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Observe your microservices with Cellery
Cellery Observability Dashboard provides the ability for developers, devops and architects to observe the microservices deployed on the Cellery Mesh. It shows the run-time dependencies and metrics of cells and microservices and provides the ability to trace requests to find the root cause for problems in the run-time.
Overview
When logged in to the dashboard you will see the landing page which provides the overview details of the system. It shows the cell dependencies with health indications on cells.
By looking at the overall system you able to identify the cells which has errors and warnings. The cell shows an error if the number of 5xx request of the cell exceeds 50% of it’s requests.
The right panels provides the information about the HTTP traffic of the overall system and lists cells with links to distributed tracing information. You can click on a specific cell to see cell its components and traffic details.
Distributed Tracing
The dashboard shows the traces for all requests which comes to Cellery system. You can filter out requests according to the cell, component and operation names.
A request can be viewed in three perspectives: timeline view, sequence diagram view, and dependency diagram view.
Timeline View
Timeline view mainly focuses on the time that the request spent on a particular operation, and hence it is easy to find out the most time consuming component and operation. Also there is an option in the timeline view, to filter out traces according to types such as components, system etc. Spans within a cell is grouped according to the cell color.
Sequence diagram View
The sequence diagram view depicts the cells and component interactions. The landing view will show the cell wise communications.
You can click on the request and see the drilled down view of how components within the same call communicate with each other.
Request Dependency Diagram View
This diagram shows the path of a request. It will show the errors and the warnings of the particular request. The size of a component is proportional to the latency incurred by that component.
Metrics
The metrics are collected from all components and gateways, and based on this the health of a component and cell is determined. Cellery Dashboard shows Cell/Component and system metrics.
Cell/Component based metrics
The metrics can be visualized both per component and cell basis. It can be viewed from the Cell/Component overview page by clicking on metrics tab. There you will be able to see metrics for inbound and outbound requests. Also, you can select an area on the request line graphs to zoom in and you will be able to view the traces to investigate more on the specific requests.
System metrics
Cellery provides both kubernetes pod and node level metrics. It illustrates data about CPU, memory, network, and file system usage. Cellery points to the Grafana dashboard to display these metrics. You can go to a component overview, select K8S Pods and click on the metrics icon to view the options.
Cell and Component overview
You can click on the cells icon on the left navigation bar to view Cell listing which also shows the metrics summary.
You can select on a cell and see the overview details. It contains cell wise dependency details and tabs for component listing and metrics.
From the components listing you can select a component to see the component’s overview details. It contains component wise dependency details and tabs for Pod listing and metrics.
Other features
The top tool bar contains options to generate cell colors. The cells in the dashboard is assigned with a unique color and it is used to identify the specific cell throughout the dashboard. You can generate new set of colors for the cells in case it is difficult to differentiate cell colors. Also, there is an option to share the dashboard with other users with the selected time range.
Conclusion
Now you have covered all the main features of the Cellery dashboard. We encourage you to use Cellery Observability Dashboard to observe your microservices as it will make your life easier when determining system status and identifying and investigating on errors.
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