Open cauemarcondes opened 1 month ago
Pinging @elastic/obs-ux-infra_services-team (Team:obs-ux-infra_services)
Prioritising as 'low' until we can get more information on when this happens (see comment).
Context : Trying to understand if this is an edge case of a common problem for many use cases/customers
After discussion with @jennypavlova and @cauemarcondes, moved this to top of refinement column and added AC in the description.
This can be updated during refinement if needed.
On the Service Inventory page, we always try to show metrics from one of the "main" transaction types (
request
,page_load
ormobile
). If a service doesn't have one of these, we use the first transaction type returned and add a new column to the Service inventory table displaying its name:✔️ Acceptance criteria
1. Must Have
Must be delivered in this issue in order for the release to be valuable
main
transaction type or a custom one (e.g.foo
)4. Will Not Have (for now)
Explicitly will not be looked at within this issue
The problem
As seen in the image above the
packetbeat
has anunknown
health status. And that's because when we are fetching ML anomalies we add a filter to only retrieve anomalies from the main transaction types. This causes to any service displayed on the Service overview page that does NOT have one of the main transaction types to always have anunknown
ML health status.The solution
Instead of filtering by transaction types, we must group anomalies by it. By doing so we can pick the anomaly from the transaction type displayed on the page.
Question
When a service has two transaction types
request
andworker
for example, by default we'll show metrics from the transaction typerequest
, but what if the transaction typeworker
has amajor
orcritical
ML anomaly? Should we change and show metrics from the transaction type with a higher anomaly?Like in this example:
Service
b
is showing metrics from therequest
transaction type (as there's no transaction type column on the table), but it has acritical
ML health status coming from theworker
transaction type.ML response: