Overview of the Loggregator System
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Loggregator gathers and streams logs and metrics from user apps in a Cloud Foundry (CF) deployment as well as metrics from CF components.
For more information, see the Loggregator repository on GitHub.
The primary use cases for Loggregator include the following:
App developers can tail their application logs or dump the recent logs from the Cloud Foundry Command Line Interface (cf CLI), or stream these to a third-party log archive and analysis service.
Operators and administrators can access the Loggregator Firehose, the combined stream of logs from all apps, and the metrics data from Cloud Foundry components.
Operators can deploy nozzles to the Firehose. A nozzle is a component that monitors the Firehose for specified events and metrics, and streams this data to external services.
The diagram below shows the architecture of Loggregator, including the Cloud Foundry components that it interacts with.
Note: The Loggregator system uses gRPC for communication between the Metron Agent and the Doppler, and between the Doppler and the Traffic Controller. This improves the stability and the performance of the Loggregator system, but it may require operators to scale their Dopplers.
Sources are logging agents that run on the Cloud Foundry components.
Metron Agents are colocated with sources. They collect logs and forward them to the Doppler servers.
Dopplers gather logs from the Metron Agents, store them in temporary buffers, and forward them to the Traffic Controller or to third-party syslog drains.
The Traffic Controller handles client requests for logs. It gathers and collates messages from all Doppler servers, and provides external API and message translation as needed for legacy APIs. The Traffic Controller also exposes the Firehose.
The Firehose is a WebSocket endpoint that streams all the event data coming from a Cloud Foundry deployment. The data stream includes logs, HTTP events, and container metrics from all applications, and metrics from all Cloud Foundry system components. Logs from system components such as the Cloud Controller are not included in the Firehose and are typically accessed through rsyslog configuration.
Because the data coming from the Firehose may contain sensitive information, such as customer information in the application logs, only users with the correct permissions can access the Firehose.
The Traffic Controller serves the Firehose over WebSocket at the
/firehose endpoint. The events coming out of the Firehose are formatted as protobuf messages conforming to the dropsonde protocol.
You can discover the address of the Traffic Controller by hitting the
info endpoint on the API and retrieving the value of the
Example for a BOSH Lite CF environment:
$ cf curl /v2/info | jq .doppler_logging_endpoint wss://doppler.192.0.2.34.xip.io:443
The Firehose carries both logs and metrics, which differ as follows:
- Report events detected, actions taken, errors, or any other messages the operator or developer wanted to generate
- Follow the syslog standard
- Are not used to trigger alerts
This section provides information about the components that are related to the Loggregator system.
Nozzles are programs which consume data from the Loggregator Firehose. Nozzles can be configured to select, buffer, and transform data, and forward it to other applications and services. Example nozzles include the following:
- The JMX Bridge OpenTSDB Firehose Nozzle, which installs with JMX Bridge
- The Datadog nozzle, which publishes metrics coming from the Firehose to Datadog
- The Syslog nozzle, which filters out log messages coming from the Firehose and sends it to a syslog server
For more information about nozzles, see the Nozzle Tutorial.
App Autoscaler allows you to configure rules that balance the performance and cost of apps by scaling them.
App Autoscaler relies on API endpoints from Loggregator’s Log Cache. If you disable Log Cache, App Autoscaler will fail.
For more information, see App Autoscaler Fails When Loggregator’s Log Cache Is Disabled.Create a pull request or raise an issue on the source for this page in GitHub