Understanding Operators

The Jaeger Operator is an implementation of a Kubernetes Operator . Operators are pieces of software that ease the operational complexity of running another piece of software. More technically, Operators are a method of packaging, deploying, and managing a Kubernetes application.

A Kubernetes application is an application that is both deployed on Kubernetes and managed using the Kubernetes APIs and kubectl (kubernetes) or oc (OKD) tooling. To be able to make the most of Kubernetes, you need a set of cohesive APIs to extend in order to service and manage your apps that run on Kubernetes. Think of Operators as the runtime that manages this type of app on Kubernetes.

Installing the Operator

Installing the Operator on Kubernetes

The following instructions will create the observability namespace and install the Jaeger Operator.

To install the operator, run:

kubectl create namespace observability # <1>
kubectl create -f https://raw.githubusercontent.com/jaegertracing/jaeger-operator/main/deploy/crds/jaegertracing.io_jaegers_crd.yaml # <2>
kubectl create -f https://raw.githubusercontent.com/jaegertracing/jaeger-operator/main/deploy/service_account.yaml
kubectl create -f https://raw.githubusercontent.com/jaegertracing/jaeger-operator/main/deploy/role.yaml
kubectl create -f https://raw.githubusercontent.com/jaegertracing/jaeger-operator/main/deploy/role_binding.yaml
kubectl create -f https://raw.githubusercontent.com/jaegertracing/jaeger-operator/main/deploy/operator.yaml

<1> This creates the namespace used by default in the deployment files. If you want to install the Jaeger operator in a different namespace, you must edit the deployment files to change observability to the desired namespace value.

<2> This installs the “Custom Resource Definition” for the apiVersion: jaegertracing.io/v1

At this point, there should be a jaeger-operator deployment available. You can view it by running the following command:

$ kubectl get deployment jaeger-operator -n observability

NAME              DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
jaeger-operator   1         1         1            1           48s

The operator is now ready to create Jaeger instances.

Installing the Operator on OKD/OpenShift

The instructions from the previous section also work for installing the operator on OKD or OpenShift. Make sure you are logged in as a privileged user, when you install the role based access control (RBAC) rules, the custom resource definition, and the operator.

oc login -u <privileged user>

oc new-project observability # <1>
oc create -f https://raw.githubusercontent.com/jaegertracing/jaeger-operator/main/deploy/crds/jaegertracing.io_jaegers_crd.yaml # <2>
oc create -f https://raw.githubusercontent.com/jaegertracing/jaeger-operator/main/deploy/service_account.yaml
oc create -f https://raw.githubusercontent.com/jaegertracing/jaeger-operator/main/deploy/role.yaml
oc create -f https://raw.githubusercontent.com/jaegertracing/jaeger-operator/main/deploy/role_binding.yaml
oc create -f https://raw.githubusercontent.com/jaegertracing/jaeger-operator/main/deploy/operator.yaml

<1> This creates the namespace used by default in the deployment files. If you want to install the Jaeger operator in a different namespace, you must edit the deployment files to change observability to the desired namespace value.

<2> This installs the “Custom Resource Definition” for the apiVersion: jaegertracing.io/v1

Once the operator is installed, grant the role jaeger-operator to users who should be able to install individual Jaeger instances. The following example creates a role binding allowing the user developer to create Jaeger instances:

oc create \
  rolebinding developer-jaeger-operator \
  --role=jaeger-operator \
  --user=developer

After the role is granted, switch back to a non-privileged user.

Quick Start - Deploying the AllInOne image

The simplest possible way to create a Jaeger instance is by creating a YAML file like the following example. This will install the default AllInOne strategy, which deploys the “all-in-one” image (agent, collector, query, ingester, Jaeger UI) in a single pod, using in-memory storage by default.

apiVersion: jaegertracing.io/v1
kind: Jaeger
metadata:
  name: simplest

The YAML file can then be used with kubectl:

kubectl apply -f simplest.yaml

In a few seconds, a new in-memory all-in-one instance of Jaeger will be available, suitable for quick demos and development purposes. To check the instances that were created, list the jaeger objects:

$ kubectl get jaegers
NAME        CREATED AT
simplest    28s

To get the pod name, query for the pods belonging to the simplest Jaeger instance:

$ kubectl get pods -l app.kubernetes.io/instance=simplest
NAME                        READY     STATUS    RESTARTS   AGE
simplest-6499bb6cdd-kqx75   1/1       Running   0          2m

Similarly, the logs can be queried either from the pod directly using the pod name obtained from the previous example, or from all pods belonging to our instance:

$ kubectl logs -l app.kubernetes.io/instance=simplest
...
{"level":"info","ts":1535385688.0951214,"caller":"healthcheck/handler.go:133","msg":"Health Check state change","status":"ready"}

$ kubectl logs -l app.kubernetes.io/instance=simplest -c jaeger
...
{"level":"info","ts":1535385688.0951214,"caller":"healthcheck/handler.go:133","msg":"Health Check state change","status":"ready"}

Deployment Strategies

When you create a Jaeger instance, it is associated with a strategy. The strategy is defined in the custom resource file, and determines the architecture to be used for the Jaeger backend. The default strategy is allInOne. The other possible values are production and streaming.

The available strategies are described in the following sections.

AllInOne (Default) strategy

This strategy is intended for development, testing, and demo purposes.

The main backend components, agent, collector and query service, are all packaged into a single executable which is configured (by default) to use in-memory storage.

Production strategy

The production strategy is intended (as the name suggests) for production environments, where long term storage of trace data is important, as well as a more scalable and highly available architecture is required. Each of the backend components is therefore separately deployed.

The agent can be injected as a sidecar on the instrumented application or as a daemonset.

The query and collector services are configured with a supported storage type - currently Cassandra or Elasticsearch. Multiple instances of each of these components can be provisioned as required for performance and resilience purposes.

The main additional requirement is to provide the details of the storage type and options, for example:

    storage:
      type: elasticsearch
      options:
        es:
          server-urls: http://elasticsearch:9200

Streaming strategy

The streaming strategy is designed to augment the production strategy by providing a streaming capability that effectively sits between the collector and the backend storage (Cassandra or Elasticsearch). This provides the benefit of reducing the pressure on the backend storage, under high load situations, and enables other trace post-processing capabilities to tap into the real time span data directly from the streaming platform (Kafka).

The only additional information required is to provide the details for accessing the Kafka platform, which is configured in the collector component (as producer) and ingester component (as consumer):

apiVersion: jaegertracing.io/v1
kind: Jaeger
metadata:
  name: simple-streaming
spec:
  strategy: streaming
  collector:
    options:
      kafka: # <1>
        producer:
          topic: jaeger-spans
          brokers: my-cluster-kafka-brokers.kafka:9092
  ingester:
    options:
      kafka: # <1>
        consumer:
          topic: jaeger-spans
          brokers: my-cluster-kafka-brokers.kafka:9092
      ingester:
        deadlockInterval: 0 # <2>
  storage:
    type: elasticsearch
    options:
      es:
        server-urls: http://elasticsearch:9200

<1> Identifies the Kafka configuration used by the collector, to produce the messages, and the ingester to consume the messages.

<2> The deadlock interval can be disabled to avoid the ingester being terminated when no messages arrive within the default 1 minute period

Understanding Custom Resource Definitions

In the Kubernetes API, a resource is an endpoint that stores a collection of API objects of a certain kind. For example, the built-in Pods resource contains a collection of Pod objects. A Custom Resource Definition (CRD) object defines a new, unique object Kind in the cluster and lets the Kubernetes API server handle its entire lifecycle.

To create Custom Resource (CR) objects, cluster administrators must first create a Custom Resource Definition (CRD). The CRDs allow cluster users to create CRs to add the new resource types into their projects. An Operator watches for custom resource objects to be created, and when it sees a custom resource being created, it creates the application based on the parameters defined in the custom resource object.

For reference, here’s how you can create a more complex all-in-one instance:

apiVersion: jaegertracing.io/v1
kind: Jaeger
metadata:
  name: my-jaeger
spec:
  strategy: allInOne # <1>
  allInOne:
    image: jaegertracing/all-in-one:latest # <2>
    options: # <3>
      log-level: debug # <4>
  storage:
    type: memory # <5>
    options: # <6>
      memory: # <7>
        max-traces: 100000
  ingress:
    enabled: false # <8>
  agent:
    strategy: DaemonSet # <9>
  annotations:
    scheduler.alpha.kubernetes.io/critical-pod: "" # <10>

<1> The default strategy is allInOne. The other possible values are production and streaming.

<2> The image to use, in a regular Docker syntax.

<3> The (non-storage related) options to be passed verbatim to the underlying binary. Refer to the Jaeger documentation and/or to the --help option from the related binary for all the available options.

<4> The option is a simple key: value map. In this case, we want the option --log-level=debug to be passed to the binary.

<5> The storage type to be used. By default it will be memory, but can be any other supported storage type (Cassandra, Elasticsearch, Kafka).

<6> All storage related options should be placed here, rather than under the ‘allInOne’ or other component options.

<7> Some options are namespaced and we can alternatively break them into nested objects. We could have specified memory.max-traces: 100000.

<8> By default, an ingress object is created for the query service. It can be disabled by setting its enabled option to false. If deploying on OpenShift, this will be represented by a Route object.

<9> By default, the operator assumes that agents are deployed as sidecars within the target pods. Specifying the strategy as “DaemonSet” changes that and makes the operator deploy the agent as DaemonSet. Note that your tracer client will probably have to override the “JAEGER_AGENT_HOST” environment variable to use the node’s IP.

<10> Define annotations to be applied to all deployments (not services). These can be overridden by annotations defined on the individual components.

You can view example custom resources for different Jaeger configurations on GitHub .

Configuring the Custom Resource

You can use the simplest example (shown above) and create a Jaeger instance using the defaults, or you can create your own custom resource file.

Storage options

Cassandra storage

When the storage type is set to Cassandra, the operator will automatically create a batch job that creates the required schema for Jaeger to run. This batch job will block the Jaeger installation, so that it starts only after the schema is successfully created. The creation of this batch job can be disabled by setting the enabled property to false:

apiVersion: jaegertracing.io/v1
kind: Jaeger
metadata:
  name: cassandra-without-create-schema
spec:
  strategy: allInOne
  storage:
    type: cassandra
    cassandraCreateSchema:
      enabled: false # <1>

<1> Defaults to true

Further aspects of the batch job can be configured as well. An example with all the possible options is shown below:

apiVersion: jaegertracing.io/v1
kind: Jaeger
metadata:
  name: cassandra-with-create-schema
spec:
  strategy: allInOne # <1>
  storage:
    type: cassandra
    options: # <2>
      cassandra:
        servers: cassandra
        keyspace: jaeger_v1_datacenter3
    cassandraCreateSchema: # <3>
      datacenter: "datacenter3"
      mode: "test"

<1> The same works for production and streaming.

<2> These options are for the regular Jaeger components, like collector and query.

<3> The options for the create-schema job.

Elasticsearch storage

Under some circumstances, the Jaeger Operator can make use of the Elasticsearch Operator  to provision a suitable Elasticsearch cluster.

When there are no es.server-urls options as part of a Jaeger production instance and elasticsearch is set as the storage type, the Jaeger Operator creates an Elasticsearch cluster via the Elasticsearch Operator by creating a Custom Resource based on the configuration provided in storage section. The Elasticsearch cluster is meant to be dedicated for a single Jaeger instance.

The self-provision of an Elasticsearch cluster can be disabled by setting the flag --es-provision to false. The default value is auto, which will make the Jaeger Operator query the Kubernetes cluster for its ability to handle a Elasticsearch custom resource. This is usually set by the Elasticsearch Operator during its installation process, so, if the Elasticsearch Operator is expected to run after the Jaeger Operator, the flag can be set to true.

Elasticsearch index cleaner job

When using elasticsearch storage by default a job is created to clean old traces from it, the options for it are listed below so you can configure it to your use case

storage:
  type: elasticsearch
  esIndexCleaner:
    enabled: false                                # turn the job deployment on and off
    numberOfDays: 7                               # number of days to wait before deleting a record
    schedule: "55 23 * * *"                       # cron expression for it to run
    image: jaegertracing/jaeger-es-index-cleaner  # image of the job

Deriving dependencies

The processing to derive dependencies will collect spans from storage, analyzes links between services and store them for later presentation in the UI. This job can only be used with the production strategy and storage type cassandra or elasticsearch.

storage:
  type: elasticsearch
  dependencies:
    enabled: true                                 # turn the job deployment on and off
    schedule: "55 23 * * *"                       # cron expression for it to run
    sparkMaster:                                  # spark master connection string, when empty spark runs in embedded local mode

The connection configuration to storage is derived from storage options.

Auto-injecting Jaeger Agent Sidecars

The operator can inject Jaeger Agent sidecars in Deployment workloads, provided that the deployment has the annotation sidecar.jaegertracing.io/inject with a suitable value. The values can be either "true" (as string), or the Jaeger instance name, as returned by kubectl get jaegers. When "true" is used, there should be exactly one Jaeger instance for the same namespace as the deployment, otherwise, the operator can’t figure out automatically which Jaeger instance to use.

The following snippet shows a simple application that will get a sidecar injected, with the Jaeger Agent pointing to the single Jaeger instance available in the same namespace:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: myapp
  annotations:
    "sidecar.jaegertracing.io/inject": "true" # <1>
spec:
  selector:
    matchLabels:
      app: myapp
  template:
    metadata:
      labels:
        app: myapp
    spec:
      containers:
      - name: myapp
        image: acme/myapp:myversion

<1> Either "true" (as string) or the Jaeger instance name.

A complete sample deployment is available at deploy/examples/business-application-injected-sidecar.yaml .

When the sidecar is injected, the Jaeger Agent can be accessed at its default location on localhost.

Installing the Agent as DaemonSet

By default, the Operator expects the agents to be deployed as sidecars to the target applications. This is convenient for several purposes, like in a multi-tenant scenario or to have better load balancing, but there are scenarios where you might want to install the agent as a DaemonSet. In that case, specify the Agent’s strategy to DaemonSet, as follows:

apiVersion: jaegertracing.io/v1
kind: Jaeger
metadata:
  name: my-jaeger
spec:
  agent:
    strategy: DaemonSet

Your tracer client will then most likely need to be told where the agent is located. This is usually done by setting the environment variable JAEGER_AGENT_HOST to the value of the Kubernetes node’s IP, for example:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: myapp
spec:
  selector:
    matchLabels:
      app: myapp
  template:
    metadata:
      labels:
        app: myapp
    spec:
      containers:
      - name: myapp
        image: acme/myapp:myversion
        env:
        - name: JAEGER_AGENT_HOST
          valueFrom:
            fieldRef:
              fieldPath: status.hostIP

OpenShift

In OpenShift, a HostPort can only be set when a special security context is set. A separate service account can be used by the Jaeger Agent with the permission to bind to HostPort, as follows:

oc create -f https://raw.githubusercontent.com/jaegertracing/jaeger-operator/main/examples/openshift/hostport-scc-daemonset.yaml # <1>
oc new-project myappnamespace
oc create -f https://raw.githubusercontent.com/jaegertracing/jaeger-operator/main/examples/openshift/service_account_jaeger-agent-daemonset.yaml # <2>
oc adm policy add-scc-to-user daemonset-with-hostport -z jaeger-agent-daemonset # <3>
oc apply -f https://raw.githubusercontent.com/jaegertracing/jaeger-operator/main/examples/openshift/agent-as-daemonset.yaml # <4>

<1> The SecurityContextConstraints with the allowHostPorts policy

<2> The ServiceAccount to be used by the Jaeger Agent

<3> Adds the security policy to the service account

<4> Creates the Jaeger Instance using the serviceAccount created in the steps above

After a few seconds, the DaemonSet should be up and running:

$ oc get daemonset agent-as-daemonset-agent-daemonset
NAME                                 DESIRED   CURRENT   READY     UP-TO-DATE   AVAILABLE
agent-as-daemonset-agent-daemonset   1         1         1         1            1

Secrets Support

The Operator supports passing secrets to the Collector, Query and All-In-One deployments. This can be used for example, to pass credentials (username/password) to access the underlying storage backend (for example: Elasticsearch). The secrets are available as environment variables in the (Collector/Query/All-In-One) nodes.

    storage:
      type: elasticsearch
      options:
        es:
          server-urls: http://elasticsearch:9200
      secretName: jaeger-secrets

The secret itself would be managed outside of the jaeger-operator custom resource.

Configuring the UI

Information on various configuration options for the UI can be found here, defined in json format.

To apply UI configuration changes within the Custom Resource, the same information can be included in yaml format as shown below:

    ui:
      options:
        dependencies:
          menuEnabled: false
        tracking:
          gaID: UA-000000-2
        menu:
        - label: "About Jaeger"
          items:
            - label: "Documentation"
              url: "https://www.jaegertracing.io/docs/latest"
        linkPatterns:
        - type: "logs"
          key: "customer_id"
          url: /search?limit=20&lookback=1h&service=frontend&tags=%7B%22customer_id%22%3A%22#{customer_id}%22%7D
          text: "Search for other traces for customer_id=#{customer_id}"

Defining Sampling Strategies

The operator can be used to define sampling strategies that will be supplied to tracers that have been configured to use a remote sampler:

apiVersion: jaegertracing.io/v1
kind: Jaeger
metadata:
  name: with-sampling
spec:
  strategy: allInOne
  sampling:
    options:
      default_strategy:
        type: probabilistic
        param: 0.5

This example defines a default sampling strategy that is probabilistic, with a 50% chance of the trace instances being sampled.

Refer to the Jaeger documentation on Collector Sampling Configuration  to see how service and endpoint sampling can be configured. The JSON representation described in that documentation can be used in the operator by converting to YAML.

Finer grained configuration

The custom resource can be used to define finer grained Kubernetes configuration applied to all Jaeger components or at the individual component level.

When a common definition (for all Jaeger components) is required, it is defined under the spec node. When the definition relates to an individual component, it is placed under the spec/<component> node.

The types of supported configuration include:

• affinity  to determine which nodes a pod can be allocated to

• annotations 

• labels 

• resources  to limit cpu and memory

• tolerations  in conjunction with taints to enable pods to avoid being repelled from a node

• volumes  and volume mounts

• serviceAccount  to run each component with separate identity

• securityContext  to define privileges of running components

apiVersion: jaegertracing.io/v1
kind: Jaeger
metadata:
  name: simple-prod
spec:
  strategy: production
  storage:
    type: elasticsearch
    options:
      es:
        server-urls: http://elasticsearch:9200
  annotations:
    key1: value1
  labels:
    key2: value2
  resources:
    requests:
      memory: "64Mi"
      cpu: "250m"
    limits:
      memory: "128Mi"
      cpu: "500m"
  affinity:
    nodeAffinity:
      requiredDuringSchedulingIgnoredDuringExecution:
        nodeSelectorTerms:
        - matchExpressions:
          - key: kubernetes.io/e2e-az-name
            operator: In
            values:
            - e2e-az1
            - e2e-az2
      preferredDuringSchedulingIgnoredDuringExecution:
      - weight: 1
        preference:
          matchExpressions:
          - key: another-node-label-key
            operator: In
            values:
            - another-node-label-value
  tolerations:
    - key: "key1"
      operator: "Equal"
      value: "value1"
      effect: "NoSchedule"
    - key: "key1"
      operator: "Equal"
      value: "value1"
      effect: "NoExecute"
  serviceAccount: nameOfServiceAccount
  securityContext:
    runAsUser: 1000
  volumeMounts:
    - name: config-vol
      mountPath: /etc/config
  volumes:
    - name: config-vol
      configMap:
        name: log-config
        items:
          - key: log_level
            path: log_level

Accessing the Jaeger Console (UI)

Kubernetes

The operator creates a Kubernetes ingress  route, which is the Kubernetes’ standard for exposing a service to the outside world, but by default it does not come with Ingress providers. Check the Kubernetes documentation  for the most appropriate way to achieve an Ingress provider for your platform. The following command enables the Ingress provider on minikube:

minikube addons enable ingress

Once Ingress is enabled, the address for the Jaeger console can be found by querying the Ingress object:

$ kubectl get ingress
NAME             HOSTS     ADDRESS          PORTS     AGE
simplest-query   *         192.168.122.34   80        3m

In this example, the Jaeger UI is available at http://192.168.122.34.

OpenShift

When the Operator is running on OpenShift, the Operator will automatically create a Route object for the query services. Use the following command to check the hostname/port:

oc get routes

By default, the Jaeger UI is protected with OpenShift’s OAuth service and any valid user is able to login. To disable this feature and leave the Jaeger UI unsecured, set the Ingress property security to none in the custom resource file:

apiVersion: jaegertracing.io/v1
kind: Jaeger
metadata:
  name: disable-oauth-proxy
spec:
  ingress:
    security: none

Custom SAR and Delegate URL values can be specified as part of the .Spec.Ingress.OpenShift.SAR and .Spec.Ingress.Openshift.DelegateURLs, as follows:

apiVersion: jaegertracing.io/v1
kind: Jaeger
metadata:
  name: custom-sar-oauth-proxy
spec:
  ingress:
    openshift:
      sar: '{"namespace": "default", "resource": "pods", "verb": "get"}'
      delegateUrls: '{"/":{"namespace": "default", "resource": "pods", "verb": "get"}}'

When the delegateUrls is set, the Jaeger Operator needs to create a new ClusterRoleBinding between the service account used by the UI Proxy ({InstanceName}-ui-proxy) and the role system:auth-delegator, as required by the OpenShift OAuth Proxy. Because of that, the service account used by the operator itself needs to have the same cluster role binding. To accomplish that, a ClusterRoleBinding such as the following has to be created:

kind: ClusterRoleBinding
apiVersion: rbac.authorization.k8s.io/v1
metadata:
  name: jaeger-operator-with-auth-delegator
  namespace: observability
subjects:
- kind: ServiceAccount
  name: jaeger-operator
  namespace: observability
roleRef:
  kind: ClusterRole
  name: system:auth-delegator
  apiGroup: rbac.authorization.k8s.io

Cluster administrators not comfortable in letting users deploy Jaeger instances with this cluster role are free to not add this cluster role to the operator’s service account. In that case, the Operator will auto-detect that the required permissions are missing and will log a message similar to: the requested instance specifies the delegateUrls option for the OAuth Proxy, but this operator cannot assign the proper cluster role to it (system:auth-delegator). Create a cluster role binding between the operator's service account and the cluster role 'system:auth-delegator' in order to allow instances to use 'delegateUrls'.

The Jaeger Operator also supports authentication using htpasswd files via the OpenShift OAuth Proxy. To make use of that, specify the htpasswdFile option within the OpenShift-specific entries, pointing to the file htpasswd file location in the local disk. The htpasswd file can be created using the htpasswd utility:

$ htpasswd -cs /tmp/htpasswd jdoe
New password:
Re-type new password:
Adding password for user jdoe

This file can then be used as the input for the kubectl create secret command:

$ kubectl create secret generic htpasswd --from-file=htpasswd=/tmp/htpasswd
secret/htpasswd created

Once the secret is created, it can be specified in the Jaeger CR as a volume/volume mount:

apiVersion: jaegertracing.io/v1
kind: Jaeger
metadata:
  name: with-htpasswd
spec:
  ingress:
    openshift:
      sar: '{"namespace": "default", "resource": "pods", "verb": "get"}'
      htpasswdFile: /usr/local/data/htpasswd
  volumeMounts:
  - name: htpasswd-volume
    mountPath: /usr/local/data
  volumes:
  - name: htpasswd-volume
    secret:
      secretName: htpasswd

Upgrading the Operator and its managed instances

Each version of the Jaeger Operator follows one Jaeger version. Whenever a new version of the Jaeger Operator is installed, all the Jaeger instances managed by the operator will be upgraded to the Operator’s supported version. For example, an instance named simplest that was created with Jaeger Operator 1.12.0 will be running Jaeger 1.12.0. Once the Jaeger Operator is upgraded to 1.13.0, the instance simplest will be upgraded to the version 1.13.0, following the official upgrade instructions from the Jaeger project.

The Jaeger Operator can be upgraded manually by changing the deployment (kubectl edit deployment jaeger-operator), or via specialized tools such as the Operator Lifecycle Manager (OLM) .

Updating a Jaeger instance (experimental)

A Jaeger instance can be updated by changing the CustomResource, either via kubectl edit jaeger simplest, where simplest is the Jaeger’s instance name, or by applying the updated YAML file via kubectl apply -f simplest.yaml.

Simpler changes such as changing the replica sizes can be applied without much concern, whereas changes to the strategy should be watched closely and might potentially cause an outage for individual components (collector/query/agent).

While changing the backing storage is supported, migration of the data is not.

Removing a Jaeger instance

To remove an instance, use the delete command with the custom resource file used when you created the instance:

kubectl delete -f simplest.yaml

Alternatively, you can remove a Jaeger instance by running:

kubectl delete jaeger simplest

Monitoring the operator

The Jaeger Operator starts a Prometheus-compatible endpoint on 0.0.0.0:8383/metrics with internal metrics that can be used to monitor the process.

Uninstalling the operator

To uninstall the operator, run the following commands:

kubectl delete -f https://raw.githubusercontent.com/jaegertracing/jaeger-operator/main/deploy/operator.yaml
kubectl delete -f https://raw.githubusercontent.com/jaegertracing/jaeger-operator/main/deploy/role_binding.yaml
kubectl delete -f https://raw.githubusercontent.com/jaegertracing/jaeger-operator/main/deploy/role.yaml
kubectl delete -f https://raw.githubusercontent.com/jaegertracing/jaeger-operator/main/deploy/service_account.yaml
kubectl delete -f https://raw.githubusercontent.com/jaegertracing/jaeger-operator/main/deploy/crds/jaegertracing.io_jaegers_crd.yaml