Hemant Seth's Blog Posts

Hemant is a Principal Product Manager at Splunk, leading the Kubernetes Monitoring offering within Splunk Observability Cloud. Prior to this role, he focused on Splunk Observability Platform administration, including identity management and license usage. Hemant brings over a decade of experience in the observability domain and holds a Master’s degree in Electrical Engineering with a specialization in Telecommunications.

Understanding The Causes of Negative Customer Experience
Observability
3 Minute Read

Understanding The Causes of Negative Customer Experience

Diving into data to discover the causes of a negative customer experience
Serving It Up with AWS and Splunk: AWS Serverless Application Repository Now Available
Tips & Tricks
4 Minute Read

Serving It Up with AWS and Splunk: AWS Serverless Application Repository Now Available

Splunker Nicolas Stone walks you through ingesting and visualizing live data from AWS into Splunk using serverless applications
Effectively-Once Semantics in Apache Pulsar
Observability
8 Minute Read

Effectively-Once Semantics in Apache Pulsar

"Exactly-once" is a controversial term in the messaging landscape. In this post we'll offer a detailed look at effectively-once delivery semantics in Apache Pulsar and how this is achieved without sacrificing performance.
Use Investigation Workbench to Reduce Time to Contain and Time to Remediate
Security
2 Minute Read

Use Investigation Workbench to Reduce Time to Contain and Time to Remediate

The latest version of Splunk Enterprise Security v 5.0 introduces Investigation Workbench, which streamlines investigations and accelerates incident response
Cyclical Statistical Forecasts and Anomalies - Part 2
Platform
6 Minute Read

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
Platform
9 Minute Read

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