Prometheus alert functions

In Prometheus, alert functions are used to define conditions and rules for generating alerts based on the monitored metrics. When the conditions specified by these functions are met, Prometheus triggers an alert that can be used to notify system administrators or take automated actions. Here are some commonly used alert functions in Prometheus:

1. ALERT(): This function is used to define an alert rule. It takes two arguments: the name of the alert and the expression that evaluates to a boolean value. When the expression evaluates to true, the alert is fired.

2. label_join(): This function is used to concatenate label values together into a new label. It takes two arguments: the destination label name and a delimiter. This function is often used to create a new label that provides additional context for an alert.

3. absent(): This function checks whether a specific time series is absent or missing. It takes one argument: the expression that represents the time series. If the time series does not exist or has no samples within the specified time range, the function evaluates to true and triggers the alert.

4. changes(): This function counts the number of times a time series changes its value within a specified time range. It takes one argument: the expression that represents the time series. The function triggers the alert if the number of changes exceeds a specified threshold.

5. increase(): This function calculates the rate of increase of a time series over a specified time range. It takes two arguments: the expression that represents the time series and the duration over which the increase is calculated. The function triggers the alert if the increase exceeds a specified threshold.

6. rate(): This function calculates the average rate of change of a time series over a specified time range. It takes one argument: the expression that represents the time series. The function triggers the alert if the rate exceeds a specified threshold.

7. up(): This function checks the availability of a target by querying the "up" metric, which indicates whether a scrape target is up or down. It takes no arguments and evaluates to 1 if the target is up and 0 if it's down. This function is often used to create alerts for target availability.

These are just a few examples of the alert functions available in Prometheus. The alerting functionality in Prometheus is highly customizable, allowing you to define complex conditions and actions based on your specific monitoring requirements.

Examples

Here are examples for each of the alert functions in Prometheus:

1. ALERT(): Define an alert rule named "HighCPUUsage" that triggers when the CPU usage exceeds 80% for more than 5 minutes:

ALERT HighCPUUsage
IF avg(cpu_usage) > 0.8
FOR 5m

2. label_join(): Create a new label named "alert_info" by joining the "instance" and "severity" labels with a hyphen ("-") delimiter:

label_join(alert_info, "-", instance, severity)

3. absent(): Trigger an alert if the metric "http_requests_total" is absent for the past 5 minutes:

ALERT MissingHttpRequests
IF absent(http_requests_total) FOR 5m

4. changes(): Generate an alert if the value of the metric "errors_total" changes more than 10 times within the last 10 minutes:

ALERT HighErrorFluctuations
IF changes(errors_total) > 10
FOR 10m

5. increase(): Raise an alert if the rate of increase of the metric "request_latency_seconds" is above 0.05 over the last 1 hour:

ALERT HighLatencyIncrease
IF increase(request_latency_seconds[1h]) > 0.05

6. rate(): Trigger an alert if the average rate of change of the metric "http_requests_total" exceeds 100 requests per second over the last 5 minutes:

ALERT HighRequestRate
IF rate(http_requests_total[5m]) > 100

7. up(): Create an alert if a target is down by checking the availability of the "up" metric:

ALERT TargetDown
IF up() == 0

These examples demonstrate how the alert functions can be used to define specific conditions and generate alerts based on the monitored metrics in Prometheus. Remember to adapt these examples to your own metric names and threshold values according to your monitoring setup.