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See AWS Costs for Each Resource

Hacker News

See AWS Costs for Each Resource

Link: https://www.vantage.sh/features/per-resource-costs Hi HN, I'm Co-Founder and CEO of Vantage and we just made "Per-Resource Costs" available to everyone, including users in our free tier. Vantage will now show you the cost of each individual AWS resource (EC2 instance, RDS instance, S3 Bucket, SNS Topic, Lambda Function, etc). You can drill down into each resource to see subcategory costs so imagine seeing specific egress costs being tied to a specific Cloudfront distribution or EC2 instance. This works by Vantage ingesting and processing Cost and Usage Reports from AWS where we process and structure this data on a per-resource basis. It is updated as often as AWS updates billing information which is typically 2-3 times per day. Unlike AWS, this isn't contingent upon you enabling cost allocation tags. We can show the costs for each resource independent from tagging. We use read-only cross account IAM roles for security best practices. We hear that customers are constantly confused over what is driving their AWS costs and we're trying to simplify that problem down. To give it a shot, sign up for free here https://console.vantage.sh/signup

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Hacker NewsStrong engagement from HN community · Strong signals: io, including · Missing: https docs, excited, just released
61%61% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
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58%58% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
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54%54% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
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37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.
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36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
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15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
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1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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