Inline with deepstream's enterprise clustering AMI going live on AWS marketplace, here's an overview of the various features it offers.
Clustering in deepstream enterprise allows multiple deepstream nodes to connect and communicate with each other. Every node that becomes part of the cluster is automatically connected to every other node in that cluster in a peer-to-peer fashion. This allows for interesting and useful features for applications such as Horizontal Scaling and Failover. We'll talk about this in a bit.
deepstream's AMI opens up the easiest avenue to clustering your deepstream enterprise nodes using AWS. It is possible to spin up an entire auto-scaling cluster using this AMI in less than 10 mins as shown in this video tutorial. All nodes part of the same auto-scaling group, automatically become part of the same cluster and exhibit all the features offered by clustering in deepstream enterprise.
Monitoring your cluster data
As you know, deepstream enterprise also offers monitoring of your data. In order to monitor the cluster data, deepstream enterprise uses the deepstream-monitoring service a.k.a deepmon, by default. However, you are not limited to this, it is entirely possible to use any of the third-party monitoring services of your choice, such as Logstash. To hook any of these third-party monitoring services, the only thing required is to enable
http in the config file of your deepstream enterprise server. You could automate this by using a script as shown in the video.
Furthermore, you can have this monitoring service push all the cluster data to a database of your choice which can then be reproduced in a visually appealing graphical dashboard as discussed further.
Using Grafana to visualize your cluster data
You can use the Grafana template offered by deepstream to conveniently export your cluster data into a graphical UI. In Grafana, when you search the list of available dashboards, you'll be able to see deepstream's grafana template. Simply import this and connect it to a database that contains your cluster's data. This will show you the metrics in the form of graphs for easy and continuous visualization.