Usability: Content easily accessible from the catalog
SignalFx customers already go to the catalog to search for anything in the system‒be it hosts, metrics, services or even dashboards. It made sense to make our new CloudWatch dashboards just show up there. Click on an AWS service namespace or instance, and you can view a customized, pre-populated dashboard for that service or instance right there. Easy to use and nothing new to learn.
Optimized for monitoring both populations as well as individual systems
One size does not fit all, and that applies to dashboards as well. A dashboard optimized for viewing a single instance will not work well (or at all) when viewing a cluster of instances. Because of this, we’ve built multiple specialized dashboards (two, three, or even up to five) per AWS service so users have the right for their context. For example, ElastiCache has clusters and instances with Redis or Memcache backends and Opsworks has stacks, layers and instances. A truly effective monitoring system must reflect this complex reality. Population analytics are used to make multi-instance, cluster-level dashboards more effective. Instead of showing a line for each member (which can be noisy), for instance, we used techniques like aggregates, percentiles, and TopN to provide more effective visualizations.
Smart drilldowns: Using dimensions and tags/properties
The catalog’s main purpose is to show all the dimensions and tags/properties available in the matching metrics. For example, select an AWS service and it shows you all individual instances of that service, the regions and AZs it exists in, as well as tags & properties applied to those instances. From there, adding the ability to navigate and filter our AWS dashboards was a no brainer. Now you can drill down into a particular AZ or tag and the dashboard intelligently updates itself to only show matching instances. The second way drilldowns are smart is you can use the service’s own hierarchy to drill down, e.g. ElastiCache clusters, Opsworks stacks, and Cloudfront distributions.
Consistency: Uniform look and feel across all services
A huge amount of time was spent in making all our AWS dashboards share a common look and feel. That goes into minute details like chart naming, axis labelling and chart types used (e.g. percentile distribution charts look and feel the same across all services). We chose specific colors for specific metric types so users will quickly get used to them and be able to grok the information with a quick visual inspection.