is a simple way to manage Docker containers on multiple hosts. It will work on x86 or ARM CPU architectures that can run Docker and Node.js. PiCluster 2.3 will be out soon and I wanted to share the exciting new Elasticsearch integration currently in the . Traditionally, PiCluster had the ability to store its log output in Elasticsearch. Starting in PiCluster 2.3, node metrics such as disk, cpu, and memory utilization is stored also. With this ability, users can easily view their host metrics over time.
Requirements
- PiCluster
- Elasticsearch 6+
- Kibana 6+
Requirements
If you want to quickly spin up an Elasticsearch cluster with Kibana in Docker, .
PiCluster Configuration
PiCluster needs to be configured for Elasticsearch so it knows where to send data. All you need to do is add the following config option in config.json
that points to your Elasticsearch endpoint and restart the PiCluster server process:
"elasticsearch": "http://my-es-endpoint:9200"
Kibana Configuration
Starting in PiCluster 2.3, there are pre-set graphs available for viewing host metrics (cpu, memory, and disk).
Creating the Index Pattern
- Click on Management ->
Index Patterns
. - Click
Create Index
. - Under
Index Pattern
, typepicluster-monitoring
- Click
Next Step
- Under
Time Filter field name
, choosedate
. - Click
Create
. - Repeat steps 1-6 for the
picluster-logging
Index Pattern.
Importing the Graphs
To import the PiCluster Monitoring graphs in Kibana:
- Click on Management ->
Saved Objects
. - Click
import
. - Navigate to the PiCluster Git directory and choose
kibana-graphs.json
- Click
open
.
Viewing the Graphs
- Click on
Visualize
. - Choose CPU, Disk, or Memory.
Viewing the PiCluster Logs
1. Click on Discover
.
2. Change the index to picluster-logging
Feel like trying it out? Check out our branch to start playing with it now or wait for it to hit our branch! To learn more about how PiCluster works, Check out our page.