Monitoring pipeline metrics

You can monitor Amazon OpenSearch Ingestion pipelines using Amazon CloudWatch, which collects raw data and processes it into readable, near real-time metrics. These statistics are kept for 15 months, so that you can access historical information and gain a better perspective on how your web application or service is performing. You can also set alarms that watch for certain thresholds, and send notifications or take actions when those thresholds are met. For more information, see the Amazon CloudWatch User Guide.

The OpenSearch Ingestion console displays a series of charts based on the raw data from CloudWatch on the Performance tab for each pipeline.

OpenSearch Ingestion reports metrics from most supported plugins. If certain plugins don't have their own table below, it means that they don't report any plugin-specific metrics. Pipeline metrics are published in the AWS/OSIS namespace.

Common metrics

The following metrics are common to all processors and sinks.

Each metric is prefixed by the sub-pipeline name and plugin name, in the format <sub_pipeline_name><plugin><metric_name>. For example, the full name of the recordsIn.count metric for a sub-pipeline named my-pipeline and the date processor would be my-pipeline.date.recordsIn.count.

Metric suffix	Description
recordsIn.count	The ingress of records to a pipeline component. This metric applies to processors and sinks. Relevant statistics: Sum Dimension: PipelineName
recordsOut.count	The egress of records from a pipeline component. This metric applies to processors and sources. Relevant statistics: Sum Dimension: PipelineName
timeElapsed.count	A count of data points recorded during execution of a pipeline component. This metric applies to processors and sinks. Relevant statistics: Sum Dimension: PipelineName
timeElapsed.sum	The total time elapsed during execution of a pipeline component. This metric applies to processors and sinks, in milliseconds. Relevant statistics: Sum Dimension: PipelineName
timeElapsed.max	The maximum time elapsed during execution of a pipeline component. This metric applies to processors and sinks, in milliseconds. Relevant statistics: Max Dimension: PipelineName

Buffer metrics

The following metrics apply to the default Bounded blocking buffer that OpenSearch Ingestion automatically configures for all pipelines.

Each metric is prefixed by the sub-pipeline name and buffer name, in the format <sub_pipeline_name><buffer_name><metric_name>. For example, the full name of the recordsWritten.count metric for a sub-pipeline named my-pipeline would be my-pipeline.BlockingBuffer.recordsWritten.count.

Metric suffix	Description
recordsWritten.count	The number of records written to a buffer. Relevant statistics: Sum Dimension: PipelineName
recordsRead.count	The number of records read from a buffer. Relevant statistics: Sum Dimension: PipelineName
recordsInFlight.value	The number of unchecked records read from a buffer. Relevant statistics: Average Dimension: PipelineName
recordsInBuffer.value	The number of records currently in a buffer. Relevant statistics: Average Dimension: PipelineName
recordsProcessed.count	The number of records read from a buffer and processed by a pipeline. Relevant statistics: Sum Dimension: PipelineName
recordsWriteFailed.count	The number of records that the pipeline failed to write to the sink. Relevant statistics: Sum Dimension: PipelineName
writeTimeElapsed.count	A count of data points recorded while writing to a buffer. Relevant statistics: Sum Dimension: PipelineName
writeTimeElapsed.sum	The total time elapsed while writing to a buffer, in milliseconds. Relevant statistics: Sum Dimension: PipelineName
writeTimeElapsed.max	The maximum time elapsed while writing to a buffer, in milliseconds. Relevant statistics: Max Dimension: PipelineName
writeTimeouts.count	The count of write timeouts to a buffer. Relevant statistics: Sum Dimension: PipelineName
readTimeElapsed.count	A count of data points recorded while reading from a buffer. Relevant statistics: Sum Dimension: PipelineName
readTimeElapsed.sum	The total time elapsed while reading from a buffer, in milliseconds. Relevant statistics: Sum Dimension: PipelineName
readTimeElapsed.max	The maximum time elapsed while reading from a buffer, in milliseconds. Relevant statistics: Max Dimension: PipelineName
checkpointTimeElapsed.count	A count of data points recorded while checkpointing. Relevant statistics: Sum Dimension: PipelineName
checkpointTimeElapsed.sum	The total time elapsed while checkpointing, in milliseconds. Relevant statistics: Sum Dimension: PipelineName
checkpointTimeElapsed.max	The maximum time elapsed while checkpointing, in milliseconds. Relevant statistics: Max Dimension: PipelineName

Signature V4 metrics

The following metrics apply to the ingestion endpoint for a pipeline and are associate with the source plugins (http, otel_trace, and otel_metrics). All requests to the ingestion endpoint must be signed using Signature Version 4. These metrics can help you identify authorization issues when connecting to your pipeline, or confirm that you're successfully authenticating.

Each metric is prefixed by the sub-pipeline name and osis_sigv4_auth. For example, sub_pipeline_name.osis_sigv4_auth.httpAuthSuccess.count.

Metric suffix	Description
httpAuthSuccess.count	The number of successful Signature V4 requests to the pipeline. Relevant statistics: Sum Dimension: PipelineName
httpAuthFailure.count	The number of failed Signature V4 requests to the pipeline. Relevant statistics: Sum Dimension: PipelineName
httpAuthServerError.count	The number of Signature V4 requests to the pipeline that returned server errors. Relevant statistics: Sum Dimension: PipelineName

Bounded blocking buffer metrics

The following metrics apply to the bounded blocking buffer. Each metric is prefixed by the sub-pipeline name and BlockingBuffer. For example, sub_pipeline_name.BlockingBuffer.bufferUsage.value.

Metric suffix	Description
bufferUsage.value	Percent usage of the buffer_size based on the number of records in the buffer. buffer_size represents the maximum number of records written into the buffer as well as in-flight records that have not been checked. Relevant statistics: Average Dimension: PipelineName

Otel trace source metrics

The following metrics apply to the OTel trace source. Each metric is prefixed by the sub-pipeline name and otel_trace_source. For example, sub_pipeline_name.otel_trace_source.requestTimeouts.count.

Metric suffix	Description
requestTimeouts.count	The number of requests that timed out. Relevant statistics: Sum Dimension: PipelineName
requestsReceived.count	The number of requests received by the plugin. Relevant statistics: Sum Dimension: PipelineName
successRequests.count	The number of requests that were successfully processed by the plugin. Relevant statistics: Sum Dimension: PipelineName
badRequests.count	The number of requests with an invalid format that were processed by the plugin. Relevant statistics: Sum Dimension: PipelineName
requestsTooLarge.count	The number of requests of which the number of spans in the content is larger than the buffer capacity. Relevant statistics: Sum Dimension: PipelineName
internalServerError.count	The number of requests processed by the plugin with a custom exception type. Relevant statistics: Sum Dimension: PipelineName
requestProcessDuration.count	A count of data points recorded while processing requests by the plugin. Relevant statistics: Sum Dimension: PipelineName
requestProcessDuration.sum	The total latency of requests processed by the plugin, in milliseconds. Relevant statistics: Sum Dimension: PipelineName
requestProcessDuration.max	The maximum latency of requests processed by the plugin, in milliseconds. Relevant statistics: Max Dimension: PipelineName
payloadSize.count	A count of the distribution of payload sizes of incoming requests, in bytes. Relevant statistics: Sum Dimension: PipelineName
payloadSize.sum	The total distribution of the payload sizes of incoming requests, in bytes. Relevant statistics: Sum Dimension: PipelineName
payloadSize.max	The maximum distribution of payload sizes of incoming requests, in bytes. Relevant statistics: Max Dimension: PipelineName

Otel metrics source metrics

The following metrics apply to the OTel metrics source. Each metric is prefixed by the sub-pipeline name and otel_metrics_source. For example, sub_pipeline_name.otel_metrics_source.requestTimeouts.count.

Metric suffix	Description
requestTimeouts.count	The total number of requests to the plugin that time out. Relevant statistics: Sum Dimension: PipelineName
requestsReceived.count	The total number of requests received by the plugin. Relevant statistics: Sum Dimension: PipelineName
successRequests.count	The number of requests successfully processed (200 response status code) by the plugin. Relevant statistics: Sum Dimension: PipelineName
requestProcessDuration.count	A count of the latency of requests processed by the plugin, in seconds. Relevant statistics: Sum Dimension: PipelineName
requestProcessDuration.sum	The total latency of requests processed by the plugin, in milliseconds. Relevant statistics: Sum Dimension: PipelineName
requestProcessDuration.max	The maximum latency of requests processed by the plugin, in milliseconds. Relevant statistics: Max Dimension: PipelineName
payloadSize.count	A count of the distribution of payload sizes of incoming requests, in bytes. Relevant statistics: Sum Dimension: PipelineName
payloadSize.sum	The total distribution of the payload sizes of incoming requests, in bytes. Relevant statistics: Sum Dimension: PipelineName
payloadSize.max	The maximum distribution of payload sizes of incoming requests, in bytes. Relevant statistics: Max Dimension: PipelineName

Http metrics

The following metrics apply to the HTTP source. Each metric is prefixed by the sub-pipeline name and http. For example, sub_pipeline_name.http.requestsReceived.count.

Metric suffix	Description
requestsReceived.count	The number of requests received by the /log/ingest endpoint. Relevant statistics: Sum Dimension: PipelineName
requestsRejected.count	The number of requests rejected (429 response status code) by the plugin. Relevant statistics: Sum Dimension: PipelineName
successRequests.count	The number of requests successfully processed (200 response status code) by the plugin. Relevant statistics: Sum Dimension: PipelineName
badRequests.count	The number of requests with invalid content type or format (400 response status code) processed by the plugin. Relevant statistics: Sum Dimension: PipelineName
requestTimeouts.count	The number of requests that time out in the HTTP source server (415 response status code). Relevant statistics: Sum Dimension: PipelineName
requestsTooLarge.count	The number of requests of which the events size in the content is larger than the buffer capacity (413 response status code). Relevant statistics: Sum Dimension: PipelineName
internalServerError.count	The number of requests processed by the plugin with a custom exception type (500 response status code). Relevant statistics: Sum Dimension: PipelineName
requestProcessDuration.count	A count of the latency of requests processed by the plugin, in seconds. Relevant statistics: Sum Dimension: PipelineName
requestProcessDuration.sum	The total latency of requests processed by the plugin, in milliseconds. Relevant statistics: Sum Dimension: PipelineName
requestProcessDuration.max	The maximum latency of requests processed by the plugin, in milliseconds. Relevant statistics: Max Dimension: PipelineName
payloadSize.count	A count of the distribution of payload sizes of incoming requests, in bytes. Relevant statistics: Sum Dimension: PipelineName
payloadSize.sum	The total distribution of the payload sizes of incoming requests, in bytes. Relevant statistics: Sum Dimension: PipelineName
payloadSize.max	The maximum distribution of payload sizes of incoming requests, in bytes. Relevant statistics: Max Dimension: PipelineName

S3 metrics

The following metrics apply to the S3 source. Each metric is prefixed by the sub-pipeline name and s3. For example, sub_pipeline_name.s3.s3ObjectsFailed.count.

Metric suffix	Description
s3ObjectsFailed.count	The total number of S3 objects that the plugin failed to read. Relevant statistics: Sum Dimension: PipelineName
s3ObjectsNotFound.count	The number of S3 objects that the plugin failed to read due to a Not Found error from S3. These metrics also count toward the s3ObjectsFailed metric. Relevant statistics: Sum Dimension: PipelineName
s3ObjectsAccessDenied.count	The number of S3 objects that the plugin failed to read due to an Access Denied or Forbidden error from S3. These metrics also count toward the s3ObjectsFailed metric. Relevant statistics: Sum Dimension: PipelineName
s3ObjectReadTimeElapsed.count	The amount of time the plugin takes to perform a GET request for an S3 object, parse it, and write events to the buffer. Relevant statistics: Sum Dimension: PipelineName
s3ObjectReadTimeElapsed.sum	The total amount of time that the plugin takes to perform a GET request for an S3 object, parse it, and write events to the buffer, in milliseconds. Relevant statistics: Sum Dimension: PipelineName
s3ObjectReadTimeElapsed.max	The maximum amount of time that the plugin takes to perform a GET request for an S3 object, parse it, and write events to the buffer, in milliseconds. Relevant statistics: Max Dimension: PipelineName
s3ObjectSizeBytes.count	The count of the distribution of S3 object sizes, in bytes. Relevant statistics: Sum Dimension: PipelineName
s3ObjectSizeBytes.sum	The total distribution of S3 object sizes, in bytes. Relevant statistics: Sum Dimension: PipelineName
s3ObjectSizeBytes.max	The maximum distribution of S3 object sizes, in bytes. Relevant statistics: Max Dimension: PipelineName
s3ObjectProcessedBytes.count	The count of the distribution of S3 objects processed by the plugin, in bytes. Relevant statistics: Sum Dimension: PipelineName
s3ObjectProcessedBytes.sum	The total distribution of S3 objects processed by the plugin, in bytes. Relevant statistics: Sum Dimension: PipelineName
s3ObjectProcessedBytes.max	The maximum distribution of S3 objects processed by the plugin, in bytes. Relevant statistics: Max Dimension: PipelineName
s3ObjectsEvents.count	The count of the distribution of S3 events received by the plugin. Relevant statistics: Sum Dimension: PipelineName
s3ObjectsEvents.sum	The total distribution of S3 events received by the plugin. Relevant statistics: Sum Dimension: PipelineName
s3ObjectsEvents.max	The maximum distribution of S3 events received by the plugin. Relevant statistics: Max Dimension: PipelineName
sqsMessageDelay.count	A count of data points recorded while S3 records an event time for the creation of an object to when it's fully parsed. Relevant statistics: Sum Dimension: PipelineName
sqsMessageDelay.sum	The total amount of time between when S3 records an event time for the creation of an object to when it's fully parsed, in milliseconds. Relevant statistics: Sum Dimension: PipelineName
sqsMessageDelay.max	The maximum amount of time between when S3 records an event time for the creation of an object to when it's fully parsed, in milliseconds. Relevant statistics: Max Dimension: PipelineName
s3ObjectsSucceeded.count	The number of S3 objects that the plugin successfully read. Relevant statistics: Sum Dimension: PipelineName
sqsMessagesReceived.count	The number of Amazon SQS messages received from the queue by the plugin. Relevant statistics: Sum Dimension: PipelineName
sqsMessagesDeleted.count	The number of Amazon SQS messages deleted from the queue by the plugin. Relevant statistics: Sum Dimension: PipelineName
sqsMessagesFailed.count	The number of Amazon SQS messages that the plugin failed to parse. Relevant statistics: Sum Dimension: PipelineName

Aggregate metrics

The following metrics apply to the Aggregate processor. Each metric is prefixed by the sub-pipeline name and aggregate. For example, sub_pipeline_name.aggregate.actionHandleEventsOut.count.

Metric suffix	Description
actionHandleEventsOut.count	The number of events that have been returned from the handleEvent call to the configured action. Relevant statistics: Sum Dimension: PipelineName
actionHandleEventsDropped.count	The number of events that have been returned from the handleEvent call to the configured action. Relevant statistics: Sum Dimension: PipelineName
actionHandleEventsProcessingErrors.count	The number of calls made to handleEvent for the configured action that resulted in an error. Relevant statistics: Sum Dimension: PipelineName
actionConcludeGroupEventsOut.count	The number of events that have been returned from the concludeGroup call to the configured action. Relevant statistics: Sum Dimension: PipelineName
actionConcludeGroupEventsDropped.count	The number of events that have not been returned from the condludeGroup call to the configured action. Relevant statistics: Sum Dimension: PipelineName
actionConcludeGroupEventsProcessingErrors.count	The number of calls made to concludeGroup for the configured action that resulted in an error. Relevant statistics: Sum Dimension: PipelineName
currentAggregateGroups.value	The current number of groups. This gauge decreases when groups are concluded, and increases when an event initiates the creation of a new group. Relevant statistics: Average Dimension: PipelineName

Date metrics

The following metrics apply to the Date processor. Each metric is prefixed by the sub-pipeline name and date. For example, sub_pipeline_name.date.dateProcessingMatchSuccess.count.

Metric suffix	Description
dateProcessingMatchSuccess.count	The number of records that match at least one of the patterns specified in the match configuration option. Relevant statistics: Sum Dimension: PipelineName
dateProcessingMatchFailure.count	The number of records that didn't match any of the patterns specified in the match configuration option. Relevant statistics: Sum Dimension: PipelineName

Grok metrics

The following metrics apply to the Grok processor. Each metric is prefixed by the sub-pipeline name and grok. For example, sub_pipeline_name.grok.grokProcessingMatch.count.

Metric suffix	Description
grokProcessingMatch.count	The number of records that found at least one pattern match from the match configuration option. Relevant statistics: Sum Dimension: PipelineName
grokProcessingMismatch.count	The number of records that didn't match any of the patterns specified in the match configuration option. Relevant statistics: Sum Dimension: PipelineName
grokProcessingErrors.count	The number of record processing errors. Relevant statistics: Sum Dimension: PipelineName
grokProcessingTimeouts.count	The number of records that timed out while matching. Relevant statistics: Sum Dimension: PipelineName
grokProcessingTime.count	A count of data points recorded while an individual record matched against patterns from the match configuration option. Relevant statistics: Sum Dimension: PipelineName
grokProcessingTime.sum	The total amount of time that each individual record takes to match against patterns from the match configuration option, in milliseconds. Relevant statistics: Sum Dimension: PipelineName
grokProcessingTime.max	The maximum amount of time that each individual record takes to match against patterns from the match configuration option, in milliseconds. Relevant statistics: Max Dimension: PipelineName

Otel trace raw metrics

The following metrics apply to the OTel trace raw processor. Each metric is prefixed by the sub-pipeline name and otel_trace_raw. For example, sub_pipeline_name.otel_trace_raw.traceGroupCacheCount.value.

Metric suffix	Description
traceGroupCacheCount.value	The number of trace groups in the trace group cache. Relevant statistics: Sum Dimension: PipelineName
spanSetCount.value	The number of span sets in the span set collection. Relevant statistics: Sum Dimension: PipelineName

Otel trace group metrics

The following metrics apply to the OTel trace group processor. Each metric is prefixed by the sub-pipeline name and otel_trace_group. For example, sub_pipeline_name.otel_trace_group.recordsInMissingTraceGroup.count.

Metric suffix	Description
recordsInMissingTraceGroup.count	The number of ingress records missing trace group fields. Relevant statistics: Sum Dimension: PipelineName
recordsOutFixedTraceGroup.count	The number of egress records with trace group fields that were filled successfully. Relevant statistics: Sum Dimension: PipelineName
recordsOutMissingTraceGroup.count	The number of egress records missing trace group fields. Relevant statistics: Sum Dimension: PipelineName

Service map stateful metrics

The following metrics apply to the Service-map stateful processor. Each metric is prefixed by the sub-pipeline name and service-map-stateful. For example, sub_pipeline_name.service-map-stateful.spansDbSize.count.

Metric suffix	Description
spansDbSize.value	The in-memory byte sizes of spans in MapDB across the current and previous window durations. Relevant statistics: Average Dimension: PipelineName
traceGroupDbSize.value	The in-memory byte sizes of trace groups in MapDB across the current and previous window durations. Relevant statistics: Average Dimension: PipelineName
spansDbCount.value	The count of spans in MapDB across the current and previous window durations. Relevant statistics: Sum Dimension: PipelineName
traceGroupDbCount.value	The count of trace groups in MapDB across the current and previous window durations. Relevant statistics: Sum Dimension: PipelineName
relationshipCount.value	The count of relationships stored across the current and previous window durations. Relevant statistics: Sum Dimension: PipelineName

OpenSearch metrics

The following metrics apply to the OpenSearch sink. Each metric is prefixed by the sub-pipeline name and opensearch. For example, sub_pipeline_name.opensearch.bulkRequestErrors.count.

Metric suffix	Description
bulkRequestErrors.count	The total number of errors encountered while sending bulk requests. Relevant statistics: Sum Dimension: PipelineName
documentsSuccess.count	The number of documents successfully sent to the OpenSearch Service by bulk request, including retries. Relevant statistics: Sum Dimension: PipelineName
documentsSuccessFirstAttempt.count	The number of documents successfully sent to OpenSearch Service by bulk request on the first attempt. Relevant statistics: Sum Dimension: PipelineName
documentErrors.count	The number of documents that failed to be sent by bulk requests. Relevant statistics: Sum Dimension: PipelineName
bulkRequestFailed.count	The number of bulk requests that failed. Relevant statistics: Sum Dimension: PipelineName
bulkRequestNumberOfRetries.count	The number of retries of failed bulk requests. Relevant statistics: Sum Dimension: PipelineName
bulkBadRequestErrors.count	The number of Bad Request errors encountered while sending bulk requests. Relevant statistics: Sum Dimension: PipelineName
bulkRequestNotAllowedErrors.count	The number of Request Not Allowed errors encountered while sending bulk requests. Relevant statistics: Sum Dimension: PipelineName
bulkRequestInvalidInputErrors.count	The number of Invalid Input errors encountered while sending bulk requests. Relevant statistics: Sum Dimension: PipelineName
bulkRequestNotFoundErrors.count	The number of Request Not Found errors encountered while sending bulk requests. Relevant statistics: Sum Dimension: PipelineName
bulkRequestTimeoutErrors.count	The number of Request Timeout errors encountered while sending bulk requests. Relevant statistics: Sum Dimension: PipelineName
bulkRequestServerErrors.count	The number of Server Error errors encountered while sending bulk requests. Relevant statistics: Sum Dimension: PipelineName
bulkRequestSizeBytes.count	A count of the distribution of payload sizes of bulk requests, in bytes. Relevant statistics: Sum Dimension: PipelineName
bulkRequestSizeBytes.sum	The total distribution of payload sizes of bulk requests, in bytes. Relevant statistics: Sum Dimension: PipelineName
bulkRequestSizeBytes.max	The maximum distribution of payload sizes of bulk requests, in bytes. Relevant statistics: Max Dimension: PipelineName
bulkRequestLatency.count	A count of data points recorded while requests are sent to the plugin, including retries. Relevant statistics: Sum Dimension: PipelineName
bulkRequestLatency.sum	The total latency of requests sent to the plugin, including retries, in milliseconds. Relevant statistics: Sum Dimension: PipelineName
bulkRequestLatency.max	The maximum latency of requests sent to the plugin, including retries, in milliseconds. Relevant statistics: Max Dimension: PipelineName
s3.dlqS3RecordsSuccess.count	The number of records successfully sent to the S3 dead letter queue. Relevant statistics: Sum Dimension: PipelineName
s3.dlqS3RecordsFailed.count	The number of recourds that failed to be sent to the S3 dead letter queue. Relevant statistics: Sum Dimension: PipelineName
s3.dlqS3RequestSuccess.count	The number of successful requests to the S3 dead letter queue. Relevant statistics: Sum Dimension: PipelineName
s3.dlqS3RequestFailed.count	The number of failed requests to the S3 dead letter queue. Relevant statistics: Sum Dimension: PipelineName
s3.dlqS3RequestLatency.count	A count of data points recorded while requests are sent to the S3 dead letter queue, including retries. Relevant statistics: Sum Dimension: PipelineName
s3.dlqS3RequestLatency.sum	The total latency of requests sent to the S3 dead letter queue, including retries, in milliseconds. Relevant statistics: Sum Dimension: PipelineName
s3.dlqS3RequestLatency.max	The maximum latency of requests sent to the S3 dead letter queue, including retries, in milliseconds. Relevant statistics: Max Dimension: PipelineName
s3.dlqS3RequestSizeBytes.count	A count of the distribution of payload sizes of requests to the S3 dead letter queue, in bytes. Relevant statistics: Sum Dimension: PipelineName
s3.dlqS3RequestSizeBytes.sum	The total distribution of payload sizes of requests to the S3 dead letter queue, in bytes. Relevant statistics: Sum Dimension: PipelineName
s3.dlqS3RequestSizeBytes.max	The maximum distribution of payload sizes of requests to the S3 dead letter queue, in bytes. Relevant statistics: Max Dimension: PipelineName

System and metering metrics

The following metrics apply to the overall OpenSearch Ingestion system. These metrics aren't prefixed by anything.

Metric	Description
system.cpu.usage.value	The percentage of available CPU usage for all data nodes. Relevant statistics: Average Dimension: PipelineName, area, id
system.cpu.count.value	The total amount of CPU usage for all data nodes. Relevant statistics: Average Dimension: PipelineName, area, id
jvm.memory.max.value	The maximum amount of memory that can be used for memory management, in bytes. Relevant statistics: Average Dimension: PipelineName, area, id
jvm.memory.used.value	The total amount of memory used, in bytes. Relevant statistics: Average Dimension: PipelineName, area, idsigna
jvm.memory.committed.value	The amount of memory that is committed for use by the Java virtual machine (JVM), in bytes. Relevant statistics: Average Dimension: PipelineName, area, id
computeUnits	The number of Ingestion OpenSearch Compute Units (Ingestion OCUs) in use by a pipeline. Relevant statistics: Max, Sum, Average Dimension: PipelineName