https://step.dev/knowledgebase/30/categories/analytics/ Recent content in Analytics on Step Documentation Hugo -- gohugo.io en Wed, 17 Mar 2021 14:24:01 +0100 https://step.dev/knowledgebase/30/plugins/analytics-integrations/jdbc/ Wed, 17 Mar 2021 14:24:01 +0100 https://step.dev/knowledgebase/30/plugins/analytics-integrations/jdbc/ The JDBC plugin writes Step measurements to a SQL-based database such as PostgreSQL or MySQL. This allows you to query and visualize Step execution data using any SQL-compatible tool. The JDBC plugin exports measurements only — it does not export keyword-emitted metrics (counters, gauges, histograms). For full metrics export, use the Prometheus or Metrics Logger integration. The plugin has been tested with PostgreSQL 12 and MySQL 8. Data model Since keywords in Step can carry arbitrary custom attributes, each measurement contains a set of fixed fields and an open-ended set of custom fields: https://step.dev/knowledgebase/30/userdocs/analytics/measurements-and-metrics/ Thu, 28 Feb 2019 14:08:01 +0100 https://step.dev/knowledgebase/30/userdocs/analytics/measurements-and-metrics/ Step analytics are built on two complementary data types: Measurements A measurement is a named, timed observation attached to a plan’s execution step. Each measurement captures a name, a duration in milliseconds, a start timestamp, a status (PASSED, FAILED, or TECHNICAL_ERROR), and optional custom attributes (key/value pairs). Measurements are created automatically by the Step framework for keyword calls as well as for instrumented plan nodes. Custom measurements with finer granularity or enriched attributes can also be defined in keyword code (see Measurements in the Keyword API). https://step.dev/knowledgebase/30/plugins/analytics-integrations/prometheus/ Wed, 17 Mar 2021 14:24:01 +0100 https://step.dev/knowledgebase/30/plugins/analytics-integrations/prometheus/ Prometheus is a popular open-source monitoring and alerting system. The Step Prometheus plugin exposes measurements and metrics at a scrape endpoint that Prometheus polls at regular intervals. In addition to Step execution data, the plugin also exposes JVM and Jetty metrics for internal controller monitoring. Note that while not directly related to this plugin, other Step components such as the Grid proxy and Java agents can also expose these metrics to Prometheus via their own configuration. https://step.dev/knowledgebase/30/userdocs/analytics/dashboards/ Thu, 28 Feb 2019 14:08:01 +0100 https://step.dev/knowledgebase/30/userdocs/analytics/dashboards/ Managing Dashboards: Overview The Dashboard List page provides a straightforward way to manage all your dashboards. This feature simplifies how you handle various analytics dashboards, making it more efficient to work with your data. Step comes with 4 pre-populated dashboards: Execution dashboard: used to analyse the performance of a single Step execution Analytics dashboard: meant to be used for schedules performance analysis, also accessible from the monitoring view Executions Overview: tracks per-execution metrics (execution count, duration, failure rate) generated at the end of each execution, giving a historical view of campaign health over time Grid Monitoring: displays agent health and activity metrics; not project-specific and accessible from any tenant Key features: Create: Easily add new dashboards for different data sets or projects. https://step.dev/knowledgebase/30/plugins/analytics-integrations/metrics-logger/ Wed, 17 Mar 2021 14:24:01 +0100 https://step.dev/knowledgebase/30/plugins/analytics-integrations/metrics-logger/ The Metrics Logger plugin writes Step measurements and metrics to structured log files using Logback. The log format is compatible with Splunk and other log aggregation tools. Enabling the plugin The plugin is disabled by default and must be explicitly enabled in step.properties: plugins.MetricsLoggerControllerPlugin.enabled=true Log configuration Log output is controlled by the CONTROLLER_DIR/bin/logback.xml file. The default configuration writes to a rolling file: <appender name="MEASUREMENTS" class="ch.qos.logback.core.rolling.RollingFileAppender"> <file>../log/measurement-logger.log</file> <rollingPolicy class="ch.qos.logback.core.rolling.FixedWindowRollingPolicy"> <fileNamePattern>../log/measurement-logger-%i.log</fileNamePattern> <minIndex>1</minIndex> <maxIndex>2</maxIndex> </rollingPolicy> <triggeringPolicy class="ch. https://step.dev/knowledgebase/30/plugins/analytics-integrations/ Wed, 17 Mar 2021 14:24:01 +0100 https://step.dev/knowledgebase/30/plugins/analytics-integrations/ Step records measurements and metrics for every execution and makes them available through its built-in analytics stack. For organizations that want to feed this data into their own monitoring stack such as Grafana, Splunk, or a custom SQL database, we provide a set of enterprise plugins that export data to external systems in real time. The following integrations are available: Integration Plugin class name Data written Enabled by default JDBC (SQL) JdbcMeasurementControllerPlugin Measurements No Prometheus PrometheusControllerPlugin Measurements + Metrics Yes Metrics Logger MetricsLoggerControllerPlugin Measurements + Metrics No Data export takes effect for new executions once the plugin is enabled. https://step.dev/knowledgebase/30/userdocs/analytics/ Thu, 28 Feb 2019 14:08:01 +0100 https://step.dev/knowledgebase/30/userdocs/analytics/ Step collects performance data — measurements and metrics — from every execution and makes it available in multiple ways: Execution and cross executions reports: through the charts, statistics tables and embedded analytics dashboards as detailed measurements and metrics list for each keyword execution in the report details Performance and Metric assertions - the collected measurements and metrics are available as well for: Performance Assertion can be defined in plan and assert collected measurements during the execution of the plan Metric Assertion can be used in assertion plan to evaluate the success of schedule over a series of executions Analytics dashboards: standalone dashboards for cross-execution analysis, scheduling health, grid monitoring, and custom investigations.