Adapt to growing data needs using containerized Splunk with HPE Alletra Storage

[StorageExperts]

Discover how containerized Splunk using HPE Alletra Storage can respond quickly to changing conditions and data needs for faster time to insights and increased agility.

–By Denise Ochoa Mendoza, Storage Solutions Engineer, HPE

Analyzing data is like raising a child. To raise a child one must be flexible and able to respond quickly to changing needs. When the child is a baby, they consume your sleep schedule. As they grow, their needs change. You trade in the sleepless nights for feedings to weekends for sports activities. The ability to adapt to their needs, while still providing the resources they need for healthy growth is a constant concern. In a similar way, data analyst have to constantly balance resources and be able to respond quickly to changing conditions and needs. Once you start acquiring data to explore you need the proper controls and balance of resources to efficiently explore the data and gain data insights.

Machine-generated data is information created automatically by mechanisms without human interaction. It’s vast and complex to explore. Some types of machine-generated data include exif data, website log files, events processing and business process management system logs, telecom and network data, databases, operating systems, and sensor and IoT devices.

Adding high-performance storage to Splunk

Splunk is a tool that enables you to be able to explore your machine generated data and turn it into actionable insights. However, depending on the workload, you might need more storage or compute. Organizations that are quickest to adapt to demands of their workloads reap the benefits. They are the fastest to understand their customer behavior and improve customer experience, detect threats, and predict maintenance cycles. So when configuring Splunk infrastructure, you want adaptability to workloads. This adaptability – and control – can be provided by using containerized Splunk.

You can easily create and manage containerized clustered deployments of Splunk by leveraging Kubernetes and the high-performance storage solution HPE Alletra Storage provides via the HPE CSI Driver. This gives you the flexibility to expand your initial Splunk footprint according to your workload needs, ensuring your organization can store and analyze data without worrying about resource constraints. With a quick and reliable deployment process, you’ll realize faster time to insights and increased agility. With Kubernetes and HPE Alletra Storage, you control the storage and compute and efficiently utilize resources.

The defacto standard of Kubernetes deployments: Red Hat OpenShift Container Platform, HPE Alletra Storage, and the HPE CSI Driver

Showing a sample lifecycle of analyzing data demonstrates how easy it is to create and manage containerized clustered Splunk deployments. The video demo below begins with a clustered Splunk deployment, then shows how to ingest sample application logs. As more data is ingested – and to accommodate demand – you’ll see how to scale the Splunk deployment to increase the number of Splunk indexers that store data. You’ll then explore the ingested data and can see site views counts from the logs. Finally, you’ll be able to visualize the data in a column chart. Watch the demo now:

The benefits add up

This solution shows a sample lifecycle of analyzing data but it can be extrapolated to many use cases. For instance, you can use it to have a singular plane of glass management for monitoring all of an organizations Kubernetes instances. Overall, together with HPE Alletra Storage, containerized Splunk offers many benefits, including improved efficiency, reliability, and scalability. This makes it a valuable tool for a wide range of use cases – from DevOps to security and data analysis.

To learn more, check out more blogs on this topic:

• HPE GreenLake for File Storage: Storage for Splunk’s cold tier that’s fast and simple
• HPE makes it easy to deploy Splunk in containers with HPE Alletra and Red Hat OpenShift

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  Meet Storage Experts blogger Denise Ochoa Mendoza, Storage Solutions Engineer, HPE

  Denise is on the worldwide storage solutions team at HPE. She is passionate about technology and her current focus on Big Data and analytics.

Storage Experts
Hewlett Packard Enterprise

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