![]() ![]() Please collect the IP address of the raspberry pi so that we can login to it. Now you are ready to start off with the configuration. Launch Raspberry Pi Configuration from the Preferences menu.This will allow us to heedlessly run the system and access it remotely over the network. Let me know in the comments if find any useful ones.Once you are done with the setup, make sure you enable SSH access on the raspberry pi. ![]() ![]() There are quite a few other metrics available from node-exporter and cAdvisor I could have used. If you want something similar then you can copy my dashboard json. This is what my Grafana dashboard looks like. static_configs : - targets : Dashboard Set Up # metrics_path defaults to '/metrics' # scheme defaults to 'http'. job_name : 'prometheus' # Override the global default and scrape targets from this job every 5 seconds. ![]() scrape_configs : # The job name is added as a label `job=` to any timeseries scraped from this config. rule_files : # - "les" # - "les" # - "les" # A scrape configuration containing exactly one endpoint to scrape: # Here it's Prometheus itself. external_labels : monitor : 'my-project' # Load and evaluate rules in this file every 'evaluation_interval' seconds. # Attach these labels to any time series or alerts when communicating with # external systems (federation, remote storage, Alertmanager). # scrape_timeout is set to the global default (10s). evaluation_interval : 120s # By default, scrape targets every 15 seconds. If you are running locally you could use localhost and # my global config global : scrape_interval : 120s # By default, scrape targets every 15 seconds. You only need to change the following environment variables to match the domain for your Raspberry Pi. Labels : - 'traefik.enable=true' - '.rule=PathPrefix(`/grafana`)' - '.=3000' - '=Authorization:-' networks : - pi data/grafana :/var/lib/grafanaĮnvironment : - GF_USERS_ALLOW_SIGN_UP=false Grafana : image : grafana/grafana :latest Privileged : true restart : unless -stopped Node-exporter : image : prom/node -exporter :latestĬontainer_name : monitoring_node_exporterĬadvisor : image : braingamer/cadvisor -arm :latest data/prometheus/config :/etc/prometheus/Ĭommand : - '-config.file=/etc/prometheus/prometheus.yml' - '=/prometheus' expose : - 9090 links : - cadvisor :cadvisor Version : '3.4' services : prometheus : image : prom/prometheus :latest Traefik - I use this as my reverse proxy if you don’t have a reverse proxy set up you can follow my previous post, Traefik vs Nginx for Reverse Proxy with Docker on a Raspberry Pi.Node Exporter - Prometheus exporter for hardware and OS metrics.cAdvisor - A container monitor from Google to monitor the resources used by containers.Prometheus - for gathering the data in a time series.There are probably quite a few services that work with Grafana for monitoring. Container data - I want to know which containers are causing high CPU and Memory usage.Hard Disk Space - I have a 32GB SD card in my Pi but I have had one fill up before which makes the whole thing unresponsive.Memory - With only 1GB of memory I need to keep an eye on how much I run on it.CPU - If the CPU ends up running at 100% a lot of the time, I might need to scale down the services running on it.In my case I am interested in the following: With any monitoring, it is important to know what you want to keep an eye on. I use Grafana a lot at work and love it, so I thought it would be good to use it to monitor my Raspberry Pi. So I am a little worried sometimes that I am going to overload it with all the docker services I am running on it. I am currently using a Raspberry Pi 2 B which is a great device but only has 1GB of RAM and 900 MHz CPU. As you might have seen from my last few posts I have quite a lot running on my Raspberry Pi. ![]()
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