Data downtime—when your organization loses or disrupts connection to its data—is costly and vexing, often caused by bugs, misconfigurations, schema changes, or traffic spikes during data ingestion. Traditional reactive approaches delay resolution. Splunk’s Machine Learning Toolkit (MLTK) enables proactive prevention by applying anomaly detection to monitor data pipelines in real time. This involves generating predictive models, detecting anomalies between expected and actual data volumes, and setting alerts, allowing teams to address issues before downtime occurs and ensuring data reliability.

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