Alert types

Kloudfuse supports many alert types that support your observability experience.

Kloudfuse supports these specific alerting types:

Metric Alerts

Metric monitors analyze continuous streams of data. When collecting metrics through Kloudfuse or APIs, you can configure alerts to trigger on specified conditions.

See Create a metric alert.

Threshold Alert: An alert triggered when a metric crosses a threshold over a specified period of time.

Tracks when a metric crosses a specified boundary value, to monitor signals that exceed known acceptable ranges.
Change Alert: An alert triggered when the change between values is greater than the specified tolerance over a specified period of time.

Tracks how quickly a metric changes by comparing current and past values.
Outlier Alert: An alert triggered when observed data has a markedly different value from the rest of the sample.

Identifies statistically significant deviations within the dataset.
Anomaly Detection Alert: An alert triggered when a pattern in the data does not conform to expected behavior.

Uses ML Models to learn normal patterns in your metrics, accounting for seasonality, to identify unexpected patterns.
Forecast Alert: An alert triggered when the forecast algorithm predicts that in the future, a metric will cross a threshold over a specified period of time.

Predicts future metric values to enable proactive deflection, before problems occur.

Log Alerts

Log monitors generate alerts when a specified a specific pattern or condition is detected within log data — when something unusual or potentially problematic happens within the system, based on information recorded in logs.

See Create a logs alert.

Threshold Alert: An alert triggered when a metric reported by a log crosses a threshold over a specified period of time.

Counts log patterns for frequency, and tracks errors, warning, and other important events in the log signals.
Outlier Alert: An alert triggered when observed data has a markedly different value from the rest of the sample.

Identifies when log patterns in one source show statistically significant deviations from other sources.
Anomaly Detection Alert: An alert triggered when a pattern in the log data does not conform to expected behavior.

Uses ML Models to learn normal patterns in your log, detecting unexpected changes in log frequency or content.
Forecast Alert: An alert triggered when the forecast algorithm predicts that in the future, an aggregation on logs will cross a threshold over a specified period of time.

Predicts future patterns to enable proactive deflection before potential issues become critical.

APM Alerts

Monitor features of APM Service metrics, when the system detects significant issues within a monitored service: high latency, excessive errors, resource exhaustion, and so on.

See Create an APM alert.

Service Threshold Alert: An alert triggered when an RED (request, error, duration) service metric crosses a threshold over a specified period of time.

Monitors service performance metrics to track response time, error rates, and request rates against defined acceptable ranges.
Service Anomaly Alert: An alert triggered when a service metric pattern in the data does not conform to expected behavior.

Uses ML Models to detect unusual patterns in your service performance data.
Span Metric Alert: An alert triggered when a trace metric crosses a specified threshold over a particular period of time.

Track detailed transaction performance through distributed tracing data to monitor operations and requests.

RUM Alerts

Monitor the performance and user experience of real users, in real time, to ensure a seamless client experience.

See Create a RUM alert.

RUM Metric Alert: An alert triggered when a client-side performance metric crosses a specified threshold over a particular period of time.

Monitor user experience metrics: page load times, user interactions, JavaScript errors, and so on.

SLO Alerts

SLO Alerts notify you when there is a risk of violating your service-level objectives (SLOs).

See Create an SLO Alert.

SLO Latency Alert: An alert triggered when the latency of a service doesn’t meet the specified targets over a period of time.

Track service response time to ensure that the services meet performance commitments of the SLO.
SLO Availability Alert: An alert triggered when the availability of the service doesn’t meet the specified targets over a period of time.

Monitor service uptime and reliability, to ensure that services satisfy the availability commitments of the SLO.
SLO Metric Alert: An alert triggered when an error rate trace metric crosses a specified threshold over a particular period of time.

Track detailed transaction performance through distributed tracing data to monitor operations and requests.

Event Alerts

Event alerts help identify and address issues before they become major problems. Events are discrete occurrences that can be generated by software or hardware.

See Create an Events alert.

Event Metric Alert: An alert triggered when an event metric crosses a threshold over a specified period of time.

Monitor system events and changes: deployments, application performance, security threats,database activity, infrastructure health, business transactions, compliance with regulations, and so on.