GEL hardware requirements

This page outlines the current hardware requirements for running Grafana Enterprise Logs (GEL). Grafana Labs reserves the right to mark a support issue as ‘unresolvable’ if these requirements are not followed. See the Grafana Labs Enterprise Support SLA for more details.

CPU and memory

GEL should be deployed on machines with a 1:4 ratio of CPU to memory, so for every CPU core there should be 4 gigabytes of memory. For most clusters, Grafana Labs recommends deploying GEL onto machines with 16 CPU cores and 64 gigabytes of memory. All the nodes in the cluster should be of the same type. This is a good mix of CPU to memory for the type of workloads that GEL usually performs.

Disk

Various components of GEL (ingester, alertmanager) require fast, persistent disk resources to be available to the host machine. For example, in the case of the ingester and ruler components, all incoming data is sent to a write-ahead log (WAL) to help withstand unexpected node termination. The following are supported configurations for several cloud providers as well as guidance for custom hardware:

Amazon Web Services (AWS)

GEL is tested to run with io1 Provisioned IOPS SSD EBS volumes to ensure adequate performance to run the system correctly. The io1 storage must be provisioned at 50 IOPS per gigabyte, with a minimum of 150Gi allocated to ensure performant I/O.

Google Cloud Platform (GCP)

GEL is tested to run with pd-ssd SSD persistent disks to ensure adequate performance to run the system correctly.

Microsoft Azure

GEL is tested to run with Premium SSD SSD persistent disks to ensure adequate performance to run the system correctly.

Custom cluster hardware

GEL requires fast disks to run. Build your cluster with fast, locally attached SSD-based disks.

Network

All components of GEL require fast network access. Nodes on which the software runs should be connected by 10 gigabit/second or faster network connection speed.

Object storage

Various GEL components require object storage for config storage as well as long-term data storage.

Amazon Web Services (AWS)

GEL is tested to run with AWS’s S3 object storage service using the Standard storage class.

Google Cloud Platform (GCP)

GEL is tested to run with GCP’s GCS object storage service using the STANDARD storage class in both regional and dual regional storage locations.

Microsoft Azure

GEL is tested to run Azure’s Blob Storage object storage service using the Standard storage class with replication type LRS.

Unmanaged object storage

GEL generally works with object storage installations which support the popular AWS S3 API. However, vendors have various performance characteristics for each solution and installation, so performance testing with your individual solution will be necessary to determine if the performance profile will work for your use case. Slower storage backed by hard disks might be acceptable for less intensive workloads, but more intensive workloads will likely require more performant object storage solutions backed by SSDs.