Co-authors: Luiz Bernardo Levenhagen and Leonardo Araujo
In this article, we will demonstrate how to integrate Openshift with Datadog using
Datadog operatorto collect metrics,logs, events and also applications' data.In this article we use the following versions:
- Openshift v4.13.11
- Datadog Operator v1.3.0
- Datadog account (more information on how to request a trial at the bottom of the blog)
About
This article is aimed at users who would like to integrate or monitor their
Openshift Clusterusing theDatadog monitoring solution.We will use the datadog operator to instantiate our agent and collect all metrics(cluster/containers), cluster and container/pod logs, network, cpu, memory consumption as well as applications' data.
Red Hat does not support the DataDog operator or its configuration, for any questions related to the use of the platform or operator, contact DataDog.
Prerequisites
- User with the cluster-admin cluster role
- Openshift 4.10 or +
- Datadog account (more information on how to request a trial at the bottom of the blog)
Procedure
Datadog
Add API Keys
- To add a new
datadog API Key, navigate toOrganization Settings>API Keys - If you have the permission to create API keys, click
New Keyin the top right corner. - Define the desired name, something that can help you identify in the future.
- Once created, copy the Key so we can use it later.
Add Application keys
- To add a new
datadog Application Key, navigate toOrganization Settings>Application Keys - If you have the permission to create Application Keys, click
New Keyin the top right corner. - Define the desired name, something that can help you identify in the future.
- Once created, copy the Key so we can use it later.
Openshift
Datadog Operator Install
- In the Openshift console, in the left side menu, click
Operator>OperatorHub> in thesearch field, typedatadog
💡 Tip
Whenever available, use a certified option.
- As we can see, we are using version 1.3.0 of operator, click
Install.
- On this screen, we will keep all the default options:
- Update channel:
stable - Installation mode:
All namespaces the cluster(default) - Installed Namespace:
openshift-operators - Update approval:
Automatic- Obs.: If you prefer, you can use the Manual option.
- Click
Install.
- Update channel:
- Wait until the installation is complete.
Create secret with Datadog keys (not mandatory, but good practice)
- In the terminal, access the openshift-operators namespace context
$ oc project openshift-operators
- Now let's create a secret to store in this API Key and Application Key, replace the values below with the keys we generated previously in the Datadog console.
$ oc create secret generic datadog-secret \
--from-literal api-key=`REPLACE_ME` \
--from-literal app-key=`REPLACE_ME`
- Let's now instatiate our datadog agent using the yaml below
$ cat <<EOF > datadog_agent.yaml
apiVersion: datadoghq.com/v2alpha1
kind: DatadogAgent
metadata:
name: datadog
namespace: openshift-operators
spec:
features:
apm:
enabled: true
unixDomainSocketConfig:
enabled: true
clusterChecks:
enabled: true
useClusterChecksRunners: true
dogstatsd:
originDetectionEnabled: true
unixDomainSocketConfig:
enabled: true
eventCollection:
collectKubernetesEvents: true
liveContainerCollection:
enabled: true
liveProcessCollection:
enabled: true
logCollection:
containerCollectAll: true
enabled: true
npm:
collectDNSStats: true
enableConntrack: true
enabled: true
global:
clusterName: DemoLab
credentials:
apiSecret:
keyName: api-key
secretName: datadog-secret
appSecret:
keyName: app-key
secretName: datadog-secret
criSocketPath: /var/run/crio/crio.sock
kubelet:
tlsVerify: false
site: datadoghq.eu
override:
clusterAgent:
containers:
cluster-agent:
securityContext:
readOnlyRootFilesystem: false
replicas: 2
serviceAccountName: datadog-agent-scc
nodeAgent:
hostNetwork: true
securityContext:
runAsUser: 0
seLinuxOptions:
level: s0
role: system_r
type: spc_t
user: system_u
serviceAccountName: datadog-agent-scc
tolerations:
- operator: Exists
- effect: NoSchedule
key: node-role.kubernetes.io/master
EOF
- Some explanations about what we are enabling in this agent
Enabling the APM (Application Performance Monitoring) feature
apm:
enabled: true
unixDomainSocketConfig:
enabled: true
Cluster Check extends the autodiscover function to non-containerized resources and checks if there is some integration/technology to monitor.
clusterChecks:
enabled: true
useClusterChecksRunners: true
Dogstatsd is responsible for collecting custom metrics and events and sending them from time to time to a metrics aggregation service on the Datadog server.
dogstatsd:
originDetectionEnabled: true
unixDomainSocketConfig:
enabled: true
Here we are enabling the collection of all logs (including container logs) and events generated in our cluster and sending them to Datadog.
eventCollection:
collectKubernetesEvents: true
liveContainerCollection:
enabled: true
liveProcessCollection:
enabled: true
logCollection:
containerCollectAll: true
enabled: true
With NPM (Network Performance Monitoring), we can have visibility of all traffic in our cluster, nodes, containers, availability zones, etc.
npm:
collectDNSStats: true
enableConntrack: true
enabled: true
In the credentials block in Global, we have the definition of the secret previously created with the API and app key.
credentials:
apiSecret:
keyName: api-key
secretName: datadog-secret
appSecret:
keyName: app-key
secretName: datadog-secret
In this block, we define the path to the cri-o service socket, we define the non-checking of tls for communication with the kubelet and in website, we define which datadog server will receive the data sent.
criSocketPath: /var/run/crio/crio.sock
kubelet:
tlsVerify: false
site: datadoghq.eu
In the clusterAgent block in override, we add SecurityContext(scc) settings and which serviceaccount should be used in the datadog-cluster-agent pods.
clusterAgent:
containers:
cluster-agent:
securityContext:
readOnlyRootFilesystem: false
replicas: 2
serviceAccountName: datadog-agent-scc
❗Note
Thedatadog-agent-scc serviceaccountis created automatically by the operator and already has all the necessary permissions for the agent to run correctly.
In the nodeAgent block in override, we define settings for SecurityContext for the datadog-agent pods, we will use the same datadog-agent-scc serviceaccount and we also define the tolerations for the nodes that have taints created, in our case for the master nodes.
nodeAgent:
hostNetwork: true
securityContext:
runAsUser: 0
seLinuxOptions:
level: s0
role: system_r
type: spc_t
user: system_u
serviceAccountName: datadog-agent-scc
tolerations:
- operator: Exists
- effect: NoSchedule
key: node-role.kubernetes.io/master
- After some explanations, let's deploy our datadog agent. Execute this command to create the object:
$ oc -n openshift-operators create -f datadog_agent.yaml
- Once created, we will validate that our agent was created correctly
$ oc -n openshift-operators get datadogagent
$ oc -n openshift-operators get pods
❗Note
Here we should have a datadog-agent running on each available openshift node.
❗Information
datadog-agent-xxxxxpods, is responsible for collecting all metrics, events, traces and logs from each node in the cluster.datadog-cluster-agent-xxxxxpods, will act as a proxy between the API server and node-based agents, Cluster Agent helps to ease the server load.
- Now let's validate the logs of the datadog-agent-xxxxx pods, to identify if there is any communication error.
$ oc logs -f -l app.kubernetes.io/managed-by=datadog-operator --max-log-requests 10
Datadog platform/UI
- Now on the Datadog platform, in the left side menu, click on
Infrastructure > and then onInfrastructure List`
❗Information
Server data, such as status, cpu information, memory and other details, may take a few minutes to be displayed.
- To view more details about a specific node, click on the node name and navigate through the available tabs. It’s just the simplest way to check your nodes/hosts.
- Under the
Infrastructuremenu, Datadog also gives you an exclusiveKubernetesmenu where you have the full picture about your cluster. You can check the state of all of your Kubernetes resources, troubleshoot patterns, access out-of-the-box Dashboards and enable some recommended Alerts to monitor your environment
- You can also explore deeper the containers running in your Openshift environment, going to
Infrastructure > Containers. Here you get chance to analyse things like logs from containers, traces, networking layer, processes running inside the container and so on...
- To view more details about network traffic, in the left side menu, go to
Infrastructure >Network Map`
- To view the logs received from the cluster or from any application or technology running in your kubernetes environment, in the left side menu, go to
Logs>Analytics, on this screen, we can view all the details, filter application logs and even view the processes.
- To view all collected metrics, in the left side menu, go to
Metrics >Explorer`, here we can view all metrics, run and save queries or create dashboards based on queries.
- Datadog provides out-of-the-box Dashboards that can be used and customized. To use one available, in the left side menu, go to
Dashboards >Dashboard List` > choose the dashboard and click on the name.
❗Note:
To customize a dashboard provided by Datadog, use the Clone feature to make the desired changes and save.
Conclusion
Using the Datadog Operator solution, we can have a complete monitoring solution for our Openshift cluster with main features such as APM, Network Analysis, Logs, Events and Metrics.
To request an Openshift trial and learn more about our solution, click here.
To request a Datadog trial and be able to replicate this knowledge, click here.
References
For more details and other configurations, start with the reference documents below.
Top comments (2)
Hello, welcome here, and thank you for your detailed walkthrough !
I was wondering : is it different from installing to a vanilla Kubernetes, or would it apply the same ? What are the key differences ? Does it depend on the Cloud provider ?
Hey @bcouetil ! happy to see here in my first post. I have not tried an env different than Openshift, so not sure if this will work in a "simple" Vanilla k8s (even though Openshift uses Vanilla, there are a lot of functionalities out of the box extending the Kubernetes, like native Operators). And no matter the Cloud provider, it should work the same.