4 results found
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Feature Suggestion: Cost Anomaly Detection for Dips
Currently, the Cost Anomaly feature is designed to capture spikes in spend but does not monitor for dips. Similarly, the Alerts feature works on defined thresholds, which is more suitable for catching increases than decreases.
It would be valuable to have a feature that can detect sudden drops in cost as well, since unexpected decreases can also indicate issues such as:
Disabled services or resources that should be running
Failures in data pipelines or workloads
Gaps in logging/monitoring or data ingestion
Sudden deletion in data
Adding anomaly detection for dips would provide a more complete view of cost changes and…
3 votesIn backlog pending PM Discovery
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Re-alerting for an active anomaly if the cost spikes by 2X or 3X
Today, once we notify for an anomaly, we do not notify again if an anomaly is active but the cost has spiked by X times, lets say twice. As a result, customer who ignored the anomaly in first place based on its cost missed the opportunity to react when the cost spike became more considerable.
6 votes -
Ability to detect anomaly on monthly cost granularity
If there is a gradual increase in cost on daly basis such increase will not be considered as an anomaly as the data would look like an expected increase however if we compare this cost over month to month the increase can be significant. Hence it is worth generating anomalies on such cost spikes on Monthly granularity.
2 votesIn backlog, pending PM Discovery
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Expand Real-time anomaly detection for additional AWS Services such as ECS
Expand DoiT’s real-time anomaly detection capabilities to cover additional AWS services, such as Amazon ECS.
Use Case:
In the event of a container being compromised—whether due to a security breach or a misconfiguration—the resulting spike in resource consumption can quickly lead to unexpected charges, potentially costing hundreds or even thousands of dollars before the issue is detected.By leveraging real-time anomaly detection, these incidents can be identified proactively using your usage logs, often before they appear in standard cloud billing or usage reports, which typically have a delay of 24 to 48 hours. This early detection helps minimize financial impact…
1 vote
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