![]() Splunk docker allows user to easily switch between different versions of Splunk by simply updating the image tag and re-upping the container, allowing users to test for regression and experiment with new features ahead of your production cluster(s) getting updated.įorwarder deployment can be tricky, especially when you are trying to manage extra dependencies like python or other tools not found on the system by default, or in the universal forwarder binaries directory. You can perform restarts and potentially destructive commands without worrying about impacting other users on the system, and you are able to work through disaster scenarios and failovers safely outside of production. You are able to have your own ecosystem for testing and tinkering with data on your laptop. You are able to use containers for Forwarders, dev environments, and even deploy Splunk in Kubernetes through the use of Splunk Operator for Kubernetes.īeing able to spin up any kind of Splunk environment in a quick and repeatable way through automation is a major enabler for Splunkers. ![]() The combination of the lower resource cost of containers and the automation capabilities of Splunk-Ansible enable the creation of entire Splunk environments in mere minutes. The automation capabilities are fueled by Splunk-Ansible, which makes it a breeze to spin up all kinds of architectures. There is a repository on their Github for maintaining docker images here: docker-splunk. Splunk has been supporting the container model of virtualization for some time now. While VMs are essentially their own complete computer on a hypervisor, only sharing resources like storage and compute, containers tend to focus on a singular application or process with guest OS and shared kernel. Containers are an alternate approach to virtualization, opposed to virtual machines (VMs). Together, let’s take a look at the power of Splunk in Docker (and containerization in general) to allow you to quickly and repeatably create a Splunk environment that has the correct architecture, the apps you need, and the conf files you need to mimic any kind of production Splunk use case.ĭocker is a daemon used to create and manage containers. Have you ever been hindered when making improvements to your Splunk apps and dashboards because you can’t “tinker” in prod? Using Splunk in Docker containers can help you circumvent that issue by creating a prod-like environment right from the comfort of your own laptop.
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