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Case Study

Augtera Application Cloud Synthetics Case Study
Posted on Wednesday, June 21st, 2023 by George K

Augtera Networks provided a major retailer with early detection and clear identification of the root cause of an application performance degradation due to a software upgrade

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A Global MSP Augments their Enterprise SD-WAN Service with Augtera Network AI to Solve Application Performance Challenge
Posted on Wednesday, February 1st, 2023 by George K

Augtera networks enabled an MSP to improve their competitive positioning and the user experience of their customers by detecting circuit performance issues, without telemetry from the circuit provider.

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An Innovative Global 500 Enterprise Leverages Augtera Network AI to Detect SD-WAN Network Brownouts Before Failure
Posted on Saturday, January 7th, 2023 by Mark Seery

Early detection of SD-WAN connectivity issues, using machine learning, enabling pro-active operations.

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Detect SD-WAN Network Brownouts before Failure
Posted on Friday, October 7th, 2022 by Mark Seery

Thanks to machine learning, it is now possible to detect when the stability of the network is compromised, thus providing actionable insights for proactive operations.

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Proactive Detection of Environmental Degradation
Posted on by Mark Seery

Proactive notification from Augtera enabled the operator to prevent an outage by getting ahead of the cooling issue before it adversely impacted service.

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AWS Outage Detected 30 Mins Prior to AWS Notice
Posted on by Mark Seery

The AWS outages were detected 30 minutes prior to AWS providing notice due to next generation AI/ML techniques used in the Augtera Network AIOps platform.

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Fortune 500 Data Center Solution
Posted on Thursday, October 6th, 2022 by Mark Seery

By implementing the Augtera Network AI platform, this Fortune 500 Enterprise has reduced MTTD by 90%+, MTTM by 50%+, MTTR by 40%+, and increased the time between incidents by a factor of 4. This is only achievable by transforming operations from being manual, reactive, and noisy to automated, proactive, and relevant.

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