How Does Your Docker Monitoring Tool Visualize Complex Relationships?

by August 30, 2017

Simplify Complexity with CA’s Docker Monitoring Tools

 

Many of today’s developers are adopting Docker Containers to help accelerate application delivery and move towards adopting a microservices application architecture.  However, this architecture introduces new layer of monitoring challenges to an already complex application environment.  Just the dynamic ephemeral nature of these Docker container environments makes it difficult to understand relationships between container, host and application, lacks the ability to understand what changed and know when and where to act when issues arise.

Why is it a challenge?

To start, Microservices introduce many new smaller applications components to an already complex application environment.  This makes it difficult to understand the performance and health of each component and their impact to other services.  With the increase in components, users find it difficult to understand application environments and every components relationship using the traditional application service maps.  Unfortunately, what you end up with is a big messy map or worse the tool may only allow the ability to zoom in and out – which only works if you know what to zoom in on.

 

What’s needed?

The ability to view the various layers of dependencies between the application, the container and the host as well as the health of each component.  But understanding the intricate relationships is just one piece of the puzzle- visualizing it in a way the human brain can easily understand is another piece all together.  To achieve this your Docker monitoring tool will need to support multi-dimensional data and have the ability to assign names or attributes to that data.  These attributes become the key to unraveling and pivoting on the data that best matches your needs.

Think of attributes in the context of your current playlist.  You probably have created specific lists of music based on genera, type of activity such as running music vs work music, or even mood.  These are attributes that help to categorize your volumes of music into a way that best meets your needs.  Similar to monitoring Docker, you need a basic set of attributes to help organize the complex sets of data in a way that best meets your performance needs.  Below are a list of attributes specific to Docker:

 

Certainly, you may also want to customize or add in your own attributes specific to your own environment – make sure your Docker monitoring solution allows you to easily add and customize attributes that best describes your data.  With these attributes assigned to the data, you can now pivot what was once a complex typology map (seen above) to a simpler view the performance of the container, the host or even the application (seen below).

 

To learn about CA’s unique Docker Monitoring capabilities, watch the webcast Future Proof Docker and Microservices with Modern Monitoring