Ingesting data into Quadrant

July 26, 2018 Jack Kwan

Quadrant’s data ingestion mechanism is simple and powerful. As a user, you will be able to gain a new level of understanding of your system through Quadrant’s rich features within minutes.

It only takes a few steps to start taking advantage of Quadrant’s capabilities. In general, you will need to provide a mechanism for Quadrant to reach out and make queries to each of your telemetry data source. After that, Quadrant will handle the rest.

The mechanisms for ingestion vary depending on your telemetry data source, but they are all very simple. For time series databases such as InfluxDB, you will need to provide Quadrant the secured hostname and login credentials of your InfluxDB instance. For cloud service providers such as Azure Application Insights and AWS Cloudwatch; just provide the appId/key pair or the ARN to Quadrant. For all ingestion mechanisms, you can optionally configure Quadrant to look at only selected parts of your telemetry data source.

After that, Quadrant will securely connect to your data sources and begin streaming data. Once data starts flowing in, everything is automatic. Quadrant will populate its causal graph with metrics and relationships in real time so that you can meaningfully and efficiently explore your data with Quadrant’s insights.

Because simultaneously ingesting data from different telemetry data sources into Quadrant is very easy, you can obtain insights across data sources that are otherwise difficult to access.

For example, assume that you collect CPU and memory telemetry of your application into InfluxDB, but you also have some load balancer latency metrics living in Cloudwatch. You would like to get some insights as to how these Cloudwatch metrics might relate to the CPU and memory metrics of your application. Normally, it would be difficult to see how these telemetry data, which do not share a common structure and live in different databases, would relate to and affect each other.

With Quadrant’s ingestion mechanisms, this is seamless and intuitive. This is because regardless the data source, Quadrant is able to understand data in its own format. Once you provide the credentials for each telemetry data source to Quadrant, it is able to understand all telemetry data the same way regardless where they come from.

In this way, Quadrant provides valuable insights across different data sources without distinction as if all of your telemetry data come from the same data source.

July 26, 2018 Jack Kwan


All rights reserved