The project where eventrouter is deployed. The default is set to default.
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Do not set the project to anything other than |
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Aggregating Container Logs
- Overview
- Pre-deployment Configuration
- Specifying Logging Ansible Variables
- Deploying the EFK Stack
- Understanding and Adjusting the deployment
- Cleanup
- Sending Logs to an External Elasticsearch Instance
- Sending Logs to an External Syslog Server
- Performing Administrative Elasticsearch Operations
- Redeploying EFK Certificates
- Changing the Aggregated Logging Driver
- Manual Elasticsearch Rollouts
- Troubleshooting EFK
Overview
As an OpenShift Container Platform cluster administrator, you can deploy the EFK stack to aggregate logs for a range of OpenShift Container Platform services. Application developers can view the logs of the projects for which they have view access. The EFK stack aggregates logs from hosts and applications, whether coming from multiple containers or even deleted pods.
The EFK stack is a modified version of the ELK stack and is comprised of:
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Elasticsearch (ES): An object store where all logs are stored.
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Fluentd: Gathers logs from nodes and feeds them to Elasticsearch.
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Kibana: A web UI for Elasticsearch.
After deployment in a cluster, the stack aggregates logs from all nodes and projects into Elasticsearch, and provides a Kibana UI to view any logs. Cluster administrators can view all logs, but application developers can only view logs for projects they have permission to view. The stack components communicate securely.
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Managing
Docker Container Logs discusses the use of |
Pre-deployment Configuration
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An Ansible playbook is available to deploy and upgrade aggregated logging. You should familiarize yourself with the Installing Clusters guide. This provides information for preparing to use Ansible and includes information about configuration. Parameters are added to the Ansible inventory file to configure various areas of the EFK stack.
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Review the sizing guidelines to determine how best to configure your deployment.
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Ensure that you have deployed a router for the cluster.
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Ensure that you have the necessary storage for Elasticsearch. Note that each Elasticsearch node requires its own storage volume. See Elasticsearch for more information.
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Determine if you need highly-available Elasticsearch. A highly-available environment requires at least three Elasticsearch nodes, each on a different host. By default, OpenShift Container Platform creates one shard for each index and zero replicas of those shards. High availability also requires multiple replicas of each shard. To create high availability, set the
openshift_logging_es_number_of_replicasAnsible variable to a value higher than1. See Elasticsearch for more information.
Specifying Logging Ansible Variables
You can override the default parameter values by specifying parameters for the EFK deployment in the inventory host file.
Read the Elasticsearch and the Fluentd sections before choosing parameters:
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By default, the Elasticsearch service uses port 9300 for TCP communication between nodes in a cluster. |
| Parameter | Description |
|---|---|
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Set to |
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If set to |
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The URL for the Kubernetes master, this does not need to be public facing but should be accessible from within the cluster. For example, https://<PRIVATE-MASTER-URL>:8443. |
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The common uninstall keeps PVC to prevent unwanted data loss during
reinstalls. To ensure that the Ansible playbook completely and irreversibly
removes all logging persistent data including PVC, set
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Coupled with |
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The image version for Eventrouter.
For example: |
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The image version for the logging eventrouter. |
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Select a sink for eventrouter, supported |
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A map of labels, such as |
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The default is set to |
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The minimum amount of CPU to allocate to eventrouter. The default is set to |
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The memory limit for eventrouter pods. The default is set to |
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Specify the name of an existing pull secret to be used for pulling component images from an authenticated registry. |
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The image version for Curator.
For example: |
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The default minimum age (in days) Curator uses for deleting log records. |
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The hour of the day Curator will run. |
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The minute of the hour Curator will run. |
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The timezone Curator uses for figuring out its run time. Provide the
timezone as a string in the tzselect(8) or timedatectl(1) "Region/Locality"
format, for example |
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The script log level for Curator. |
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The log level for the Curator process. |
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The amount of CPU to allocate to Curator. |
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The amount of memory to allocate to Curator. |
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A node selector that specifies which nodes are eligible targets for deploying Curator instances. |
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Equivalent to |
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Equivalent to |
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Set to |
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The image version for Kibana.
For example: |
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The external host name for web clients to reach Kibana. |
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The amount of CPU to allocate to Kibana. |
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The amount of memory to allocate to Kibana. |
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The image version for the Kibana proxy.
For example: |
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When |
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The amount of CPU to allocate to Kibana proxy. |
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The amount of memory to allocate to Kibana proxy. |
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The number of nodes to which Kibana should be scaled up. |
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A node selector that specifies which nodes are eligible targets for deploying Kibana instances. |
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A map of environment variables to add to the Kibana deployment configuration. For example, {"ELASTICSEARCH_REQUESTTIMEOUT":"30000"}. |
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The public facing key to use when creating the Kibana route. |
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The cert that matches the key when creating the Kibana route. |
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Optional. The CA to goes with the key and cert used when creating the Kibana route. |
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Equivalent to |
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Equivalent to |
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Equivalent to |
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Equivalent to |
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Equivalent to |
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Equivalent to |
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Equivalent to |
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Set to |
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The external-facing hostname to use for the route and the TLS server
certificate. The default is set to For example, if |
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The location of the certificate Elasticsearch uses for the external TLS server cert. The default is a generated cert. |
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The location of the key Elasticsearch uses for the external TLS server cert. The default is a generated key. |
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The location of the CA cert Elasticsearch uses for the external TLS server cert. The default is the internal CA. |
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Set to |
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The external-facing hostname to use for the route and the TLS server certificate.
The default is set to For example, if |
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The location of the certificate Elasticsearch uses for the external TLS server cert. The default is a generated cert. |
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The location of the key Elasticsearch uses for the external TLS server cert. The default is a generated key. |
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The location of the CA cert Elasticsearch uses for the external TLS server cert. The default is the internal CA. |
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The image version for Fluentd.
For example: |
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A node selector that specifies which nodes are eligible targets for deploying Fluentd instances. Any node where Fluentd should run (typically, all) must have this label before Fluentd is able to run and collect logs. When scaling up the Aggregated Logging cluster after installation,
the As part of the installation, it is recommended that you add the Fluentd node selector label to the list of persisted node labels. |
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The CPU limit for Fluentd pods. |
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The memory limit for Fluentd pods. |
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Set to |
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List of nodes that should be labeled for Fluentd to be deployed. The default is
to label all nodes with ['--all']. The null value is
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When |
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Location of audit log file. The default is |
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Location of the Fluentd |
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Set to |
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Specify a comma-separated list of fields that you do not want to be altered
when processing the extra fields generated when using
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Specify a list of comma-delimited fields to keep as empty fields when using
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Set to |
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Set to |
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Specify the name of the field to move undefined fields into when using
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Set to |
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Specify a character to replace any |
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Specify a limit to the number of undefined fields when using
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Set to |
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Set to |
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The name of the Elasticsearch service where Fluentd should send logs. |
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The port for the Elasticsearch service where Fluentd should send logs. |
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The location of the CA Fluentd uses to communicate with |
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The location of the client certificate Fluentd uses for |
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The location of the client key Fluentd uses for |
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Elasticsearch nodes to deploy. High availability requires three or more. |
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The amount of CPU limit for the Elasticsearch cluster. |
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Amount of RAM to reserve per Elasticsearch instance. It must be at least 512M. Possible suffixes are G,g,M,m. |
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The number of replicas per primary shard for each new index. Defaults to '0'. A minimum of |
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The number of primary shards for every new index created in ES. Defaults to |
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A key/value map added to a PVC in order to select specific PVs. |
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To dynamically provision the backing storage, set the parameter value to If you set a value for the |
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To use a non-default storage class, specify the storage class name, such as
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Size of the persistent volume claim to
create per Elasticsearch instance. For example, 100G. If omitted, no PVCs are
created, and ephemeral volumes are used instead. If you set this parameter, the logging installer sets If the |
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The image version for Elasticsearch.
For example: |
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Sets the Elasticsearch storage type. If you are using Persistent Elasticsearch Storage, the logging installer sets this to |
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Prefix for the names of persistent volume claims to be used as storage for
Elasticsearch nodes. A number is appended per node, such as
logging-es-1. If they do not already exist, they are created with size
When
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The amount of time Elasticsearch will wait before it tries to recover. Supported time units are seconds (s) or minutes (m). |
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Number of a supplemental group ID for access to Elasticsearch storage volumes. Backing volumes should allow access by this group ID. |
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A node selector specified as a map that determines which nodes are eligible targets
for deploying Elasticsearch nodes. Use this map to place these instances on nodes that are reserved or optimized for running them.
For example, the selector could be |
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Equivalent to |
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Equivalent to |
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Equivalent to |
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Equivalent to |
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Equivalent to |
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Equivalent to |
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Equivalent to |
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Equivalent to |
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Equivalent to |
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Equivalent to |
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Equivalent to |
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Equivalent to |
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Equivalent to |
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A node selector that specifies which nodes are eligible targets
for deploying Elasticsearch nodes. This can be used to place
these instances on nodes reserved or optimized for running them.
For example, the selector could be |
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The default value, You may also set the value #oc auth can-i view pod/logs -n default yes If you do not have appropriate access, contact your cluster administrator. |
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Adjusts the time that the Ansible playbook waits for the Elasticsearch cluster to enter a green state after upgrading a given Elasticsearch node.
Large shards, 50 GB or more, can take more than 60 minutes to initialize, causing the Ansible playbook to abort the upgrade procedure.
The default is |
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A node selector that specifies which nodes are eligible targets for deploying Kibana instances. |
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A node selector that specifies which nodes are eligible targets for deploying Curator instances. |
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Set to |
Custom Certificates
You can specify custom certificates using the following inventory variables instead of relying on those generated during the deployment process. These certificates are used to encrypt and secure communication between a user’s browser and Kibana. The security-related files will be generated if they are not supplied.
| File Name | Description |
|---|---|
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A browser-facing certificate for the Kibana server. |
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A key to be used with the browser-facing Kibana certificate. |
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The absolute path on the control node to the CA file to use for the browser facing Kibana certs. |
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A browser-facing certificate for the Ops Kibana server. |
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A key to be used with the browser-facing Ops Kibana certificate. |
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The absolute path on the control node to the CA file to use for the browser facing ops Kibana certs. |
If you need to redeploy these certificates, see Redeploy EFK Certificates.
Deploying the EFK Stack
The EFK stack is deployed using an Ansible playbook to the EFK components. Run the playbook from the default OpenShift Ansible location using the default inventory file.
$ cd /usr/share/ansible/openshift-ansible
$ ansible-playbook [-i </path/to/inventory>] \
playbooks/openshift-logging/config.yml
Running the playbook deploys all resources needed to support the stack; such as
Secrets, ServiceAccounts, and deploymentConfigs, deployed to the project openshift-logging.
The playbook waits to deploy the component pods until the stack is running. If the wait steps fail, the
deployment could still be successful; it may be retrieving the component images
from the registry which can take up to a few minutes. You can watch the
process with:
$ oc get pods -w logging-curator-1541129400-l5h77 0/1 Running 0 11h (1) logging-es-data-master-ecu30lr4-1-deploy 0/1 Running 0 11h (2) logging-fluentd-2lgwn 1/1 Running 0 11h (3) logging-fluentd-lmvms 1/1 Running 0 11h logging-fluentd-p9nd7 1/1 Running 0 11h logging-kibana-1-zk94k 2/2 Running 0 11h (4)
| 1 | The Curator pod. Only one pod is needed for Curator. |
| 2 | The Elasticsearch pod on this host. |
| 3 | The Fliuentd pods. There is one pod for each node in the cluster. |
| 4 | The Kibana pods. |
You can use the `oc get pods -o wide command to see the nodes where the Fluentd pod are deployed:
$ oc get pods -o wide NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE logging-es-data-master-5av030lk-1-2x494 2/2 Running 0 38m 154.128.0.80 ip-153-12-8-6.wef.internal <none> logging-fluentd-lqdxg 1/1 Running 0 2m 154.128.0.85 ip-153-12-8-6.wef.internal <none> logging-kibana-1-gj5kc 2/2 Running 0 39m 154.128.0.77 ip-153-12-8-6.wef.internal <none>
They will eventually enter Running status. For additional details about the status of the pods during deployment by retrieving associated events:
$ oc describe pods/<pod_name>
Check the logs if the pods do not run successfully:
$ oc logs -f <pod_name>
Understanding and Adjusting the deployment
This section describes adjustments that you can make to deployed components.
Ops Cluster
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The logs for the default, openshift, and openshift-infra projects are automatically aggregated and grouped into the .operations item in the Kibana interface. The project where you have deployed the EFK stack (logging, as documented here) is not aggregated into .operations and is found under its ID. |
If you set openshift_logging_use_ops to true in your inventory file, Fluentd is
configured to split logs between the main Elasticsearch cluster and another
cluster reserved for operations logs, which are defined as node system logs and
the projects default, openshift, and openshift-infra. Therefore, a
separate Elasticsearch cluster, a separate Kibana, and a separate Curator are
deployed to index, access, and manage operations logs. These deployments are set
apart with names that include -ops. Keep these separate deployments in mind if
you enable this option. Most of the following discussion also applies to the
operations cluster if present, just with the names changed to include -ops.
Elasticsearch
Elasticsearch (ES) is an object store where all logs are stored.
Elasticsearch organizes the log data into datastores, each called an index. Elasticsearch subdivides each index into multiple pieces called shards, which it spreads across a set of Elasticsearch nodes in your cluster. You can configure Elasticsearch to make copies of the shards, called replicas. Elasticsearch also spreads replicas across the Elactisearch nodes. The combination of shards and replicas is intended to provide redundancy and resilience to failure. For example, if you configure three shards for the index with one replica, Elasticsearch generates a total of six shards for that index: three primary shards and three replicas as a backup.
The OpenShift Container Platform logging installer ensures each Elasticsearch node is deployed using a unique deployment configuration that includes its own storage volume.
You can create an additional deployment configuration for each Elasticsearch node you add to the logging system.
During installation, you can use the openshift_logging_es_cluster_size Ansible variable to specify the number of Elasticsearch nodes.
Alternatively, you can scale up your existing cluster by modifying the
openshift_logging_es_cluster_size in the inventory file and re-running the
logging playbook. Additional clustering parameters can be modified and are
described in Specifying Logging Ansible Variables.
Refer to Elastic’s documentation for considerations involved in choosing storage and network location as directed below.
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A highly-available Elasticsearch environment requires at least three Elasticsearch nodes,
each on a different host, and setting the |
Viewing all Elasticsearch deployments
To view all current Elasticsearch deployments:
$ oc get dc --selector logging-infra=elasticsearch
Configuring Elasticsearch for High Availability
A highly-available Elasticsearch environment requires at least three Elasticsearch nodes,
each on a different host, and setting the openshift_logging_es_number_of_replicas Ansible variable
to a value of 1 or higher to create replicas.
Use the following scenarios as a guide for an OpenShift Container Platform cluster with three Elasticsearch nodes:
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With
openshift_logging_es_number_of_replicasset to1, two nodes have a copy of all of the Elasticsearch data in the cluster. This ensures that if a node with Elasticsearch data goes down, another node has a copy of all of the Elasticsearch data in the cluster. -
With
openshift_logging_es_number_of_replicasset to3, four nodes have a copy of all of the Elasticsearch data in the cluster. This ensures that if three nodes with Elasticsearch data go down, one node has a copy of all of the Elasticsearch data in the cluster.In this scenario, with multiple Elasticsearch nodes going down, Elasticsearch status would be RED, and new Elasticsearch shards would not be allocated. However, because of the high availability, you do not lose your Elasticsearch data.
Note that there is a trade-off between high availability and performance.
For example, having openshift_logging_es_number_of_replicas=2 and
openshift_logging_es_number_of_shards=3 requires Elasticsearch to spend
significant resources replicating the shard data among the nodes in the cluster.
Also, using a higher number of replicas requires doubling or tripling the data storage
requirements on each node, so you must take that into account when planning
persistent storage for Elasticsearch.
Considerations when Configuring the Number of Shards
For the openshift_logging_es_number_of_shards parameter, consider:
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For higher performance, increase the number of shards. For example, in a three node cluster, set
openshift_logging_es_number_of_shards=3. This will cause each index to be split into three parts (shards), and the load for processing the index will be spread out over all 3 nodes. -
If you have a large number of projects, you might see performance degradation if you have more than a few thousand shards in the cluster. Either reduce the number of shards or reduce the curation time.
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If you have a small number of very large indices, you might want to configure
openshift_logging_es_number_of_shards=3or higher. Elasticsearch recommends using a maximum shard size of less than 50 GB.
Node Selector
Because Elasticsearch can use a lot of resources, all members of a cluster should have low latency network connections to each other and to any remote storage. Ensure this by directing the instances to dedicated nodes, or a dedicated region within your cluster, using a node selector.
To configure a node selector, specify the openshift_logging_es_nodeselector
configuration option in the inventory file. This applies to all Elasticsearch
deployments; if you need to individualize the node selectors, you must manually
edit each deployment configuration after deployment. The node selector is
specified as a python compatible dict. For example, {"node-type":"infra",
"region":"east"}.
Persistent Elasticsearch Storage
By default, the openshift_logging Ansible role creates an ephemeral
deployment in which all data in a pod is lost upon pod restart.
For production environments, each Elasticsearch deployment configuration requires a persistent storage volume. You can specify an existing persistent volume claim or allow OpenShift Container Platform to create one.
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Use existing PVCs. If you create your own PVCs for the deployment, OpenShift Container Platform uses those PVCs.
Name the PVCs to match the
openshift_logging_es_pvc_prefixsetting, which defaults tologging-es. Assign each PVC a name with a sequence number added to it:logging-es-0,logging-es-1,logging-es-2, and so on. -
Allow OpenShift Container Platform to create a PVC. If a PVC for Elsaticsearch does not exist, OpenShift Container Platform creates the PVC based on parameters in the Ansible inventory file.
Parameter Description openshift_logging_es_pvc_sizeSpecify the size of the PVC request.
openshift_logging_elasticsearch_storage_typeSpecify the storage type as
pvc.This is an optional parameter. If you set the
openshift_logging_es_pvc_sizeparameter to a value greater than 0, the logging installer automatically sets this parameter topvcby default.openshift_logging_es_pvc_prefixOptionally, specify a custom prefix for the PVC.
For example:
openshift_logging_elasticsearch_storage_type=pvc openshift_logging_es_pvc_size=104802308Ki openshift_logging_es_pvc_prefix=es-logging
If using dynamically provisioned PVs, the OpenShift Container Platform logging installer creates PVCs that use the default storage class or the PVC specified with the openshift_logging_elasticsearch_pvc_storage_class_name parameter.
If using NFS storage, the OpenShift Container Platform installer creates the persistent volumes, based on the openshift_logging_storage_* parameters
and the OpenShift Container Platform logging installer creates PVCs, using the openshift_logging_es_pvc_* parameters.
Make sure you specify the correct parameters in order to use persistent volumes with EFK.
Also set the openshift_enable_unsupported_configurations=true parameter in the Ansible inventory file, as the logging installer blocks the installation of NFS with core infrastructure by default.
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Using NFS storage as a volume or a persistent volume, or using NAS such as Gluster, is not supported for Elasticsearch storage, as Lucene relies on file system behavior that NFS does not supply. Data corruption and other problems can occur. |
If your environment requires NFS storage, use one of the following methods:
Using NFS as a persistent volume
You can deploy NFS as an automatically provisioned persistent volume or using a predefined NFS volume.
For more information, see Sharing an NFS mount across two persistent volume claims to leverage shared storage for use by two separate containers.
Using automatically provisioned NFS
To use NFS as a persistent volume where NFS is automatically provisioned:
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Add the following lines to the Ansible inventory file to create an NFS auto-provisioned storage class and dynamically provision the backing storage:
openshift_logging_es_pvc_storage_class_name=$nfsclass openshift_logging_es_pvc_dynamic=true
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Use the following command to deploy the NFS volume using the logging playbook:
ansible-playbook /usr/share/ansible/openshift-ansible/playbooks/openshift-logging/config.yml
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Use the following steps to create a PVC:
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Edit the Ansible inventory file to set the PVC size:
openshift_logging_es_pvc_size=50Gi
The logging playbook selects a volume based on size and might use an unexpected volume if any other persistent volume has same size.
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Use the following command to rerun the Ansible deploy_cluster.yml playbook:
ansible-playbook /usr/share/ansible/openshift-ansible/playbooks/deploy_cluster.yml
The installer playbook creates the NFS volume based on the
openshift_logging_storagevariables.
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Using a predefined NFS volume
To deploy logging alongside the OpenShift Container Platform cluster using an existing NFS volume:
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Edit the Ansible inventory file to configure the NFS volume and set the PVC size:
openshift_logging_storage_kind=nfs openshift_logging_storage_access_modes=['ReadWriteOnce'] openshift_logging_storage_nfs_directory=/share (1) openshift_logging_storage_nfs_options='*(rw,root_squash)' (1) openshift_logging_storage_labels={'storage': 'logging'} openshift_logging_elasticsearch_storage_type=pvc openshift_logging_es_pvc_size=10Gi openshift_logging_es_pvc_storage_class_name='' openshift_logging_es_pvc_dynamic=true openshift_logging_es_pvc_prefix=logging1 These parameters work only with the /usr/share/ansible/openshift-ansible/playbooks/deploy_cluster.ymlinstallation playbook. The parameters will not work with the/usr/share/ansible/openshift-ansible/playbooks/openshift-logging/config.ymlplaybook. -
Use the following command to redeploy the EFK stack:
ansible-playbook /usr/share/ansible/openshift-ansible/playbooks/deploy_cluster.yml
Using NFS as local storage
You can allocate a large file on an NFS server and mount the file to the nodes. You can then use the file as a host path device.
$ mount -F nfs nfserver:/nfs/storage/elasticsearch-1 /usr/local/es-storage $ chown 1000:1000 /usr/local/es-storage
Then, use /usr/local/es-storage as a host-mount as described below. Use a different backing file as storage for each Elasticsearch node.
This loopback must be maintained manually outside of OpenShift Container Platform, on the node. You must not maintain it from inside a container.
It is possible to use a local disk volume (if available) on each node host as storage for an Elasticsearch replica. Doing so requires some preparation as follows.
-
The relevant service account must be given the privilege to mount and edit a local volume:
$ oc adm policy add-scc-to-user privileged \ system:serviceaccount:openshift-logging:aggregated-logging-elasticsearchIf you upgraded from an earlier version of OpenShift Container Platform, cluster logging might have been installed in the
loggingproject. You should adjust the service account accordingly. -
Each Elasticsearch node definition must be patched to claim that privilege, for example:
$ for dc in $(oc get deploymentconfig --selector component=es -o name); do oc scale $dc --replicas=0 oc patch $dc \ -p '{"spec":{"template":{"spec":{"containers":[{"name":"elasticsearch","securityContext":{"privileged": true}}]}}}}' done -
The Elasticsearch replicas must be located on the correct nodes to use the local storage, and must not move around, even if those nodes are taken down for a period of time. This requires giving each Elasticsearch replica a node selector that is unique to a node where an administrator has allocated storage for it. To configure a node selector, edit each Elasticsearch deployment configuration, adding or editing the nodeSelector section to specify a unique label that you have applied for each desired node:
apiVersion: v1
kind: deploymentConfig
spec:
template:
spec:
nodeSelector:
logging-es-node: "1" (1)
| 1 | This label must uniquely identify a replica with a single node that bears that
label, in this case logging-es-node=1.
|
For example, if your deployment has three infrastructure nodes, you could add labels for those nodes as follows:
$ oc label node <nodename1> logging-es-node=0 $ oc label node <nodename2> logging-es-node=1 $ oc label node <nodename3> logging-es-node=2
For information about adding a label to a node, see Updating Labels on Nodes.
To automate applying the node selector, you can instead use the oc patch command:
$ oc patch dc/logging-es-<suffix> \
-p '{"spec":{"template":{"spec":{"nodeSelector":{"logging-es-node":"0"}}}}}'
Once you have completed these steps, you can apply a local host mount to each replica. The following example assumes storage is mounted at the same path on each node.
$ for dc in $(oc get deploymentconfig --selector component=es -o name); do
oc set volume $dc \
--add --overwrite --name=elasticsearch-storage \
--type=hostPath --path=/usr/local/es-storage
oc rollout latest $dc
oc scale $dc --replicas=1
done
Configuring hostPath storage for Elasticsearch
You can provision OpenShift Container Platform clusters using hostPath storage for Elasticsearch.
To use a local disk volume on each node host as storage for an Elasticsearch replica:
-
Create a local mount point on each infrastructure node for the local Elasticsearch storage:
$ mkdir /usr/local/es-storage
-
Create a filesystem on the Elasticsearch volume:
$ mkfs.ext4 /dev/xxx
-
Mount the elasticsearch volume:
$ mount /dev/xxx /usr/local/es-storage
-
Add the following line to
/etc/fstab:$ /dev/xxx /usr/local/es-storage ext4
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Change ownership for the mount point:
$ chown 1000:1000 /usr/local/es-storage
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Give the privilege to mount and edit a local volume to the relevant service account:
$ oc adm policy add-scc-to-user privileged \ system:serviceaccount:openshift-logging:aggregated-logging-elasticsearchIf you upgraded from an earlier version of OpenShift Container Platform, cluster logging might have been installed in the
loggingproject. You should adjust the service account accordingly. -
To claim that privilege, patch each Elasticsearch replica definition, as shown in the example, which specifies
--selector component=es-opsfor an Ops cluster:$ for dc in $(oc get deploymentconfig --selector component=es -o name); do oc scale $dc --replicas=0 oc patch $dc \ -p '{"spec":{"template":{"spec":{"containers":[{"name":"elasticsearch","securityContext":{"privileged": true}}]}}}}' done -
Locate the Elasticsearch replicas on the correct nodes to use the local storage, and do not move them around, even if those nodes are taken down for a period of time. To specify the node location, give each Elasticsearch replica a node selector that is unique to a node where an administrator has allocated storage for it.
To configure a node selector, edit each Elasticsearch deployment configuration, adding or editing the
nodeSelectorsection to specify a unique label that you have applied for each node you desire:apiVersion: v1 kind: deploymentConfig spec: template: spec: nodeSelector: logging-es-node: "1"The label must uniquely identify a replica with a single node that bears that label, in this case
logging-es-node=1. -
Create a node selector for each required node. Use the
oc labelcommand to apply labels to as many nodes as needed.For example, if your deployment has three infrastructure nodes, you could add labels for those nodes as follows:
$ oc label node <nodename1> logging-es-node=0 $ oc label node <nodename2> logging-es-node=1 $ oc label node <nodename3> logging-es-node=2
To automate application of the node selector, use the
oc patchcommand instead of theoc labelcommand, as follows:$ oc patch dc/logging-es-<suffix> \ -p '{"spec":{"template":{"spec":{"nodeSelector":{"logging-es-node":"1"}}}}}' -
Once you have completed these steps, you can apply a local host mount to each replica. The following example assumes storage is mounted at the same path on each node, and specifies
--selector component=es-opsfor an Ops cluster.$ for dc in $(oc get deploymentconfig --selector component=es -o name); do oc set volume $dc \ --add --overwrite --name=elasticsearch-storage \ --type=hostPath --path=/usr/local/es-storage oc rollout latest $dc oc scale $dc --replicas=1 done
Changing the Scale of Elasticsearch
If you need to scale up the number of Elasticsearch nodes in your cluster, you can create a deployment configuration for each Elasticsearch node you want to add.
Due to the nature of persistent volumes and how Elasticsearch is configured to store its data and recover the cluster, you cannot simply increase the nodes in an Elasticsearch deployment configuration.
The simplest way to change the scale of Elasticsearch is to modify the inventory host file and re-run the logging playbook as described previously. If you have supplied persistent storage for the deployment, this should not be disruptive.
|
Resizing an Elasticsearch cluster using the logging playbook is only possible when
the new |
Changing the Number of Elasticsearch Replicas
You can change the number of Elasticsearch replicas by editing the openshift_logging_es_number_of_replicas value
in the inventory host file and re-running the logging playbook as described previously.
The changes apply only to the new indices. Existing indices continue to use the previous number of replicas. For example, if you change the number of indices from 3 to 2, your cluster will use 2 replicas for new indices and 3 replicas for existing indices.
You can modify the replica count for the existing indices by running the following command:
$ oc exec -c elasticsearch $pod -- es_util --query=project.* -d '{"index":{"number_of_replicas":"2"}}' (1)
| 1 | Specify the number of replicas you want for existing indices. |
Expose Elasticsearch as a Route
By default, Elasticsearch deployed with OpenShift aggregated logging is not accessible from outside the logging cluster. You can enable a route for external access to Elasticsearch for those tools that want to access its data.
You have access to Elasticsearch using your OpenShift token, and you can provide the external Elasticsearch and Elasticsearch Ops hostnames when creating the server certificate (similar to Kibana).
-
To access Elasticsearch as a reencrypt route, define the following variables:
openshift_logging_es_allow_external=True openshift_logging_es_hostname=elasticsearch.example.com
-
Change to the playbook directory and run the following Ansible playbook:
$ cd /usr/share/ansible/openshift-ansible $ ansible-playbook [-i </path/to/inventory>] \ playbooks/openshift-logging/config.yml -
To log in to Elasticsearch remotely, the request must contain three HTTP headers:
Authorization: Bearer $token X-Proxy-Remote-User: $username X-Forwarded-For: $ip_address
-
You must have access to the project in order to be able to access to the logs. For example:
$ oc login <user1> $ oc new-project <user1project> $ oc new-app <httpd-example>
-
You need to get the token of this ServiceAccount to be used in the request:
$ token=$(oc whoami -t)
-
Using the token previously configured, you should be able access Elasticsearch through the exposed route:
$ curl -k -H "Authorization: Bearer $token" -H "X-Proxy-Remote-User: $(oc whoami)" -H "X-Forwarded-For: 127.0.0.1" https://es.example.test/project.my-project.*/_search?q=level:err | python -mjson.tool
Fluentd
Fluentd is deployed as a DaemonSet that deploys nodes according to a node
label selector, which you can specify with the inventory parameter
openshift_logging_fluentd_nodeselector and the default is logging-infra-fluentd.
As part of the OpenShift cluster installation, it is recommended that you add the
Fluentd node selector to the list of persisted
node labels.
Fluentd uses journald as the system log source. These are log messages from
the operating system, the container runtime, and OpenShift.
The available container runtimes provide minimal information to identify the source of log messages. Log collection and normalization of logs can occur after a pod is deleted and additional metadata cannot be retrieved from the API server, such as labels or annotations.
If a pod with a given name and namespace is deleted before the log collector finishes processing logs, there might not be a way to distinguish the log messages from a similarly named pod and namespace. This can cause logs to be indexed and annotated to an index that is not owned by the user who deployed the pod.
|
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. |
Clean installations of OpenShift Container Platform 3.9 or later use json-file as the default log
driver, but environments upgraded from OpenShift Container Platform 3.7 will maintain their
existing journald log driver configuration. It is recommended to use the
json-file log driver. See Changing the Aggregated
Logging Driver for instructions to change your existing log driver
configuration to json-file.
Viewing Fluentd Logs
How you view logs depends upon the LOGGING_FILE_PATH setting.
-
If
LOGGING_FILE_PATHpoints to a file, use the logs utility to print out the contents of Fluentd log files:oc exec <pod> -- logs (1)
1 Specify the name of the Fluentd pod. Note the space before logs.For example:
oc exec logging-fluentd-lmvms -- logs
The contents of log files are printed out, starting with the oldest log. Use
-foption to follow what is being written into the logs. -
If you are using
LOGGING_FILE_PATH=console, Fluentd writes logs to its default location,/var/log/fluentd/fluentd.log. You can retrieve the logs with theoc logs -f <pod_name>command.For example
oc logs -f fluentd.log
Configuring Fluentd Log Location
Fluentd writes logs to a specified file, by default /var/log/fluentd/fluentd.log, or to the console, based on the LOGGING_FILE_PATH environment variable.
To change the default output location for the Fluentd logs, use the LOGGING_FILE_PATH parameter
in the default inventory file.
You can specify a particular file or use the Fluentd default location:
LOGGING_FILE_PATH=console (1) LOGGING_FILE_PATH=<path-to-log/fluentd.log> (2)
| 1 | Sends the log output to the Fluentd default location. Retrieve the logs with the oc logs -f <pod_name> command. |
| 2 | Sends the log output to the specified file. Retrieve the logs with the oc exec <pod_name> — logs command. |
After changing these parameters, re-run the logging installer playbook:
$ cd /usr/share/ansible/openshift-ansible
$ ansible-playbook [-i </path/to/inventory>] \
playbooks/openshift-logging/config.yml
Configuring Fluentd Log Rotation
When the current Fluentd log file reaches a specified size, OpenShift Container Platform automatically renames the fluentd.log log file so that new logging data can be collected. Log rotation is enabled by default.
The following example shows logs in a cluster where the maximum log size is 1Mb and four logs should be retained. When the fluentd.log reaches 1Mb, OpenShift Container Platform deletes the current fluentd.log.4, renames each of the Fluentd logs in turn, and creates a new fluentd.log.
fluentd.log 0b fluentd.log.1 1Mb fluentd.log.2 1Mb fluentd.log.3 1Mb fluentd.log.4 1Mb
You can control the size of the Fluentd log files and how many of the renamed files that OpenShift Container Platform retains using environment variables.
| Parameter | Description |
|---|---|
|
The maximum size of a single Fluentd log file in Bytes. If the size of the flientd.log file exceeds this value, OpenShift Container Platform renames the fluentd.log.* files and creates a new fluentd.log. The default is 1024000 (1MB). |
|
The number of logs that Fluentd retains before deleting. The default value is |
For example:
$ oc set env ds/logging-fluentd LOGGING_FILE_AGE=30 LOGGING_FILE_SIZE=1024000"
Turn off log rotation by setting LOGGING_FILE_PATH=console.
This causes Fluentd to write logs to the Fluentd default location, /var/log/fluentd/fluentd.log, where you can retrieve them using the oc logs -f <pod_name> command.
$ oc set env ds/fluentd LOGGING_FILE_PATH=console
Disabling JSON parsing of logs with MERGE_JSON_LOG
By default, Fluentd determines if a log message is in JSON format and merges the message into the JSON payload document posted to Elasticsearch.
When using JSON parsing you might experience:
-
log loss due to Elasticsearch rejecting documents due to inconsistent type mappings;
-
buffer storage leaks caused by rejected message cycling;
-
overwritten data for fields with same names.
For information on how to mitigate some of these problems, see Configuring how the log collector normalizes logs.
You can disable JSON parsing to avoid these problems or if you do not need to parse JSON from your logs.
To disable JSON parsing:
-
Run the following command:
oc set env ds/logging-fluentd MERGE_JSON_LOG=false (1)
1 Set this to falseto disable this feature ortrueto enable this feature.To ensure this setting is applied each time you run Ansible, add
openshift_logging_fluentd_merge_json_log="false"to your Ansible inventory.
Configuring how the log collector normalizes logs
Cluster Logging uses a specific data model, like a database schema, to store log records and their metadata in the logging store. There are some restrictions on the data:
-
There must be a
"message"field containing the actual log message. -
There must be a
"@timestamp"field containing the log record timestamp in RFC 3339 format, preferably millisecond or better resolution. -
There must be a
"level"field with the log level, such aserr,info,unknown, and so forth.
|
For more information on the data model, see Exported Fields. |
Because of these requirements, conflicts and inconsistencies can arise with log data collected from different subsystems.
For example, if you use the MERGE_JSON_LOG feature (MERGE_JSON_LOG=true), it can be extremely useful to have your applications log their output in JSON, and have the log collector automatically parse and index the data in Elasticsearch. However, this leads to several problems, including:
-
field names can be empty, or contain characters that are illegal in Elasticsearch;
-
different applications in the same namespace might output the same field name with a different value data type;
-
applications might emit too many fields;
-
fields may conflict with the cluster logging built-in fields.
You can configure how cluster logging treats fields from disparate sources by editing the Fluentd log collector daemonset and setting environment variables in the table below.
-
Undefined fields. Fields unknown to the ViaQ data model are called undefined. Log data from disparate systems can contain undefined fields. The data model requires all top-level fields to be defined and described.
Use the parameters to configure how OpenShift Container Platform moves any undefined fields under a top-level field called
undefinedto avoid conflicting with the well known top-level fields. You can add undefined fields to the top-level fields and move others to anundefinedcontainer.You can also replace special characters in undefined fields and convert undefined fields to their JSON string representation. Converting to JSON string preserves the structure of the value, so that you can retrieve the value later and convert it back to a map or an array.
-
Simple scalar values like numbers and booleans are changed to a quoted string. For example:
10becomes"10",3.1415becomes"3.1415",falsebecomes"false". -
Map/dict values and array values are converted to their JSON string representation:
"mapfield":{"key":"value"}becomes"mapfield":"{\"key\":\"value\"}"and"arrayfield":[1,2,"three"]becomes"arrayfield":"[1,2,\"three\"]".
-
-
Defined fields. Defined fields appear in the top levels of the logs. You can configure which fields are considered defined fields.
The default top-level fields, defined through the
CDM_DEFAULT_KEEP_FIELDSparameter, areCEE,time,@timestamp,aushape,ci_job,collectd,docker,fedora-ci,file,foreman,geoip,hostname,ipaddr4,ipaddr6,kubernetes,level,message,namespace_name,namespace_uuid,offset,openstack,ovirt,pid,pipeline_metadata,service,systemd,tags,testcase,tlog,viaq_msg_id.Any fields not included in
${CDM_DEFAULT_KEEP_FIELDS}or${CDM_EXTRA_KEEP_FIELDS}are moved to${CDM_UNDEFINED_NAME}ifCDM_USE_UNDEFINEDistrue. See the table below for more information on these parameters.The
CDM_DEFAULT_KEEP_FIELDSparameter is for only advanced users, or if you are instructed to do so by Red Hat support. -
Empty fields. Empty fields have no data. You can determine which empty fields to retain from logs.
| Parameters | Definition | Example |
|---|---|---|
|
Specify an extra set of defined fields to be kept at the top level of the logs in addition to the |
|
|
Specify fields to retain in CSV format even if empty. Empty defined fields not specified are dropped. The default is "message", keep empty messages. |
|
|
Set to |
|
|
Specify a name for the undefined top level field if using |
|
|
If the number of undefined fields is greater than this number, all undefined fields are converted to their JSON string representation
and stored in the NOTE: This parameter is honored even if |
|
|
Set to |
|
|
Specify a character to use in place of a dot character '.' in an undefined field. |
|
|
If you set the When the log collector rolls over the indices, it creates a brand new index. The field definitions are updated and you will not get the 400 error. For more information, see Setting MERGE_JSON_LOG and CDM_UNDEFINED_TO_STRING. |
To configure undefined and empty field processing, edit the logging-fluentd daemonset:
-
Configure how to process fields, as needed:
-
Specify the fields to move using
CDM_EXTRA_KEEP_FIELDS. -
Specify any empty fields to retain in the
CDM_KEEP_EMPTY_FIELDSparameter in CSV format.
-
-
Configure how to process undefined fields, as needed:
-
Set
CDM_USE_UNDEFINEDtotrueto move undefined fields to the top-levelundefinedfield: -
Specify a name for the undefined fields using the
CDM_UNDEFINED_NAMEparameter. -
Set
CDM_UNDEFINED_MAX_NUM_FIELDSto a value other than the default-1, to set an upper bound on the number of undefined fields in a single record.
-
-
Specify
CDM_UNDEFINED_DOT_REPLACE_CHARto change any dot.characters in an undefined field name to another character. For example, ifCDM_UNDEFINED_DOT_REPLACE_CHAR=@@@and there is a field namedfoo.bar.bazthe field is transformed intofoo@@@bar@@@baz. -
Set
UNDEFINED_TO_STRINGtotrueto convert undefined fields to their JSON string representation.
|
If you configure the For example, when |
Setting MERGE_JSON_LOG and CDM_UNDEFINED_TO_STRING
If you set the MERGE_JSON_LOG and CDM_UNDEFINED_TO_STRING environment variables to true, you might receive an Elasticsearch 400 error. When MERGE_JSON_LOG=true, the log collector adds fields with data types other than string. If you set CDM_UNDEFINED_TO_STRING=true, Fluentd attempts to add those fields as a string value resulting in the Elasticsearch 400 error. The error clears when the indices roll over for the next day.
When Fluentd rolls over the indices for the next day’s logs, it will create a brand new index. The field definitions are updated and you will not get the 400 error.
Records that have hard errors, such as schema violations, corrupted data, and so forth, cannot be retried. The log collector sends the records for error handling. If you add a
<label @ERROR> section to your Fluentd config, as the last <label>, you can handle these records as needed.
For example:
data:
fluent.conf:
....
<label @ERROR>
<match **>
@type file
path /var/log/fluent/dlq
time_slice_format %Y%m%d
time_slice_wait 10m
time_format %Y%m%dT%H%M%S%z
compress gzip
</match>
</label>
This section writes error records to the Elasticsearch dead letter queue (DLQ) file. See the fluentd documentation for more information about the file output.
Then you can edit the file to clean up the records manually, edit the file to use with the Elasticsearch /_bulk index API and use cURL to add those records. For more information on Elasticsearch Bulk API, see the Elasticsearch documentation.
Join Multi-line Docker Logs
You can configure Fluentd to reconstruct whole log records from Docker log partial fragments. With this feature active, Fluentd reads multi-line Docker logs, reconstructs them, and stores the logs as one record in Elasticsearch with no missing data.
However, because this feature can cause a performance regression, the feature is off by default and must be manually enabled.
The following Fluentd environment variables configure cluster logging to process multi-line Docker logs:
| Parameter | Description |
|---|---|
USE_MULTILINE_JSON |
Set to |
USE_MULTILINE_JOURNAL |
Set to |
You can use the following command to determine which log driver is being used:
$ docker info | grep -i log
One of the following is output:
Logging Driver: json-file
Logging Driver: journald
To turn on multi-line Docker logs processing:
-
Use the following command to enable the multiline Docker logs:
-
For the
json-filelog driver:oc set env daemonset/logging-fluentd USE_MULTILINE_JSON=true
-
For the
journaldlog driver:oc set env daemonset/logging-fluentd USE_MULTILINE_JOURNAL=true
The Fluentd pods in the cluster restart.
-
Configuring Fluentd to Send Logs to an External Log Aggregator
You can configure Fluentd to send a copy of its logs to an external log
aggregator, in addition to the default Elasticsearch, using the secure-forward
plug-in. From there, you can further process log records after the locally
hosted Fluentd has processed them.
|
You cannot configure the |
The logging deployment provides a secure-forward.conf section in the Fluentd configmap
for configuring the external aggregator:
<store>
@type secure_forward
self_hostname pod-${HOSTNAME}
shared_key thisisasharedkey
secure yes
enable_strict_verification yes
ca_cert_path /etc/fluent/keys/your_ca_cert
ca_private_key_path /etc/fluent/keys/your_private_key
ca_private_key_passphrase passphrase
<server>
host ose1.example.com
port 24284
</server>
<server>
host ose2.example.com
port 24284
standby
</server>
<server>
host ose3.example.com
port 24284
standby
</server>
</store>
This can be updated using the oc edit command:
$ oc edit configmap/logging-fluentd
Certificates to be used in secure-forward.conf can be added to the existing
secret that is mounted on the Fluentd pods. The your_ca_cert and
your_private_key values must match what is specified in secure-forward.conf
in configmap/logging-fluentd:
$ oc patch secrets/logging-fluentd --type=json \
--patch "[{'op':'add','path':'/data/your_ca_cert','value':'$(base64 -w 0 /path/to/your_ca_cert.pem)'}]"
$ oc patch secrets/logging-fluentd --type=json \
--patch "[{'op':'add','path':'/data/your_private_key','value':'$(base64 -w 0 /path/to/your_private_key.pem)'}]"
|
Replace |
When configuring the external aggregator, it must be able to accept messages securely from Fluentd.
If the external aggregator is another Fluentd server, it must have the
fluent-plugin-secure-forward plug-in installed and make use of the input
plug-in it provides:
<source>
@type secure_forward
self_hostname ${HOSTNAME}
bind 0.0.0.0
port 24284
shared_key thisisasharedkey
secure yes
cert_path /path/for/certificate/cert.pem
private_key_path /path/for/certificate/key.pem
private_key_passphrase secret_foo_bar_baz
</source>
You can find further explanation of how to set up the
fluent-plugin-secure-forward plug-in in the
fluent-plugin-secure-forward repository.
Reducing the Number of Connections from Fluentd to the API Server
|
For more information on Red Hat Technology Preview features support scope, see https://access.redhat.com/support/offerings/techpreview/. |
mux is a Secure Forward listener service.
| Parameter | Description |
|---|---|
|
The default is set to |
|
Values for |
|
The default is set to |
|
The default is |
|
24284 |
|
500M |
|
2Gi |
|
The default is |
|
The default value is empty, allowing for additional namespaces to create for
external |
Throttling logs in Fluentd
For projects that are especially verbose, an administrator can throttle down the rate at which the logs are read in by Fluentd before being processed.
|
Throttling can contribute to log aggregation falling behind for the configured projects; log entries can be lost if a pod is deleted before Fluentd catches up. |
|
Throttling does not work when using the systemd journal as the log source. The throttling implementation depends on being able to throttle the reading of the individual log files for each project. When reading from the journal, there is only a single log source, no log files, so no file-based throttling is available. There is not a method of restricting the log entries that are read into the Fluentd process. |
To tell Fluentd which projects it should be restricting, edit the throttle configuration in its ConfigMap after deployment:
$ oc edit configmap/logging-fluentd
The format of the throttle-config.yaml key is a YAML file that contains project names and the desired rate at which logs are read in on each node. The default is 1000 lines at a time per node. For example:
-
Projects
project-name: read_lines_limit: 50 second-project-name: read_lines_limit: 100
-
Logging
logging: read_lines_limit: 500 test-project: read_lines_limit: 10 .operations: read_lines_limit: 100
To make changes to Fluentd, change the configuration and restart the Fluentd pods to apply the changes. To make changes to Elasticsearch, you must first scale down Fluentd and then scale down Elasticsearch to zero. After making your changes, scale Elasticsearch first and then scale Fluentd back to its original setting.
To scale Elasticsearch to zero:
$ oc scale --replicas=0 dc/<ELASTICSEARCH_DC>
Change nodeSelector in the daemonset configuration to match zero:
Get the Fluentd node selector:
$ oc get ds logging-fluentd -o yaml |grep -A 1 Selector
nodeSelector:
logging-infra-fluentd: "true"
Use the
oc patch command to modify the daemonset nodeSelector:$ oc patch ds logging-fluentd -p '{"spec":{"template":{"spec":{"nodeSelector":{"nonexistlabel":"true"}}}}}'
Get the Fluentd node selector:
$ oc get ds logging-fluentd -o yaml |grep -A 1 Selector
nodeSelector:
"nonexistlabel: "true"
Scale Elasticsearch back up from zero:
$ oc scale --replicas=# dc/<ELASTICSEARCH_DC>
Change nodeSelector in the daemonset configuration back to logging-infra-fluentd: "true".
Use the oc patch command to modify the daemonset nodeSelector:
oc patch ds logging-fluentd -p '{"spec":{"template":{"spec":{"nodeSelector":{"logging-infra-fluentd":"true"}}}}}'
Tune Buffer Chunk Limit
If Fluentd logger is unable to keep up with a high number of logs, it will need to switch to file buffering to reduce memory usage and prevent data loss.
The Fluentd buffer_chunk_limit is determined by the environment variable
BUFFER_SIZE_LIMIT, which has the default value 8m. The file buffer size per
output is determined by the environment variable FILE_BUFFER_LIMIT, which has
the default value 256Mi. The permanent volume size must be larger than
FILE_BUFFER_LIMIT multiplied by the output.
On the Fluentd and Mux pods, permanent volume /var/lib/fluentd should be prepared by the PVC or hostmount, for example. That area is then used for the file buffers.
The buffer_type and buffer_path are configured in the Fluentd configuration files as
follows:
$ egrep "buffer_type|buffer_path" *.conf
output-es-config.conf:
buffer_type file
buffer_path `/var/lib/fluentd/buffer-output-es-config`
output-es-ops-config.conf:
buffer_type file
buffer_path `/var/lib/fluentd/buffer-output-es-ops-config`
filter-pre-mux-client.conf:
buffer_type file
buffer_path `/var/lib/fluentd/buffer-mux-client`The Fluentd buffer_queue_limit is the value of the variable BUFFER_QUEUE_LIMIT. This value is 32 by default.
The environment variable BUFFER_QUEUE_LIMIT is calculated as (FILE_BUFFER_LIMIT / (number_of_outputs * BUFFER_SIZE_LIMIT)).
If the BUFFER_QUEUE_LIMIT variable has the default set of values:
-
FILE_BUFFER_LIMIT = 256Mi -
number_of_outputs = 1 -
BUFFER_SIZE_LIMIT = 8Mi
The value of buffer_queue_limit will be 32. To change the buffer_queue_limit, you need to change the value of FILE_BUFFER_LIMIT.
In this formula, number_of_outputs is 1 if all the logs are sent to a single resource, and it is incremented by 1 for each additional resource. For example, the value of number_of_outputs is:
-
1- if all logs are sent to a single ElasticSearch pod -
2- if application logs are sent to an ElasticSearch pod and ops logs are sent to another ElasticSearch pod -
4- if application logs are sent to an ElasticSearch pod, ops logs are sent to another ElasticSearch pod, and both of them are forwarded to other Fluentd instances
Kibana
To access the Kibana console from the OpenShift Container Platform web console, add the
loggingPublicURL parameter in the
master
webconsole-config configmap file, with the URL of the Kibana console (the
kibana-hostname parameter). The value must be an HTTPS URL:
... clusterInfo: ... loggingPublicURL: "https://kibana.example.com" ...
Setting the loggingPublicURL parameter creates a View Archive button on the
OpenShift Container Platform web console under the Browse → Pods → <pod_name> →
Logs tab. This links to the Kibana console.
|
You need to log in to the Kibana console when your valid login cookie expires, for example: you need to log in:
|
You can scale the Kibana deployment as usual for redundancy:
$ oc scale dc/logging-kibana --replicas=2
|
To ensure the scale persists across multiple executions of the logging playbook,
make sure to update the |
You can see the user interface by visiting the site specified by the
openshift_logging_kibana_hostname variable.
See the Kibana documentation for more information on Kibana.
Kibana Visualize
Kibana Visualize enables you to create visualizations and dashboards for
monitoring container and pod logs allows administrator users (cluster-admin or
cluster-reader) to view logs by deployment, namespace, pod, and container.
Kibana Visualize exists inside the Elasticsearch and ES-OPS pod, and must be run inside those pods. To load dashboards and other Kibana UI objects, you must first log in to Kibana as the user you want to add the dashboards to, then log out. This will create the necessary per-user configuration that the next step relies on. Then, run:
$ oc exec <$espod> -- es_load_kibana_ui_objects <user-name>
Where $espod is the name of any one of your Elasticsearch pods.
Adding Custom Fields to Kibana Visualize
If your OpenShift Container Platform cluster generates logs in JSON format that contain custom fields
that are not defined in the Elasticsearch .operations.* or the project.*
indices, you cannot create visualizations with these fields because the custom fields are not
available in Kibana.
However, you can add the custom fields to the Elasticsearch indices, which allows you to add the fields to the Kibana index patterns for use in Kibana Visualize.
|
The custom fields are applied to only the indices created after the template is updated. |
To add custom fields to Kibana Visualize:
-
Add custom fields to an Elasticsearch index template:
-
Determine which Elasticsearch index you want to add the fields to, either the
.operations.*or theproject.*index. If there is a specific project that has the custom fields, you add the fields to a specific index for the project, for example:project.this-project-has-time-fields.*. -
Create a JSON file for the custom fields, similar to the following:
For example:
{ "order": 20, "mappings": { "_default_": { "properties": { "mytimefield1": { (1) "doc_values": true, "format": "yyyy-MM-dd HH:mm:ss,SSSZ||yyyy-MM-dd'T'HH:mm:ss.SSSSSSZ||yyyy-MM-dd'T'HH:mm:ssZ||dateOptionalTime", "index": "not_analyzed", "type": "date" }, "mytimefield2": { "doc_values": true, "format": "yyyy-MM-dd HH:mm:ss,SSSZ||yyyy-MM-dd'T'HH:mm:ss.SSSSSSZ||yyyy-MM-dd'T'HH:mm:ssZ||dateOptionalTime", "index": "not_analyzed", "type": "date" } } } }, "template": "project.<project-name>.*" (2) }1 Add a custom field and parameters. 2 Specify the .operations.*orproject.*index. -
Change to the
openshift-loggingproject:$ oc project openshift-logging
-
Get the name of one of the Elasticsearch pods:
$ oc get -n logging pods -l component=es NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE logging-es-data-master-5av030lk-1-2x494 2/2 Running 0 38m 154.128.0.80 ip-153-12-8-6.wef.internal <none>
-
Load the JSON file into the Elasticsearch pod:
$ cat <json-file-name> | \ (1) oc exec -n logging -i -c elasticsearch <es-pod-name> -- \ (2) curl -s -k --cert /etc/elasticsearch/secret/admin-cert \ --key /etc/elasticsearch/secret/admin-key \ https://localhost:9200/_template/<json-file-name> -XPUT -d@- | \ (1) python -mjson.tool1 The name of the JSON file you created. 2 The name of the Elasticsearch pod. { "acknowledged": true } -
If you have a separate OPS cluster, get the name of one of the es-ops Elasticsearch pods:
$ oc get -n logging pods -l component=es-ops NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE logging-es-ops-data-master-o7nhcbo4-5-b7stm 2/2 Running 0 38m 154.128.0.80 ip-153-12-8-6.wef.internal <none>
-
Load the JSON file into the es-ops Elasticsearch pod:
$ cat <json-file-name> | \ (1) oc exec -n logging -i -c elasticsearch <esops-pod-name> -- \ (2) curl -s -k --cert /etc/elasticsearch/secret/admin-cert \ --key /etc/elasticsearch/secret/admin-key \ https://localhost:9200/_template/<json-file-name> -XPUT -d@- | \ (1) python -mjson.tool1 The name of the JSON file you created. 2 The name of the OPS cluster Elasticsearch pod. The output appears similar to the following:
{ "acknowledged": true } -
Verify that the indices are updated:
oc exec -n logging -i -c elasticsearch <es-pod-name> -- \ (1) curl -s -k --cert /etc/elasticsearch/secret/admin-cert \ --key /etc/elasticsearch/secret/admin-key \ https://localhost:9200/project.*/_search?sort=<custom-field>:desc | \ (2) python -mjson.tool1 The name of the Elasticsearch or OPS cluster Elasticsearch pod. 2 The name of a custom field you added. The command outputs the index records for your custom fields sorted in descending order.
The settings do not apply to existing indices. If you want to apply the settings to existing indices, perform a re-index.
-
-
Add the custom fields to Kibana:
-
Get the existing index pattern file from your Elasticsearch container:
$ mkdir index_patterns $ cd index_patterns $ oc project openshift-logging $ for espod in $( oc get pods -l component=es -o jsonpath='{.items[*].metadata.name}' ) ; do > for ff in $( oc exec -c elasticsearch <es-pod-name> -- ls /usr/share/elasticsearch/index_patterns ) ; do > oc exec -c elasticsearch <es-pod-name> -- cat /usr/share/elasticsearch/index_patterns/$ff > $ff > done > break > doneThe index pattern files are downloaded to the /usr/share/elasticsearch/index_patterns directory.
For example:
index_patterns $ ls com.redhat.viaq-openshift.index-pattern.json
-
Edit the corresponding index pattern files to add a definition for each custom field to the
fieldsvalue:For example:
{\"count\": 0, \"name\": \"mytimefield2\", \"searchable\": true, \"aggregatable\": true, \"readFromDocValues\": true, \"type\": \"date\", \"scripted\": false},The definition must contain the
\"searchable\": true,and\"aggregatable\": true,parameters in order to be used in visualizations. The data type must correspond to the Elasticsearch field definition you added above. For example, if you added themyfieldfield in Elasticsearch that is anumbertype, you cannot addmyfieldto Kibana as astringtype. -
In the index pattern file, add the name of the Kibana index pattern to the index pattern files:
For example, to use the operations.\* index pattern:
"title": "*operations.*"
To use the project.MYNAMESPACE.\* index pattern:
"title": "project.MYNAMESPACE.*"
-
Identify the user name and get the hash value of the user name. The index patterns are stored using the hash of the user name. Run the following two commands in order:
$ get_hash() { > printf "%s" "$1" | sha1sum | awk '{print $1}' > }$ get_hash admin d0aeb5660fc2140aec35850c4da997
-
Apply the index pattern file to Elasticsearch:
cat com.redhat.viaq-openshift.index-pattern.json | \ (1) oc exec -i -c elasticsearch <espod-name> -- es_util \ --query=".kibana.<user-hash>/index-pattern/<index>" -XPUT --data-binary @- | \ (2) python -mjson.tool1 The name of the index pattern file. 2 The user hash and the index, either .operations.*orproject.*.For example:
cat index-pattern.json | \ oc exec -i -c elasticsearch mypod-23-gb9pl -- es_util \ --query=".kibana.d0aeb5660fc2140aec35850c4da997/index-pattern/project.MYNAMESPACE.*" -XPUT --data-binary @- | \ python -mjson.toolThe output appears similar to the following:
{ "_id": ".operations.*", "_index": ".kibana.d0aeb5660fc2140aec35850c4da997", "_shards": { "failed": 0, "successful": 2, "total": 2 }, "_type": "index-pattern", "_version": 1, "created": true, "result": "created" } -
Exit and restart the Kibana console for the custom fields to appear in the Available Fields list and in the fields list on the Management → Index Patterns page.
-
Curator
Curator allows administrators to configure scheduled Elasticsearch maintenance operations to be performed automatically on a per-project basis. It is scheduled to perform actions daily based on its configuration. Only one Curator pod is recommended per Elasticsearch cluster. Curator pods only run at the time stated in the cronjob and then the pod terminates upon completion. Curator is configured via a YAML configuration file with the following structure:
|
The time zone is set based on the host node where the curator pod runs. |
$PROJECT_NAME:
$ACTION:
$UNIT: $VALUE
$PROJECT_NAME:
$ACTION:
$UNIT: $VALUE
...
The available parameters are:
| Variable Name | Description |
|---|---|
|
The actual name of a project, such as myapp-devel. For OpenShift Container Platform operations
logs, use the name |
|
The action to take, currently only |
|
One of |
|
An integer for the number of units. |
|
Use |
|
The list of regular expressions that match project names. |
|
The valid and properly escaped regular expression pattern enclosed by single quotation marks. |
For example, to configure Curator to:
-
Delete indices in the myapp-dev project older than
1 day -
Delete indices in the myapp-qe project older than
1 week -
Delete operations logs older than
8 weeks -
Delete all other projects indices after they are
31 daysold -
Delete indices older than 1 day that are matched by the '^project\..+\-dev.*$' regex
-
Delete indices older than 2 days that are matched by the '^project\..+\-test.*$' regex
Use:
config.yaml: |
myapp-dev:
delete:
days: 1
myapp-qe:
delete:
weeks: 1
.operations:
delete:
weeks: 8
.defaults:
delete:
days: 31
.regex:
- pattern: '^project\..+\-dev\..*$'
delete:
days: 1
- pattern: '^project\..+\-test\..*$'
delete:
days: 2
|
When you use |
Using the Curator Actions File
Setting the OpenShift Container Platform custom configuration file format ensures internal indices are not mistakenly deleted.
To use the actions file, add an exclude rule to your Curator configuration to retain these indices. You must manually add all of the required patterns.
actions.yaml: |
actions:
action: delete_indices
description: be careful!
filters:
- exclude: false
kind: regex
filtertype: pattern
value: '^project\.myapp\..*$'
- direction: older
filtertype: age
source: name
timestring: '%Y.%m.%d'
unit_count: 7
unit: days
options:
continue_if_exception: false
timeout_override: '300'
ignore_empty_list: true
action: delete_indices
description: be careful!
filters:
- exclude: false
kind: regex
filtertype: pattern
value: '^\.operations\..*$'
- direction: older
filtertype: age
source: name
timestring: '%Y.%m.%d'
unit_count: 56
unit: days
options:
continue_if_exception: false
timeout_override: '300'
ignore_empty_list: true
action: delete_indices
description: be careful!
filters:
- exclude: true
kind: regex
filtertype: pattern
value: '^project\.myapp\..*$|^\.operations\..*$|^\.searchguard\..*$|^\.kibana$'
- direction: older
filtertype: age
source: name
timestring: '%Y.%m.%d'
unit_count: 30
unit: days
options:
continue_if_exception: false
timeout_override: '300'
ignore_empty_list: true
Creating the Curator Configuration
The openshift_logging Ansible role provides a ConfigMap from which Curator
reads its configuration. You may edit or replace this ConfigMap to reconfigure
Curator. Currently the logging-curator ConfigMap is used to configure both
your ops and non-ops Curator instances. Any .operations configurations are
in the same location as your application logs configurations.
-
To create the Curator configuration, edit the configuration in the deployed ConfigMap:
$ oc edit configmap/logging-curator
Or, manually create the jobs from a cronjob:
oc create job --from=cronjob/logging-curator <job_name>
-
For scripted deployments, copy the configuration file that was created by the installer and create your new OpenShift Container Platform custom configuration:
$ oc extract configmap/logging-curator --keys=curator5.yaml,config.yaml --to=/my/config edit /my/config/curator5.yaml edit /my/config/config.yaml $ oc delete configmap logging-curator ; sleep 1 $ oc create configmap logging-curator \ --from-file=curator5.yaml=/my/config/curator5.yaml \ --from-file=config.yaml=/my/config/config.yaml \ ; sleep 1 -
Alternatively, if you are using the actions file:
$ oc extract configmap/logging-curator --keys=curator5.yaml,actions.yaml --to=/my/config edit /my/config/curator5.yaml edit /my/config/actions.yaml $ oc delete configmap logging-curator ; sleep 1 $ oc create configmap logging-curator \ --from-file=curator5.yaml=/my/config/curator5.yaml \ --from-file=actions.yaml=/my/config/actions.yaml \ ; sleep 1
-
The next scheduled job uses this configuration.
You can use the following commands to control the cronjob:
# suspend cronjob
oc patch cronjob logging-curator -p '{"spec":{"suspend":true}}'
# resume cronjob
oc patch cronjob logging-curator -p '{"spec":{"suspend":false}}
# change cronjob schedule
oc patch cronjob logging-curator -p '{"spec":{"schedule":"0 0 * * *"}}' (1)
| 1 | The schedule option accepts schedules in cron format. |
Cleanup
Remove everything generated during the deployment.
$ cd /usr/share/ansible/openshift-ansible
$ ansible-playbook [-i </path/to/inventory>] \
playbooks/openshift-logging/config.yml \
-e openshift_logging_install_logging=False
Sending Logs to an External Elasticsearch Instance
Fluentd sends logs to the value of the ES_HOST, ES_PORT, OPS_HOST,
and OPS_PORT environment variables of the Elasticsearch deployment
configuration. The application logs are directed to the ES_HOST destination,
and operations logs to OPS_HOST.
|
Sending logs directly to an AWS Elasticsearch instance is not supported. Use
Fluentd Secure Forward to direct logs to
an instance of Fluentd that you control and that is configured with the
|
To direct logs to a specific Elasticsearch instance, edit the deployment configuration and replace the value of the above variables with the desired instance:
$ oc edit ds/<daemon_set>
For an external Elasticsearch instance to contain both application and
operations logs, you can set ES_HOST and OPS_HOST to the same destination,
while ensuring that ES_PORT and OPS_PORT also have the same value.
Only Mutual TLS configuration is supported, as the provided Elasticsearch instance does. Patch or recreate the logging-fluentd secret with your client key, client cert, and CA.
|
If you are not using the provided Kibana and Elasticsearch images, you will not have the same multi-tenant capabilities and your data will not be restricted by user access to a particular project. |
Sending Logs to an External Syslog Server
Use the fluent-plugin-remote-syslog plug-in on the host to send logs to an
external syslog server.
Set environment variables in the logging-fluentd or logging-mux daemonsets:
- name: REMOTE_SYSLOG_HOST (1)
value: host1
- name: REMOTE_SYSLOG_HOST_BACKUP
value: host2
- name: REMOTE_SYSLOG_PORT_BACKUP
value: 5555| 1 | The desired remote syslog host. Required for each host. |
This will build two destinations. The syslog server on host1 will be
receiving messages on the default port of 514, while host2 will be receiving
the same messages on port 5555.
Alternatively, you can configure your own custom fluent.conf in the
logging-fluentd or logging-mux ConfigMaps.
Fluentd Environment Variables
| Parameter | Description |
|---|---|
|
Defaults to |
|
(Required) Hostname or IP address of the remote syslog server. |
|
Port number to connect on. Defaults to |
|
Set the syslog severity level. Defaults to |
|
Set the syslog facility. Defaults to |
|
Defaults to |
|
Removes the prefix from the tag, defaults to |
|
If specified, uses this field as the key to look on the record, to set the tag on the syslog message. |
|
If specified, uses this field as the key to look on the record, to set the payload on the syslog message. |
|
Set the transport layer protocol type. Defaults to |
|
This implementation is insecure, and should only be used in environments where you can guarantee no snooping on the connection. |
Fluentd Logging Ansible Variables
| Parameter | Description |
|---|---|
|
The default is set to |
|
Hostname or IP address of the remote syslog server, this is mandatory. |
|
Port number to connect on, defaults to |
|
Set the syslog severity level, defaults to |
|
Set the syslog facility, defaults to |
|
The default is set to |
|
Removes the prefix from the tag, defaults to |
|
If string is specified, uses this field as the key to look on the record, to set the tag on the syslog message. |
|
If string is specified, uses this field as the key to look on the record, to set the payload on the syslog message. |
Mux Logging Ansible Variables
| Parameter | Description |
|---|---|
|
The default is set to |
|
Hostname or IP address of the remote syslog server, this is mandatory. |
|
Port number to connect on, defaults to |
|
Set the syslog severity level, defaults to |
|
Set the syslog facility, defaults to |
|
The default is set to |
|
Removes the prefix from the tag, defaults to |
|
If string is specified, uses this field as the key to look on the record, to set the tag on the syslog message. |
|
If string is specified, uses this field as the key to look on the record, to set the payload on the syslog message. |
Performing Administrative Elasticsearch Operations
As of logging version 3.2.0, an administrator certificate, key, and CA that can be used to communicate with and perform administrative operations on Elasticsearch are provided within the logging-elasticsearch secret.
|
To confirm whether or not your EFK installation provides these, run: $ oc describe secret logging-elasticsearch |
-
Connect to an Elasticsearch pod that is in the cluster on which you are attempting to perform maintenance.
-
To find a pod in a cluster use either:
$ oc get pods -l component=es -o name | head -1 $ oc get pods -l component=es-ops -o name | head -1
-
Connect to a pod:
$ oc rsh <your_Elasticsearch_pod>
-
Once connected to an Elasticsearch container, you can use the certificates mounted from the secret to communicate with Elasticsearch per its Indices APIs documentation.
Fluentd sends its logs to Elasticsearch using the index format project.{project_name}.{project_uuid}.YYYY.MM.DD where YYYY.MM.DD is the date of the log record.
For example, to delete all logs for the openshift-logging project with uuid 3b3594fa-2ccd-11e6-acb7-0eb6b35eaee3 from June 15, 2016, we can run:
$ curl --key /etc/elasticsearch/secret/admin-key \ --cert /etc/elasticsearch/secret/admin-cert \ --cacert /etc/elasticsearch/secret/admin-ca -XDELETE \ "https://localhost:9200/project.logging.3b3594fa-2ccd-11e6-acb7-0eb6b35eaee3.2016.06.15"
Redeploying EFK Certificates
You can use an Ansible playbook to perform a certificate rotation for the EFK stack without needing to run the install/upgrade playbook.
This playbook deletes the current certificate files, generates new EFK certificates, updates certificate secrets, and restarts Kibana and Elasticsearch to force those components to read in the updated certificates.
To redeploy EFK certificates:
-
Use the Ansible playbook to redeploy the EFK certificates:
$ cd /usr/share/ansible/openshift-ansible $ ansible-playbook playbooks/openshift-logging/redeploy-certificates.yml
Changing the Aggregated Logging Driver
For aggregated logging, it is recommended to use the json-file log driver.
|
When using the |
Fluentd determines the driver Docker is using by checking the /etc/docker/daemon.json and /etc/sysconfig/docker files.
You can determine which driver Docker is using with the docker info command:
# docker info | grep Logging Logging Driver: journald
To change to json-file:
-
Modify either the /etc/sysconfig/docker or /etc/docker/daemon.json files.
For example:
# cat /etc/sysconfig/docker OPTIONS=' --selinux-enabled --log-driver=json-file --log-opt max-size=1M --log-opt max-file=3 --signature-verification=False' cat /etc/docker/daemon.json { "log-driver": "json-file", "log-opts": { "max-size": "1M", "max-file": "1" } } -
Restart the Docker service:
systemctl restart docker
-
Restart Fluentd.
Restarting Fluentd on more than a dozen nodes at once will create a large load on the Kubernetes scheduler. Exercise caution when using the following the directions to restart Fluentd.
There are two methods for restarting Fluentd. You can restart the Fluentd on one node or a set of nodes, or on all nodes.
-
The following steps demonstrate how to restart Fluentd on one node or a set of nodes.
-
List the nodes where Fluentd is running:
$ oc get nodes -l logging-infra-fluentd=true
-
For each node, remove the label and turn off Fluentd:
$ oc label node $node logging-infra-fluentd-
-
Verify Fluentd is off:
$ oc get pods -l component=fluentd
-
For each node, restart Fluentd:
$ oc label node $node logging-infra-fluentd=true
-
-
The following steps demonstrate how to restart the Fluentd all nodes.
-
Turn off Fluentd on all nodes:
$ oc label node -l logging-infra-fluentd=true --overwrite logging-infra-fluentd=false
-
Verify Fluentd is off:
$ oc get pods -l component=fluentd
-
Restart Fluentd on all nodes:
$ oc label node -l logging-infra-fluentd=false --overwrite logging-infra-fluentd=true
-
Verify Fluentd is on:
$ oc get pods -l component=fluentd
-
-
Manual Elasticsearch Rollouts
As of OpenShift Container Platform 3.7 the Aggregated Logging stack updated the Elasticsearch
deployment Config object so that it no longer has a Config Change Trigger, meaning
any changes to the dc will not result in an automatic rollout. This was to prevent
unintended restarts happening in the Elasticsearch cluster, which could create excessive shard
rebalancing as cluster members restart.
This section presents two restart procedures: rolling-restart and full-restart. Where a rolling restart applies appropriate changes to the Elasticsearch cluster without down time (provided three masters are configured) and a full restart safely applies major changes without risk to existing data.
Performing an Elasticsearch Rolling Cluster Restart
A rolling restart is recommended, when any of the following changes are made:
-
nodes on which Elasticsearch pods run require a reboot
-
logging-elasticsearch configmap
-
logging-es-* deployment configuration
-
new image deployment, or upgrade
This will be the recommended restart policy going forward.
|
Any action you do for an Elasticsearch cluster will need to be repeated for the ops cluster
if |
-
Prevent shard balancing when purposely bringing down nodes:
$ oc exec -c elasticsearch <any_es_pod_in_the_cluster> -- \ curl -s \ --cacert /etc/elasticsearch/secret/admin-ca \ --cert /etc/elasticsearch/secret/admin-cert \ --key /etc/elasticsearch/secret/admin-key \ -XPUT 'https://localhost:9200/_cluster/settings' \ -d '{ "transient": { "cluster.routing.allocation.enable" : "none" } }' -
Once complete, for each
dcyou have for an Elasticsearch cluster, runoc rollout latestto deploy the latest version of thedcobject:$ oc rollout latest <dc_name>
You will see a new pod deployed. Once the pod has two ready containers, you can move on to the next
dc. -
Once all `dc`s for the cluster have been rolled out, re-enable shard balancing:
$ oc exec -c elasticsearch <any_es_pod_in_the_cluster> -- \ curl -s \ --cacert /etc/elasticsearch/secret/admin-ca \ --cert /etc/elasticsearch/secret/admin-cert \ --key /etc/elasticsearch/secret/admin-key \ -XPUT 'https://localhost:9200/_cluster/settings' \ -d '{ "transient": { "cluster.routing.allocation.enable" : "all" } }'
Performing an Elasticsearch Full Cluster Restart
A full restart is recommended when changing major versions of Elasticsearch or other changes which might put data integrity a risk during the change process.
|
Any action you do for an Elasticsearch cluster will need to be repeated for the ops cluster
if |
|
When making changes to the |
-
Disable all external communications to the Elasticsearch cluster while it is down. Edit your non-cluster logging service (for example,
logging-es,logging-es-ops) to no longer match the Elasticsearch pods running:$ oc patch svc/logging-es -p '{"spec":{"selector":{"component":"es-blocked","provider":"openshift"}}}' -
Perform a shard synced flush to ensure there are no pending operations waiting to be written to disk prior to shutting down:
$ oc exec -c elasticsearch <any_es_pod_in_the_cluster> -- \ curl -s \ --cacert /etc/elasticsearch/secret/admin-ca \ --cert /etc/elasticsearch/secret/admin-cert \ --key /etc/elasticsearch/secret/admin-key \ -XPOST 'https://localhost:9200/_flush/synced' -
Prevent shard balancing when purposely bringing down nodes:
$ oc exec -c elasticsearch <any_es_pod_in_the_cluster> -- \ curl -s \ --cacert /etc/elasticsearch/secret/admin-ca \ --cert /etc/elasticsearch/secret/admin-cert \ --key /etc/elasticsearch/secret/admin-key \ -XPUT 'https://localhost:9200/_cluster/settings' \ -d '{ "transient": { "cluster.routing.allocation.enable" : "none" } }' -
Once complete, for each
dcyou have for an Elasticsearch cluster, scale down all nodes:$ oc scale dc <dc_name> --replicas=0
-
Once scale down is complete, for each
dcyou have for an Elasticsearch cluster, runoc rollout latestto deploy the latest version of thedcobject:$ oc rollout latest <dc_name>
You will see a new pod deployed. Once the pod has two ready containers, you can move on to the next
dc. -
Once deployment is complete, for each
dcyou have for an Elasticsearch cluster, scale up the nodes:$ oc scale dc <dc_name> --replicas=1
-
Once the scale up is complete, enable all external communications to the ES cluster. Edit your non-cluster logging service (for example,
logging-es,logging-es-ops) to match the Elasticsearch pods running again:$ oc patch svc/logging-es -p '{"spec":{"selector":{"component":"es","provider":"openshift"}}}'
Troubleshooting EFK
The following is troubleshooting information for a number of commonly identified issues with cluster logging deployments:
Troubleshooting related to all EFK components
The following troubleshooting issues apply to the EFK stack in general.
deployment fails, ReplicationControllers scaled to 0
If you perform a deployment that does not successfully bring up an
instance before a ten-minute timeout, OpenShift Container Platform considers the deployment as failed
and scales down to zero instances. The oc get pods command shows a deployer pod
with a non-zero exit code and no deployed pods.
In the following example, the deployer pod name for an Elasticsearch deployment is shown;
this is from ReplicationController logging-es-2e7ut0iq-1, which is a deployment
of deploymentConfig logging-es-2e7ut0iq.
NAME READY STATUS RESTARTS AGE logging-es-2e7ut0iq-1-deploy 1/1 ExitCode:255 0 1m
deployment failure can happen for a number of transitory reasons, such as the image pull taking too long or nodes being unresponsive.
Examine the deployer pod logs for possible reasons or attempt to redeploy:
$ oc deploy --latest logging-es-2e7ut0iq
Alternatively, attempt to scale up the existing deployment:
$ oc scale --replicas=1 logging-es-2e7ut0iq-1
If the problem persists, examine the pod, events, and systemd unit logs to determine the source of the problem.
Cannot resolve kubernetes.default.svc.cluster.local
This internal alias for the master must be resolvable by the included DNS server on the master.
Depending on your platform, you can run the dig command (for example, in a container) against the master to check whether this is the case:
$ dig kubernetes.default.svc.cluster.local @localhost [...] ;; QUESTION SECTION: ;kubernetes.default.svc.cluster.local. IN A ;; ANSWER SECTION: kubernetes.default.svc.cluster.local. 30 IN A 172.30.0.1
Older versions of cluster logging did not automatically define this internal alias for the master. You might need to upgrade your cluster in order to use aggregated logging. If your cluster is up to date, there might be a problem with your pods reaching the SkyDNS resolver at the master or the pod could have been blocked from running. You must resolve this problem before deploying again.
Cannot connect to the master or services
If DNS resolution does not return at all or the address cannot be connected to from within a pod (such as the fluentd pod), this could be an indication of a system firewall/network problem. You must debug this problem.
Troubleshooting related to ElasticSearch
The following troubleshooting issues apply to the ElasticSearch components of the EFK stack.
Elasticsearch deployments never succeed and rollback to previous version
This situation typically occurs itself on OpenShift Container Platform with cluster logging deployed on AWS. Describing the Elasticsearch pods typically reveals issues re-attaching the pods storage:
$ oc describe pod <elasticsearch-pod>
Consider patching each Elasticsearch deployment configuration to allow more time for AWS to make the storage available:
$ oc patch dc <elasticsearch-deployment-config> -p '{"spec":{"strategy":{"recreateParams": {"timeoutSeconds":1800}}}}'
Searchguard index remains red
This is a known issue related to upgrading and moving to a single SearchGuard index per cluster instead of one index per deployment configuration. The Elasticsearch Explain API is used to discover the reason and removing the index to node assignment is required:
$ oc -c elasticsearch exec ${pod} -- es_util --query=".searchguard/_settings" -XPUT -d "{\"index.routing.allocation.include._name\": \"\"}"
Elasticsearch pods never become ready
This is known issue when the initialization and seeding process fails, which
can be from a red .searchguard index.
for p in $(oc get pods -l component=es -o jsonpath={.items[*].metadata.name}); do \
oc exec -c elasticsearch $p -- touch /opt/app-root/src/init_failures; \
done
Kibana
The following troubleshooting issues apply to the Kibana components of the EFK stack.
Looping log in on Kibana
If you launch the Kibana console and login successfully, you are incorrectly redirected back to Kibana, which immediately redirects back to the login screen.
The likely cause for this issue is that the OAuth2 proxy in front of Kibana must share a secret with the master’s OAuth2 server in order to identify it as a valid client. This problem could indicate that the secrets do not match. Nothing reports this problem in a way that can be exposed.
This can happen when you deploy logging more than once. For example, if you fix the initial deployment and the secret
used by Kibana is replaced while the matching master oauthclient entry to match is not replaced.
You can do the following:
$ oc delete oauthclient/kibana-proxy
Follow the openshift-ansible instructions to re-run the openshift_logging role.
This replaces the oauthclient and your next successful login should not loop.
*"error":"invalid\_request" on login*
Login error on Kibana
When attempting to visit the Kibana console, you might receive a browser error instead:
{"error":"invalid_request","error_description":"The request is missing a required parameter,
includes an invalid parameter value, includes a parameter more than once, or is otherwise malformed."}
This problem can be caused by a mismatch between the OAuth2 client and server. The return address for the client must be in a whitelist so the server can securely redirect back after logging in. If there is a mismatch, the error message is shown.
This can be caused by an oauthclient entry lingering from a
previous deployment, in which case you can replace it:
$ oc delete oauthclient/kibana-proxy
Follow the openshift-ansible instructions to re-run the openshift_logging role,
which replaces the oauthclient entry. Return to the Kibana console and log in again.
If the problem persists, check that you are accessing Kibana at a URL listed in the OAuth client. This issue can be caused by accessing the URL at a forwarded port, such as 1443 instead of the standard 443 HTTPS port.
You can adjust the server whitelist by editing its oauthclient:
$ oc edit oauthclient/kibana-proxy
Edit the list of redirect URIs accepted to include the address you are actually using. After you save and exit, this should resolve the error.
Kibana access shows 503 error
If you receive a proxy error when viewing the Kibana console, it could be caused by one of two issues.
-
Kibana might not be recognizing pods. If ElasticSearch is slow in starting up, Kibana might error out trying to reach ElasticSearch and Kibana does not consider it alive. You can check whether the relevant service has any endpoints:
$ oc describe service logging-kibana Name: logging-kibana [...] Endpoints: <none>
If any Kibana pods are live, endpoints should be listed. If they are not, check the state of the Kibana pod(s) and deployment.
-
The named route for accessing the Kibana service might be masked.
This can happen if you perform a test deployment in one project, then deploy in a different project without completely removing the first deployment. When multiple routes are sent to the same destination, the default router only routes to the first destination created. Check the problematic route to see if it is defined in multiple places:
$ oc get route --all-namespaces --selector logging-infra=support NAMESPACE NAME HOST/PORT PATH SERVICE logging kibana kibana.example.com logging-kibana logging kibana-ops kibana-ops.example.com logging-kibana-ops
In this example there are no overlapping routes.