Installation options

To install and configure the self-hosted Instana backend, you have 2 installation options: a single-node or multi-node cluster setup and Kubernetes cluster setup

Option 1: Self-Hosted Standard Edition

Instana is deployed on a single-node or multi-node cluster, which needs lesser memory and infrastructure as compared to a Kubernetes cluster.

For more information, see Installing a Self-Hosted Standard Edition .

For a seamless and enhanced user experience, Self-Hosted Standard Edition is the recommended choice for deploying Instana self-hosted. Self-Hosted Standard Edition simplifies the deployment process with the stanctl tool, which automates cluster deployment, data store installation, component setup, updates, and other key functions, which reduces the complexity that is associated with Kubernetes cluster management.

You can deploy Self-Hosted Standard Edition in single-node or multi-node configuration. It supports multiple architectures, including Linux x86_64 and Linux arm64. Additionally, it allows full mirroring in air-gapped environments.

You can use it with or without internet connectivity, making it a versatile solution. By utilizing a lightweight, optimized Kubernetes distribution, Self-Hosted Standard Edition minimizes memory and infrastructure requirements, providing a more efficient alternative to traditional Kubernetes deployments.

Option 2: Self-Hosted Custom Edition (Kubernetes or Red Hat OpenShift Container Platform)

k8s-architecture

Custom Edition is the most scalable and flexible option, purpose-built for large, and complex workloads, where Instana is deployed on a Kubernetes cluster.

The benefits of Custom Edition include high scalability and flexibility, and high-availability options. Successful deployment and management of Custom Edition at scale requires an investment of resources and expertise.

Deploying and managing at scale requires a team with experience (or willing to develop it) in the deployment, maintenance and optimization of Kubernetes, and scalable data store administration and management.