About log collection and forwarding - Log collection and forwarding | Logging

Log collection
- Log collector types
- Log collection limitations
- Log collector features by type
- Collector outputs
Log forwarding
Log forwarding implementations
- Legacy implementation
- Multi log forwarder feature
Enabling the multi log forwarder feature for a cluster
- Authorizing log collection RBAC permissions
Creating a log forwarder
Enabling multi-line exception detection
- Details
- Troubleshooting
Sending audit logs to the internal log store
About forwarding logs to third-party systems
- Creating a Secret
Forwarding JSON logs from containers in the same pod to separate indices
Forwarding logs to an external Elasticsearch instance
Forwarding logs using the Fluentd forward protocol
- Enabling nanosecond precision for Logstash to ingest data from fluentd
Forwarding logs using the syslog protocol
- Adding log source information to message output
- Syslog parameters
- Additional RFC5424 syslog parameters
Forwarding logs to a Kafka broker
Forwarding logs to Amazon CloudWatch
- Forwarding logs to Amazon CloudWatch from STS enabled clusters
- Creating a secret for AWS CloudWatch with an existing AWS role
Forwarding logs to Loki
- Troubleshooting Loki rate limit errors
Forwarding logs to Google Cloud Platform (GCP)
Forwarding logs to Splunk
Forwarding logs over HTTP
Forwarding application logs from specific projects
Forwarding application logs from specific pods
Troubleshooting log forwarding

The Red Hat OpenShift Logging Operator deploys a collector based on the ClusterLogForwarder resource specification. There are two collector options supported by this Operator: the legacy Fluentd collector, and the Vector collector.

Fluentd is deprecated and is planned to be removed in a future release. Red Hat provides bug fixes and support for this feature during the current release lifecycle, but this feature no longer receives enhancements. As an alternative to Fluentd, you can use Vector instead.

Log collection

The log collector is a daemon set that deploys pods to each OpenShift Container Platform node to collect container and node logs.

By default, the log collector uses the following sources:

System and infrastructure logs generated by journald log messages from the operating system, the container runtime, and OpenShift Container Platform.
/var/log/containers/*.log for all container logs.

If you configure the log collector to collect audit logs, it collects them from /var/log/audit/audit.log.

The log collector collects the logs from these sources and forwards them internally or externally depending on your logging configuration.

Log collector types

Vector is a log collector offered as an alternative to Fluentd for the logging.

You can configure which logging collector type your cluster uses by modifying the ClusterLogging custom resource (CR) collection spec:

Example ClusterLogging CR that configures Vector as the collector

  apiVersion: "logging.openshift.io/v1"
  kind: ClusterLogging
  metadata:
    name: instance
    namespace: openshift-logging
  spec:
    collection:
    logs:
      type: vector
      vector: {}
# ...

Log collection limitations

The container runtimes provide minimal information to identify the source of log messages: project, pod name, and container ID. This information is not sufficient to uniquely identify the source of the logs. If a pod with a given name and project is deleted before the log collector begins processing its logs, information from the API server, such as labels and annotations, might not be available. There might not be a way to distinguish the log messages from a similarly named pod and project or trace the logs to their source. This limitation means that log collection and normalization are considered best effort.

The available container runtimes provide minimal information to identify the source of log messages and do not guarantee unique individual log messages or that these messages can be traced to their source.

Log collector features by type

Table 1. Log Sources
Feature	Fluentd	Vector
App container logs	✓	✓
App-specific routing	✓	✓
App-specific routing by namespace	✓	✓
Infra container logs	✓	✓
Infra journal logs	✓	✓
Kube API audit logs	✓	✓
OpenShift API audit logs	✓	✓
Open Virtual Network (OVN) audit logs	✓	✓

Table 2. Authorization and Authentication
Feature	Fluentd	Vector
Elasticsearch certificates	✓	✓
Elasticsearch username / password	✓	✓
Cloudwatch keys	✓	✓
Cloudwatch STS	✓	✓
Kafka certificates	✓	✓
Kafka username / password	✓	✓
Kafka SASL	✓	✓
Loki bearer token	✓	✓

Table 3. Normalizations and Transformations
Feature	Fluentd	Vector
Viaq data model - app	✓	✓
Viaq data model - infra	✓	✓
Viaq data model - infra(journal)	✓	✓
Viaq data model - Linux audit	✓	✓
Viaq data model - kube-apiserver audit	✓	✓
Viaq data model - OpenShift API audit	✓	✓
Viaq data model - OVN	✓	✓
Loglevel Normalization	✓	✓
JSON parsing	✓	✓
Structured Index	✓	✓
Multiline error detection	✓	✓
Multicontainer / split indices	✓	✓
Flatten labels	✓	✓
CLF static labels	✓	✓

Table 4. Tuning
Feature	Fluentd	Vector
Fluentd readlinelimit	✓
Fluentd buffer	✓
- chunklimitsize	✓
- totallimitsize	✓
- overflowaction	✓
- flushthreadcount	✓
- flushmode	✓
- flushinterval	✓
- retrywait	✓
- retrytype	✓
- retrymaxinterval	✓
- retrytimeout	✓

Table 5. Visibility
Feature	Fluentd	Vector
Metrics	✓	✓
Dashboard	✓	✓
Alerts	✓	✓

Table 6. Miscellaneous
Feature	Fluentd	Vector
Global proxy support	✓	✓
x86 support	✓	✓
ARM support	✓	✓
IBM Power support	✓	✓
IBM Z support	✓	✓
IPv6 support	✓	✓
Log event buffering	✓
Disconnected Cluster	✓	✓

Collector outputs

The following collector outputs are supported:

Table 7. Supported outputs
Feature	Fluentd	Vector
Elasticsearch v6-v8	✓	✓
Fluent forward	✓
Syslog RFC3164	✓	✓ (Logging 5.7+)
Syslog RFC5424	✓	✓ (Logging 5.7+)
Kafka	✓	✓
Cloudwatch	✓	✓
Cloudwatch STS	✓	✓
Loki	✓	✓
HTTP	✓	✓ (Logging 5.7+)
Google Cloud Logging	✓	✓
Splunk		✓ (Logging 5.6+)

Log forwarding

Administrators can create ClusterLogForwarder resources that specify which logs are collected, how they are transformed, and where they are forwarded to.

ClusterLogForwarder resources can be used up to forward container, infrastructure, and audit logs to specific endpoints within or outside of a cluster. Transport Layer Security (TLS) is supported so that log forwarders can be configured to send logs securely.

Administrators can also authorize RBAC permissions that define which service accounts and users can access and forward which types of logs.

Log forwarding implementations

There are two log forwarding implementations available: the legacy implementation, and the multi log forwarder feature.

Only the Vector collector is supported for use with the multi log forwarder feature. The Fluentd collector can only be used with legacy implementations.

Legacy implementation

In legacy implementations, you can only use one log forwarder in your cluster. The ClusterLogForwarder resource in this mode must be named instance, and must be created in the openshift-logging namespace. The ClusterLogForwarder resource also requires a corresponding ClusterLogging resource named instance in the openshift-logging namespace.

Multi log forwarder feature

The multi log forwarder feature is available in logging 5.8 and later, and provides the following functionality:

Administrators can control which users are allowed to define log collection and which logs they are allowed to collect.
Users who have the required permissions are able to specify additional log collection configurations.
Administrators who are migrating from the deprecated Fluentd collector to the Vector collector can deploy a new log forwarder separately from their existing deployment. The existing and new log forwarders can operate simultaneously while workloads are being migrated.

In multi log forwarder implementations, you are not required to create a corresponding ClusterLogging resource for your ClusterLogForwarder resource. You can create multiple ClusterLogForwarder resources using any name, in any namespace, with the following exceptions:

You cannot create a ClusterLogForwarder resource named instance in the openshift-logging namespace, because this is reserved for a log forwarder that supports the legacy workflow using the Fluentd collector.
You cannot create a ClusterLogForwarder resource named collector in the openshift-logging namespace, because this is reserved for the collector.

Enabling the multi log forwarder feature for a cluster

To use the multi log forwarder feature, you must create a service account and cluster role bindings for that service account. You can then reference the service account in the ClusterLogForwarder resource to control access permissions.

In order to support multi log forwarding in additional namespaces other than the openshift-logging namespace, you must update the Red Hat OpenShift Logging Operator to watch all namespaces. This functionality is supported by default in new Red Hat OpenShift Logging Operator version 5.8 installations.

Authorizing log collection RBAC permissions

In logging 5.8 and later, the Red Hat OpenShift Logging Operator provides collect-audit-logs, collect-application-logs, and collect-infrastructure-logs cluster roles, which enable the collector to collect audit logs, application logs, and infrastructure logs respectively.

You can authorize RBAC permissions for log collection by binding the required cluster roles to a service account.

Prerequisites

The Red Hat OpenShift Logging Operator is installed in the openshift-logging namespace.
You have administrator permissions.

Procedure

Create a service account for the collector. If you want to write logs to storage that requires a token for authentication, you must include a token in the service account.

Bind the appropriate cluster roles to the service account:

Example binding command

$ oc adm policy add-cluster-role-to-user <cluster_role_name> system:serviceaccount:<namespace_name>:<service_account_name>

Additional resources

Creating a log forwarder

To create a log forwarder, you must create a ClusterLogForwarder CR that specifies the log input types that the service account can collect. You can also specify which outputs the logs can be forwarded to. If you are using the multi log forwarder feature, you must also reference the service account in the ClusterLogForwarder CR.

If you are using the multi log forwarder feature on your cluster, you can create ClusterLogForwarder custom resources (CRs) in any namespace, using any name. If you are using a legacy implementation, the ClusterLogForwarder CR must be named instance, and must be created in the openshift-logging namespace.

You need administrator permissions for the namespace where you create the ClusterLogForwarder CR.

ClusterLogForwarder resource example

apiVersion: "logging.openshift.io/v1"
kind: ClusterLogForwarder
metadata:
  name: <log_forwarder_name> (1)
  namespace: <log_forwarder_namespace> (2)
spec:
  serviceAccountName: <service_account_name> (3)
  pipelines:
   - inputRefs:
     - <log_type> (4)
     outputRefs:
     - <output_name> (5)
  outputs:
  - name: <output_name> (6)
    type: <output_type> (5)
    url: <log_output_url> (7)
# ...

1 In legacy implementations, the CR name must be instance. In multi log forwarder implementations, you can use any name.

2 In legacy implementations, the CR namespace must be openshift-logging. In multi log forwarder implementations, you can use any namespace.

3 The name of your service account. The service account is only required in multi log forwarder implementations.

4 The log types that are collected. The value for this field can be audit for audit logs, application for application logs, infrastructure for infrastructure logs, or a named input that has been defined for your application.

The type of output that you want to forward logs to. The value of this field can be default, loki, kafka, elasticsearch, fluentdForward, syslog, or cloudwatch.

The default output type is not supported in mutli log forwarder implementations.

6 A name for the output that you want to forward logs to.

7 The URL of the output that you want to forward logs to.

Enabling multi-line exception detection

Enables multi-line error detection of container logs.

Enabling this feature could have performance implications and may require additional computing resources or alternate logging solutions.

Log parsers often incorrectly identify separate lines of the same exception as separate exceptions. This leads to extra log entries and an incomplete or inaccurate view of the traced information.

Example java exception

java.lang.NullPointerException: Cannot invoke "String.toString()" because "<param1>" is null
    at testjava.Main.handle(Main.java:47)
    at testjava.Main.printMe(Main.java:19)
    at testjava.Main.main(Main.java:10)

To enable logging to detect multi-line exceptions and reassemble them into a single log entry, ensure that the ClusterLogForwarder Custom Resource (CR) contains a detectMultilineErrors field, with a value of true.

Example ClusterLogForwarder CR

apiVersion: logging.openshift.io/v1
kind: ClusterLogForwarder
metadata:
  name: instance
  namespace: openshift-logging
spec:
  pipelines:
    - name: my-app-logs
      inputRefs:
        - application
      outputRefs:
        - default
      detectMultilineErrors: true

Details

When log messages appear as a consecutive sequence forming an exception stack trace, they are combined into a single, unified log record. The first log message’s content is replaced with the concatenated content of all the message fields in the sequence.

Table 8. Supported languages per collector:
Language	Fluentd	Vector
Java	✓	✓
JS	✓	✓
Ruby	✓	✓
Python	✓	✓
Golang	✓	✓
PHP	✓
Dart	✓	✓

Troubleshooting

When enabled, the collector configuration will include a new section with type: detect_exceptions

Example vector configuration section

[transforms.detect_exceptions_app-logs]
 type = "detect_exceptions"
 inputs = ["application"]
 languages = ["All"]
 group_by = ["kubernetes.namespace_name","kubernetes.pod_name","kubernetes.container_name"]
 expire_after_ms = 2000
 multiline_flush_interval_ms = 1000

Example fluentd config section

<label @MULTILINE_APP_LOGS>
  <match kubernetes.**>
    @type detect_exceptions
    remove_tag_prefix 'kubernetes'
    message message
    force_line_breaks true
    multiline_flush_interval .2
  </match>
</label>

Sending audit logs to the internal log store

By default, the logging sends container and infrastructure logs to the default internal log store defined in the ClusterLogging custom resource. However, it does not send audit logs to the internal store because it does not provide secure storage. If this default configuration meets your needs, you do not need to configure the Cluster Log Forwarder.

To send audit logs to the internal Elasticsearch log store, use the Cluster Log Forwarder as described in Forwarding audit logs to the log store.

About forwarding logs to third-party systems

To send logs to specific endpoints inside and outside your OpenShift Container Platform cluster, you specify a combination of outputs and pipelines in a ClusterLogForwarder custom resource (CR). You can also use inputs to forward the application logs associated with a specific project to an endpoint. Authentication is provided by a Kubernetes Secret object.

output

The destination for log data that you define, or where you want the logs sent. An output can be one of the following types:

elasticsearch. An external Elasticsearch instance. The elasticsearch output can use a TLS connection.
fluentdForward. An external log aggregation solution that supports Fluentd. This option uses the Fluentd forward protocols. The fluentForward output can use a TCP or TLS connection and supports shared-key authentication by providing a shared_key field in a secret. Shared-key authentication can be used with or without TLS.
syslog. An external log aggregation solution that supports the syslog RFC3164 or RFC5424 protocols. The syslog output can use a UDP, TCP, or TLS connection.
cloudwatch. Amazon CloudWatch, a monitoring and log storage service hosted by Amazon Web Services (AWS).
loki. Loki, a horizontally scalable, highly available, multi-tenant log aggregation system.
kafka. A Kafka broker. The kafka output can use a TCP or TLS connection.
default. The internal OpenShift Container Platform Elasticsearch instance. You are not required to configure the default output. If you do configure a default output, you receive an error message because the default output is reserved for the Red Hat OpenShift Logging Operator.

pipeline

Defines simple routing from one log type to one or more outputs, or which logs you want to send. The log types are one of the following:

application. Container logs generated by user applications running in the cluster, except infrastructure container applications.
infrastructure. Container logs from pods that run in the openshift*, kube*, or default projects and journal logs sourced from node file system.
audit. Audit logs generated by the node audit system, auditd, Kubernetes API server, OpenShift API server, and OVN network.

You can add labels to outbound log messages by using key:value pairs in the pipeline. For example, you might add a label to messages that are forwarded to other data centers or label the logs by type. Labels that are added to objects are also forwarded with the log message.

input

Forwards the application logs associated with a specific project to a pipeline.

In the pipeline, you define which log types to forward using an inputRef parameter and where to forward the logs to using an outputRef parameter.

Secret

A key:value map that contains confidential data such as user credentials.

Note the following:

If a ClusterLogForwarder CR object exists, logs are not forwarded to the default Elasticsearch instance, unless there is a pipeline with the default output.
By default, the logging sends container and infrastructure logs to the default internal Elasticsearch log store defined in the ClusterLogging custom resource. However, it does not send audit logs to the internal store because it does not provide secure storage. If this default configuration meets your needs, do not configure the Log Forwarding API.
If you do not define a pipeline for a log type, the logs of the undefined types are dropped. For example, if you specify a pipeline for the application and audit types, but do not specify a pipeline for the infrastructure type, infrastructure logs are dropped.
You can use multiple types of outputs in the ClusterLogForwarder custom resource (CR) to send logs to servers that support different protocols.
The internal OpenShift Container Platform Elasticsearch instance does not provide secure storage for audit logs. We recommend you ensure that the system to which you forward audit logs is compliant with your organizational and governmental regulations and is properly secured. The logging does not comply with those regulations.

The following example forwards the audit logs to a secure external Elasticsearch instance, the infrastructure logs to an insecure external Elasticsearch instance, the application logs to a Kafka broker, and the application logs from the my-apps-logs project to the internal Elasticsearch instance.

Sample log forwarding outputs and pipelines

apiVersion: "logging.openshift.io/v1"
kind: ClusterLogForwarder
metadata:
  name: instance (1)
  namespace: openshift-logging (2)
spec:
  outputs:
   - name: elasticsearch-secure (3)
     type: "elasticsearch"
     url: https://elasticsearch.secure.com:9200
     secret:
        name: elasticsearch
   - name: elasticsearch-insecure (4)
     type: "elasticsearch"
     url: http://elasticsearch.insecure.com:9200
   - name: kafka-app (5)
     type: "kafka"
     url: tls://kafka.secure.com:9093/app-topic
  inputs: (6)
   - name: my-app-logs
     application:
        namespaces:
        - my-project
  pipelines:
   - name: audit-logs (7)
     inputRefs:
      - audit
     outputRefs:
      - elasticsearch-secure
      - default
     labels:
       secure: "true" (8)
       datacenter: "east"
   - name: infrastructure-logs (9)
     inputRefs:
      - infrastructure
     outputRefs:
      - elasticsearch-insecure
     labels:
       datacenter: "west"
   - name: my-app (10)
     inputRefs:
      - my-app-logs
     outputRefs:
      - default
   - inputRefs: (11)
      - application
     outputRefs:
      - kafka-app
     labels:
       datacenter: "south"

1	The name of the `ClusterLogForwarder` CR must be `instance`.
2	The namespace for the `ClusterLogForwarder` CR must be `openshift-logging`.
3	Configuration for an secure Elasticsearch output using a secret with a secure URL. A name to describe the output. The type of output: `elasticsearch`. The secure URL and port of the Elasticsearch instance as a valid absolute URL, including the prefix. The secret required by the endpoint for TLS communication. The secret must exist in the `openshift-logging` project.
4	Configuration for an insecure Elasticsearch output: A name to describe the output. The type of output: `elasticsearch`. The insecure URL and port of the Elasticsearch instance as a valid absolute URL, including the prefix.
5	Configuration for a Kafka output using a client-authenticated TLS communication over a secure URL A name to describe the output. The type of output: `kafka`. Specify the URL and port of the Kafka broker as a valid absolute URL, including the prefix.
6	Configuration for an input to filter application logs from the `my-project` namespace.
7	Configuration for a pipeline to send audit logs to the secure external Elasticsearch instance: A name to describe the pipeline. The `inputRefs` is the log type, in this example `audit`. The `outputRefs` is the name of the output to use, in this example `elasticsearch-secure` to forward to the secure Elasticsearch instance and `default` to forward to the internal Elasticsearch instance. Optional: Labels to add to the logs.
8	Optional: String. One or more labels to add to the logs. Quote values like "true" so they are recognized as string values, not as a boolean.
9	Configuration for a pipeline to send infrastructure logs to the insecure external Elasticsearch instance.
10	Configuration for a pipeline to send logs from the `my-project` project to the internal Elasticsearch instance. A name to describe the pipeline. The `inputRefs` is a specific input: `my-app-logs`. The `outputRefs` is `default`. Optional: String. One or more labels to add to the logs.
11	Configuration for a pipeline to send logs to the Kafka broker, with no pipeline name: The `inputRefs` is the log type, in this example `application`. The `outputRefs` is the name of the output to use. Optional: String. One or more labels to add to the logs.

Fluentd log handling when the external log aggregator is unavailable

If your external logging aggregator becomes unavailable and cannot receive logs, Fluentd continues to collect logs and stores them in a buffer. When the log aggregator becomes available, log forwarding resumes, including the buffered logs. If the buffer fills completely, Fluentd stops collecting logs. OpenShift Container Platform rotates the logs and deletes them. You cannot adjust the buffer size or add a persistent volume claim (PVC) to the Fluentd daemon set or pods.

Supported Authorization Keys

Common key types are provided here. Some output types support additional specialized keys, documented with the output-specific configuration field. All secret keys are optional. Enable the security features you want by setting the relevant keys. You are responsible for creating and maintaining any additional configurations that external destinations might require, such as keys and secrets, service accounts, port openings, or global proxy configuration. Open Shift Logging will not attempt to verify a mismatch between authorization combinations.

Transport Layer Security (TLS)

Using a TLS URL ('http://…' or 'ssl://…') without a Secret enables basic TLS server-side authentication. Additional TLS features are enabled by including a Secret and setting the following optional fields:

tls.crt: (string) File name containing a client certificate. Enables mutual authentication. Requires tls.key.
tls.key: (string) File name containing the private key to unlock the client certificate. Requires tls.crt.
passphrase: (string) Passphrase to decode an encoded TLS private key. Requires tls.key.
ca-bundle.crt: (string) File name of a customer CA for server authentication.

Username and Password

username: (string) Authentication user name. Requires password.
password: (string) Authentication password. Requires username.

Simple Authentication Security Layer (SASL)

sasl.enable (boolean) Explicitly enable or disable SASL. If missing, SASL is automatically enabled when any of the other sasl. keys are set.
sasl.mechanisms: (array) List of allowed SASL mechanism names. If missing or empty, the system defaults are used.
sasl.allow-insecure: (boolean) Allow mechanisms that send clear-text passwords. Defaults to false.

Creating a Secret

You can create a secret in the directory that contains your certificate and key files by using the following command:

$ oc create secret generic -n openshift-logging <my-secret> \
 --from-file=tls.key=<your_key_file>
 --from-file=tls.crt=<your_crt_file>
 --from-file=ca-bundle.crt=<your_bundle_file>
 --from-literal=username=<your_username>
 --from-literal=password=<your_password>

Generic or opaque secrets are recommended for best results.

Forwarding JSON logs from containers in the same pod to separate indices

You can forward structured logs from different containers within the same pod to different indices. To use this feature, you must configure the pipeline with multi-container support and annotate the pods. Logs are written to indices with a prefix of app-. It is recommended that Elasticsearch be configured with aliases to accommodate this.

JSON formatting of logs varies by application. Because creating too many indices impacts performance, limit your use of this feature to creating indices for logs that have incompatible JSON formats. Use queries to separate logs from different namespaces, or applications with compatible JSON formats.

Prerequisites

Logging for Red Hat OpenShift: 5.5

Procedure

Create or edit a YAML file that defines the ClusterLogForwarder CR object:

apiVersion: "logging.openshift.io/v1"
kind: ClusterLogForwarder
metadata:
  name: instance
  namespace: openshift-logging
spec:
  outputDefaults:
    elasticsearch:
      structuredTypeKey: kubernetes.labels.logFormat (1)
      structuredTypeName: nologformat
      enableStructuredContainerLogs: true (2)
  pipelines:
  - inputRefs:
    - application
    name: application-logs
    outputRefs:
    - default
    parse: json

1	Uses the value of the key-value pair that is formed by the Kubernetes `logFormat` label.
2	Enables multi-container outputs.

Create or edit a YAML file that defines the Pod CR object:

    apiVersion: v1
    kind: Pod
    metadata:
      annotations:
        containerType.logging.openshift.io/heavy: heavy (1)
        containerType.logging.openshift.io/low: low
    spec:
      containers:
      - name: heavy (2)
        image: heavyimage
      - name: low
        image: lowimage

1	Format: `containerType.logging.openshift.io/<container-name>: <index>`
2	Annotation names must match container names

This configuration might significantly increase the number of shards on the cluster.

Additional Resources

Kubernetes Annotations

Forwarding logs to an external Elasticsearch instance

You can optionally forward logs to an external Elasticsearch instance in addition to, or instead of, the internal OpenShift Container Platform Elasticsearch instance. You are responsible for configuring the external log aggregator to receive log data from OpenShift Container Platform.

To configure log forwarding to an external Elasticsearch instance, you must create a ClusterLogForwarder custom resource (CR) with an output to that instance, and a pipeline that uses the output. The external Elasticsearch output can use the HTTP (insecure) or HTTPS (secure HTTP) connection.

To forward logs to both an external and the internal Elasticsearch instance, create outputs and pipelines to the external instance and a pipeline that uses the default output to forward logs to the internal instance. You do not need to create a default output. If you do configure a default output, you receive an error message because the default output is reserved for the Red Hat OpenShift Logging Operator.

If you want to forward logs to only the internal OpenShift Container Platform Elasticsearch instance, you do not need to create a ClusterLogForwarder CR.

Prerequisites

You must have a logging server that is configured to receive the logging data using the specified protocol or format.

Procedure

Create or edit a YAML file that defines the ClusterLogForwarder CR object:

apiVersion: "logging.openshift.io/v1"
kind: ClusterLogForwarder
metadata:
  name: instance (1)
  namespace: openshift-logging (2)
spec:
  outputs:
   - name: elasticsearch-insecure (3)
     type: "elasticsearch" (4)
     url: http://elasticsearch.insecure.com:9200 (5)
   - name: elasticsearch-secure
     type: "elasticsearch"
     url: https://elasticsearch.secure.com:9200 (6)
     secret:
        name: es-secret (7)
  pipelines:
   - name: application-logs (8)
     inputRefs: (9)
     - application
     - audit
     outputRefs:
     - elasticsearch-secure (10)
     - default (11)
     labels:
       myLabel: "myValue" (12)
   - name: infrastructure-audit-logs (13)
     inputRefs:
     - infrastructure
     outputRefs:
     - elasticsearch-insecure
     labels:
       logs: "audit-infra"

1	The name of the `ClusterLogForwarder` CR must be `instance`.
2	The namespace for the `ClusterLogForwarder` CR must be `openshift-logging`.
3	Specify a name for the output.
4	Specify the `elasticsearch` type.
5	Specify the URL and port of the external Elasticsearch instance as a valid absolute URL. You can use the `http` (insecure) or `https` (secure HTTP) protocol. If the cluster-wide proxy using the CIDR annotation is enabled, the output must be a server name or FQDN, not an IP Address.
6	For a secure connection, you can specify an `https` or `http` URL that you authenticate by specifying a `secret`.
7	For an `https` prefix, specify the name of the secret required by the endpoint for TLS communication. The secret must exist in the `openshift-logging` project, and must have keys of: tls.crt, tls.key, and ca-bundle.crt that point to the respective certificates that they represent. Otherwise, for `http` and `https` prefixes, you can specify a secret that contains a username and password. For more information, see the following "Example: Setting secret that contains a username and password."
8	Optional: Specify a name for the pipeline.
9	Specify which log types to forward by using the pipeline: `application,` `infrastructure`, or `audit`.
10	Specify the name of the output to use when forwarding logs with this pipeline.
11	Optional: Specify the `default` output to send the logs to the internal Elasticsearch instance.
12	Optional: String. One or more labels to add to the logs.
13	Optional: Configure multiple outputs to forward logs to other external log aggregators of any supported type: A name to describe the pipeline. The `inputRefs` is the log type to forward by using the pipeline: `application,` `infrastructure`, or `audit`. The `outputRefs` is the name of the output to use. Optional: String. One or more labels to add to the logs.

Create the CR object:
```
$ oc create -f <file-name>.yaml
```

Example: Setting a secret that contains a username and password

You can use a secret that contains a username and password to authenticate a secure connection to an external Elasticsearch instance.

For example, if you cannot use mutual TLS (mTLS) keys because a third party operates the Elasticsearch instance, you can use HTTP or HTTPS and set a secret that contains the username and password.

Create a Secret YAML file similar to the following example. Use base64-encoded values for the username and password fields. The secret type is opaque by default.
```
apiVersion: v1
kind: Secret
metadata:
  name: openshift-test-secret
data:
  username: <username>
  password: <password>
```

Create the secret:

$ oc create secret -n openshift-logging openshift-test-secret.yaml

Specify the name of the secret in the ClusterLogForwarder CR:

kind: ClusterLogForwarder
metadata:
  name: instance
  namespace: openshift-logging
spec:
  outputs:
   - name: elasticsearch
     type: "elasticsearch"
     url: https://elasticsearch.secure.com:9200
     secret:
        name: openshift-test-secret

In the value of the url field, the prefix can be http or https.

Create the CR object:
```
$ oc create -f <file-name>.yaml
```

Forwarding logs using the Fluentd forward protocol

You can use the Fluentd forward protocol to send a copy of your logs to an external log aggregator that is configured to accept the protocol instead of, or in addition to, the default Elasticsearch log store. You are responsible for configuring the external log aggregator to receive the logs from OpenShift Container Platform.

To configure log forwarding using the forward protocol, you must create a ClusterLogForwarder custom resource (CR) with one or more outputs to the Fluentd servers, and pipelines that use those outputs. The Fluentd output can use a TCP (insecure) or TLS (secure TCP) connection.

Prerequisites

You must have a logging server that is configured to receive the logging data using the specified protocol or format.

Procedure

Create or edit a YAML file that defines the ClusterLogForwarder CR object:

apiVersion: logging.openshift.io/v1
kind: ClusterLogForwarder
metadata:
  name: instance (1)
  namespace: openshift-logging (2)
spec:
  outputs:
   - name: fluentd-server-secure (3)
     type: fluentdForward (4)
     url: 'tls://fluentdserver.security.example.com:24224' (5)
     secret: (6)
        name: fluentd-secret
   - name: fluentd-server-insecure
     type: fluentdForward
     url: 'tcp://fluentdserver.home.example.com:24224'
  pipelines:
   - name: forward-to-fluentd-secure (7)
     inputRefs:  (8)
     - application
     - audit
     outputRefs:
     - fluentd-server-secure (9)
     - default (10)
     labels:
       clusterId: "C1234" (11)
   - name: forward-to-fluentd-insecure (12)
     inputRefs:
     - infrastructure
     outputRefs:
     - fluentd-server-insecure
     labels:
       clusterId: "C1234"

1	The name of the `ClusterLogForwarder` CR must be `instance`.
2	The namespace for the `ClusterLogForwarder` CR must be `openshift-logging`.
3	Specify a name for the output.
4	Specify the `fluentdForward` type.
5	Specify the URL and port of the external Fluentd instance as a valid absolute URL. You can use the `tcp` (insecure) or `tls` (secure TCP) protocol. If the cluster-wide proxy using the CIDR annotation is enabled, the output must be a server name or FQDN, not an IP address.
6	If using a `tls` prefix, you must specify the name of the secret required by the endpoint for TLS communication. The secret must exist in the `openshift-logging` project, and must have keys of: tls.crt, tls.key, and ca-bundle.crt that point to the respective certificates that they represent.
7	Optional: Specify a name for the pipeline.
8	Specify which log types to forward by using the pipeline: `application,` `infrastructure`, or `audit`.
9	Specify the name of the output to use when forwarding logs with this pipeline.
10	Optional: Specify the `default` output to forward logs to the internal Elasticsearch instance.
11	Optional: String. One or more labels to add to the logs.
12	Optional: Configure multiple outputs to forward logs to other external log aggregators of any supported type: A name to describe the pipeline. The `inputRefs` is the log type to forward by using the pipeline: `application,` `infrastructure`, or `audit`. The `outputRefs` is the name of the output to use. Optional: String. One or more labels to add to the logs.

Create the CR object:
```
$ oc create -f <file-name>.yaml
```

Enabling nanosecond precision for Logstash to ingest data from fluentd

For Logstash to ingest log data from fluentd, you must enable nanosecond precision in the Logstash configuration file.

Procedure

In the Logstash configuration file, set nanosecond_precision to true.

Example Logstash configuration file

input { tcp { codec => fluent { nanosecond_precision => true } port => 24114 } }
filter { }
output { stdout { codec => rubydebug } }

Forwarding logs using the syslog protocol

You can use the syslog RFC3164 or RFC5424 protocol to send a copy of your logs to an external log aggregator that is configured to accept the protocol instead of, or in addition to, the default Elasticsearch log store. You are responsible for configuring the external log aggregator, such as a syslog server, to receive the logs from OpenShift Container Platform.

To configure log forwarding using the syslog protocol, you must create a ClusterLogForwarder custom resource (CR) with one or more outputs to the syslog servers, and pipelines that use those outputs. The syslog output can use a UDP, TCP, or TLS connection.

Prerequisites

You must have a logging server that is configured to receive the logging data using the specified protocol or format.

Procedure

Create or edit a YAML file that defines the ClusterLogForwarder CR object:

apiVersion: logging.openshift.io/v1
kind: ClusterLogForwarder
metadata:
  name: instance (1)
  namespace: openshift-logging (2)
spec:
  outputs:
   - name: rsyslog-east (3)
     type: syslog (4)
     syslog: (5)
       facility: local0
       rfc: RFC3164
       payloadKey: message
       severity: informational
     url: 'tls://rsyslogserver.east.example.com:514' (6)
     secret: (7)
        name: syslog-secret
   - name: rsyslog-west
     type: syslog
     syslog:
      appName: myapp
      facility: user
      msgID: mymsg
      procID: myproc
      rfc: RFC5424
      severity: debug
     url: 'tcp://rsyslogserver.west.example.com:514'
  pipelines:
   - name: syslog-east (8)
     inputRefs: (9)
     - audit
     - application
     outputRefs: (10)
     - rsyslog-east
     - default (11)
     labels:
       secure: "true" (12)
       syslog: "east"
   - name: syslog-west (13)
     inputRefs:
     - infrastructure
     outputRefs:
     - rsyslog-west
     - default
     labels:
       syslog: "west"

1	The name of the `ClusterLogForwarder` CR must be `instance`.
2	The namespace for the `ClusterLogForwarder` CR must be `openshift-logging`.
3	Specify a name for the output.
4	Specify the `syslog` type.
5	Optional: Specify the syslog parameters, listed below.
6	Specify the URL and port of the external syslog instance. You can use the `udp` (insecure), `tcp` (insecure) or `tls` (secure TCP) protocol. If the cluster-wide proxy using the CIDR annotation is enabled, the output must be a server name or FQDN, not an IP address.
7	If using a `tls` prefix, you must specify the name of the secret required by the endpoint for TLS communication. The secret must exist in the `openshift-logging` project, and must have keys of: tls.crt, tls.key, and ca-bundle.crt that point to the respective certificates that they represent.
8	Optional: Specify a name for the pipeline.
9	Specify which log types to forward by using the pipeline: `application,` `infrastructure`, or `audit`.
10	Specify the name of the output to use when forwarding logs with this pipeline.
11	Optional: Specify the `default` output to forward logs to the internal Elasticsearch instance.
12	Optional: String. One or more labels to add to the logs. Quote values like "true" so they are recognized as string values, not as a boolean.
13	Optional: Configure multiple outputs to forward logs to other external log aggregators of any supported type: A name to describe the pipeline. The `inputRefs` is the log type to forward by using the pipeline: `application,` `infrastructure`, or `audit`. The `outputRefs` is the name of the output to use. Optional: String. One or more labels to add to the logs.

Create the CR object:
```
$ oc create -f <file-name>.yaml
```

Adding log source information to message output

You can add namespace_name, pod_name, and container_name elements to the message field of the record by adding the AddLogSource field to your ClusterLogForwarder custom resource (CR).

  spec:
    outputs:
    - name: syslogout
      syslog:
        addLogSource: true
        facility: user
        payloadKey: message
        rfc: RFC3164
        severity: debug
        tag: mytag
      type: syslog
      url: tls://syslog-receiver.openshift-logging.svc:24224
    pipelines:
    - inputRefs:
      - application
      name: test-app
      outputRefs:
      - syslogout

This configuration is compatible with both RFC3164 and RFC5424.

Example syslog message output without AddLogSource

<15>1 2020-11-15T17:06:14+00:00 fluentd-9hkb4 mytag - - -  {"msgcontent"=>"Message Contents", "timestamp"=>"2020-11-15 17:06:09", "tag_key"=>"rec_tag", "index"=>56}

Example syslog message output with AddLogSource

<15>1 2020-11-16T10:49:37+00:00 crc-j55b9-master-0 mytag - - -  namespace_name=clo-test-6327,pod_name=log-generator-ff9746c49-qxm7l,container_name=log-generator,message={"msgcontent":"My life is my message", "timestamp":"2020-11-16 10:49:36", "tag_key":"rec_tag", "index":76}

Syslog parameters

You can configure the following for the syslog outputs. For more information, see the syslog RFC3164 or RFC5424 RFC.

facility: The syslog facility. The value can be a decimal integer or a case-insensitive keyword:
- 0 or kern for kernel messages
- 1 or user for user-level messages, the default.
- 2 or mail for the mail system
- 3 or daemon for system daemons
- 4 or auth for security/authentication messages
- 5 or syslog for messages generated internally by syslogd
- 6 or lpr for the line printer subsystem
- 7 or news for the network news subsystem
- 8 or uucp for the UUCP subsystem
- 9 or cron for the clock daemon
- 10 or authpriv for security authentication messages
- 11 or ftp for the FTP daemon
- 12 or ntp for the NTP subsystem
- 13 or security for the syslog audit log
- 14 or console for the syslog alert log
- 15 or solaris-cron for the scheduling daemon
- 16–23 or local0 – local7 for locally used facilities
Optional: payloadKey: The record field to use as payload for the syslog message.

Configuring the payloadKey parameter prevents other parameters from being forwarded to the syslog.
rfc: The RFC to be used for sending logs using syslog. The default is RFC5424.
severity: The syslog severity to set on outgoing syslog records. The value can be a decimal integer or a case-insensitive keyword:
- 0 or Emergency for messages indicating the system is unusable
- 1 or Alert for messages indicating action must be taken immediately
- 2 or Critical for messages indicating critical conditions
- 3 or Error for messages indicating error conditions
- 4 or Warning for messages indicating warning conditions
- 5 or Notice for messages indicating normal but significant conditions
- 6 or Informational for messages indicating informational messages
- 7 or Debug for messages indicating debug-level messages, the default
tag: Tag specifies a record field to use as a tag on the syslog message.
trimPrefix: Remove the specified prefix from the tag.

Additional RFC5424 syslog parameters

The following parameters apply to RFC5424:

appName: The APP-NAME is a free-text string that identifies the application that sent the log. Must be specified for RFC5424.
msgID: The MSGID is a free-text string that identifies the type of message. Must be specified for RFC5424.
procID: The PROCID is a free-text string. A change in the value indicates a discontinuity in syslog reporting. Must be specified for RFC5424.

Forwarding logs to a Kafka broker

You can forward logs to an external Kafka broker in addition to, or instead of, the default log store.

To configure log forwarding to an external Kafka instance, you must create a ClusterLogForwarder custom resource (CR) with an output to that instance, and a pipeline that uses the output. You can include a specific Kafka topic in the output or use the default. The Kafka output can use a TCP (insecure) or TLS (secure TCP) connection.

Procedure

Create or edit a YAML file that defines the ClusterLogForwarder CR object:

apiVersion: logging.openshift.io/v1
kind: ClusterLogForwarder
metadata:
  name: instance (1)
  namespace: openshift-logging (2)
spec:
  outputs:
   - name: app-logs (3)
     type: kafka (4)
     url: tls://kafka.example.devlab.com:9093/app-topic (5)
     secret:
       name: kafka-secret (6)
   - name: infra-logs
     type: kafka
     url: tcp://kafka.devlab2.example.com:9093/infra-topic (7)
   - name: audit-logs
     type: kafka
     url: tls://kafka.qelab.example.com:9093/audit-topic
     secret:
        name: kafka-secret-qe
  pipelines:
   - name: app-topic (8)
     inputRefs: (9)
     - application
     outputRefs: (10)
     - app-logs
     labels:
       logType: "application" (11)
   - name: infra-topic (12)
     inputRefs:
     - infrastructure
     outputRefs:
     - infra-logs
     labels:
       logType: "infra"
   - name: audit-topic
     inputRefs:
     - audit
     outputRefs:
     - audit-logs
     - default (13)
     labels:
       logType: "audit"

1	The name of the `ClusterLogForwarder` CR must be `instance`.
2	The namespace for the `ClusterLogForwarder` CR must be `openshift-logging`.
3	Specify a name for the output.
4	Specify the `kafka` type.
5	Specify the URL and port of the Kafka broker as a valid absolute URL, optionally with a specific topic. You can use the `tcp` (insecure) or `tls` (secure TCP) protocol. If the cluster-wide proxy using the CIDR annotation is enabled, the output must be a server name or FQDN, not an IP address.
6	If using a `tls` prefix, you must specify the name of the secret required by the endpoint for TLS communication. The secret must exist in the `openshift-logging` project, and must have keys of: tls.crt, tls.key, and ca-bundle.crt that point to the respective certificates that they represent.
7	Optional: To send an insecure output, use a `tcp` prefix in front of the URL. Also omit the `secret` key and its `name` from this output.
8	Optional: Specify a name for the pipeline.
9	Specify which log types to forward by using the pipeline: `application,` `infrastructure`, or `audit`.
10	Specify the name of the output to use when forwarding logs with this pipeline.
11	Optional: String. One or more labels to add to the logs.
12	Optional: Configure multiple outputs to forward logs to other external log aggregators of any supported type: A name to describe the pipeline. The `inputRefs` is the log type to forward by using the pipeline: `application,` `infrastructure`, or `audit`. The `outputRefs` is the name of the output to use. Optional: String. One or more labels to add to the logs.
13	Optional: Specify `default` to forward logs to the internal Elasticsearch instance.

Optional: To forward a single output to multiple Kafka brokers, specify an array of Kafka brokers as shown in the following example:

# ...
spec:
  outputs:
  - name: app-logs
    type: kafka
    secret:
      name: kafka-secret-dev
    kafka:  (1)
      brokers: (2)
        - tls://kafka-broker1.example.com:9093/
        - tls://kafka-broker2.example.com:9093/
      topic: app-topic (3)
# ...

1	Specify a `kafka` key that has a `brokers` and `topic` key.
2	Use the `brokers` key to specify an array of one or more brokers.
3	Use the `topic` key to specify the target topic that receives the logs.

Apply the ClusterLogForwarder CR by running the following command:
```
$ oc apply -f <filename>.yaml
```

Forwarding logs to Amazon CloudWatch

You can forward logs to Amazon CloudWatch, a monitoring and log storage service hosted by Amazon Web Services (AWS). You can forward logs to CloudWatch in addition to, or instead of, the default log store.

To configure log forwarding to CloudWatch, you must create a ClusterLogForwarder custom resource (CR) with an output for CloudWatch, and a pipeline that uses the output.

Procedure

Create a Secret YAML file that uses the aws_access_key_id and aws_secret_access_key fields to specify your base64-encoded AWS credentials. For example:

apiVersion: v1
kind: Secret
metadata:
  name: cw-secret
  namespace: openshift-logging
data:
  aws_access_key_id: QUtJQUlPU0ZPRE5ON0VYQU1QTEUK
  aws_secret_access_key: d0phbHJYVXRuRkVNSS9LN01ERU5HL2JQeFJmaUNZRVhBTVBMRUtFWQo=

Create the secret. For example:
```
$ oc apply -f cw-secret.yaml
```

Create or edit a YAML file that defines the ClusterLogForwarder CR object. In the file, specify the name of the secret. For example:

apiVersion: "logging.openshift.io/v1"
kind: ClusterLogForwarder
metadata:
  name: instance (1)
  namespace: openshift-logging (2)
spec:
  outputs:
   - name: cw (3)
     type: cloudwatch (4)
     cloudwatch:
       groupBy: logType (5)
       groupPrefix: <group prefix> (6)
       region: us-east-2 (7)
     secret:
        name: cw-secret (8)
  pipelines:
    - name: infra-logs (9)
      inputRefs: (10)
        - infrastructure
        - audit
        - application
      outputRefs:
        - cw (11)

1	The name of the `ClusterLogForwarder` CR must be `instance`.
2	The namespace for the `ClusterLogForwarder` CR must be `openshift-logging`.
3	Specify a name for the output.
4	Specify the `cloudwatch` type.
5	Optional: Specify how to group the logs: `logType` creates log groups for each log type `namespaceName` creates a log group for each application name space. It also creates separate log groups for infrastructure and audit logs. `namespaceUUID` creates a new log groups for each application namespace UUID. It also creates separate log groups for infrastructure and audit logs.
6	Optional: Specify a string to replace the default `infrastructureName` prefix in the names of the log groups.
7	Specify the AWS region.
8	Specify the name of the secret that contains your AWS credentials.
9	Optional: Specify a name for the pipeline.
10	Specify which log types to forward by using the pipeline: `application,` `infrastructure`, or `audit`.
11	Specify the name of the output to use when forwarding logs with this pipeline.

Create the CR object:
```
$ oc create -f <file-name>.yaml
```

Example: Using ClusterLogForwarder with Amazon CloudWatch

Here, you see an example ClusterLogForwarder custom resource (CR) and the log data that it outputs to Amazon CloudWatch.

Suppose that you are running an OpenShift Container Platform cluster named mycluster. The following command returns the cluster’s infrastructureName, which you will use to compose aws commands later on:

$ oc get Infrastructure/cluster -ojson | jq .status.infrastructureName
"mycluster-7977k"

To generate log data for this example, you run a busybox pod in a namespace called app. The busybox pod writes a message to stdout every three seconds:

$ oc run busybox --image=busybox -- sh -c 'while true; do echo "My life is my message"; sleep 3; done'
$ oc logs -f busybox
My life is my message
My life is my message
My life is my message
...

You can look up the UUID of the app namespace where the busybox pod runs:

$ oc get ns/app -ojson | jq .metadata.uid
"794e1e1a-b9f5-4958-a190-e76a9b53d7bf"

In your ClusterLogForwarder custom resource (CR), you configure the infrastructure, audit, and application log types as inputs to the all-logs pipeline. You also connect this pipeline to cw output, which forwards the logs to a CloudWatch instance in the us-east-2 region:

apiVersion: "logging.openshift.io/v1"
kind: ClusterLogForwarder
metadata:
  name: instance
  namespace: openshift-logging
spec:
  outputs:
   - name: cw
     type: cloudwatch
     cloudwatch:
       groupBy: logType
       region: us-east-2
     secret:
        name: cw-secret
  pipelines:
    - name: all-logs
      inputRefs:
        - infrastructure
        - audit
        - application
      outputRefs:
        - cw

Each region in CloudWatch contains three levels of objects:

log group
- log stream
  - log event

With groupBy: logType in the ClusterLogForwarding CR, the three log types in the inputRefs produce three log groups in Amazon Cloudwatch:

$ aws --output json logs describe-log-groups | jq .logGroups[].logGroupName
"mycluster-7977k.application"
"mycluster-7977k.audit"
"mycluster-7977k.infrastructure"

Each of the log groups contains log streams:

$ aws --output json logs describe-log-streams --log-group-name mycluster-7977k.application | jq .logStreams[].logStreamName
"kubernetes.var.log.containers.busybox_app_busybox-da085893053e20beddd6747acdbaf98e77c37718f85a7f6a4facf09ca195ad76.log"

$ aws --output json logs describe-log-streams --log-group-name mycluster-7977k.audit | jq .logStreams[].logStreamName
"ip-10-0-131-228.us-east-2.compute.internal.k8s-audit.log"
"ip-10-0-131-228.us-east-2.compute.internal.linux-audit.log"
"ip-10-0-131-228.us-east-2.compute.internal.openshift-audit.log"
...

$ aws --output json logs describe-log-streams --log-group-name mycluster-7977k.infrastructure | jq .logStreams[].logStreamName
"ip-10-0-131-228.us-east-2.compute.internal.kubernetes.var.log.containers.apiserver-69f9fd9b58-zqzw5_openshift-oauth-apiserver_oauth-apiserver-453c5c4ee026fe20a6139ba6b1cdd1bed25989c905bf5ac5ca211b7cbb5c3d7b.log"
"ip-10-0-131-228.us-east-2.compute.internal.kubernetes.var.log.containers.apiserver-797774f7c5-lftrx_openshift-apiserver_openshift-apiserver-ce51532df7d4e4d5f21c4f4be05f6575b93196336be0027067fd7d93d70f66a4.log"
"ip-10-0-131-228.us-east-2.compute.internal.kubernetes.var.log.containers.apiserver-797774f7c5-lftrx_openshift-apiserver_openshift-apiserver-check-endpoints-82a9096b5931b5c3b1d6dc4b66113252da4a6472c9fff48623baee761911a9ef.log"
...

Each log stream contains log events. To see a log event from the busybox Pod, you specify its log stream from the application log group:

$ aws logs get-log-events --log-group-name mycluster-7977k.application --log-stream-name kubernetes.var.log.containers.busybox_app_busybox-da085893053e20beddd6747acdbaf98e77c37718f85a7f6a4facf09ca195ad76.log
{
    "events": [
        {
            "timestamp": 1629422704178,
            "message": "{\"docker\":{\"container_id\":\"da085893053e20beddd6747acdbaf98e77c37718f85a7f6a4facf09ca195ad76\"},\"kubernetes\":{\"container_name\":\"busybox\",\"namespace_name\":\"app\",\"pod_name\":\"busybox\",\"container_image\":\"docker.io/library/busybox:latest\",\"container_image_id\":\"docker.io/library/busybox@sha256:0f354ec1728d9ff32edcd7d1b8bbdfc798277ad36120dc3dc683be44524c8b60\",\"pod_id\":\"870be234-90a3-4258-b73f-4f4d6e2777c7\",\"host\":\"ip-10-0-216-3.us-east-2.compute.internal\",\"labels\":{\"run\":\"busybox\"},\"master_url\":\"https://kubernetes.default.svc\",\"namespace_id\":\"794e1e1a-b9f5-4958-a190-e76a9b53d7bf\",\"namespace_labels\":{\"kubernetes_io/metadata_name\":\"app\"}},\"message\":\"My life is my message\",\"level\":\"unknown\",\"hostname\":\"ip-10-0-216-3.us-east-2.compute.internal\",\"pipeline_metadata\":{\"collector\":{\"ipaddr4\":\"10.0.216.3\",\"inputname\":\"fluent-plugin-systemd\",\"name\":\"fluentd\",\"received_at\":\"2021-08-20T01:25:08.085760+00:00\",\"version\":\"1.7.4 1.6.0\"}},\"@timestamp\":\"2021-08-20T01:25:04.178986+00:00\",\"viaq_index_name\":\"app-write\",\"viaq_msg_id\":\"NWRjZmUyMWQtZjgzNC00MjI4LTk3MjMtNTk3NmY3ZjU4NDk1\",\"log_type\":\"application\",\"time\":\"2021-08-20T01:25:04+00:00\"}",
            "ingestionTime": 1629422744016
        },
...

Example: Customizing the prefix in log group names

In the log group names, you can replace the default infrastructureName prefix, mycluster-7977k, with an arbitrary string like demo-group-prefix. To make this change, you update the groupPrefix field in the ClusterLogForwarding CR:

cloudwatch:
    groupBy: logType
    groupPrefix: demo-group-prefix
    region: us-east-2

The value of groupPrefix replaces the default infrastructureName prefix:

$ aws --output json logs describe-log-groups | jq .logGroups[].logGroupName
"demo-group-prefix.application"
"demo-group-prefix.audit"
"demo-group-prefix.infrastructure"

Example: Naming log groups after application namespace names

For each application namespace in your cluster, you can create a log group in CloudWatch whose name is based on the name of the application namespace.

If you delete an application namespace object and create a new one that has the same name, CloudWatch continues using the same log group as before.

If you consider successive application namespace objects that have the same name as equivalent to each other, use the approach described in this example. Otherwise, if you need to distinguish the resulting log groups from each other, see the following "Naming log groups for application namespace UUIDs" section instead.

To create application log groups whose names are based on the names of the application namespaces, you set the value of the groupBy field to namespaceName in the ClusterLogForwarder CR:

cloudwatch:
    groupBy: namespaceName
    region: us-east-2

Setting groupBy to namespaceName affects the application log group only. It does not affect the audit and infrastructure log groups.

In Amazon Cloudwatch, the namespace name appears at the end of each log group name. Because there is a single application namespace, "app", the following output shows a new mycluster-7977k.app log group instead of mycluster-7977k.application:

$ aws --output json logs describe-log-groups | jq .logGroups[].logGroupName
"mycluster-7977k.app"
"mycluster-7977k.audit"
"mycluster-7977k.infrastructure"

If the cluster in this example had contained multiple application namespaces, the output would show multiple log groups, one for each namespace.

The groupBy field affects the application log group only. It does not affect the audit and infrastructure log groups.

Example: Naming log groups after application namespace UUIDs

For each application namespace in your cluster, you can create a log group in CloudWatch whose name is based on the UUID of the application namespace.

If you delete an application namespace object and create a new one, CloudWatch creates a new log group.

If you consider successive application namespace objects with the same name as different from each other, use the approach described in this example. Otherwise, see the preceding "Example: Naming log groups for application namespace names" section instead.

To name log groups after application namespace UUIDs, you set the value of the groupBy field to namespaceUUID in the ClusterLogForwarder CR:

cloudwatch:
    groupBy: namespaceUUID
    region: us-east-2

In Amazon Cloudwatch, the namespace UUID appears at the end of each log group name. Because there is a single application namespace, "app", the following output shows a new mycluster-7977k.794e1e1a-b9f5-4958-a190-e76a9b53d7bf log group instead of mycluster-7977k.application:

$ aws --output json logs describe-log-groups | jq .logGroups[].logGroupName
"mycluster-7977k.794e1e1a-b9f5-4958-a190-e76a9b53d7bf" // uid of the "app" namespace
"mycluster-7977k.audit"
"mycluster-7977k.infrastructure"

The groupBy field affects the application log group only. It does not affect the audit and infrastructure log groups.

Forwarding logs to Amazon CloudWatch from STS enabled clusters

For clusters with AWS Security Token Service (STS) enabled, you can create an AWS service account manually or create a credentials request by using the Cloud Credential Operator(CCO) utility ccoctl.

Prerequisites

Logging for Red Hat OpenShift: 5.5 and later

Procedure

Create a CredentialsRequest custom resource YAML by using the template below:

CloudWatch credentials request template

apiVersion: cloudcredential.openshift.io/v1
kind: CredentialsRequest
metadata:
  name: <your_role_name>-credrequest
  namespace: openshift-cloud-credential-operator
spec:
  providerSpec:
    apiVersion: cloudcredential.openshift.io/v1
    kind: AWSProviderSpec
    statementEntries:
      - action:
          - logs:PutLogEvents
          - logs:CreateLogGroup
          - logs:PutRetentionPolicy
          - logs:CreateLogStream
          - logs:DescribeLogGroups
          - logs:DescribeLogStreams
        effect: Allow
        resource: arn:aws:logs:*:*:*
  secretRef:
    name: <your_role_name>
    namespace: openshift-logging
  serviceAccountNames:
    - logcollector

Use the ccoctl command to create a role for AWS using your CredentialsRequest CR. With the CredentialsRequest object, this ccoctl command creates an IAM role with a trust policy that is tied to the specified OIDC identity provider, and a permissions policy that grants permissions to perform operations on CloudWatch resources. This command also creates a YAML configuration file in /<path_to_ccoctl_output_dir>/manifests/openshift-logging-<your_role_name>-credentials.yaml. This secret file contains the role_arn key/value used during authentication with the AWS IAM identity provider.
```
$ ccoctl aws create-iam-roles \
--name=<name> \
--region=<aws_region> \
--credentials-requests-dir=<path_to_directory_with_list_of_credentials_requests>/credrequests \
--identity-provider-arn=arn:aws:iam::<aws_account_id>:oidc-provider/<name>-oidc.s3.<aws_region>.amazonaws.com (1)
```
1 <name> is the name used to tag your cloud resources and should match the name used during your STS cluster install

Apply the secret created:

$ oc apply -f output/manifests/openshift-logging-<your_role_name>-credentials.yaml

Create or edit a ClusterLogForwarder custom resource:

apiVersion: "logging.openshift.io/v1"
kind: ClusterLogForwarder
metadata:
  name: instance (1)
  namespace: openshift-logging (2)
spec:
  outputs:
   - name: cw (3)
     type: cloudwatch (4)
     cloudwatch:
       groupBy: logType (5)
       groupPrefix: <group prefix> (6)
       region: us-east-2 (7)
     secret:
        name: <your_role_name> (8)
  pipelines:
    - name: to-cloudwatch (9)
      inputRefs: (10)
        - infrastructure
        - audit
        - application
      outputRefs:
        - cw (11)

1	The name of the `ClusterLogForwarder` CR must be `instance`.
2	The namespace for the `ClusterLogForwarder` CR must be `openshift-logging`.
3	Specify a name for the output.
4	Specify the `cloudwatch` type.
5	Optional: Specify how to group the logs: `logType` creates log groups for each log type `namespaceName` creates a log group for each application name space. Infrastructure and audit logs are unaffected, remaining grouped by `logType`. `namespaceUUID` creates a new log groups for each application namespace UUID. It also creates separate log groups for infrastructure and audit logs.
6	Optional: Specify a string to replace the default `infrastructureName` prefix in the names of the log groups.
7	Specify the AWS region.
8	Specify the name of the secret that contains your AWS credentials.
9	Optional: Specify a name for the pipeline.
10	Specify which log types to forward by using the pipeline: `application,` `infrastructure`, or `audit`.
11	Specify the name of the output to use when forwarding logs with this pipeline.

Additional resources

AWS STS API Reference

Creating a secret for AWS CloudWatch with an existing AWS role

If you have an existing role for AWS, you can create a secret for AWS with STS using the oc create secret --from-literal command.

Procedure

In the CLI, enter the following to generate a secret for AWS:

$ oc create secret generic cw-sts-secret -n openshift-logging --from-literal=role_arn=arn:aws:iam::123456789012:role/my-role_with-permissions

Example Secret

apiVersion: v1
kind: Secret
metadata:
  namespace: openshift-logging
  name: my-secret-name
stringData:
  role_arn: arn:aws:iam::123456789012:role/my-role_with-permissions

Forwarding logs to Loki

You can forward logs to an external Loki logging system in addition to, or instead of, the internal default OpenShift Container Platform Elasticsearch instance.

To configure log forwarding to Loki, you must create a ClusterLogForwarder custom resource (CR) with an output to Loki, and a pipeline that uses the output. The output to Loki can use the HTTP (insecure) or HTTPS (secure HTTP) connection.

Prerequisites

You must have a Loki logging system running at the URL you specify with the url field in the CR.

Procedure

Create or edit a YAML file that defines the ClusterLogForwarder CR object:

  apiVersion: "logging.openshift.io/v1"
  kind: ClusterLogForwarder
  metadata:
    name: instance (1)
    namespace: openshift-logging (2)
  spec:
    outputs:
     - name: loki-insecure (3)
       type: "loki" (4)
       url: http://loki.insecure.com:3100 (5)
       loki:
          tenantKey: kubernetes.namespace_name
          labelKeys: kubernetes.labels.foo
     - name: loki-secure (6)
       type: "loki"
       url: https://loki.secure.com:3100
       secret:
          name: loki-secret (7)
       loki:
          tenantKey: kubernetes.namespace_name (8)
          labelKeys: kubernetes.labels.foo (9)
    pipelines:
     - name: application-logs (10)
       inputRefs:  (11)
       - application
       - audit
       outputRefs: (12)
       - loki-secure

1	The name of the `ClusterLogForwarder` CR must be `instance`.
2	The namespace for the `ClusterLogForwarder` CR must be `openshift-logging`.
3	Specify a name for the output.
4	Specify the type as `"loki"`.
5	Specify the URL and port of the Loki system as a valid absolute URL. You can use the `http` (insecure) or `https` (secure HTTP) protocol. If the cluster-wide proxy using the CIDR annotation is enabled, the output must be a server name or FQDN, not an IP Address. Loki’s default port for HTTP(S) communication is 3100.
6	For a secure connection, you can specify an `https` or `http` URL that you authenticate by specifying a `secret`.
7	For an `https` prefix, specify the name of the secret required by the endpoint for TLS communication. The secret must exist in the `openshift-logging` project, and must have keys of: tls.crt, tls.key, and ca-bundle.crt that point to the respective certificates that they represent. Otherwise, for `http` and `https` prefixes, you can specify a secret that contains a username and password. For more information, see the following "Example: Setting secret that contains a username and password."
8	Optional: Specify a meta-data key field to generate values for the `TenantID` field in Loki. For example, setting `tenantKey: kubernetes.namespace_name` uses the names of the Kubernetes namespaces as values for tenant IDs in Loki. To see which other log record fields you can specify, see the "Log Record Fields" link in the following "Additional resources" section.
9	Optional: Specify a list of meta-data field keys to replace the default Loki labels. Loki label names must match the regular expression `[a-zA-Z_:][a-zA-Z0-9_:]*`. Illegal characters in meta-data keys are replaced with `_` to form the label name. For example, the `kubernetes.labels.foo` meta-data key becomes Loki label `kubernetes_labels_foo`. If you do not set `labelKeys`, the default value is: `[log_type, kubernetes.namespace_name, kubernetes.pod_name, kubernetes_host]`. Keep the set of labels small because Loki limits the size and number of labels allowed. See Configuring Loki, limits_config. You can still query based on any log record field using query filters.
10	Optional: Specify a name for the pipeline.
11	Specify which log types to forward by using the pipeline: `application,` `infrastructure`, or `audit`.
12	Specify the name of the output to use when forwarding logs with this pipeline.

Because Loki requires log streams to be correctly ordered by timestamp, labelKeys always includes the kubernetes_host label set, even if you do not specify it. This inclusion ensures that each stream originates from a single host, which prevents timestamps from becoming disordered due to clock differences on different hosts.

Create the CR object:
```
$ oc create -f <file-name>.yaml
```

Troubleshooting Loki rate limit errors

If the Log Forwarder API forwards a large block of messages that exceeds the rate limit to Loki, Loki generates rate limit (429) errors.

These errors can occur during normal operation. For example, when adding the logging to a cluster that already has some logs, rate limit errors might occur while the logging tries to ingest all of the existing log entries. In this case, if the rate of addition of new logs is less than the total rate limit, the historical data is eventually ingested, and the rate limit errors are resolved without requiring user intervention.

In cases where the rate limit errors continue to occur, you can fix the issue by modifying the LokiStack custom resource (CR).

The LokiStack CR is not available on Grafana-hosted Loki. This topic does not apply to Grafana-hosted Loki servers.

Conditions

The Log Forwarder API is configured to forward logs to Loki.

Your system sends a block of messages that is larger than 2 MB to Loki. For example:

"values":[["1630410392689800468","{\"kind\":\"Event\",\"apiVersion\":\
.......
......
......
......
\"received_at\":\"2021-08-31T11:46:32.800278+00:00\",\"version\":\"1.7.4 1.6.0\"}},\"@timestamp\":\"2021-08-31T11:46:32.799692+00:00\",\"viaq_index_name\":\"audit-write\",\"viaq_msg_id\":\"MzFjYjJkZjItNjY0MC00YWU4LWIwMTEtNGNmM2E5ZmViMGU4\",\"log_type\":\"audit\"}"]]}]}

After you enter oc logs -n openshift-logging -l component=collector, the collector logs in your cluster show a line containing one of the following error messages:

429 Too Many Requests Ingestion rate limit exceeded

Example Vector error message

2023-08-25T16:08:49.301780Z  WARN sink{component_kind="sink" component_id=default_loki_infra component_type=loki component_name=default_loki_infra}: vector::sinks::util::retries: Retrying after error. error=Server responded with an error: 429 Too Many Requests internal_log_rate_limit=true

Example Fluentd error message

2023-08-30 14:52:15 +0000 [warn]: [default_loki_infra] failed to flush the buffer. retry_times=2 next_retry_time=2023-08-30 14:52:19 +0000 chunk="604251225bf5378ed1567231a1c03b8b" error_class=Fluent::Plugin::LokiOutput::LogPostError error="429 Too Many Requests Ingestion rate limit exceeded for user infrastructure (limit: 4194304 bytes/sec) while attempting to ingest '4082' lines totaling '7820025' bytes, reduce log volume or contact your Loki administrator to see if the limit can be increased\n"

The error is also visible on the receiving end. For example, in the LokiStack ingester pod:

Example Loki ingester error message

level=warn ts=2023-08-30T14:57:34.155592243Z caller=grpc_logging.go:43 duration=1.434942ms method=/logproto.Pusher/Push err="rpc error: code = Code(429) desc = entry with timestamp 2023-08-30 14:57:32.012778399 +0000 UTC ignored, reason: 'Per stream rate limit exceeded (limit: 3MB/sec) while attempting to ingest for stream

Procedure

Update the ingestionBurstSize and ingestionRate fields in the LokiStack CR:

apiVersion: loki.grafana.com/v1
kind: LokiStack
metadata:
  name: logging-loki
  namespace: openshift-logging
spec:
  limits:
    global:
      ingestion:
        ingestionBurstSize: 16 (1)
        ingestionRate: 8 (2)
# ...

1	The `ingestionBurstSize` field defines the maximum local rate-limited sample size per distributor replica in MB. This value is a hard limit. Set this value to at least the maximum logs size expected in a single push request. Single requests that are larger than the `ingestionBurstSize` value are not permitted.
2	The `ingestionRate` field is a soft limit on the maximum amount of ingested samples per second in MB. Rate limit errors occur if the rate of logs exceeds the limit, but the collector retries sending the logs. As long as the total average is lower than the limit, the system recovers and errors are resolved without user intervention.

Additional resources

Forwarding logs to Google Cloud Platform (GCP)

You can forward logs to Google Cloud Logging in addition to, or instead of, the internal default OpenShift Container Platform log store.

Using this feature with Fluentd is not supported.

Prerequisites

Red Hat OpenShift Logging Operator 5.5.1 and later

Procedure

Create a secret using your Google service account key.

$ oc -n openshift-logging create secret generic gcp-secret --from-file google-application-credentials.json=<your_service_account_key_file.json>

Create a ClusterLogForwarder Custom Resource YAML using the template below:

apiVersion: "logging.openshift.io/v1"
kind: "ClusterLogForwarder"
metadata:
  name: "instance"
  namespace: "openshift-logging"
spec:
  outputs:
    - name: gcp-1
      type: googleCloudLogging
      secret:
        name: gcp-secret
      googleCloudLogging:
        projectId : "openshift-gce-devel" (1)
        logId : "app-gcp" (2)
  pipelines:
    - name: test-app
      inputRefs: (3)
        - application
      outputRefs:
        - gcp-1

1	Set either a `projectId`, `folderId`, `organizationId`, or `billingAccountId` field and its corresponding value, depending on where you want to store your logs in the GCP resource hierarchy.
2	Set the value to add to the `logName` field of the Log Entry.
3	Specify which log types to forward by using the pipeline: `application`, `infrastructure`, or `audit`.

Additional resources

Forwarding logs to Splunk

You can forward logs to the Splunk HTTP Event Collector (HEC) in addition to, or instead of, the internal default OpenShift Container Platform log store.

Using this feature with Fluentd is not supported.

Prerequisites

Red Hat OpenShift Logging Operator 5.6 or later
A ClusterLogging instance with vector specified as the collector
Base64 encoded Splunk HEC token

Procedure

Create a secret using your Base64 encoded Splunk HEC token.

$ oc -n openshift-logging create secret generic vector-splunk-secret --from-literal hecToken=<HEC_Token>

Create or edit the ClusterLogForwarder Custom Resource (CR) using the template below:

  apiVersion: "logging.openshift.io/v1"
  kind: "ClusterLogForwarder"
  metadata:
    name: "instance" (1)
    namespace: "openshift-logging" (2)
  spec:
    outputs:
      - name: splunk-receiver (3)
        secret:
          name: vector-splunk-secret (4)
        type: splunk (5)
        url: <http://your.splunk.hec.url:8088> (6)
    pipelines: (7)
      - inputRefs:
          - application
          - infrastructure
        name: (8)
        outputRefs:
          - splunk-receiver (9)

1	The name of the ClusterLogForwarder CR must be `instance`.
2	The namespace for the ClusterLogForwarder CR must be `openshift-logging`.
3	Specify a name for the output.
4	Specify the name of the secret that contains your HEC token.
5	Specify the output type as `splunk`.
6	Specify the URL (including port) of your Splunk HEC.
7	Specify which log types to forward by using the pipeline: `application`, `infrastructure`, or `audit`.
8	Optional: Specify a name for the pipeline.
9	Specify the name of the output to use when forwarding logs with this pipeline.

Forwarding logs over HTTP

Forwarding logs over HTTP is supported for both the Fluentd and Vector log collectors. To enable, specify http as the output type in the ClusterLogForwarder custom resource (CR).

Procedure

Create or edit the ClusterLogForwarder CR using the template below:

Example ClusterLogForwarder CR

apiVersion: "logging.openshift.io/v1"
kind: "ClusterLogForwarder"
metadata:
  name: "instance"
  namespace: "openshift-logging"
spec:
  outputs:
    - name: httpout-app
      type: http
      url: (1)
      http:
        headers: (2)
          h1: v1
          h2: v2
        method: POST
      secret:
        name: (3)
      tls:
        insecureSkipVerify: (4)
  pipelines:
    - name:
      inputRefs:
        - application
      outputRefs:
        - (5)

1	Destination address for logs.
2	Additional headers to send with the log record.
3	Secret name for destination credentials.
4	Values are either `true` or `false`.
5	This value should be the same as the output name.

Forwarding application logs from specific projects

You can use the Cluster Log Forwarder to send a copy of the application logs from specific projects to an external log aggregator. You can do this in addition to, or instead of, using the default Elasticsearch log store. You must also configure the external log aggregator to receive log data from OpenShift Container Platform.

To configure forwarding application logs from a project, you must create a ClusterLogForwarder custom resource (CR) with at least one input from a project, optional outputs for other log aggregators, and pipelines that use those inputs and outputs.

Prerequisites

You must have a logging server that is configured to receive the logging data using the specified protocol or format.

Procedure

Create or edit a YAML file that defines the ClusterLogForwarder CR object:

apiVersion: logging.openshift.io/v1
kind: ClusterLogForwarder
metadata:
  name: instance (1)
  namespace: openshift-logging (2)
spec:
  outputs:
   - name: fluentd-server-secure (3)
     type: fluentdForward (4)
     url: 'tls://fluentdserver.security.example.com:24224' (5)
     secret: (6)
        name: fluentd-secret
   - name: fluentd-server-insecure
     type: fluentdForward
     url: 'tcp://fluentdserver.home.example.com:24224'
  inputs: (7)
   - name: my-app-logs
     application:
        namespaces:
        - my-project
  pipelines:
   - name: forward-to-fluentd-insecure (8)
     inputRefs: (9)
     - my-app-logs
     outputRefs: (10)
     - fluentd-server-insecure
     labels:
       project: "my-project" (11)
   - name: forward-to-fluentd-secure (12)
     inputRefs:
     - application
     - audit
     - infrastructure
     outputRefs:
     - fluentd-server-secure
     - default
     labels:
       clusterId: "C1234"

1	The name of the `ClusterLogForwarder` CR must be `instance`.
2	The namespace for the `ClusterLogForwarder` CR must be `openshift-logging`.
3	Specify a name for the output.
4	Specify the output type: `elasticsearch`, `fluentdForward`, `syslog`, or `kafka`.
5	Specify the URL and port of the external log aggregator as a valid absolute URL. If the cluster-wide proxy using the CIDR annotation is enabled, the output must be a server name or FQDN, not an IP address.
6	If using a `tls` prefix, you must specify the name of the secret required by the endpoint for TLS communication. The secret must exist in the `openshift-logging` project and have tls.crt, tls.key, and ca-bundle.crt keys that each point to the certificates they represent.
7	Configuration for an input to filter application logs from the specified projects.
8	Configuration for a pipeline to use the input to send project application logs to an external Fluentd instance.
9	The `my-app-logs` input.
10	The name of the output to use.
11	Optional: String. One or more labels to add to the logs.
12	Configuration for a pipeline to send logs to other log aggregators. Optional: Specify a name for the pipeline. Specify which log types to forward by using the pipeline: `application,` `infrastructure`, or `audit`. Specify the name of the output to use when forwarding logs with this pipeline. Optional: Specify the `default` output to forward logs to the internal Elasticsearch instance. Optional: String. One or more labels to add to the logs.

Create the CR object:
```
$ oc create -f <file-name>.yaml
```

Forwarding application logs from specific pods

As a cluster administrator, you can use Kubernetes pod labels to gather log data from specific pods and forward it to a log collector.

Suppose that you have an application composed of pods running alongside other pods in various namespaces. If those pods have labels that identify the application, you can gather and output their log data to a specific log collector.

To specify the pod labels, you use one or more matchLabels key-value pairs. If you specify multiple key-value pairs, the pods must match all of them to be selected.

Procedure

Create or edit a YAML file that defines the ClusterLogForwarder CR object. In the file, specify the pod labels using simple equality-based selectors under inputs[].name.application.selector.matchLabels, as shown in the following example.

Example ClusterLogForwarder CR YAML file

apiVersion: logging.openshift.io/v1
kind: ClusterLogForwarder
metadata:
  name: instance (1)
  namespace: openshift-logging (2)
spec:
  pipelines:
    - inputRefs: [ myAppLogData ] (3)
      outputRefs: [ default ] (4)
  inputs: (5)
    - name: myAppLogData
      application:
        selector:
          matchLabels: (6)
            environment: production
            app: nginx
        namespaces: (7)
        - app1
        - app2
  outputs: (8)
    - default
    ...

1	The name of the `ClusterLogForwarder` CR must be `instance`.
2	The namespace for the `ClusterLogForwarder` CR must be `openshift-logging`.
3	Specify one or more comma-separated values from `inputs[].name`.
4	Specify one or more comma-separated values from `outputs[]`.
5	Define a unique `inputs[].name` for each application that has a unique set of pod labels.
6	Specify the key-value pairs of pod labels whose log data you want to gather. You must specify both a key and value, not just a key. To be selected, the pods must match all the key-value pairs.
7	Optional: Specify one or more namespaces.
8	Specify one or more outputs to forward your log data to. The optional `default` output shown here sends log data to the internal Elasticsearch instance.

Optional: To restrict the gathering of log data to specific namespaces, use inputs[].name.application.namespaces, as shown in the preceding example.
Optional: You can send log data from additional applications that have different pod labels to the same pipeline.
1. For each unique combination of pod labels, create an additional inputs[].name section similar to the one shown.
2. Update the selectors to match the pod labels of this application.
3. Add the new inputs[].name value to inputRefs. For example:
  - inputRefs: [ myAppLogData, myOtherAppLogData ]
Create the CR object:
```
$ oc create -f <file-name>.yaml
```

Additional resources

For more information on matchLabels in Kubernetes, see Resources that support set-based requirements.

Additional resources

Logging for egress firewall and network policy rules

Troubleshooting log forwarding

When you create a ClusterLogForwarder custom resource (CR), if the Red Hat OpenShift Logging Operator does not redeploy the Fluentd pods automatically, you can delete the Fluentd pods to force them to redeploy.

Prerequisites

You have created a ClusterLogForwarder custom resource (CR) object.

Procedure

Delete the Fluentd pods to force them to redeploy.

$ oc delete pod --selector logging-infra=collector