Metrics

osm-edge generates detailed metrics related to all traffic within the mesh and the osm-edge control plane. These metrics provide insights into the behavior of applications in the mesh and the mesh itself helping users to troubleshoot, maintain and analyze their applications.

osm-edge collects metrics directly from the sidecar proxies (Pipy). With these metrics the user can get information about the overall volume of traffic, errors within traffic and the response time for requests.

Additionally, osm-edge generates metrics for the control plane components. These metrics can be used to monitor the behavior and health of the service mesh.

osm-edge uses Prometheus to gather and store consistent traffic metrics and statistics for all applications running in the mesh. Prometheus is an open-source monitoring and alerting toolkit which is commonly used on (but not limited to) Kubernetes and Service Mesh environments.

Each application that is part of the mesh runs in a Pod which contains an Pipy sidecar that exposes metrics (proxy metrics) in the Prometheus format. Furthermore, every Pod that is a part of the mesh and in a namespace with metrics enabled has Prometheus annotations, which makes it possible for the Prometheus server to scrape the application dynamically. This mechanism automatically enables scraping of metrics whenever a pod is added to the mesh.

osm-edge metrics can be viewed with Grafana which is an open source visualization and analytics software. It allows you to query, visualize, alert on, and explore your metrics.

Grafana uses Prometheus as backend timeseries database. If Grafana and Prometheus are chosen to be deployed through osm-edge installation, necessary rules will be set upon deployment for them to interact. Conversely, on a “Bring-Your-Own” or “BYO” model (further explained below), installation of these components will be taken care of by the user.

Installing Metrics Components

osm-edge can either provision Prometheus and Grafana instances at install time or osm-edge can connect to an existing Prometheus and/or Grafana instance. We call the latter pattern “Bring-Your-Own” or “BYO”. The sections below describe how to configure metrics by allowing osm-edge to automatically provision the metrics components and with the BYO method.

Automatic Provisioning

By default, both Prometheus and Grafana are disabled.

However, when configured with the --set=osm.deployPrometheus=true flag, osm-edge installation will deploy a Prometheus instance to scrape the sidecar’s metrics endpoints. Based on the metrics scraping configuration set by the user, osm-edge will annotate pods part of the mesh with necessary metrics annotations to have Prometheus reach and scrape the pods to collect relevant metrics. The scraping configuration file defines the default Prometheus behavior and the set of metrics collected by osm-edge.

To install Grafana for metrics visualization, pass the --set=osm.deployGrafana=true flag to the osm install command. osm-edge provides a pre-configured dashboard that is documented in osm-edge Grafana dashboards.

 osm install --set=osm.deployPrometheus=true \
             --set=osm.deployGrafana=true

Note: The Prometheus and Grafana instances deployed automatically by osm-edge have simple configurations that do not include high availability, persistent storage, or locked down security. If production-grade instances are required, pre-provision them and follow the BYO instructions on this page to integrate them with osm-edge.

Bring-Your-Own

Prometheus

The following section documents the additional steps needed to allow an already running Prometheus instance to poll the endpoints of an osm-edge mesh.

List of Prerequisites for BYO Prometheus

• Already running an accessible Prometheus instance outside of the mesh.
• A running osm-edge control plane instance, deployed without metrics stack.
• We will assume having Grafana reach Prometheus, exposing or forwarding Prometheus or Grafana web ports and configuring Prometheus to reach Kubernetes API services is taken care of or otherwise out of the scope of these steps.

Configuration

• Make sure the Prometheus instance has appropriate RBAC rules to be able to reach both the pods and Kubernetes API - this might be dependent on specific requirements and situations for different deployments:

- apiGroups: [""]
   resources: ["nodes", "nodes/proxy",  "nodes/metrics", "services", "endpoints", "pods", "ingresses", "configmaps"]
   verbs: ["list", "get", "watch"]
 - apiGroups: ["extensions"]
   resources: ["ingresses", "ingresses/status"]
   verbs: ["list", "get", "watch"]
 - nonResourceURLs: ["/metrics"]
   verbs: ["get"]

• If desired, use the Prometheus Service definition to allow Prometheus to scrape itself:

annotations:
  prometheus.io/scrape: "true"
  prometheus.io/port: "<API port for prometheus>" # Depends on deployment - osm-edge automatic deployment uses 7070 by default, controlled by `values.yaml`

• Amend Prometheus’ configmap to reach the pods/Pipy endpoints. osm-edge automatically appends the port annotations to the pods and takes care of pushing the listener configuration to the pods for Prometheus to reach:

- job_name: 'kubernetes-pods'
   kubernetes_sd_configs:
   - role: pod
   relabel_configs:
   - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scrape]
      action: keep
      regex: true
   - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_path]
      action: replace
      target_label: __metrics_path__
      regex: (.+)
   - source_labels: [__address__, __meta_kubernetes_pod_annotation_prometheus_io_port]
      action: replace
      regex: ([^:]+)(?::\d+)?;(\d+)
      replacement: $1:$2
      target_label: __address__
   - source_labels: [__meta_kubernetes_namespace]
      action: replace
      target_label: source_namespace
   - source_labels: [__meta_kubernetes_pod_name]
      action: replace
      target_label: source_pod_name
   - regex: '(__meta_kubernetes_pod_label_app)'
      action: labelmap
      replacement: source_service
   - regex: '(__meta_kubernetes_pod_label_osm_sidecar_uid|__meta_kubernetes_pod_label_pod_template_hash|__meta_kubernetes_pod_label_version)'
      action: drop
   - source_labels: [__meta_kubernetes_pod_controller_kind]
      action: replace
      target_label: source_workload_kind
   - source_labels: [__meta_kubernetes_pod_controller_name]
      action: replace
      target_label: source_workload_name
   - source_labels: [__meta_kubernetes_pod_controller_kind]
      action: replace
      regex: ^ReplicaSet$
      target_label: source_workload_kind
      replacement: Deployment
   - source_labels:
      - __meta_kubernetes_pod_controller_kind
      - __meta_kubernetes_pod_controller_name
      action: replace
      regex: ^ReplicaSet;(.*)-[^-]+$
      target_label: source_workload_name

Grafana

The following section assumes a Prometheus instance has already been configured as a data source for a running Grafana instance. Refer to the Prometheus and Grafana demo for an example on how to create and configure a Grafana instance.

Importing osm-edge Dashboards

osm-edge Dashboards are available through our repository, which can be imported as json blobs on the web admin portal.

Detailed instructions for importing osm-edge dashboards can be found in the Prometheus and Grafana demo. Refer to osm-edge Grafana dashboard for an overview of the pre-configured dashboards.

Metrics scraping

Metrics scraping can be configured using the osm metrics command. By default, osm-edge does not configure metrics scraping for pods in the mesh. Metrics scraping can be enabled or disabled at namespace scope such that pods belonging to configured namespaces can be enabled or disabled for scraping metrics.

For metrics to be scraped, the following prerequisites must be met:

• The namespace must be a part of the mesh, ie. it must be labeled with the openservicemesh.io/monitored-by label with an appropriate mesh name. This can be done using the osm namespace add command.
• A running service able to scrape Prometheus endpoints. osm-edge provides configuration for an automatic bringup of Prometheus; alternatively users can bring their own Prometheus.

To enable one or more namespaces for metrics scraping:

osm metrics enable --namespace test
osm metrics enable --namespace "test1, test2"

To disable one or more namespaces for metrics scraping:

osm metrics disable --namespace test
osm metrics disable --namespace "test1, test2"

Enabling metrics scraping on a namespace also causes the osm-injector to add the following annotations to pods in that namespace:

prometheus.io/scrape: true
prometheus.io/port: 15010
prometheus.io/path: /stats/prometheus

Available Metrics

osm-edge exports metrics about the traffic within the mesh as well as metrics about the control plane.

Custom Pipy Metrics

To implement the SMI Metrics Specification, the Pipy proxy in osm-edge generates the following statistics for HTTP traffic

osm_request_total: a counter metric that is self-incrementing with each proxy request. By querying this metric, you can see the success and failure rates of requests for the services in the mesh.

osm_request_duration_ms: A histogram metric that indicates the duration of a proxy request in milliseconds. This metric is queried to understand the latency between services in the mesh.

Both metrics have the following labels.

source_kind: the Kubernetes resource type of the workload that generated the request, e.g. Deployment, DaemonSet, etc.

destination_kind: The Kubernetes resource type that processes the requested workload, e.g. Deployment, DaemonSet, etc.

source_name: The name of the Kubernetes that generated the requested workload.

destination_name: The name of the Kubernetes that processed the requested workload.

source_pod: the name of the pod in Kubernetes that generated the request.

destination_pod: the name of the pod that processed the request in Kubernetes.

source_namespace: the namespace in Kubernetes of the workload that generated the request.

destination_namespace: the namespace in Kubernetes of the workload that processed the request.

In addition, the osm_request_total metric has a response_code tag that indicates the HTTP status code of the request, e.g. 200, 404, etc.

Control Plane

The following metrics are exposed in the Prometheus format by the osm-edge control plane components. The osm-controller and osm-injector pods have the following Prometheus annotation.

annotations:
   prometheus.io/scrape: 'true'
   prometheus.io/port: '9091'

Error Code Metrics

When an error occurs in the osm-edge control plane the ErrCodeCounter Prometheus metric is incremented for the related osm-edge error code. For the complete list of error codes and their descriptions, see osm-edge Control Plane Error Code Troubleshooting Guide.

The fully-qualified name of the error code metric is osm_error_err_code_count.

Note: Metrics corresponding to errors that result in process restarts might not be scraped in time.

Query metrics from Prometheus

Before you begin

Ensure that you have followed the steps to run osm-edge Demo

Querying proxy metrics for request count

1. Verify that the Prometheus service is running in your cluster
   • In kubernetes, execute the following command: kubectl get svc osm-prometheus -n <osm-namespace>.
   • Note: <osm-namespace> refers to the namespace where the osm control plane is installed.
2. Open up the Prometheus UI
   • Ensure you are in root of the repository and execute the following script: ./scripts/port-forward-prometheus.sh
   • Visit the following url http://localhost:7070 in your web browser
3. Execute a Prometheus query
   • In the “Expression” input box at the top of the web page, enter the text: sidecar_cluster_upstream_rq_xx{sidecar_response_code_class="2"} and click the execute button
   • This query will return the successful http requests

Sample result will be:

Visualize metrics with Grafana

List of Prerequisites for Viewing Grafana Dashboards

Ensure that you have followed the steps to run osm-edge Demo

Viewing a Grafana dashboard for service to service metrics

1. Verify that the Prometheus service is running in your cluster
   • In kubernetes, execute the following command: kubectl get svc osm-prometheus -n <osm-namespace>
2. Verify that the Grafana service is running in your cluster
   • In kubernetes, execute the following command: kubectl get svc osm-grafana -n <osm-namespace>
3. Open up the Grafana UI
   • Ensure you are in root of the repository and execute the following script: ./scripts/port-forward-grafana.sh
   • Visit the following url http://localhost:3000 in your web browser
4. The Grafana UI will request for login details, use the following default settings:
   • username: admin
   • password: admin
5. Viewing Grafana dashboard for service to service metrics
   • From the Grafana’s dashboards left hand corner navigation menu you can navigate to the osm-edge Service to Service Dashboard in the folder osm-edge Data Plane
   • Or visit the following url http://localhost:3000/d/OSMs2sMetrics/osm-service-to-service-metrics?orgId=1 in your web browser

osm-edge Service to Service Metrics dashboard will look like:

osm-edge Grafana dashboards

osm-edge provides some pre-cooked Grafana dashboards to display and track services related information captured by Prometheus:

1. osm-edge Data Plane

   • osm-edge Data Plane Performance Metrics: This dashboard lets you view the performance of osm-edge’s data plane
   • osm-edge Service to Service Metrics: This dashboard lets you view the traffic metrics from a given source service to a given destination service
   • osm-edge Pod to Service Metrics: This dashboard lets you investigate the traffic metrics from a pod to all the services it connects/talks to
   • osm-edge Workload to Service Metrics: This dashboard provides the traffic metrics from a workload (deployment, replicaSet) to all the services it connects/talks to
   • osm-edge Workload to Workload Metrics: This dashboard displays the latencies of requests in the mesh from workload to workload

2. osm-edge Control Plane

   • osm-edge Control Plane Metrics: This dashboard provides traffic metrics from the given service to osm-edge’s control plane
   • Mesh and Pipy Details: This dashboard lets you view the performance and behavior of osm-edge’s control plane

Feedback

Was this page helpful?

Glad to hear it! Please tell us how we can improve.

Sorry to hear that. Please tell us how we can improve.