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This guide provides step-by-step instructions on configuring and using Coralogix Application Performance Monitoring (APM). Follow these steps to effectively onboard your services, install collectors, correlate resources, and leverage advanced features.
Before setting up APM, you must select and configure a data pipeline and TCO pipeline to send us your data.
You can enjoy our APM features in multiple ways, using either of our data pipelines: Events2Metrics and Span Metrics.
We recommend configuring span sampling to get the best results using Span Metrics. This allows the user to view traces, service connections, and maps in the Coralogix platform.
Feature | E2M | SpanMetrics | Span Metrics & Span Sampling |
---|---|---|---|
Overview | Full content | Service Map is not displayed. Apdex thresholds are based on your collector’s buckets. | Includes Service Map, which shows connections between services or spans based on the traces that are being sent. Metrics are presented in APM features, except for the map. Apdex thresholds are based on your collector’s buckets. |
Operations | Full content | Full content | Full content |
Flows | Full content | Full content | Full content |
SLO | Full content | Thresholds for latency SLO, are based on your collector’s buckets. | Thresholds for latency SLO are based on your collector’s bucket. |
Map | Full content | No content | Partial content displayed Connections between services or spans based on the traces that are being sent are presented. Metrics are presented in APM features, except for the map. |
Assign the Medium (Monitoring) TCO pipeline to the traces sent to Coralogix.
To set up APM, instrument your service and install the Otel Collector.
To get started with Coralogix APM, generate spans from your services by instrumenting them. Choose the relevant documentation for your service’s programming language:
Install the OpenTelemetry Collector. The Collector is an intermediary component responsible for aggregating and transmitting data, playing a key role in the overall APM workflow. Once installed, the Coralogix Events2Metrics feature automatically converts your spans and logs to metrics to be displayed in your UI. Select from any of the following configuration options:
APM should run once your service is instrumented and the Collector is installed.
Investigate service-resource correlation within your Kubernetes environment in your APM Resources tab or Kubernetes Dashboard. This correlation relies on span tags and metric labels.
Span tags are metadata attached to requests moving through a distributed system, facilitating traceability and correlation. Each microservice adds or propagates span tags, creating a trace that visualizes the request’s path, aiding in identifying performance bottlenecks and dependencies.
Metric labels are key-value pairs associated with metrics collected from Kubernetes resources. These labels offer additional context to metrics, such as CPU usage or network traffic, making organizing and analyzing data based on service names, pod names, or environments easier.
Coralogix recommends the Kubernetes Complete Observability integration package for comprehensive Kubernetes and application observability. Deploying the Kubernetes OpenTelemetry extension enables telemetry data collection and full service-resource correlation in your APM Resources tab or Kubernetes Dashboard, without any additional steps.
If you are not using the Kubernetes Complete Observability integration package, take the following steps:
K8s.deployment.name
label. In case of using StatefulSets or DaemonSets, replace K8s.deployment.name
with K8s.DaemonSets.name
or K8s.StatefulSets.name
, respectively.Correlate ECS-EC2 or ECS Fargate performance metrics with your service as follows:
Service-resource correlation within your Kubernetes environment is presented in your APM Resources tab.
If you are using Prometheus to send us telemetry, ensure that kube state metrics and node exporter metrics are sent by Prometheus Operator to set up metric labels for Kubernetes resource correlation in your Kubernetes Dashboard. You may validate the metrics by following these instructions.
Investigate the logs produced by your service by enriching your logs with a subsystem name matching the service name. Alternatively, set up the correlation by following these instructions.
Set up your service level objectives by following these instructions.
Auto-instrument AWS Lambda by following these instructions.
Learn about Tail Sampling with OpenTelemetry using Kubernetes and Docker.
Need help?
Our world-class customer success team is available 24/7 to walk you through your setup and answer any questions that may come up.
Feel free to reach out to us via our in-app chat or by sending us an email at [email protected].