Pulsar

Apache Pulsar serves Prometheus text at /metrics on its web port (:8080). A standalone process hosts the broker, the BookKeeper managed-ledger storage, and the functions worker together, and exposes all of their metrics on that one endpoint. The OpenTelemetry Collector's prometheus receiver scrapes it, collecting 270+ metrics from Pulsar 2.x+ across broker message rate / throughput / backlog and publish latency, per-topic and per-subscription rates and backlog, the BookKeeper storage write-latency path, and the JVM runtime. This guide configures the receiver and ships metrics to base14 Scout.

Prerequisites

Requirement	Minimum	Recommended
Apache Pulsar	2.x	4.x (4.0.3)
OTel Collector Contrib	0.90.0	0.153.0
base14 Scout	Any	-

Before starting:

• The Pulsar web port (8080) must be reachable from the host running the Collector.
• Metrics are enabled by default - no configuration changes are needed on the Pulsar side.
• A Scout account and OTLP endpoint.
• OTel Collector installed - see Docker Compose Setup.

What You'll Monitor

Metrics are grouped into three tiers by how you use them. Scrape Core always, alert on Operational, and reach for Diagnostic during an incident or capacity review.

A few things shape this surface, and they matter for every tier below:

• up is the liveness signal here. The prometheus receiver emits up = 1 when /metrics responds - that is the scrape liveness signal. pulsar_health (Pulsar 4.0.0+) is Pulsar's own broker self health-check (1 = healthy), and broker-wide backlog (pulsar_broker_msg_backlog) is the headline "are consumers keeping up" signal.
• Standalone collapses several roles into one /metrics. Broker aggregates (pulsar_broker_*), per-topic series (pulsar_* with a topic label), per-subscription series (pulsar_subscription_*), and the BookKeeper managed-ledger internals (pulsar_ml_*) all come from the same endpoint. A real cluster splits these across broker, bookie, and function-worker processes - the metric names are identical, so the same scrape config applies per process.
• Two write paths, two latency histograms. pulsar_broker_publish_latency is the producer-facing publish latency, while pulsar_storage_write_latency_* and pulsar_storage_ledger_write_latency_* are the BookKeeper persistence latencies behind it. Compare them to localize a publish slowdown to broker vs storage.
• Histograms expand into buckets. The _le_* / _sum / _count families are Pulsar's native bucket layout, not OTel exponential histograms; the receiver keeps each bucket as its own series.
• Managed-ledger names keep their case as exposed. pulsar_ml_AddEntryErrors, pulsar_ml_ReadEntriesRate, and pulsar_ml_StoredMessagesSize reproduce BookKeeper's camel-case exactly - they are not normalized to snake_case.
• The per-topic, per-subscription, and managed-ledger families warm up under traffic. They populate only after a topic exists and produces / consumes - a fresh idle standalone shows mostly broker-level zeros plus the JVM runtime. Left enabled, they populate once traffic flows.
• The JVM / Jetty / Caffeine / process families are the host runtime, not Pulsar product signals: jvm_*, jetty_*, caffeine_cache_*, process_*. Filter to pulsar_.*|up with a keep rule if the runtime is covered elsewhere.

Core - is it up, moving messages, and keeping consumers fed

Metric	What it tells you
up	Scrape liveness - 1 = the Pulsar metrics endpoint responded. The liveness signal on this surface.
pulsar_health	Broker self health-check result - 1 = healthy (Pulsar 4.0.0+).
pulsar_broker_rate_in	Broker-wide messages published per second - headline ingest throughput.
pulsar_broker_rate_out	Broker-wide messages dispatched per second - headline delivery throughput.
pulsar_broker_msg_backlog	Broker-wide unacked-message backlog - the headline "are consumers keeping up" signal.
pulsar_broker_publish_latency	Producer-facing publish latency - the write SLO.

Operational - what to alert on

Group	Metrics	What it tells you
Broker throughput	pulsar_broker_throughput_in, pulsar_broker_throughput_out	Broker-wide inbound / outbound bytes per second.
Broker entity counts	pulsar_broker_topics_count, pulsar_broker_subscriptions_count, pulsar_broker_producers_count, pulsar_broker_consumers_count, pulsar_active_connections	Topics, subscriptions, producers, consumers, and live client connections on the broker.
Dispatch backpressure	pulsar_broker_pending_bytes_to_dispatch, pulsar_broker_throttled_connections	Bytes queued for dispatch and connections being throttled - producers hitting rate limits.
Lookup path	pulsar_broker_lookup_failures_total, pulsar_broker_lookup_pending_requests, pulsar_broker_topic_load_pending_requests	Failed topic lookups, lookups in flight, and queued topic-load requests.
Broker storage	pulsar_broker_storage_size, pulsar_broker_storage_write_rate, pulsar_broker_storage_read_rate, pulsar_broker_storage_read_cache_misses_rate, pulsar_broker_storage_backlog_quota_exceeded_evictions_total	Stored size, write / read rates, read-cache misses, and messages evicted by quota policy (data loss).
Per-topic rate / throughput	pulsar_rate_in, pulsar_rate_out, pulsar_throughput_in, pulsar_throughput_out, pulsar_publish_rate_limit_times	Per-topic publish / dispatch message rate, bytes per second, and rate-limit hits.
Per-topic backlog	pulsar_msg_backlog, pulsar_storage_backlog_size, pulsar_storage_backlog_age_seconds, pulsar_storage_backlog_quota_limit	Per-topic unacked backlog, backlog bytes, age of the oldest unacked message, and the configured quota.
Storage write latency	pulsar_storage_write_latency_sum, pulsar_storage_write_latency_count, pulsar_storage_write_latency_le_*	Per-topic persistence write-latency distribution - the storage write SLO behind a publish.
Per-subscription health	pulsar_subscription_back_log, pulsar_subscription_unacked_messages, pulsar_subscription_blocked_on_unacked_messages, pulsar_subscription_msg_rate_redeliver, pulsar_subscription_msg_drop_rate, pulsar_subscription_msg_rate_out	Per-subscription backlog, unacked count, the blocked flag, redelivery and drop rate, and dispatch rate.
Write errors	pulsar_ml_AddEntryErrors, pulsar_ml_ReadEntriesErrors	Managed-ledger entry-write / read errors - the BookKeeper path is failing.
Topic load / metadata	pulsar_topic_load_failed_count, pulsar_metadata_store_ops_latency_ms	Failed topic loads and metadata-store (ZooKeeper / RocksDB) operation latency - slow metadata stalls topic ops cluster-wide.

Diagnostic - for investigation and tuning

Higher cardinality; reach for these during an incident or capacity review.

Group	Representative metrics	When you reach for it
Per-topic detail	pulsar_average_msg_size, pulsar_in_bytes_total, pulsar_out_bytes_total, pulsar_in_messages_total, pulsar_out_messages_total, pulsar_storage_logical_size, pulsar_storage_offloaded_size, pulsar_storage_write_rate, pulsar_delayed_message_index_size_bytes	Per-topic byte / message totals, logical and offloaded storage size, and delayed-delivery index size.
Entry-size / ledger-write histograms	pulsar_entry_size_sum / _count / _le_*, pulsar_storage_ledger_write_latency_sum / _count / _le_*	The message-entry size distribution and the BookKeeper ledger write latency behind the topic write path.
Per-namespace counts	pulsar_producers_count, pulsar_consumers_count, pulsar_subscriptions_count, pulsar_topics_count	Per-namespace producer / consumer / subscription / topic accounting.
Per-subscription detail	pulsar_subscription_consumers_count, pulsar_subscription_msg_ack_rate, pulsar_subscription_msg_throughput_out, pulsar_subscription_msg_rate_expired, pulsar_subscription_delayed, pulsar_subscription_in_replay	Consumer count, ack rate, outbound throughput, TTL expiry, and delayed / replay detail on a subscription.
Subscription progress timestamps	pulsar_subscription_last_acked_timestamp, pulsar_subscription_last_consumed_timestamp, pulsar_subscription_last_mark_delete_advanced_timestamp	A stalled timestamp marks a stuck consumer.
Subscription server-side filters	pulsar_subscription_filter_accepted_msg_count, pulsar_subscription_filter_rejected_msg_count, pulsar_subscription_filter_rescheduled_msg_count	Outcomes when a subscription has a server-side selector attached.
Managed-ledger internals	pulsar_ml_AddEntryBytesRate, pulsar_ml_ReadEntriesRate, pulsar_ml_StoredMessagesSize, pulsar_ml_NumberOfMessagesInBacklog, pulsar_ml_MarkDeleteRate, pulsar_ml_cache_*, pulsar_ml_AddEntryLatencyBuckets, pulsar_ml_LedgerSwitchLatencyBuckets	BookKeeper add / read rates, stored size, mark-delete rate, the read cache, and the latency bucket layouts.
Schema registry / topic load	pulsar_schema_get_ops_latency, pulsar_schema_put_ops_latency, pulsar_topic_load_rate_s, pulsar_topic_load_times, pulsar_topic_load_time_*_ms	Schema read / write latency and topic-load rate / time percentiles.
Transactions / resource groups	pulsar_txn_tb_active_total, pulsar_txn_tb_committed_total, pulsar_txn_tb_aborted_total, pulsar_resource_group_aggregate_usage_secs, pulsar_resource_group_calculate_quota_secs	Transaction-buffer counts and resource-group usage / quota timings.
Functions worker	pulsar_function_worker_*	Functions-worker scheduling, rebalance, instance-count, and leader state.
Web thread pool	pulsar_web_executor_active_threads, pulsar_web_executor_idle_threads, pulsar_web_executor_max_threads	Web / admin thread-pool sizing.
JVM / Jetty / Caffeine / process runtime	jvm_memory_bytes_used, jvm_memory_direct_bytes_used, jvm_gc_collection_seconds, jvm_threads_current, jetty_*, caffeine_cache_*, process_cpu_seconds_total, process_resident_memory_bytes, log4j2_appender_total	Host runtime - heap, off-heap direct memory, GC, threads, the admin HTTP server, in-process caches, and OS process stats.
Scrape meta	scrape_duration_seconds, scrape_samples_scraped	Receiver-side scrape health, not from Pulsar.

Full metric list: run curl -s http://localhost:8080/metrics against your Pulsar broker.

Key Alerts to Configure

Threshold guidance for the most useful Core and Operational series. These are starting points; tune them to your workload.

Metric	Threshold	Why it matters
up	== 0 for > 1m	The metrics endpoint stopped responding - check the broker process and the web port.
pulsar_health	< 1	The broker self health-check is failing (Pulsar 4.0.0+) - check BookKeeper and the metadata store.
pulsar_broker_msg_backlog / pulsar_storage_backlog_age_seconds	Backlog rising vs baseline, or age climbing	Consumers are not keeping up - scale consumers or investigate slow processing.
pulsar_subscription_blocked_on_unacked_messages	== 1	A subscription hit its unacked-message limit - consumers are not acking; check consumer health.
pulsar_subscription_msg_rate_redeliver	Rising vs baseline	Consumers are failing to ack and messages are being redelivered - check consumer errors and ack timeout.
pulsar_ml_AddEntryErrors	> 0	The BookKeeper write path is failing - check bookie health and disk.
pulsar_broker_publish_latency / pulsar_storage_write_latency_*	p99 rising vs baseline	Writes are slow - compare broker vs storage latency to localize.
rate(pulsar_broker_storage_backlog_quota_exceeded_evictions_total)	> 0	Messages are being evicted by quota policy (data loss) - raise the quota or drain the backlog.
rate(pulsar_broker_lookup_failures_total)	> 0	Clients cannot resolve topic ownership - check the metadata store and broker load.
pulsar_metadata_store_ops_latency_ms	p99 rising vs baseline	Slow metadata operations stall topic load / unload cluster-wide - check ZooKeeper / RocksDB.

The liveness, health, blocked-flag, and error / eviction alerts read states or events; the latency and backlog alerts are relative to your own baseline. Set absolute thresholds only against your own workload and provisioned capacity.

Access Setup

Pulsar exposes Prometheus metrics natively - no exporter sidecar is needed. The /metrics endpoint on the web port (8080) is unauthenticated by default.

Bring up a standalone instance, which runs the broker, BookKeeper storage, and functions worker in one process:

Run Pulsar standalone

docker run -d --name pulsar \
  -p 6650:6650 -p 8080:8080 \
  apachepulsar/pulsar:4.0.3 \
  bin/pulsar standalone

Verify the metrics endpoint is serving:

Verify access

# Confirm the broker is healthy
curl -s http://localhost:8080/admin/v2/brokers/health

# Confirm the Prometheus endpoint responds
curl -s http://localhost:8080/metrics | head -20

A secured production cluster fronts the web port with TLS and authentication. When metrics are behind auth, point the scrape job at https and supply the broker's credentials to the receiver; restrict the endpoint at the network layer either way.

Configuration

The recommended config scrapes Pulsar's /metrics and keeps only the Pulsar series with a metric_relabel_configs keep filter, dropping the JVM / Jetty / Caffeine runtime noise the endpoint also emits:

config/otel-collector.yaml

receivers:
  prometheus:
    config:
      scrape_configs:
        - job_name: pulsar
          scrape_interval: 10s
          static_configs:
            - targets:
                - ${env:PULSAR_HOST}:8080   # Pulsar web port; default /metrics
          metric_relabel_configs:
            - source_labels: [__name__]
              regex: "pulsar_.*|up"
              action: keep

processors:
  resource:
    attributes:
      - key: environment
        value: ${env:ENVIRONMENT}
        action: upsert
      - key: service.name
        value: ${env:SERVICE_NAME}
        action: upsert

  batch:
    timeout: 10s
    send_batch_size: 1024

exporters:
  otlphttp/b14:
    endpoint: ${env:OTEL_EXPORTER_OTLP_ENDPOINT}
    tls:
      insecure_skip_verify: true

service:
  pipelines:
    metrics:
      receivers: [prometheus]
      processors: [resource, batch]
      exporters: [otlphttp/b14]

The keep filter scopes collection to the pulsar_* product families plus the up liveness series, and drops the jvm_* / jetty_* / caffeine_cache_* / process_* host-runtime series. Remove the filter if you want the runtime in Scout too.

Environment Variables

.env

PULSAR_HOST=localhost
ENVIRONMENT=your_environment
SERVICE_NAME=your_service_name
OTEL_EXPORTER_OTLP_ENDPOINT=https://<your-tenant>.base14.io

Verify the Setup

Start the Collector and check for metrics within 60 seconds:

Verify metrics collection

# Check Collector logs for scraped Pulsar metrics
docker logs otel-collector 2>&1 | grep -i "pulsar"

# Confirm the broker health metric is exposed
curl -s http://localhost:8080/metrics | grep pulsar_health

# Confirm broker throughput is exposed
curl -s http://localhost:8080/metrics | grep pulsar_broker_rate_in

Troubleshooting

Connection refused on port 8080

Cause: The Collector cannot reach the Pulsar web endpoint.

Fix:

1. Verify Pulsar is running: docker ps | grep pulsar or bin/pulsar-admin brokers list.
2. Confirm the web port is open: curl http://localhost:8080/metrics.
3. Check firewall rules if the Collector runs on a separate host.

Only broker-level metrics appear

Cause: There is no topic with traffic yet. The per-topic (pulsar_* with a topic label), per-subscription (pulsar_subscription_*), and managed-ledger (pulsar_ml_*) families populate only once a topic exists and produces / consumes.

Look at: the broker-level series first - if pulsar_broker_* populates but the per-topic / per-subscription / pulsar_ml_* families read 0 or are absent, the broker is healthy and simply idle.

Fix:

1. Create a topic and produce a test message: bin/pulsar-client produce persistent://public/default/test -m "hello".
2. Run a consumer so the subscription and managed-ledger families advance.
3. Re-check: curl -s http://localhost:8080/metrics | grep pulsar_subscription.

Publish latency is high

Cause: Writes are slow, either at the broker or in BookKeeper storage.

Look at: pulsar_broker_publish_latency against the storage latencies - pulsar_storage_write_latency_* and the Diagnostic pulsar_storage_ledger_write_latency_*. If the storage latency tracks the publish latency, the bottleneck is BookKeeper; if not, it is broker-side. Check pulsar_ml_AddEntryErrors for write-path failures.

Fix:

1. Inspect bookie health and disk if storage latency is climbing.
2. Check broker CPU and jvm_gc_collection_seconds if the broker side is slow.

No metrics appearing in Scout

Cause: Metrics are collected but not exported.

Fix:

1. Check Collector logs for export errors: docker logs otel-collector.
2. Verify OTEL_EXPORTER_OTLP_ENDPOINT is set correctly.
3. Confirm the pipeline includes both the receiver and the exporter.

FAQ

Does this work with Pulsar running in Kubernetes?

Yes. Set the Collector's targets to the broker's web-port service DNS (e.g., pulsar-broker.pulsar.svc.cluster.local:8080). With the Apache Pulsar Helm chart the broker web port is exposed by default. The Collector can run as a sidecar or a DaemonSet.

What is the difference between standalone and a cluster for monitoring?

Standalone runs the broker, BookKeeper bookie, and functions worker in one process, so all metrics come from one /metrics. A production cluster splits those roles across separate processes - the metric names are the same, so add a scrape job per broker, bookie, and function-worker endpoint:

config/otel-collector.yaml (cluster)

receivers:
  prometheus:
    config:
      scrape_configs:
        - job_name: pulsar-broker
          static_configs:
            - targets:
                - broker-1:8080
                - broker-2:8080
        - job_name: pulsar-bookie
          static_configs:
            - targets:
                - bookie-1:8000
                - bookie-2:8000
        - job_name: pulsar-function-worker
          static_configs:
            - targets:
                - fn-worker-1:6750

Each process is scraped independently and identified by its instance label.

Why do I only see broker-level metrics?

The per-topic, per-subscription, and managed-ledger families populate only once a topic exists and has active producers or consumers. An idle standalone shows mostly broker-level zeros plus the JVM runtime. Produce and consume on a topic to advance them.

Why are the pulsar_ml_* metrics in camel-case?

The BookKeeper managed-ledger family (pulsar_ml_AddEntryErrors, pulsar_ml_ReadEntriesRate, pulsar_ml_StoredMessagesSize, and the rest) keeps BookKeeper's camel-case by design. The prometheus receiver reproduces the name exactly as exposed and does not normalize it to snake_case.

Related Guides

• OTel Collector Configuration - Advanced collector configuration.
• Docker Compose Setup - Run the Collector locally.
• Kubernetes Helm Setup - Production deployment.
• Creating Alerts - Alert on Pulsar metrics.
• Kafka Monitoring - Consumer lag and partition offsets for another high-throughput streaming broker.
• RabbitMQ Monitoring - Queue depth and consumer health for a classic message queue.

What's Next?

• Create Dashboards: Explore pre-built dashboards or build your own. See Create Your First Dashboard.
• Monitor More Components: Add monitoring for Kafka, RabbitMQ, and other components.
• Fine-tune Collection: The Diagnostic tier is higher cardinality. You can scope its collection with metric_relabel_configs if you need to, and reach for it during incident investigation.