Generating span related metric data streams by an analytic engine
A method of generating metrics data associated with a microservices-based application comprises ingesting a plurality of spans and mapping an ingested span of the plurality of spans to a span identity, wherein the span identity comprises a tuple of information identifying a type of span associated with the span identity, wherein the tuple of information comprises user-configured dimensions. The method further comprises grouping the ingested span by the span identity, wherein the ingested span is grouped with other spans from the plurality of spans comprising a same span identity. The method also comprises computing metrics associated with the span identity and using the metrics to generate a stream of metric data associated with the span identity.
1. A method of generating metrics data associated with a microservices-based application, the method comprising:
ingesting a plurality of spans associated with one or more applications executing in a distributed computing environment;
mapping each span of the plurality of spans to a span identity that corresponds to a type of span;
grouping the plurality of spans based on the span identity associated with each span of the plurality of spans;
computing metrics associated with the span identity by aggregating information extracted from spans associated with the span identity;
generating, based on the metrics, a stream of metric data associated with the span identity;
generating an alert signal based on values associated with the stream of metric data satisfying a condition; and
responsive to generating the alert signal, extending the span identity with user-configured tags to extract information regarding an operation associated with the span identity.
2. The method of claim 1 , wherein each of the plurality of spans includes a plurality of attributes and one or more user-configured tags.
3. The method of claim 1 , wherein the condition corresponds to at least one value of the stream of metric data exceeding a predetermined threshold.
4. The method of claim 2 , wherein the plurality of attributes includes:
an operation name,
a service name,
a kind tag,
an error flag, or
a flag indicating if the span is part of a service mesh.
5. The method of claim 1 , wherein the metrics computed are selected from one or more of a minimum span duration, a median span duration, a maximum span duration, a p90 latency value, a p99 latency value, and a count of spans associated with the span identity.
6. The method of claim 1 , wherein an analytic engine computes the metrics periodically for a given number of time-periods, and wherein the analytic engine resets the metrics at an end of each time-period.
7. The method of claim 6 , wherein the analytic engine resides in a cloud network.
8. The method of claim 1 , wherein the step of computing metrics further comprises:
generating a fixed size bin histogram for the span identity;
inserting values associated with each span corresponding to the span identity in respective bins of the fixed size bin histogram; and
computing the metrics by tracking counts associated with each bin in the fixed size bin histogram.
9. The method of claim 1 , further comprising:
determining whether the span identity is associated with a cross-service call; and
responsive to a determination that the span identity is associated with a cross-service call, extending the span identity with user-configured tags to extract information regarding the cross-service call.
10. The method of claim 1 , further comprising:
rendering, in a user interface, an application topology graph depicting metrics corresponding to a plurality of services associated with one or more applications executing in the distributed computing environment.
11. A non-transitory computer-readable medium having computer-readable program code embodied therein for causing a computer system to perform a method of generating metrics data associated with a microservices-based application, the method comprising:
ingesting a plurality of spans associated with one or more applications executing in a distributed computing environment;
mapping each span of the plurality of spans to a span identity that corresponds to a type of span;
grouping the plurality of spans based on the span identity associated with each span of the plurality of spans;
computing metrics associated with the span identity by aggregating information extracted from spans associated with the span identity;
generating, based on the metrics, a stream of metric data associated with the span identity;
generating an alert signal based on values associated with the stream of metric data satisfying a condition; and
responsive to generating the alert signal, extending the span identity with user-configured tags to extract information regarding an operation associated with the span identity.
12. The non-transitory computer-readable medium of claim 11 , wherein each of the plurality of spans includes a plurality of attributes and one or more user-configured tags.
13. The non-transitory computer-readable medium of claim 11 , wherein the condition corresponds to at least one value of the stream of metric data exceeding a predetermined threshold.
14. The non-transitory computer-readable medium of claim 11 , wherein the metrics computed are selected from one or more of a minimum span duration, a median span duration, a maximum span duration, a p90 latency value, a p99 latency value, and a count of spans associated with the span identity.
15. The non-transitory computer-readable medium of claim 11 , wherein an analytic engine computes the metrics periodically for a given number of time-periods, and wherein the analytic engine resets the metrics at an end of each time-period.
16. The non-transitory computer-readable medium of claim 11 , wherein the step of computing metrics further comprises:
generating a fixed size bin histogram for the span identity;
inserting values associated with each span corresponding to the span identity in respective bins of the fixed size bin histogram; and
computing the metrics by tracking counts associated with each bin in the fixed size bin histogram.
17. A system for performing a method of generating metrics data associated with a microservices-based application, the system comprising:
a processing device communicatively coupled with a memory and configured to:
ingest a plurality of spans associated with one or more applications executing in a distributed computing environment;
map each span of the plurality of spans to a span identity that corresponds to a type of span;
group the plurality of spans based on the span identity associated with each span of the plurality of spans;
compute metrics associated with the span identity by aggregating information extracted from spans associated with the span identity;
generate, based on the metrics, a stream of metric data associated with the span identity;
generate an alert signal based on values associated with the stream of metric data satisfying a condition; and
extend the span identity with user-configured tags to extract information regarding an operation associated with the span identity in response to the alert signal being generated.
18. The system of claim 17 , wherein the metrics computed are selected from one or more of a minimum span duration, a median span duration, a maximum span duration, a p90 latency value, a p99 latency value, and a count of spans associated with the span identity.