Mastering Prometheus and Grafana Stack

Install Prometheus on macOS with Homebrew, verify brew, and run brew install prometheus to set up the service. Access http://localhost:1990 with default admin/password and adjust YAML and certificates as needed.

Learn to collect metrics with Prometheus using node exporter, the first type of exporter for unix-based systems. Monitor cpu, disk, memory, and network, and extend with pluggable metric collectors.

Run node exporter as a systemd service on Ubuntu by creating a Prometheus user and group, placing the binary in the right directory, and enabling and starting the service.

Prometheus offers six binary operators—equal, not equal, greater, less, greater or equal, and less or equal—for comparing scalars and instant vectors, filtering and intersecting results based on matching values.

Master Prometheus queries by using metric names with label filters and matchers, including eq, not equal, and regex expressions to filter time series.

Learn how to use time offsets in Prometheus to fetch past time series, compare instant vectors on graphs, and apply aggregates such as average by code after offset.

Master Prometheus data operations by applying log and log10 transformations, sorting with sort and sort_desc, and using time and timestamp to capture item times, while exploring clamp and offset effects.

Learn how Prometheus alert manager prevents alert fatigue by defining threshold-based alerts and aggregating and deduplicating notifications. Route alerts to emails, Slack messages, PagerDuty, Opsgenie, or webhook targets.

Discover how alert manager converts Prometheus alerts into notifications (email, SMS, Slack), deduplicates across servers, and supports silencing. Configure via alertmanager.yml and access its web user interface on port 1993.

install alert manager on mac using macports, configure its yaml file in /opt/local/etc, start and restart the service with port load and unload, and access the web UI at localhost:1993.

Install the alert manager for Prometheus on Ubuntu by downloading the Linux package, creating a Prometheus user and directories, and enabling the systemd service to run on port 1993.

Connect Alertmanager to Slack using incoming web hooks, configure the Slack receiver and webhook URL, and send alert notifications to a chosen Slack channel.

Learn how Prometheus recording rules precompute averages and sums for dashboard data from iOttie devices. Organize YAML rule files and place them in /etc/prometheus/rules for efficient loading.

Create a Prometheus recording rule by applying rate to node exporter CPU seconds total, then average by CPU to obtain an instant vector for dashboards.

Learn how Prometheus client libraries expose metrics from your app, handle short lived jobs, and choose from four official libraries or community options, with a Python example.

Expose metrics from a Python console app using the Prometheus client library, create a summary metric to time requests, and run an HTTP endpoint for Prometheus scraping.

Import the Prometheus client counter and gauge. Create metrics like my underlying counter and my gauge, use increment, set, and exception-counting decorators, and note that counters end with _total.

Attach labels to your Prometheus metrics using the Python client library, assign label values with the labels function, and expose labeled metrics as a Prometheus target.

Learn to use the Prometheus dotnet client library to create counters, gauges, and summaries, expose a /metrics endpoint on localhost:8000, and count exceptions with a metric counter.