Buyer’s Guide - August 2026

The 7 best Apache Pulsar monitoring tools, ranked

Q: Is Pulsar Manager enough for monitoring my Pulsar cluster?

No. Pulsar Manager is the official web GUI for administration (tenants, namespaces, topics, subscriptions, brokers) with basic topic monitoring built in. It has no alerting, no long-term metric retention, and no deep BookKeeper, ZooKeeper, or transaction metrics. Production monitoring still needs Prometheus/Grafana or a dedicated tool alongside it.

Pulsar monitoring is harder than it looks because the architecture splits serving (brokers) from storage (BookKeeper) and adds ZooKeeper coordination, so a real tool has to cover several component types plus topic-level signals like backlog, throughput, and consumer lag. This ranking grades seven options on Pulsar metric depth, time to value, resolution, alerting, and how the bill scales as your cluster grows horizontally.

Start with Netdata (free) Jump to rankings

Why this list exists

Most “Pulsar monitoring” searches return generic APM roundups, and that is the first trap. Pulsar is not one process: brokers serve traffic, BookKeeper bookies own storage, and ZooKeeper coordinates the cluster. A tool that watches only the broker is blind to the layer where most storage incidents start. Worse, most general-purpose platforms (New Relic, Dynatrace, Elastic, SigNoz) have no dedicated Pulsar integration at all, and WhaTap’s dedicated Pulsar monitoring is being discontinued at the end of 2026. The credible field is smaller than the search results suggest.

The second trap is treating Apache Pulsar Manager as a monitoring solution. It is the official administration GUI, excellent for tenants, namespaces, and topic operations, but it has no alerting, no long-term metric retention, and no BookKeeper or ZooKeeper depth. It is a companion, not a platform.

Three dimensions decide the outcome for most buyers:

Coverage across the stack. Broker, bookie, ZooKeeper, proxy, and functions metrics, plus topic-level backlog, throughput, and storage signals. Partial coverage means partial incidents.
Time to value versus assembly effort. The officially documented path is Prometheus scraping Pulsar’s endpoints plus Grafana dashboards, which is powerful but is a stack you build and operate. Dedicated tools trade flexibility for working charts in minutes.
Cost shape as the cluster grows. Pulsar scales horizontally. Per-host pricing grows linearly with cluster size; flat per-node pricing with unlimited metrics does not; open source is free to obtain but you pay to run it.

One caveat on numbers: we do not quote competitor list prices. They change, they hide behind quotes, and the shape of the pricing model matters more than any single figure. We link each vendor’s official pricing page so you can verify the current state yourself. For hands-on configuration details, our Apache Pulsar guides cover operator-level setup for the approaches below.

We assembled the shortlist from tools with verifiable, documented Pulsar coverage: the officially documented Prometheus/Grafana path, dedicated integrations from observability vendors, the Apache project’s own tooling, the managed Pulsar platform, and the storage backend the Pulsar Helm chart now ships with. Vendors with no dedicated Pulsar support were excluded rather than padded in.

The heaviest weights go to metric depth across the whole Pulsar stack and time to value, because Pulsar’s multi-component architecture makes both the biggest practical differentiators. Resolution is graded with one honest caveat: Pulsar’s own Prometheus metrics refresh about once a minute, which caps effective Pulsar-counter resolution for every Prometheus-scraping tool regardless of scrape interval. Cost is graded on pricing shape, not list prices.

Tester credit

Compiled by the Netdata team - Updated August 12, 2026

Sources verified

Scoring criteria

Pulsar metric depth and coverage 25%
Broker, bookie, ZooKeeper, proxy, functions, transactions, and topic-level backlog/throughput/storage.
Time to value and setup effort 20%
Auto-discovery and shipped charts versus assembling scrape configs, dashboards, and alerts by hand.
Real-time resolution 15%
Per-second collection versus 15-60s scrapes; Pulsar’s own metrics refresh about once a minute.
Alerting and anomaly detection 15%
Pulsar-relevant alerting out of the box, and ML/anomaly detection versus static thresholds.
Cost model predictability 15%
How the bill scales as Pulsar clusters grow horizontally.
Ecosystem fit 10%
Kubernetes/Helm support, OpenTelemetry, Prometheus and remote-write interoperability.

Vendor 01 / 07 · #netdata

Netdata

Real-time, per-second infrastructure and application monitoring with a dedicated Apache Pulsar collector and built-in ML anomaly detection.

Best for

Teams that want Pulsar monitoring working within minutes of installing an agent, with no scrape configs or dashboard assembly
SREs who need per-second visibility into broker hosts, bookies, and ZooKeeper nodes alongside Pulsar-specific charts
Cost-conscious fleets that want unlimited metrics at a flat per-node price

Pricing

Per-node pricing: Netdata Cloud Business starts at $4.50/node/month on annual plans, and the per-node price decreases as node count grows
Free Cloud tier for small fleets (Community plan, capped by connected node count)
Agents are open source (GPLv3+) and remain free; paid plans include unlimited metrics, logs, users, and retention

Pros

Dedicated Apache Pulsar collector (go.d.plugin) that auto-detects the installation and generates 20+ charts on messages/second, throughput rate, storage size, and topic producers, subscriptions, and consumers
Collects broker statistics directly from Pulsar’s Prometheus endpoint with no extra configuration
Per-second collection with ML-based anomaly detection on every metric (Netdata claims 99% false-positive reduction)
Unified view: Pulsar metrics plus host-level CPU, memory, disk, and network for brokers, bookies, and ZooKeeper nodes in one agent
Open source agent, free Cloud tier for small fleets, and flat per-node pricing with unlimited metrics and retention

Where teams pair it

The Pulsar collector is broker-centric; deep BookKeeper ledger internals and transaction-coordinator metrics need extra scrape jobs against bookie endpoints
No Pulsar-specific alert templates or curated Pulsar dashboards ship out of the box; teams define their own backlog and throughput alert rules (unsupervised ML anomaly detection covers baseline behaviour in the meantime)
Pulsar’s own Prometheus metrics refresh about once a minute, so per-second collection shows host-level detail while Pulsar counters update at Pulsar’s cadence (true for every Prometheus-scraping tool)

Verdict

Netdata is the only option here that combines a purpose-built Pulsar collector with per-second, ML-assisted monitoring of the hosts underneath (brokers, bookies, ZooKeeper) in a single agent, at a flat per-node price with unlimited metrics. Install the agent on a broker and the Pulsar charts appear; install it on the bookies and ZooKeeper nodes and the storage and coordination layers light up too, which is exactly the coverage Pulsar’s architecture demands. The honest caveat: the collector is broker-centric, so BookKeeper ledger internals need extra scrape jobs, and you will write your own backlog alert rules rather than importing Pulsar-specific templates. For teams that want working Pulsar visibility in minutes instead of assembling a stack, it is the fastest path.

Start free -> See Netdata pricing ->

Vendor 02 / 07 · #prometheus-grafana

Prometheus + Grafana

The officially documented Apache Pulsar monitoring stack: Prometheus scrapes Pulsar’s metrics endpoints and Grafana visualizes them.

Best for

Teams already running a Prometheus/Grafana platform who want Pulsar in the same dashboards
Platform engineers who prefer assembling and owning their monitoring stack
Kubernetes deployments using the official Pulsar Helm chart, which ships Prometheus, Grafana, and Pulsar-specific alerting rules

Pricing

Prometheus is open source and self-hosted: storage, retention, and high availability are yours to operate
Grafana OSS is open source and self-hosted; Grafana Cloud is SaaS with a free tier and usage-based Pro pricing (per active series, per GB of logs, per active user)
The bill grows with scrape volume, retention, and active series

Pros

The approach documented by Apache Pulsar itself: broker metrics at :8080/metrics, BookKeeper at :8000/metrics, ZooKeeper at :8000/:8001
Ready-made Grafana dashboards from StreamNative and DataStax covering overview, topics, messaging, and per-component views
PromQL querying and alerting rules integrated with Alertmanager, Kubernetes PodMonitors, and the wider CNCF ecosystem
Pulsar emits OpenTelemetry metrics (experimental, 3.3.0+) that can flow through the OTel Collector into Prometheus-compatible backends

Cons

No turnkey Pulsar product: you assemble scrape configs, dashboards, alert rules, and retention yourself
Default scrape intervals of 15-60s miss sub-minute spikes, and Pulsar’s own metric refresh is about 1 minute
No built-in anomaly detection or root-cause correlation; alerting is threshold-based unless you add more tooling
Storage and high availability are DIY; long-term retention requires remote write or a TSDB such as VictoriaMetrics

Verdict

This is the default path and the one the Pulsar project documents, so it ranks second on ecosystem gravity alone. The flexibility is real: every Pulsar metric is reachable, community dashboards are mature, and the official Helm chart ships Prometheus, Grafana, and Pulsar-specific alerting rules. The cost is assembly and operation. You own scrape configs, alert rules, storage, and HA, and effort scales with cluster size. Teams with an existing Prometheus platform should stay on it; teams starting from zero should be honest about the build-and-run burden.

Read full Netdata vs Prometheus -> Grafana pricing ->

Vendor 03 / 07 · #datadog

Datadog

SaaS observability platform with a dedicated, agent-based Apache Pulsar integration covering broker, BookKeeper, proxy, functions, and transaction metrics.

Best for

Enterprises already standardized on Datadog who want Pulsar in the same dashboards as the rest of their stack
Teams that want a maintained, out-of-the-box Pulsar integration with broad metric coverage and log collection

Pricing

Per-host, modular pricing: Infrastructure, APM, and Log Management are billed separately, so the bill grows with host count and each product you add
Usage-based add-ons (custom metrics, log ingestion, spans) sit on top of per-host fees

Pros

Dedicated Pulsar check bundled in the Datadog Agent (OpenMetrics-based), so no separate exporter to run
Broad metric coverage: broker, BookKeeper/bookie, managed ledger, namespace/topic, consumer and subscription backlog, load manager, proxy, replication, compaction, functions, sinks, sources, and transactions
Includes Pulsar log collection for Pulsar’s default log format alongside metrics
Service check (pulsar.openmetrics.health) reports endpoint availability

Cons

Per-host pricing across modular products makes large Pulsar fleets expensive; costs scale linearly with cluster size
Agent check cadence is far coarser than per-second (typically 15s or more), so short-lived spikes can be missed
No Pulsar-specific anomaly detection; alerting is threshold-based on the integration’s metrics

Verdict

Datadog has the deepest dedicated Pulsar integration among SaaS APM vendors, covering components most tools ignore, including transactions and functions. If your organization already pays for Datadog, enabling the Pulsar check is the obvious move and the metric breadth is genuinely strong. The objection is economic: Pulsar clusters scale horizontally, and per-host modular pricing scales right along with them, before log ingestion and custom metrics enter the bill. Check cadence is also coarse relative to per-second tools, which matters when a backlog spike lives for thirty seconds.

Read full Netdata vs Datadog -> Datadog pricing ->

Vendor 04 / 07 · #pulsar-manager

Apache Pulsar Manager

The Apache Software Foundation’s official web GUI for managing and monitoring Pulsar clusters, including topic and subscription stats.

Best for

Operators who want an official GUI for day-to-day Pulsar administration (tenants, namespaces, topics, brokers)
Teams that need basic topic and subscription monitoring alongside management without adding a commercial tool

Pricing

Open source Apache project, self-hosted: you deploy and operate it via Docker, Helm chart, or binary package

Pros

Official Apache project maintained by the Pulsar community; deploys via Docker, Helm chart, or binary package
Manages multiple clusters (Environments) from one UI: tenants, namespaces, topics, subscriptions, brokers, clusters, and JWT auth
Topics monitoring shows per-topic and per-subscription stats; the Apache Pulsar docs point to Pulsar Manager for per-topic dashboards

Cons

A management console, not an observability platform: no alerting, no long-term metric retention, no anomaly detection
No deep BookKeeper, ZooKeeper, or transaction metrics; those need Prometheus/Grafana or another tool
Must be deployed in the same network as the clusters because the backend talks directly to brokers and bookies

Verdict

Pulsar Manager earns its place because nearly every Pulsar operator will use it, and the per-topic and per-subscription views are genuinely useful for quick checks. But be clear-eyed about what it is: an administration console with light monitoring, not a monitoring tool. There is no alerting, no retention, and no visibility into BookKeeper or ZooKeeper, which is where production incidents hide. Run it alongside a real monitoring stack, not instead of one.

Apache Pulsar Manager on GitHub -> Pulsar monitoring docs ->

Vendor 05 / 07 · #streamnative

StreamNative Cloud

Managed Apache Pulsar platform from the original Pulsar developers, with built-in cluster metrics, a local Prometheus endpoint, and remote write to your own monitoring stack.

Best for

Teams running StreamNative Cloud who want managed Pulsar with metrics, logs, and alerts without operating a monitoring stack
Organizations that want to push Pulsar metrics into their existing Prometheus or Datadog platform via remote write

Pricing

Usage-based managed service with deployment tiers (Serverless, Dedicated, BYOC); functions and connectors billed by Function Processing Units
Observability features are included with the managed service; the bill grows with cluster size and message throughput

Pros

Metrics API covering tenants, namespaces, topics, connectors, and functions, plus a Local Metrics Endpoint (BYOC Pro) exposing system-level broker and bookie metrics
Remote Write integration to Prometheus-compatible systems and Datadog
Pulsar Detector monitors cluster health and distribution latency within and across clusters
Built by original Apache Pulsar and BookKeeper committers; StreamNative maintains the widely used apache-pulsar-grafana-dashboard project

Cons

Only relevant if you run Pulsar on StreamNative Cloud; it is a feature of the managed service, not a standalone monitoring tool
System-level metrics require BYOC Pro and a support request to enable the Local Metrics Endpoint
No per-second resolution or built-in anomaly detection; observability is metrics-forward with alerts

Verdict

If your Pulsar runs on StreamNative Cloud, this is the best observability you can get for it, full stop. The metrics API is broad, remote write lets you federate into your existing Prometheus or Datadog platform, and the people maintaining the dashboards wrote much of Pulsar itself. The ranking reflects scope, not quality: none of this applies to self-managed clusters, and the deepest system-level metrics sit behind a BYOC Pro support request. StreamNative customers should use it heavily; everyone else should skip this card.

StreamNative observability docs -> StreamNative pricing ->

Vendor 06 / 07 · #victoriametrics

VictoriaMetrics

Prometheus-compatible time-series database used as the metrics backend for large Pulsar deployments, including the official Pulsar Helm chart since 4.0.0.

Best for

Large Pulsar fleets that outgrow Prometheus storage and want a drop-in PromQL-compatible backend
Kubernetes Pulsar deployments using the Helm chart’s victoria-metrics-k8s-stack

Pricing

Open source and self-hosted (single-node and cluster versions): you run and operate it
Managed VictoriaMetrics Cloud with capacity-tier pricing; the bill grows with ingestion rate and retention

Pros

Drop-in Prometheus compatibility (PromQL, scrape configs, remote write) with a lower RAM and disk footprint than Prometheus at high cardinality
Used by the Apache Pulsar Helm chart since 4.0.0; community Grafana dashboards (lhotari/pulsar-grafana-dashboards) are built for the victoria-metrics-k8s-stack
vmalert provides Prometheus-compatible alerting and recording rules
Open source core with a managed cloud option

Cons

A storage backend, not a Pulsar monitoring product: no Pulsar-specific dashboards, alert templates, or anomaly detection of its own
You still need Grafana (or similar) for visualization and must define Pulsar alert rules yourself
Pulsar-specific value depends on community dashboards and the Helm chart integration

Verdict

VictoriaMetrics is not a Pulsar monitoring tool; it is where Pulsar metrics live when Prometheus storage falls over. That matters more than it sounds, because Pulsar emits metrics per topic, per subscription, and per component, and cardinality climbs fast on busy clusters. The Helm chart adopting the victoria-metrics-k8s-stack in 4.0.0 makes this the path of least resistance for Kubernetes deployments at scale. You still assemble dashboards and alerts yourself, so budget the same platform effort as the Prometheus option.

Read full Netdata vs VictoriaMetrics -> VictoriaMetrics plans ->

Vendor 07 / 07 · #opsramp

OpsRamp

Enterprise IT operations platform (HPE) with dedicated agent-based monitors for Apache Pulsar brokers and BookKeeper nodes.

Best for

Enterprise IT operations teams (MSPs and large organizations) that manage Pulsar alongside a broad hybrid infrastructure estate
Organizations already on OpsRamp or HPE GreenLake who want Pulsar in their standard ITOM tooling

Pricing

Quote-based SaaS with no public pricing; the bill grows with monitored resources and platform modules

Pros

Dedicated Apache Pulsar Broker monitor and Apache Pulsar Bookkeeper monitor with pre-configured dashboards
Agent-based discovery and monitoring integrated with event management, alerting, and automation
Part of HPE’s observability and IT operations portfolio with AIOps-style event correlation

Cons

Enterprise ITOM platform, not a Pulsar-specialist tool; Pulsar coverage is broker and bookkeeper metrics without the depth of dedicated observability platforms
No public pricing; quote-based contracts favor large enterprises
Little presence in the Pulsar community; most Pulsar users pair Prometheus/Grafana instead

Verdict

OpsRamp deserves credit for shipping actual Pulsar broker and BookKeeper monitors when larger observability names have none. For an enterprise already running OpsRamp or HPE GreenLake, folding Pulsar into the existing ITOM estate is sensible and the pre-configured dashboards save setup time. For everyone else it is a hard sell: no public pricing, an enterprise procurement motion, and Pulsar coverage that stops well short of what the dedicated tools here provide. A niche fit, fairly ranked last.

OpsRamp Pulsar Broker monitor docs -> OpsRamp site ->

Frequently Asked Questions

How do I monitor Apache Pulsar?

Pulsar exposes Prometheus-format metrics out of the box: broker at :8080/metrics, BookKeeper at :8000/metrics, ZooKeeper at :8000/:8001, plus functions worker metrics. The officially documented path is Prometheus scraping these endpoints with Grafana dashboards on top. Dedicated alternatives include Netdata’s Pulsar collector (auto-discovery, per-second host data), Datadog’s agent-based Pulsar check, and Pulsar Manager for admin and topic views. Note that Pulsar’s message rates update about every minute regardless of how fast your scraper runs.

What metrics should I monitor in Apache Pulsar?

Start with subscription backlog (pulsar_subscription_backlog), the primary consumer-health signal. Add throughput in/out and message rate in/out per broker, namespace, and topic. For capacity planning, track storage size, storage write latency, and offloaded size. Round it out with consumer lag and unacked messages, replication backlog and rate, broker load manager usage, and bookie writable status, because BookKeeper write trouble surfaces as messaging latency downstream.

Does Apache Pulsar support OpenTelemetry?

Yes, starting in Pulsar 3.3.0, but it is experimental and broker-only for now (proxy and function worker support is planned later). OTLP export runs every 60 seconds by default and is disabled out of the box; set OTEL_SDK_DISABLED=false to enable it. Pulsar itself exposes only the metrics signal, not logs or traces, and the OTel metrics are semantically equivalent to the existing Prometheus metrics, so you are choosing a transport, not new data.

What is consumer backlog in Pulsar and how do I alert on it?

Backlog is the number of messages pending in a subscription that consumers have not yet acknowledged. A growing backlog with a flat consumption rate means a saturated or failing consumer. Alert on pulsar_subscription_backlog per topic and subscription, and keep a top-topics-by-backlog dashboard for triage. Pulsar also has backlog quota policies that can block producers when limits are exceeded, so unmonitored backlog can turn into a producer-side outage.

Prometheus and Grafana vs a dedicated monitoring tool for Pulsar: which is better?

Prometheus plus Grafana is the official, most flexible path, but you assemble scrape configs, dashboards, alert rules, and storage yourself. Dedicated tools like Netdata and Datadog provide out-of-the-box Pulsar charts and faster time to value. The tradeoffs are resolution (per-second collection versus 15-60s scrape intervals) and alerting (static thresholds versus ML-based anomaly detection). Teams with an existing Prometheus platform usually stay; teams starting fresh should weigh the assembly effort honestly.

Is Pulsar Manager enough for monitoring my Pulsar cluster?

How do I monitor Apache Pulsar on Kubernetes?

The official Pulsar Helm chart ships Prometheus, Grafana, and Alertmanager with Pulsar-specific dashboards and alerting rules, and a PodMonitor scrapes Pulsar component metrics automatically. Since Pulsar 4.0.0 the chart also supports the victoria-metrics-k8s-stack, with compatible community dashboards available. Netdata and Datadog agents also run as DaemonSets if you want host-level plus Pulsar metrics per node.

How much does Apache Pulsar monitoring cost?

Pricing shapes differ more than prices: per-node with unlimited metrics (Netdata), per-host modular (Datadog), per-active-series and per-user usage (Grafana Cloud), open source self-hosted (Prometheus, Pulsar Manager, VictoriaMetrics), usage-based managed service (StreamNative), and quote-based (OpsRamp). Because Pulsar clusters scale horizontally, per-host pricing grows linearly with cluster size while flat per-node pricing does not. Open source tools are free to obtain, but you pay to run and operate them, so include infrastructure and engineering time in the comparison.

The 7 best Apache Pulsar monitoring tools, ranked

How we evaluated Pulsar monitoring tools

Netdata

Prometheus + Grafana

Datadog

Apache Pulsar Manager

StreamNative Cloud

VictoriaMetrics

OpsRamp

Frequently Asked Questions

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