1h 10m Advanced Released: 8/7/2018
In order to prevent outages, it's essential that you leverage a monitoring and alerting tool in your Kubernetes environment. Prometheus—an open-source systems monitoring and alerting toolkit—pairs particularly well with Kubernetes. In this course, learn how this toolkit integrates with Kubernetes and works to monitor distributed systems. Instructor Robert Starmer steps through how to enable Prometheus monitoring and shares how Prometheus monitors Kubernetes systems. He also discusses monitoring application-specific data, adding sidecar containers for app data, filtering and combining metrics, and displaying metrics in the web console. To wrap up, he discusses how to create a simple alert in Prometheus and generate application-driven alerts.
- Logging vs. monitoring
- Enabling Prometheus monitoring
- Capturing Kubernetes infrastructure data
- Capturing container data with cAdvisor
- Monitoring application-specific data
- Filtering and combining metrics
- Displaying metrics in the web console
- Using Grafana as a dashboard
- Using metrics data
- Skills covered in this course
- Prometheus.ioKubernetes
Software Developer Software Developer Technology Manager Software Developer Technology Manager Where they work IBM IBM Accenture Accenture Tata Consultancy Services Tata Consultancy Services AT&T AT&T Infosys Infosys
Robert Starmer Cloud Advisor, Founder of Kumulus Technologies
What is Prometheus?
- Features
- Components
- Architecture
- When does it fit?
- When does it not fit?
- What is Prometheus?
Prometheus is an open-source systems monitoring and alerting toolkit originally built at SoundCloud. Since its inception in 2012, many companies and organizations have adopted Prometheus, and the project has a very active developer and user community. It is now a standalone open source project and maintained independently of any company. To emphasize this, and to clarify the project's governance structure, Prometheus joined the Cloud Native Computing Foundation in 2016 as the second hosted project, after Kubernetes.
For more elaborate overviews of Prometheus, see the resources linked from the media section.
Prometheus's main features are:
a multi-dimensional data model with time series data identified by metric name and key/value pairs PromQL, a flexible query language to leverage this dimensionality no reliance on distributed storage; single server nodes are autonomous time series collection happens via a pull model over HTTP pushing time series is supported via an intermediary gateway targets are discovered via service discovery or static configuration multiple modes of graphing and dashboarding support Components The Prometheus ecosystem consists of multiple components, many of which are optional:
the main Prometheus server which scrapes and stores time series data client libraries for instrumenting application code a push gateway for supporting short-lived jobs special-purpose exporters for services like HAProxy, StatsD, Graphite, etc. an alertmanager to handle alerts various support tools Most Prometheus components are written in Go, making them easy to build and deploy as static binaries.
This diagram illustrates the architecture of Prometheus and some of its ecosystem components:
