SignalFx is a cloud monitoring and alerting solution for modern enterprise infrastructures. This chart will deploy the SignalFx agent as a DaemonSet to all nodes in your cluster. It is designed to be run in only one release at a time.
See the agent docs for more information on how the agent works. The installation steps will be different since you are using Helm but the agent otherwise behaves identically.
The Smart Agent has three main components:
Observers watch the various environments that we support to discover running services and automatically configure the Smart Agent to send metrics for those services.
Monitors collect metrics from the host system and services. They are configured under the monitor’s list in the Smart Agent config. For application-specific monitors, you can define discovery rules in your monitor configuration. A separate monitor instance is created for each discovered instance of applications that match a discovery rule. See Auto-Discovery for more information.
Many of the monitors are built around collected, an open source third-party monitor, and use it to collect metrics. Some other monitors do not use collected. However, either type is configured in the same way.
For a list of supported monitors and their configurations, see Monitor Config.
The Smart Agent is primarily intended to monitor services/applications running on the same host as the Smart Agent. This is in keeping with the collectd model. The main issue with monitoring services on other hosts is that the host dimension that collectd sets on all metrics will currently get set to the hostname of the machine that the Smart Agent is running on. This allows everything to have a consistent host dimension so that metrics can be matched to a specific machine during metric analysis.
The writer collects metrics emitted by the configured monitors and sends them to SignalFx on a regular basis. There are a few things that can be configured in the writer, but this is generally only necessary if you have a very large number of metrics flowing through a single agent.
Analyze across 100,000’s of ephemeral components for better insight into today’s cloud environments.
The service discovery and collects streaming metrics across every component in the cloud, replacing traditional point tools and providing real-time visibility into today’s dynamic cloud and container environments. The massive scalability of the service is optimized for the container, microservices, and function based architectures and provides powerful visualization, proactive alerting, and collaborative triage capabilities for organizations at any stages of their cloud transition.
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