The current recommended way of installing and managing Jaeger in a production Kubernetes cluster is via the Jaeger Operator.
You can still use, report issues and send pull-requests against this repository, but not all features from the Operator are possible or will be backported to the templates from this repository here.
Use the templates from this repository if you need a quick start and don't want to install the Operator.
Please see CONTRIBUTING.md
This template uses an in-memory storage with a limited functionality for local testing and development. The image used defaults to the latest version released. Do not use this template in production environments. Note that functionality may differ from the pinned docker versions for production.
Install everything in the current namespace:
kubectl create -f https://raw.githubusercontent.com/jaegertracing/jaeger-kubernetes/master/all-in-one/jaeger-all-in-one-template.ymlOnce everything is ready, kubectl get service jaeger-query tells you where to find Jaeger URL.
If you are using minikube to setup your Kubernetes cluster, the command minikube service jaeger-query --url
can be used instead.
The docker image tags are manually pinned and manually updated. You should use the current pinned version for production.
The Jaeger Collector and Query require a backing storage to exist before being started up. As a starting point for your own templates, we provide basic templates deploying Cassandra and Elasticsearch. None of them are ready for production and should be adapted before any real usage.
To use our Cassandra template:
kubectl create -f https://raw.githubusercontent.com/jaegertracing/jaeger-kubernetes/master/production/configmap.yml
kubectl create -f https://raw.githubusercontent.com/jaegertracing/jaeger-kubernetes/master/production/cassandra.yml
For Elasticsearch, use:
kubectl create -f https://raw.githubusercontent.com/jaegertracing/jaeger-kubernetes/master/production-elasticsearch/configmap.yml
kubectl create -f https://raw.githubusercontent.com/jaegertracing/jaeger-kubernetes/master/production-elasticsearch/elasticsearch.yml
The Cassandra template includes also a Kubernetes Job that creates the schema required by the Jaeger components. It's advisable
to wait for this job to finish before deploying the Jaeger components. To check the status of the job, run:
kubectl get job jaeger-cassandra-schema-job
The job should have 1 in the SUCCESSFUL column.
The Jaeger Collector, Query and Agent require a ConfigMap to exist on the same namespace, named jaeger-configuration.
This ConfigMap is included in the storage templates, as each backing storage have their own specific configuration entries,
but in your environment, you'll probably manage it differently.
If changes are required for the configuration, the edit command can be used:
kubectl edit configmap jaeger-configuration
The main production template deploys the Collector and the Query Service (with UI) as separate individually scalable services,
as well as the Agent as DaemonSet.
kubectl create -f https://raw.githubusercontent.com/jaegertracing/jaeger-kubernetes/master/jaeger-production-template.yml
If the backing storage is not ready by the time the Collector/Agent start, they will fail and Kubernetes will reschedule the pod. It's advisable to either wait for the backing storage to stabilize, or to ignore such failures for the first few minutes.
Once everything is ready, kubectl get service jaeger-query tells you where to find Jaeger URL, or
minikube service jaeger-query --url when using minikube.
As the agent is deployed as a DaemonSet, the node's IP address can be stored as an environment variable and passed down
to the application as:
env:
- name: JAEGER_AGENT_HOST
valueFrom:
fieldRef:
fieldPath: status.hostIPThe Jaeger Agent is designed to be deployed local to your service, so that it can receive traces via UDP keeping your
application's load minimal. By default, the template above installs the agent as a DaemonSet, but this means that all
pods running on a given node will send data to the same agent. If that's not suitable for your workload, an alternative
is to deploy the agent as a sidecar. To accomplish that, just add it as a container within any struct that supports
spec.containers, like a Pod, Deployment and so on. More about this be found on the blog post
Deployment strategies for the Jaeger Agent.
Assuming that your application is named myapp and the image is for it is mynamespace/hello-myimage, your
Deployment descriptor would be something like:
- apiVersion: apps/v1
kind: Deployment
metadata:
name: myapp
spec:
selector:
matchLabels:
app.kubernetes.io/name: myapp
template:
metadata:
labels:
app.kubernetes.io/name: myapp
spec:
containers:
- image: mynamespace/hello-myimage
name: myapp
ports:
- containerPort: 8080
- image: jaegertracing/jaeger-agent
name: jaeger-agent
ports:
- containerPort: 5775
protocol: UDP
- containerPort: 6831
protocol: UDP
- containerPort: 6832
protocol: UDP
- containerPort: 5778
protocol: TCP
args: ["--collector.host-port=jaeger-collector.jaeger-infra.svc:14267"]The Jaeger Agent will then be available to your application at localhost:5775/localhost:6831/localhost:6832/localhost:5778.
In most cases, you don't need to specify a hostname or port to your Jaeger Tracer, as it will default to the right
values already.
As the Jaeger Agent is deployed with the other components, your application needs to tell the Jaeger Client where to find the agent. Refer to your client's documentation for the appropriate mechanism, but most clients allow this to be set via the environment variable JAEGER_AGENT_HOST in environment variable like so:
env:
- name: JAEGER_SERVICE_NAME
value: <YOUR SERVICE NAME>
- name: JAEGER_AGENT_HOST
value: jaeger-all-in-one-agent
- name: JAEGER_SAMPLER_TYPE
value: const
- name: JAEGER_SAMPLER_PARAM
value: "1"The following service names are supported by HTTP sender:
| Service Name | Port |
|---|---|
jaeger-collector |
14268 |
zipkin |
9411 |
The following service names are supported by UDP sender:
- jaeger-agent
Even though this template uses a stateful Cassandra, backing storage is set to emptyDir. It's more
appropriate to create a PersistentVolumeClaim/PersistentVolume and use it instead. Note that this
Cassandra deployment does not support deleting pods or scaling down, as this might require
administrative tasks that are dependent on the final deployment architecture.
Jaeger production deployment needs an external process to derive dependency links between services. Project spark-dependencies provides this functionality.
This job should be periodically run before end of a day. The following command creates CronJob
scheduled 5 minutes before the midnight.
For Cassandra, use:
kubectl run jaeger-spark-dependencies --schedule="55 23 * * *" --env="STORAGE=cassandra" --env="CASSANDRA_CONTACT_POINTS=cassandra:9042" --restart=Never --image=jaegertracing/spark-dependenciesFor Elasticsearch, use:
kubectl run jaeger-spark-dependencies --schedule="55 23 * * *" --env="STORAGE=elasticsearch" --env="ES_NODES=elasticsearch:9200" --env="ES_USERNAME=changeme" --env="ES_PASSWORD=changeme" --restart=Never --image=jaegertracing/spark-dependenciesIf you want to run the job only once and immediately then remove scheduled flag.
The Jaeger project automatically creates new Docker images with tags that mirror the release number. The production manifests uses pinned versions as to not accidentally break people on new releases.
A general tip for deploying docker images (i.e. on kubernetes): it's recommended that you do not use the tag
:latestin production but rather pin the latest version. See the kubernetes best practices for more details.
A curated Chart for Kubernetes Helm that adds all components required to run Jaeger.
If you need to remove the Jaeger components created by this template, run:
kubectl delete all,daemonset,configmap -l jaeger-infraTests are based on Arquillian Cube which require an active connection to
kubernetes cluster (via kubectl). When executing tests from IDE make sure that template is copied to
target/test-classes.
minikube start
./mvnw clean verify -Pcassandra,elasticsearch,all-in-one