP, and protects customers with Insured Commitments that reduce the risk of underutilized commitments.
Usage AI's answer:
Usage.ai doesn't just recommend savings - it automatically purchases, manages, and optimizes cloud commitments, backed by Insured Commitments that reduce financial risk and maximize long-term savings.
Usage AI's answer:
Usage.ai is built for DevOps, FinOps, Cloud Architects, Engineering leaders, and IT decision-makers who want to reduce cloud costs across AWS, Azure, and GCP without manual commitment management.
Usage AI's answer:
Usage.ai was founded in 2020 after its founder saw companies either overpaying for cloud infrastructure or avoiding long-term cloud commitments because of the financial risk. The company set out to make cloud savings automatic, risk-free, and easy, helping businesses save without code changes or lock-in.
Usage AI's answer:
Primary technologies used by Usage.ai:
Based on our record, Prometheus seems to be a lot more popular than Usage AI. While we know about 300 links to Prometheus, we've tracked only 3 mentions of Usage AI. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Prometheus scrapes metrics from the stack. Node exporter covers the host, cAdvisor covers containers, and individual services expose their own endpoints where supported. The main value isn't dashboards (though those exist) - it's having a queryable record of system state over time, and a place to hook alerts when something drifts. - Source: dev.to / 18 days ago
Prometheus is the industry-standard time-series database for infrastructure metrics. Paired with Grafana for visualization and Alertmanager for routing, it forms the backbone of monitoring at companies from startups to Netflix-scale deployments. This isn't a single tool โ it's an ecosystem. - Source: dev.to / 26 days ago
To monitor and analyze rate limiting metrics, we're using a combination of Redis and Prometheus. We're storing rate limiting metrics in Redis and then using Prometheus to scrape the metrics and display them in a dashboard. Here's an example of how we're storing rate limiting metrics in Redis:. - Source: dev.to / about 1 month ago
In this post, we compare two forecasting models, Chronos (ChronosโBolt) and Toto, on telemetry from Prometheus and OpenSearch. We judge them with two easy metrics: MASE for point accuracy and CRPS for the quality of uncertainty. - Source: dev.to / about 1 month ago
For monitoring infrastructure, Prometheus and Grafana are widely used for pipeline metrics collection and alerting. For orchestration that includes built-in run observability, Apache Airflow tracks run history, task durations, and failure states in a web UI. Python with SQLAlchemy is the standard stack for custom pipeline implementation with relational state management. - Source: dev.to / 2 months ago
Thanks for sharing your project! Cloud costs have gotten ridiculously out of control (an Andreessen Horowitz report estimates that the excess cost of public cloud is $500 billion per year [1]) and it's great to see more projects tackling this problem. I'm curious to see if you plan on implementing automation, or if the tool is focused on recommendations? We've built a tool at Usage.AI that automatically buys and... - Source: Hacker News / about 4 years ago
+1 on WalterGR's question. Google Cloud recently hiked prices (again), doubling prices for some of its services [1], though Amazon has a better track record of keeping prices steady (or even reducing them) [2]. There are also newer innovations that aren't discussed in that comparison, like Google's Commited Use Discounts and Azure Reserved VM Instances (their answers to Amazon's Reserved Instances). If you're... - Source: Hacker News / about 4 years ago
FYI, you didn't provide a clear link or anything. Just the privacy policy in footer. Looks like it is this: https://usage.ai. - Source: Hacker News / about 4 years ago
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