Buyer’s Guide - August 2026

The 10 best Apache Tomcat monitoring tools, ranked

Tomcat outages rarely come from CPU or RAM. They come from thread pool exhaustion, heap pressure, and connector errors that generic server monitors never see. We ranked ten tools on the metrics that actually break Tomcat in production: JVM health, thread pools, connectors, sessions, and JDBC pools.

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The 10 best Apache Tomcat monitoring tools, ranked product interface

Why this list exists

Tomcat monitoring is not generic infrastructure monitoring. Tomcat is a JVM application server, which means the signals that predict an outage live in the JVM (heap usage, garbage collection pauses, thread counts) and in Tomcat’s JMX MBeans (connector request counts and processing time, thread pool utilization, active sessions, JDBC connection pools). A tool that watches CPU and memory will tell you the server is sick, but not that currentThreadsBusy is about to hit maxThreads.

The mistake buyers make is picking a dashboard that looks good in a demo but misses the Tomcat-specific failure modes. Thread pool exhaustion under a traffic spike can develop in seconds. A monitor polling every 60 seconds will show you a clean graph right up until requests start queuing.

Three dimensions decide the outcome for most teams:

Metric depth. Does the tool reach the JMX MBean tree (GlobalRequestProcessor, ThreadPool, Manager, DataSource) or only the Server Status endpoint or JVM-level stats? JDBC pools and servlet-level metrics separate deep tools from shallow ones.
Resolution. Per-second collection catches transient thread spikes and heap pressure that 15 to 60 second polling averages away.
Setup cost. Zero-config auto-detection beats enabling JMX Remote, writing exporter YAML, and assembling dashboards by hand.

One note on pricing: we do not quote list prices for any vendor except Netdata. Pricing pages change, negotiated rates differ, and a stale number is worse than no number. Instead, each card describes the pricing shape and what makes the bill grow, with a link to the vendor’s official pricing page. For operator-level detail on the metrics themselves, see our Tomcat monitoring guides. For Netdata’s costs, see our pricing page.

We assembled the shortlist from tools that document Tomcat-specific collection: JMX-based checks, Server Status endpoint parsers, and Java agents with Tomcat instrumentation. Generic server monitors without documented Tomcat metric coverage were excluded.

Metric depth carries the most weight because it is the hardest to bolt on later: a tool either reaches connectors, thread pools, sessions, and JDBC pools or it does not. Setup time and resolution follow, because a deep tool that takes a week to configure, or a fast tool that polls once a minute, both fail the same production incident.

Tester credit

Compiled by the Netdata team - Updated August 12, 2026

Sources verified

Scoring criteria

Tomcat metric depth and specificity 25%
Connectors, thread pools, sessions, JVM heap and GC, JDBC pools. CPU and RAM do not qualify.
Setup and time-to-value 20%
Auto-detection beats JMX Remote configuration and hand-built exporters.
Data resolution and real-time visibility 15%
Per-second collection surfaces thread pool spikes far earlier than 15-60 second polling.
Alerting and anomaly detection 15%
Tomcat-specific alerts and anomaly detection, not just static host thresholds.
Total cost of ownership 15%
Pricing shape plus the operational cost of running the platform.
Ecosystem and extensibility 10%
Logs, traces, Kubernetes, and community dashboard support.

Vendor 01 / 10 · #netdata

Netdata

Real-time, per-second Tomcat and JVM monitoring with an open source agent and ML anomaly detection on every metric.

Best for

Teams that want per-second Tomcat and JVM visibility without assembling a stack
SREs who want ML anomaly detection on every metric out of the box
Organizations that want an open source agent with no vendor lock-in

Pricing

Agents are open source (AGPL) and free; free Cloud tier covers small fleets up to 5 nodes
Cloud Business starts at $4.50/node/month on annual plans, with the per-node price decreasing as node count grows
Unlimited metrics, logs, users, and retention included; no per-GB ingest charges

Pros

Tomcat collector parses the Server Status endpoint at 1-second default resolution: JVM memory, memory pools, connector requests, bandwidth, processing time, errors, and thread utilization
Zero-configuration auto-detection when Netdata and Tomcat share a host; multi-instance and remote Tomcat supported via configurable jobs
ML anomaly detection runs on every collected metric, so thread pool and heap anomalies surface without hand-tuned thresholds
800+ integrations cover the rest of the stack around Tomcat, plus AI-assisted root cause analysis
Verified results include 80% MTTR reduction, 90% cost reduction, and 99% false-positive reduction

Where teams pair it

The collector reads the Server Status HTTP endpoint rather than JMX directly, so the full MBean tree is out of reach: JDBC connection pools, servlet-level metrics, string cache, and web cache are not collected. Teams that need JDBC pool visibility pair it with a JMX-based collector.
No Tomcat-specific alert templates ship enabled by default for this integration; teams create their own alerts for thread pool and heap thresholds.
The Server Status endpoint requires read-only credentials before collection starts, and auto-detection only applies when Netdata and Tomcat are co-located.

Verdict

Netdata leads this list because it is the only tool here that combines per-second resolution, zero-config Tomcat detection, and ML anomaly detection at an open source price point. The collector covers the operational metrics that break Tomcat in production: connector requests, processing time, errors, bandwidth, threads, and JVM memory pools, all at one-second granularity. The honest caveat is depth: reading the Server Status endpoint instead of JMX means no JDBC pool, servlet, or cache metrics, and there are no pre-built Tomcat alert templates. If your Tomcat failure modes live in JDBC pool exhaustion, pair Netdata with a JMX-based collector. For everything else, it is the fastest path from install to useful Tomcat visibility on this list.

Start free -> Tomcat collector docs ->

Vendor 02 / 10 · #prometheus-grafana

Prometheus + Grafana

The open source standard: jmx_exporter exposes the full Tomcat MBean tree to Prometheus, and Grafana visualizes it.

Best for

Teams already standardized on Prometheus and Grafana
Organizations that want full control over their monitoring stack and data
Platform teams that can invest in assembling exporters, dashboards, and alert rules

Pricing

Open source and self-hosted: you run and operate Prometheus, Grafana, and jmx_exporter yourself
Grafana Cloud SaaS is usage-based: per active series for metrics, per GB for logs and traces, with a free tier capped by usage
Cost grows with active series count, log volume, and retention; self-hosting means you own HA, storage, upgrades, and backup

Pros

jmx_exporter is the de facto standard for exposing Tomcat JMX MBeans and is actively maintained, with v1.5.0 released in October 2025
Deepest metric coverage on this list: thread pools, connectors, sessions, JSP, and servlets via the full MBean tree
Grafana Cloud ships an official Apache Tomcat integration with out-of-the-box dashboards for JVM CPU, heap, GC, classes, and threads
Huge community ecosystem of dashboards and alert rules, with a vendor-neutral OpenTelemetry instrumentation path

Cons

Build-your-own stack: you assemble jmx_exporter configuration, Prometheus scrape configs, Grafana dashboards, and alert rules
jmx_exporter runs inside the JVM and consumes Java heap; its memory overhead is a known community complaint
Default scrape intervals of 15 to 60 seconds are far coarser than per-second collection, so transient thread pool spikes can slip between scrapes

Verdict

This is the most flexible open source path for Tomcat monitoring and the deepest on raw JMX coverage. If your team already runs Prometheus, adding jmx_exporter to Tomcat is the obvious move, and the Grafana Cloud Tomcat integration removes much of the dashboard work. The tradeoffs are real: the exporter eats heap inside the JVM you are trying to watch, scrape intervals are minute-scale by default, and you own the operation of the whole stack. Rank it second for depth and ecosystem, not for speed to value.

Read full Netdata vs Prometheus -> Grafana Cloud pricing ->

Vendor 03 / 10 · #datadog

Datadog

Commercial observability platform with a JMX-based Tomcat check covering 30+ Tomcat and JVM metrics.

Best for

Organizations already on Datadog that want Tomcat metrics alongside the rest of their stack
Teams that need deep JMX coverage including JDBC pools, servlets, string cache, and web cache
Enterprises that want one platform for metrics, logs, traces, and APM

Pricing

Per-host pricing for infrastructure monitoring plus usage-based charges for logs, APM spans, and custom metrics
The bill grows with host count, log ingest and index volume, span volume, and custom metric cardinality
A small free tier capped by host count exists, with limited retention

Pros

JMX-based check collects 30+ Tomcat metrics: error count, JDBC connection pool stats, JSP count, request count, processing time, servlet stats, string cache, thread pool, and web cache
Collects both Catalina and Tomcat bean domains from Agent 7.49 onward, covering standalone and embedded (Spring Boot) Tomcat
Pre-built Tomcat dashboards and monitors, plus log collection from Tomcat logs with source tagging
Single platform if you also need APM, tracing, and log management

Cons

Requires enabling JMX Remote on Tomcat and editing YAML; it is not zero-config
Per-host plus usage-based pricing makes the bill grow unpredictably with log and span volume
Agents older than 7.49 only collect the Catalina bean domain, missing embedded Tomcat metrics
Default JMX collection interval is around 15 seconds, not per-second

Verdict

Datadog has the deepest commercial Tomcat coverage on this list: JDBC pools, servlets, and caches that most platforms never touch. For shops already paying for Datadog, enabling the Tomcat check is the obvious choice. The costs are setup friction (JMX Remote plus YAML) and a bill that scales with hosts and usage in ways that are hard to forecast. Teams burned by a Datadog invoice should model log and span volume before committing.

Read full Netdata vs Datadog -> Datadog pricing ->

Vendor 04 / 10 · #dynatrace

Dynatrace

AI-powered platform that auto-discovers Tomcat applications and adds code-level tracing and JMX metrics.

Best for

Enterprises that want automatic Tomcat discovery and end-to-end tracing without manual instrumentation
Teams that need continuous profiling, method hotspots, and thread analysis in production
Organizations that want AI-driven root cause analysis across the full stack

Pricing

Per-host pricing based on memory (billed per GiB-hour) plus usage charges for logs, traces, events, metric datapoints, and RUM sessions
The bill grows with host memory, ingest and retention volume, datapoints, and session count
No free tier; evaluation happens through a trial or a public sandbox with sample data

Pros

OneAgent automatically detects Tomcat applications and microservices with no manual JMX configuration
Built-in JMX monitoring for Tomcat connection and thread pools plus web request activity
Java Servlet 5.0 tracing provides end-to-end transaction visibility through Tomcat
Continuous profiling with method hotspots, memory profiling, and thread analysis; OpenTelemetry and Micrometer support for custom telemetry

Cons

Pricing is complex: memory-based host billing plus per-GiB and per-datapoint charges make cost forecasting difficult
Full-stack capabilities are overkill for teams that only need Tomcat metrics
Heavier agent footprint than lightweight collectors, and no free tier for ongoing small deployments

Verdict

Dynatrace is the strongest enterprise option here: automatic discovery removes the JMX configuration burden entirely, and servlet tracing plus continuous profiling go far beyond metrics. The collection interval is not published, which is worth asking about in a proof of concept. The ranking reflects fit for this topic, not quality: if you need full-stack observability and can justify the spend, Dynatrace may be your number one. If you need Tomcat metrics, it is more platform than the problem requires.

Read full Netdata vs Dynatrace -> Dynatrace pricing ->

Vendor 05 / 10 · #newrelic

New Relic

Usage-based observability whose Java agent auto-instruments Tomcat for JVM metrics, traces, and errors.

Best for

Teams that want Java agent auto-instrumentation with no JMX configuration
Organizations that prefer usage-based pricing over per-host licensing
Developers who want JVM visibility (heap, GC, threads) alongside APM traces

Pricing

Usage-based: data ingest per GB plus per-user pricing for platform access tiers; unlimited hosts and agents included
The bill grows with data ingest volume and paid user count
A free tier with a monthly ingest allowance and one full platform user is available

Pros

Tomcat quickstart auto-instruments Tomcat through the New Relic Java agent with a javaagent flag
Solid JVM metrics: heap usage, garbage collection times, thread counts, and loaded classes
APM traces and error tracking for applications deployed on Tomcat come with the same agent
Unlimited hosts and agents included, so Tomcat fleet size does not directly drive the bill

Cons

No dedicated Tomcat JMX MBean collection: connectors, sessions, and JDBC pools are thinner than JMX-based tools provide
Usage-based ingest pricing can grow quickly with high-traffic Tomcat fleets
Requires adding the Java agent to every Tomcat JVM, which means a restart and JVM flag change per instance

Verdict

New Relic is the easiest path to JVM-level Tomcat visibility: add the agent, restart, and you get heap, GC, threads, traces, and errors. What you do not get is the Tomcat container itself. Connector processing time, session counts, and JDBC pool state are not the Java agent’s focus, so teams debugging connector-level saturation will find gaps. A good fit for developer-led teams that think in transactions, less so for ops teams that think in thread pools.

Read full Netdata vs New Relic -> New Relic pricing ->

Vendor 06 / 10 · #zabbix

Zabbix

Open source, self-hosted monitoring with an official Apache Tomcat by JMX template and low-level discovery.

Best for

Organizations already running Zabbix that want Tomcat added to their monitoring
Teams that prefer self-hosted open source with no per-node fees
Enterprises that need JMX-based Tomcat monitoring with low-level discovery

Pricing

Open source and self-hosted: you run and operate the Zabbix server, database, web frontend, and Java gateway
Commercial support and professional services are available from Zabbix
Cost is operational: the infrastructure and effort to run and maintain the platform

Pros

Official Apache Tomcat by JMX template with low-level discovery for request processors, thread pools, contexts, and protocol handlers
Built-in triggers include a busy worker thread alert at a default 75% threshold, version change detection, and gzip compression checks
JMX agent items require no external scripts; template versions exist for Zabbix 5.0 through 7.4

Cons

Requires running the Zabbix Java gateway and configuring JMX access on each Tomcat instance
The template is tested on Tomcat 8.5.59; newer Tomcat versions may need adjustments
Default JMX polling is around one minute, and JVM memory and GC require the separate Java JMX template rather than the Tomcat one

Verdict

For existing Zabbix shops, the official Tomcat template is genuinely good: low-level discovery finds your request processors and thread pools automatically, and the busy-thread trigger ships ready to use. The gaps are resolution and completeness. Minute-level polling smooths away exactly the transient spikes that matter, and JVM memory lives in a different template, so a full picture means running both. A solid sixth for Zabbix-centric organizations; a hard sell as a greenfield Tomcat monitoring choice.

Read full Netdata vs Zabbix -> Zabbix pricing ->

Vendor 07 / 10 · #manageengine

ManageEngine Applications Manager

Application performance monitoring with purpose-built Tomcat support, including automated thread and heap dump actions.

Best for

IT operations teams that want Tomcat monitoring with automated diagnostic actions
Organizations that want APM Insight transaction tracing alongside server monitoring
Teams that prefer self-hosted commercial software with per-monitor licensing

Pricing

Licensed per monitor (each application instance, server, service, or URL) plus per-user fees
Annual subscription or perpetual licensing models
A free edition covers a small number of apps or servers; the bill grows with monitor count and users

Pros

Purpose-built Tomcat monitoring: JVM memory, JDBC connection pools, thread pools, web application sessions, and response time
Automated operational actions: trigger garbage collection, capture heap dumps, and schedule thread dumps to identify blocking code
APM Insight captures web transactions with element breakdown and SQL statement analysis
Memory leak detection and performance forecasting using machine learning

Cons

Polling interval is not published on the product page, so real-time behavior needs validation in a trial
Per-monitor licensing grows expensive as Tomcat instances and applications multiply
The UI and workflow orientation is IT operations rather than developer-centric

Verdict

Applications Manager does something almost nothing else on this list does: it acts on Tomcat, not just observes it. Scheduled thread dumps and on-demand heap dumps are exactly what you want at 2 a.m. when a thread pool wedges. The metric coverage is strong, including JDBC pools and sessions. It lands seventh because the unpublished polling interval, per-monitor cost curve, and IT-ops-centric interface narrow its audience, but for teams that want Tomcat-specific operational workflows, it deserves a serious trial.

Read full Netdata vs ManageEngine -> ManageEngine pricing ->

Vendor 08 / 10 · #sematext

Sematext

Full-stack observability with auto-discovery of Tomcat instances and their logs, plus JVM metrics in the Tomcat integration.

Best for

Teams that want automatic Tomcat instance and log discovery
Organizations that want metrics, logs, and OpenTelemetry-native tracing in one platform
Small to mid-size teams that want simple per-host pricing on the metrics side

Pricing

Per-host pricing for infrastructure monitoring plus per-GB charges for logs and per-agent pricing for service monitoring
The bill grows with host count, log volume and retention, and monitored services
A free plan per app and a trial period are available

Pros

Automated discovery of Tomcat instances and their logs; new instances are monitored without manual configuration
JVM metrics included in the Tomcat integration
Full-stack coverage: metrics, logs, real user monitoring, and OpenTelemetry-native distributed tracing
Deployable on bare metal, VMs, Docker, and Kubernetes

Cons

Tomcat-specific metric depth is thinner than JMX-based collectors; no JDBC pool or servlet-level metrics are documented
Log volume charges add a separate per-GB cost dimension on top of host pricing
No full-featured profilers, and a smaller community ecosystem than Datadog or Prometheus

Verdict

Sematext is a competent turnkey option: auto-discovery means new Tomcat instances show up monitored without anyone touching a config file, and having logs and traces in the same platform shortens investigations. The Tomcat metric depth is the limitation. JVM metrics are there, but the container-level detail that JMX-based tools expose is not documented. Reasonable for teams that value consolidated telemetry over Tomcat depth.

Visit Sematext -> Sematext pricing ->

Vendor 09 / 10 · #site24x7

Site24x7

SaaS monitoring that covers Tomcat via a Java agent or plugin, with JVM heap, GC, and thread visibility.

Best for

Teams already using Site24x7 for website and infrastructure monitoring
Organizations that want SaaS Tomcat monitoring without running a server
IT ops teams that want alerts on Tomcat thread pool exhaustion

Pricing

Per-monitor licensing across three monitor types: basic, host, and advanced
Plans include fixed allotments of each type, with add-ons to expand capacity
The bill grows with monitor count, synthetic runs, RUM page views, and log volume; no free tier, with a trial period

Pros

Tomcat monitoring via Java agent or plugin with JVM heap memory, garbage collection frequency, and thread details
Thread pool exhaustion alerts when active threads approach the configured maximum
Strong educational documentation on Tomcat JMX MBeans, from GlobalRequestProcessor to DataSource
Part of a broader SaaS platform covering websites, servers, databases, and applications

Cons

No documented JMX MBean collection for connectors or JDBC pools; depth depends on what the Java agent exposes
Per-monitor licensing means every additional Tomcat instance and monitor type grows the bill
SaaS-only deployment rules out air-gapped or on-premises-only environments

Verdict

Site24x7 makes sense when it is already in the building. The Java agent gives you JVM heap, GC, and thread visibility, and the thread pool exhaustion alert targets a real Tomcat failure mode. What it lacks is documented connector and JDBC pool depth, and the per-monitor licensing model punishes fleet growth. For Site24x7 customers it is a natural extension; as a dedicated Tomcat monitoring choice it trails the field on depth.

Read full Netdata vs Site24x7 -> Site24x7 pricing ->

Vendor 10 / 10 · #solarwinds

SolarWinds Server & Application Monitor

Enterprise server and application monitoring that tracks Tomcat through JMX and access logs.

Best for

Enterprises already standardized on the SolarWinds Orion Platform
IT ops teams monitoring Tomcat alongside SQL Server, Exchange, and Active Directory
Organizations that want out-of-the-box dashboards and automated report delivery

Pricing

Licensed per node or per component, in transition from perpetual to subscription licensing
The bill grows with the number of monitored nodes or components
No published self-serve price list; purchasing requires sales engagement

Pros

Monitors Tomcat through JMX and access logs: memory usage, garbage collection, thread usage, and response time
Specific metrics include free/total/max memory, total processing time, request count, bytes sent and received, and error count
Out-of-the-box dashboards with automatic discovery of server-to-application relationships
Custom thresholds, baselines, and SQL-based custom reports

Cons

Licensing is complex and mid-transition from perpetual to subscription
No self-serve pricing; every evaluation goes through sales
No documented JDBC pool or servlet-level metrics, and the platform is built for enterprise IT ops rather than developer workflows

Verdict

SolarWinds SAM covers the Tomcat basics competently: memory, GC, threads, requests, and errors via JMX and access logs, wrapped in the Orion Platform’s dashboards and reporting. It ranks last for this topic because the Tomcat-specific depth stops short of JDBC pools and servlets, the licensing model is in flux, and there is no way to price it without a sales call. If your organization already runs Orion, use it. If you are choosing fresh, every tool above it gets you to Tomcat visibility faster.

Read full Netdata vs SolarWinds -> SolarWinds pricing ->

Frequently Asked Questions

How do I monitor Apache Tomcat?

You monitor Apache Tomcat through JMX, the Server Status HTTP endpoint, or a Java agent. JMX gives the deepest access to Tomcat’s MBean tree but requires enabling JMX Remote or using the JMXProxyServlet. The built-in Server Status HTTP endpoint is simpler and avoids opening JMX Remote, though it needs a user with a manager-jmx or manager-status role. Agent-based collection uses Java agents or platform agents. Tools differ in which approach they take: Netdata parses the Server Status endpoint, Datadog and Zabbix use JMX, and New Relic uses a Java agent.

What Tomcat metrics should I monitor?

Start with JVM heap memory (used versus max) and garbage collection count and time. Watch the thread pool: currentThreadsBusy against maxThreads, alerting when busy threads reach 75 to 80 percent of max. Track connector metrics (request count, processing time, error count, bytes sent and received), session metrics (activeSessions, maxActive, rejectedSessions), and the JDBC connection pool (numActive, numIdle, maxActive). Those five groups cover the failure modes that actually take Tomcat down.

What is the best way to collect Tomcat metrics?

JMX is the richest source: it exposes the full MBean tree including GlobalRequestProcessor, ThreadPool, Manager, DataSource, Memory, and GarbageCollector. The Server Status endpoint (manager/status?XML=true) is simpler and avoids opening JMX Remote, but exposes fewer metrics. Java agents such as New Relic’s and Site24x7’s instrument the JVM directly and add tracing, but may not expose Tomcat-container MBeans. For Prometheus shops, jmx_exporter bridges JMX to Prometheus and is the standard open source path.

How do I monitor Tomcat thread pool exhaustion?

Watch currentThreadsBusy against maxThreads on the Catalina ThreadPool MBean. When busy threads hit max, requests queue and response times spike, so alert at 75 to 80 percent of max rather than at saturation. Zabbix ships a built-in trigger for this, Site24x7 offers thread pool exhaustion alerts, and Netdata collects connector request threads (idle and busy) at per-second resolution. When exhaustion hits, a thread dump taken at that moment is the fastest way to identify the blocking code.

Is JMX required for Tomcat monitoring?

No. Tomcat’s Server Status HTTP endpoint exposes a useful subset of metrics without opening JMX Remote, which matters because JMX Remote has security implications if exposed to the network. JMX is required for the deepest visibility: JDBC pools, servlet-level stats, string cache, web cache, and per-connector thread pools. If you do use JMX, prefer the JMXProxyServlet or firewall the JMX ports. Netdata uses the Server Status endpoint; Datadog, Zabbix, and jmx_exporter use JMX.

How do I monitor Tomcat in Docker or Kubernetes?

Agent-based tools such as Netdata, Datadog, Dynatrace, and New Relic can monitor Tomcat containers from the host or as a sidecar. jmx_exporter can run as a Java agent inside the Tomcat container and be scraped by Prometheus, which is what Grafana Cloud’s Tomcat integration expects. The OpenTelemetry Java agent is the vendor-neutral path for metrics, traces, and logs from Tomcat running in Kubernetes.

How often should I collect Tomcat metrics?

Per-second collection catches transient thread pool spikes and heap pressure that 15 to 60 second polling misses. Typical JMX polling is 15 to 60 seconds, which covers Datadog, Zabbix, and default Prometheus scrape intervals. The right interval depends on how fast your failure modes develop: thread pool exhaustion can happen in seconds under a traffic spike. Faster collection increases storage and cost, especially on usage-based pricing, so weigh resolution against the bill.

Can I monitor Tomcat for free?

Yes. Netdata’s agent is open source with a free Cloud tier for small fleets, and Prometheus plus Grafana plus jmx_exporter and Zabbix are open source and self-hosted. Open source means you run and operate the monitoring platform yourself, and that operating cost is real. Commercial free tiers exist from Datadog, New Relic, and ManageEngine with caps on hosts, ingest, or apps. Tomcat Manager and JConsole are built-in tools included with Tomcat and the JDK, but they lack history, alerting, and multi-host correlation.

What is the difference between Tomcat Manager and a monitoring tool?

Tomcat Manager is a built-in admin web app for deploying, starting, stopping, and inspecting applications. Its status page shows current metrics but no history, so you cannot see trends or investigate past incidents. Tomcat Manager also includes a JMXProxyServlet that can query MBean values on demand. A monitoring tool adds the capabilities Tomcat Manager lacks: historical data, alerting, anomaly detection, multi-host correlation, and dashboards. Use Tomcat Manager for ad-hoc inspection; use a monitoring tool for ongoing visibility.

The 10 best Apache Tomcat monitoring tools, ranked

How we evaluated Tomcat monitoring tools

Netdata

Prometheus + Grafana

Datadog

Dynatrace

New Relic

Zabbix

ManageEngine Applications Manager

Sematext

Site24x7

SolarWinds Server & Application Monitor

Frequently Asked Questions

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