Update WarpStream integration

Author: dd-pub-platform[bot]

warpstream/README.md

@@ -9,7 +9,7 @@ WarpStream is a data streaming platform compatible with Apache Kafka®, designed
 ### Installation
 
 1.  [Install the Datadog Agent][1].
-2.  Manually install the WarpStream integration. See [Use Community Integrations][2] for more details based on the environment.
+2.  Manually install the WarpStream integration. For environment-specific instructions, see [Use Community Integrations][2].
 
 ### Configuration
 
@@ -23,9 +23,9 @@ The WarpStream integration has two components:
 
 The WarpStream integration's [metrics][3] come from both the Agent and StatsD portions.
 
-#### Configure the Datadog Agent WarpStream integration
+#### Configure the WarpStream integration for the Datadog Agent
 
-Edit the `url` in `warpstream.d/conf.yaml`, in the `conf.d/` folder at the root of your Agent's configuration directory. See the [sample `warpstream.d/conf.yaml`][4] for all available configuration options.
+Edit the `url` in `warpstream.d/conf.yaml`,  located in the `conf.d/` folder at the root of your Agent's configuration directory. See the [sample `warpstream.d/conf.yaml`][4] for all available configuration options.
 
 The `url` value must match your WarpStream Agent HTTP server (port 8080 by default).
 

warpstream/metadata.csv

@@ -99,8 +99,8 @@ warpstream.consumer_group_num_partitions,gauge,,,,number of partitions in each c
 warpstream.consumer_group_num_topics,gauge,,,,number of topics in each consumer group,0,warpstream,consumer_group_num_topics,
 warpstream.consumer_group_state,gauge,,,,"indicates state of consumer group, tagged by 'consumer_group' and 'group_state'",0,warpstream,consumer_group_state,
 warpstream.container_running,gauge,,,,gauge set to 1 to indicate that the container is running,0,warpstream,container_running,
-warpstream.cpu_utilization_go_runtime,gauge,,,,current process's CPU utilization from the go runtime's perspective,0,warpstream,cpu_utilization_go_runtime,
-warpstream.cpu_utilization_os,gauge,,,,current process's CPU utilization from the operating system's perspective,0,warpstream,cpu_utilization_os,
+warpstream.cpu_utilization_go_runtime,gauge,,,,"current process's CPU utilization from the Go runtime's perspective, recorded as a ratio between 0 and 1",0,warpstream,cpu_utilization_go_runtime,
+warpstream.cpu_utilization_os,gauge,,,,"current process's CPU utilization from the operating system's perspective, recorded as a ratio between 0 and 1",0,warpstream,cpu_utilization_os,
 warpstream.diagnostic_status,gauge,,,,"diagnostic status, tagged by 'diagnostic_name', 'diagnostic_type', 'successful' and 'muted'. This metric is deprecated, you should use 'diagnostic_failure' instead.",0,warpstream,diagnostic_status,
 warpstream.error_count,count,,,,counts the number of errors logged,0,warpstream,error_count,
 warpstream.fast_retrier_execution,count,,,,counts the number of times the fast retrier was used,1,warpstream,fast_retrier_execution,
@@ -277,3 +277,18 @@ warpstream.bento_output_connection_failed,count,,,,counts the number of times th
 warpstream.tableflow_ingestion_lag_seconds,gauge,,second,,measures how far behind the ingestion process is from the source Kafka topic,0,warpstream,tableflow_ingestion_lag_seconds,
 warpstream.tableflow_query_lag_seconds,gauge,,second,,measures the time from when data is produced to Kafka until it is queryable (ingestion lag and catalog sync delay),0,warpstream,tableflow_query_lag_seconds,
 warpstream.bento_output_error,count,,,,counts the number of send attempts that have failed in Managed Data Pipelines. On failed batched sends this count is incremented once only,1,warpstream,bento_output_error,
+warpstream.cpu_utilization_go_runtime_moving_average_sample,count,,,,counts each value appended to the Go runtime CPU utilization moving average,1,warpstream,cpu_utilization_go_runtime_moving_average_sample,
+warpstream.cpu_utilization_go_runtime_moving_average_sample_utilization_distribution,gauge,,,,"distribution of the values appended to the Go runtime CPU utilization moving average, recorded as ratios between 0 and 1",0,warpstream,cpu_utilization_go_runtime_moving_average_sample_utilization_distribution,
+warpstream.agent_kafka_produce_forwarded_records_counter,count,,,,counts the number of records successfully forwarded to the source Kafka cluster during auto migration,1,warpstream,agent_kafka_produce_forwarded_records_counter,
+warpstream.agent_kafka_produce_forwarded_compressed_bytes,gauge,,byte,,distribution of the number of compressed bytes successfully forwarded to the source Kafka cluster during auto migration,0,warpstream,agent_kafka_produce_forwarded_compressed_bytes,
+warpstream.agent_kafka_produce_forwarded_compressed_bytes_counter,count,,byte,,counts the number of compressed bytes successfully forwarded to the source Kafka cluster during auto migration,1,warpstream,agent_kafka_produce_forwarded_compressed_bytes_counter,
+warpstream.agent_cpu,gauge,,percent,,latest CPU usage percentage reported by a live agent heartbeat,0,warpstream,agent_cpu,
+warpstream.min_offset,gauge,,,,oldest offset still retained for a topic partition,1,warpstream,min_offset,
+warpstream.max_offset,gauge,,,,high watermark offset (next offset to be written) for a topic partition,1,warpstream,max_offset,
+warpstream.consumer_group_commit_ts,gauge,,nanosecond,,timestamp (nanoseconds since epoch) of the last offset commit for a partition consumed by a Kafka consumer group,0,warpstream,consumer_group_commit_ts,
+warpstream.partition_size_estimated_compressed_bytes,gauge,,byte,,estimated compressed size in bytes of a topic partition's retained data,0,warpstream,partition_size_estimated_compressed_bytes,
+warpstream.agent_num_vcpus,gauge,,,,number of vCPUs reported by a live agent heartbeat,0,warpstream,agent_num_vcpus,
+warpstream.produced_records,count,,,,monotonically increasing count of records produced to a topic partition,1,warpstream,produced_records,
+warpstream.partition_size_uncompressed_bytes,gauge,,byte,,uncompressed size in bytes of a topic partition's retained data,0,warpstream,partition_size_uncompressed_bytes,
+warpstream.consumer_group_max_offset,gauge,,,,high watermark offset for a partition consumed by a Kafka consumer group,1,warpstream,consumer_group_max_offset,
+warpstream.agent_heartbeat,gauge,,,,"one sample per live agent heartbeat. Always 1; labels identify the agent, role set, group, availability zone, and other placement metadata",0,warpstream,agent_heartbeat,