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Splunk is pleased to announce the general availability of Ingest Processor, a Splunk-hosted offering within Splunk Cloud Platform designed to help customers achieve greater efficiencies in data transformation and improved visibility into data in motion.
Latest Articles
Splunk Cloud DIY: Even More Self-Service Options to Manage Your Cloud Environment
Splunk Cloud has been rapidly evolving to deliver richer capabilities and meet your unique business needs, including easier-to-use self-service capabilities
Custom Anomaly Detection with Splunk IT Service Intelligence and Machine Learning Toolkit v3.2 - Part 1
Part 1 of a two-part series providing a detailed and technical walkthrough around customizing a custom Splunk ITSI Machine Learning workflow
Custom Anomaly Detection with Splunk IT Service Intelligence and Machine Learning Toolkit v3.2 - Part 2
Part 2 of a two-part series providing a detailed and technical walkthrough around customizing a custom Splunk ITSI Machine Learning workflow
Unleashing Data Ingestion from Apache Kafka
Splunk Connect for Kafka introduces a scalable approach to tap into the growing volume of data flowing into Apache Kafka
Dynamic Data: Self-Storage - Compliance, Cloud and Data Lifecycle
Introducing Dynamic Data: Self-Storage, a new feature in Splunk Cloud that puts data storage in your control
Pivotal Cloud Foundry Health Monitoring
Operational and Application level monitoring of your Pivotal Cloud Foundry environment
Cyclical Statistical Forecasts and Anomalies - Part 3
The final of a three-part series on the basics of statistical anomalies and forecasting in Splunk to create brilliant alerts for single values moving through time
Cyclical Statistical Forecasts and Anomalies - Part 2
Get brilliant alerts over big data using some Splunk goodness such as summary indexes or data model accelerations to operate forecasts at greater scale
Cyclical Statistical Forecasts and Anomalies - Part 1
Using the Machine Learning Toolkit to build a basic forecasting, thresholding, and alerting mechanism to apply to nearly any type of time series metric
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