Url: tls://openshift-logforwarding-splunk.svc:24224 An example is shown below: apiVersion: "/v1" A pipeline is defined in the ClusterLogForwarder resource to associate the log type and the output. OpenShift allows for logs to be sent to an instance of Elasticsearch (either OpenShift’s included instance and/or external) or several external integration points, including (but not limited to) syslog and Fluentd Fluentd.
application - Container logs generated by user applications running in the cluster, except infrastructure container applications.Logs collected by OpenShift are categorized into three distinct categories: A new ClusterLogForwarder resource allows for one to define the types of logs that should be sent externally to OpenShift along with the destination type. Starting with OpenShift 4.3 and made Generally Available in OpenShift 4.6, a new approach called the Log Forwarding API was made available to not only simplify the ability to integrate with external log aggregation solutions, but to also align with many of the concepts employed by OpenShift 4, such as expressing configurations through the use of Custom Resources. The ability to automate this configuration while avoiding conflicting with the platform life cycle, such as upgrades, became a challenge. In OpenShift 3, to enable this type of functionality, not only was the deployment of the forwarder required, but meticulous modification to the ConfigMap used by the OpenShift’s Fluentd was also required. Splunk takes the role of the external log aggregation system in this case. The common approach is to deploy a separate instance of Fluentd that acts as a bridge (forwarder) between the Fluentd collectors provided by OpenShift and the external log aggregation system. As a result, support has been available for this type of integration since OpenShift 3. The need to integrate OpenShift with an external log aggregation system has been a common inquiry. Instead of running the risks involved in operating two simultaneous solutions, an alternative approach can be used to integrate OpenShift with Splunk. Not only does this increase the platform resource requirements, but there is also a possibility that the two may conflict with one another. If both the included EFK stack and Splunk Connect were deployed simultaneously, the result would be two independent Fluentd deployments running on each underlying host. While Splunk Connect is a suitable standalone option for integrating OpenShift with Splunk, there is a desire for the use of the included EFK stack while also integrating with Splunk. Splunk Connect leverages many of the same technologies as the out-of-the box EFK stack that is included with OpenShift such as a DaemonSet of containers that collects logs from each underlying host which are then transmitted to Splunk. One such option is Splunk Connect for Kubernetes, which provides a turn-key supportable solution for integrating OpenShift with Splunk. Splunk is an enterprise logging solution, and given its popularity, integrations with OpenShift have been made available. However, as in the case in many organizations, existing enterprise log collection solutions may already be in place for which logs from applications running on OpenShift must also be made available. OpenShift provides a log aggregation solution based on the ElasticSearch, Fluentd, and Kibana (EFK) stack as an included feature that fulfills the need for having to create a similar solution of your own.
The ability to collect logs emitted by these applications is essential to understanding the current operating state. Unlike traditional infrastructures where applications operate on relatively static instances, containerized workloads deploying into an orchestration platform, such as Kubernetes and OpenShift, operate across a fleet of underlying hosts where multiple instances of an application may be running at a given time. Observability is one of the greatest metrics of success when operating in a containerized environment, and one of the fundamental types of observability is application logging.