SignalFx Cuts Down Noise for Cloud Operations

SignalFx, a provider of monitoring and operational intelligence solutions for the cloud, has announced the general availability of its latest release featuring new alerting capabilities that enable cloud operations teams to better monitor and manage cloud infrastructure, containers, and applications.

Determining the best alert conditions in cloud environments, and the impact new alert conditions will have on the operations team, is a complex process. SignalFx aims to remove the complexity and maximize the productivity of the cloud operations team with tools that expedite the creation, deployment and tuning of alerts using machine learning algorithms that adapt to changing environmental conditions.

Now cloud operations professionals can preview the alert conditions on historical data, leverage prebuilt advanced alert conditions for cloud applications such as anomaly and outlier detection, and quickly build custom alerts through the SignalFx API and alert condition library.

Key features of the updated release are the ability to test and preview the results of alert conditions on historical data, allowing users to see the frequency and efficacy of alerts before applying them to live, real-time data streams, removing the cost and confusion of unnecessarily firing alerts.

SignalFx also includes pre-built alert conditions specifically designed for cloud operations, including outlier detection, sudden changes, historical anomaly, and a custom alert function library.

 The new alerting features are built on SignalFx’s streaming analytics technology for time-series metrics. The software applies analytics and evaluates alert conditions against data as it arrives in real time, enabling SignalFx to build sophisticated alert conditions that detect and fire rapidly on a condition being met across populations of thousands of instances. 

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