Skip to main content

Testnet

AWS:

  • m5a.large or any equivalent instance type

Bare Metal:

  • 8GB RAM
  • 2 vCPUs
  • At least 300 GB of storage - make sure it's extendable

Same as for Mainnet, setting the node up via the install script is the recommended way here as well. The only difference is that you will need to run the install script as shown below:

./avalanchego-installer.sh --fuji --ip <your_public_ip_here> --rpc any

We will specify the --fuji flag here because Fuji is the name of the Avalanche Testnet.

Same sync check can be applied here as well. If the result is true, it means your node is fully synced.

The Avalanchego node exports both RPC and WS APIs on the same port: 9650

In order to test the WS endpoint, we will need to install a package called node-ws.

An example WS call would look like this:

wscat --connect ws://localhost:9650/ext/bc/C/ws
> {"id":1, "jsonrpc":"2.0", "method": "eth_blockNumber","params": []}

Monitoring Guidelines

In order to maintain a healthy node that passes the Integrity Protocol's checks, you should have a monitoring system in place. Blockchain nodes usually offer metrics regarding the node's behaviour and health - a popular way to offer these metrics is Prometheus-like metrics. The most popular monitoring stack, which is also open source, consists of:

  • Prometheus - scrapes and stores metrics as time series data (blockchain nodes cand send the metrics to it);
  • Grafana - allows querying, visualization and alerting based on metrics (can use Prometheus as a data source);
  • Alertmanager - handles alerting (can use Prometheus metrics as data for creating alerts);
  • Node Exporter - exposes hardware and kernel-related metrics (can send the metrics to Prometheus).

We will assume that Prometheus/Grafana/Alertmanager are already installed (we will provide a detailed guide of how to set up monitoring and alerting with the Prometheus + Grafana stack at a later time; for now, if you do not have the stack already installed, please follow this official basic guide here).

We recommend installing the Node Exporter utility since it offers valuable information regarding CPU, RAM & storage. This way, you will be able to monitor possible hardware bottlenecks, or to check if your node is underutilized - you could use these valuable insights to make decisions regarding scaling up/down the allocated hardware resources.

Below, you can find a script that installs Node Exporter as a systemd service.

#!/bin/bash

# set the latest version
VERSION=1.3.1

# download and untar the binary
wget https://github.com/prometheus/node_exporter/releases/download/v${VERSION}/node_exporter-${VERSION}.linux-amd64.tar.gz
tar xvf node_exporter-*.tar.gz
sudo cp ./node_exporter-${VERSION}.linux-amd64/node_exporter /usr/local/bin/

# create system user
sudo useradd --no-create-home --shell /usr/sbin/nologin node_exporter

# change ownership of node exporter binary
sudo chown node_exporter:node_exporter /usr/local/bin/node_exporter

# remove temporary files
rm -rf ./node_exporter*

# create systemd service file
cat > /etc/systemd/system/node_exporter.service <<EOF
[Unit]
Description=Node Exporter
Wants=network-online.target
After=network-online.target
[Service]
User=node_exporter
Group=node_exporter
Type=simple
ExecStart=/usr/local/bin/node_exporter
[Install]
WantedBy=multi-user.target
EOF

# enable the node exporter service and start it
sudo systemctl daemon-reload
sudo systemctl enable node_exporter.service
sudo systemctl start node_exporter.service

As a reminder, Node Exporter uses port 9100 by default, so be sure to expose this port to the machine which holds the Prometheus server. The same should be done for the metrics port(s) of the blockchain node (in this case, we should expose port 9650).

Having installed Node Exporter and having already exposed the node's metrics, these should be added as targets under the scrape_configs section in your Prometheus configuration file (i.e. /etc/prometheus/prometheus.yml), before reloading the new config (either by restarting or reloading the config - please check the official documentation). This should look similar to this:

scrape_configs:
- job_name: 'avalanche-node'
scrape_interval: 10s
metrics_path: /ext/metrics
static_configs:
- targets:
- '<NODE0_IP>:9650'
- '<NODE1_IP>:9650' # you can add any number of nodes as targets
- job_name: 'avalanche-node-exporter'
scrape_interval: 10s
metrics_path: /metrics
static_configs:
- targets:
- '<NODE0_IP>:9100'
- '<NODE1_IP>:9100' # you can add any number of nodes as targets

In the configuration file above, please replace:

  • <NODE0_IP> - node 0's IP
  • <NODE1_IP> - node 1's IP (you can add any number of nodes as targets)
  • ...
  • <NODEN_IP> - node N's IP (you can add any number of nodes as targets)

That being said, the most important metrics that should be checked are:

  • node_cpu_seconds_total - CPU metrics exposed by Node Exporter - for monitoring purposes, you could use the following expression:
    • 100 - (avg by (instance) (rate(node_cpu_seconds_total{job="avalanche-node-exporter",mode="idle"}[5m])) * 100), which means the average percentage of CPU usage over the last 5 minutes;
  • node_memory_MemTotal_bytes/node_memory_MemAvailable_bytes - RAM metrics exposed by Node Exporter - for monitoring purposes, you could use the following expression:
    • (node_memory_MemTotal_bytes{job="avalanche-node-exporter"} - node_memory_MemAvailable_bytes{job="avalanche-node-exporter"}) / 1073741824, which means the amount of RAM (in GB) used, excluding cache/buffers;
  • node_network_receive_bytes_total - network traffic metrics exposed by Node Exporter - for monitoring purposes, you could use the following expression:
    • rate(node_network_receive_bytes_total{job="avalanche-node-exporter"}[1m]), which means the average network traffic received, per second, over the last minute (in bytes);
  • node_filesystem_avail_bytes - FS metrics exposed by Node Exporter - for monitoring purposes, you could use the following expression:
    • node_filesystem_avail_bytes{job="avalanche-node-exporter",device="<DEVICE>"} / 1073741824, which means the filesystem space available to non-root users (in GB) for a certain device <DEVICE> (i.e. /dev/sda or wherever the blockchain data is stored) - this can be used to get an alert whenever the available space left is below a certain threshold (please be careful how you choose this threshold: if you have storage that can easily be increased - for example, EBS storage from AWS, you can set a lower threshold, but if you run your node on a bare metal machine which is not easily upgradable, you should set a higher threshold just to be sure you are able to find a solution before it fills up);
  • up - Prometheus automatically generated metrics - for monitoring purposes, you could use the following expression:
    • up{job="avalanche-node"}, which has 2 possible values: 1, if the node is up, or 0, if the node is down - this can be used to get an alert whenever the node goes down (i.e. it can be triggered at each restart of the node);
  • avalanche_C_last_accepted_height - this is a metric that can be used in order to check if the node is currently syncing with the network - for monitoring purposes, you could use the following expression:
    • avalanche_C_last_accepted_height{job="avalanche-node"}, which is going to show the latest block that has been received by the node on the C-Chain - this can be used to get an alert whenever the node is not syncing blocks anymore (i.e less than 5 blocks in the past 5 minutes);
  • avalanche_network_peers - for monitoring purposes, you could use the following expression:
    • avalanche_network_peers{job="avalanche-node"}, which means the number of peers connected to the node - this can be used to get an alert whenever there are less peers than a certain threshold for a certain period of time (i.e. less than 3 peers for 5 minutes);

You can use the above metrics to create both Grafana dashboards and Alertmanager alerts.

info

Please make sure to also check the Official Docs and the Github Repository in order to make sure you are keeping your node up to date.