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📥 Installation of the Bleemeo Community Edition

This page documents how to install all the components of the Bleemeo Community edition:

  • SquirrelDB: a scalable and highly available timeseries database.
  • Cassandra: a distributed database used for SquirrelDB long term storage.
  • Glouton: a powerful monitoring agent.
  • NATS: a high-performance messaging system used by Glouton to send its metrics.
  • SquirrelDB Ingestor: forward metrics sent by Glouton over MQTT to SquirrelDB.
  • Grafana: display the metrics and provide alerting.

Quickstart

A docker compose is available to quickly deploy and test all the components.

SquirrelDB

SquirrelDB is a timeseries database, highly optimized for storing metrics. It has several interesting features:

  • Blazing fast read of recent metrics using an in-memory store for short term storage.
  • Efficient and scalable long term storage with Cassandra.
  • Expose a PromQL endpoint, making it compatible with Prometheus compatible tools, like Grafana to view your metrics.

Installing SquirrelDB is easy with Docker. First let's create a Docker network so all our components will be able to communicate.

docker network create bleemeo

Now let's run Cassandra that will hold our long term storage.

docker run -d --name "cassandra" --restart unless-stopped --net bleemeo \
-v cassandra:/var/lib/cassandra \
-e MAX_HEAP_SIZE=128M -e HEAP_NEWSIZE=24M cassandra

Then we can start SquirrelDB and connect it to Cassandra.

docker run -d --name "squirreldb" --restart unless-stopped --net bleemeo \
-e SQUIRRELDB_CASSANDRA_ADDRESSES=cassandra:9042 bleemeo/squirreldb

MQTT

MQTT is a standard messaging protocol providing a lightweight publish/subscribe messaging transport. In this example we will use NATS as our MQTT server, it provides a high-performance and scalable messaging system. You are free to use any other MQTT server, it will work the same.

We need to write a configuration file for NATS to make it expose a MQTT endpoint.

cat > nats.conf << EOF
server_name: "bleemeo-mqtt"

jetstream {}

mqtt {
port: 1883
}
EOF

Then we can run NATS with this configuration.

docker run -d --name "nats" --restart unless-stopped -p 1883:1883 \
--net bleemeo -v $(pwd)/nats.conf:/etc/nats/nats.conf:ro \
nats -c /etc/nats/nats.conf

Note that in production the MQTT port should be protected, especially if it's exposed over internet, NATS should be configured to use TLS and authentication. See NATS TLS documentation and the authentication setup for more information.

SquirrelDB Ingestor

We can run SquirrelDB Ingestor with some configuration to tell him where to find our database and the MQTT server.

docker run -d --name="squirreldb-ingestor" --restart unless-stopped --net bleemeo \
-e INGESTOR_REMOTE_WRITE_URL="http://squirreldb:9201/api/v1/write" \
-e INGESTOR_MQTT_BROKER_URL="tcp://nats:1883" \
bleemeo/squirreldb-ingestor

Again we can check the logs to make it sure it successfully connected to MQTT.

docker logs -f squirreldb-ingestor

You should see the message MQTT connection established.

Glouton

Now let's setup our monitoring agent.

Glouton is a monitoring agent that makes observing your infrastructure easy. It provides a lot of features:

  • gathers system metrics from Prometheus node_exporter
  • automatically discovers your services to retrieve relevant metrics.
  • Kubernetes native: create metrics and checks for pods

We need to configure the agent to send its metrics to NATS. We assume here that NATS is running on our monitoring server which has the IP 192.168.1.101, as in the diagram below.

Network Network

The following command will create the configuration file glouton.conf to tell the agent the address of our MQTT server and the metrics it should send.

# This should be the address where the NATS MQTT server is running
MONITORING_SERVER_ADDRESS="192.168.1.101"

cat > glouton.conf << EOF
agent:
metrics_format: prometheus

bleemeo:
enable: false

mqtt:
enable: true
hosts:
- $MONITORING_SERVER_ADDRESS
port: 1883

# Allow node exporter metrics.
metric:
allow_metrics:
- node_*
EOF

Now we can run Glouton:

docker run -d --name="glouton" --restart unless-stopped \
-v $(pwd)/glouton.conf:/etc/glouton/conf.d/90-local.conf:ro \
-v /var/lib/glouton:/var/lib/glouton -v /var/run/docker.sock:/var/run/docker.sock \
-v /:/hostroot:ro --pid=host --net=host \
--cap-add SYS_PTRACE --cap-add SYS_ADMIN bleemeo/bleemeo-agent

We can check the logs to make sure everything is working:

docker logs -f glouton

You should see the message Open Source MQTT connection established.

To sum up what we did, we set up a working Time Series Database to store our metrics, we started a MQTT server, SquirrelDB Ingestor and a monitoring agent. The agent sends its metrics to MQTT, SquirrelDB Ingestor reads them and write them in SquirrelDB.

Grafana

Now that our metrics are stored in our Time Series Database, we are only missing something to view them and be notified of problems. For that we can use Grafana.

docker run -d --name="grafana" --restart unless-stopped -p 127.0.0.1:3000:3000 \
--net bleemeo grafana/grafana

After Grafana is started, you can open http://localhost:3000 and login with the credentials admin/admin.

Next you need to add a Prometheus source, with the URL http://squirreldb:9201.

SquirrelDB source

Then import the Node Exporter dashboard with the ID 1860, using the SquirrelDB data source we just configured.

You should see the system metrics gathered by the agent.

SquirrelDB source

To be notified when an issue occurs, you can create alerting rules with Grafana.

Conclusion

You have successfully deployed the Bleemeo Community Edition 🎉

If you want you can install Glouton on your other servers and connect them to MQTT to be able to monitor all your infrastructure from one dashboard.

Note that we set up SquirrelDB, Cassandra and the ingestor on a single node, but all of these components can be scaled as needed. For more information, check out our high availability documentation.