The Challenge
Manual Detection, Alerts and Troubleshooting Processes

Relying on traditional observability tools to detect, alert on, and troubleshoot issues presents several shortcomings, including:

  • Slow Time to Identify: Massive data volumes must be centralized and analyzed before alerts are triggered.
  • Manual Detection: Teams manually created monitors and alerts. These are time-consuming and make it impossible to catch every issue.
  • Manual Troubleshooting Processes: When an alert fires, engineers must manually sift through logs to determine the root cause of the issue.

In addition to these shortcomings, teams frequently experience alert fatigue, leading to missed alerts or delayed responses.

The Solution
Automated Detection and Troubleshooting Insights

Edge Delta can help you optimize MTTI by alerting on issues faster and with greater accuracy. In addition, the platform provides insights to help you streamline your troubleshooting processes.

  • Automatically Detect Every Anomaly

    Edge Delta automatically monitors your datasets for anomalous behaviors, so you can detect issues – whether you’ve built logic to detect them or not.

  • Increase Alert Speed and Accuracy

    Trigger alerts at the infrastructure level to dramatically improve MTTI. Alerts fire when behavior meets Edge Delta’s confidence threshold, reducing noise and alert fatigue.

  • Simplify Troubleshooting Processes

    When an alert fires, Edge Delta surfaces the relevant data, affected components, and other contextual information to make troubleshooting easy.

Detect Known and Unknown Issues

Edge Delta automatically detects anomalous behavior in your log data by:

  • Converting logs to metrics, baselining the KPIs, and notifying teams on irregular behavior
  • Detecting spikes in unusual ERROR, FAIL, or other negative sentiment logs
  • Assigning confidence of an anomaly against predefined thresholds to ensure accuracy

Speed Up Root-Cause Analysis

Edge Delta saves you time when troubleshooting issues by:

  • Surfacing the data that caused a given alert
  • Helping you understand the volume and sentiment of the messages created
  • Identifying the affected systems or components

Super League Gaming reduces troubleshooting times by 6x

The esports platform started using Edge Delta so their developers could access larger datasets and save time troubleshooting issues.

Read the full case study

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