Published by FetchNode · Capability sources reviewed 7 November 2026 · Worksheet updated 2026-11-07

The best APM for Django depends on the job

There is no single best APM for Django. A Django APM should show where a request spent its time. Pick the tool that answers that question, or a narrower one, before you compare feature lists.

Compare the tools Check what you need first

Editorial disclosure: FetchNode publishes this comparison and is included in it. We do not accept placement fees or assign a paid ranking. Capabilities below are summarized from the official sources linked on this page, reviewed 7 November 2026. Plans change. This page does not quote prices or benchmarks. Verify current details with each vendor.

Short answer

What is the best APM for Django?

The best APM for Django depends on the production bottleneck you need to see:

  • Slow views, ORM queries, and N+1 detection: Scout APM or AppSignal.
  • Grouped errors first, with tracing available: Sentry. A lighter developer suite: Honeybadger.
  • Django inside a wider tracing platform: Datadog or New Relic.
  • You already run Elasticsearch and Kibana: Elastic APM.
  • You want to operate the pipeline: OpenTelemetry for traces, or Prometheus + Grafana for metrics.
  • Several Django websites, and the question is which one needs you: FetchNode, which puts errors, traffic analytics and imported Search Console data in one dashboard.

Django APM tools and Django performance monitoring tools are not one shelf. An APM answers where the request spent its time. An error tracker answers what failed. A metrics stack answers which number changed. For the broader production question, start with the Django monitoring overview. For one choice in more detail, read the Sentry alternative for Django, Django error monitoring, or the stuck Celery task checks. For replacing Sentry and Google Analytics together, read the Sentry and Google Analytics comparison for Django.

At-a-glance APM feature comparison

Django APM tools, by the job they do

Use this to shortlist. Each mark repeats a fact already stated on this page. It is not a score. A vendor may sell an adjacent product, so confirm the current plan before you treat a cell as a hard limit.

  • Yes Documented for this job
  • Part Documented, with the limit in the cell
  • No This page says it is not the job
  • — Not stated on this page
Marks follow the sources linked on this page. A blank job was not stated, which is not the same as unsupported.
Tool Errors Performance / traces Traffic analytics Search data Celery / jobs Self-hosted
FetchNodeWhich website needs attention ErrorsYesGrouped exceptions Performance / tracesPartRequest timing; no distributed tracing Traffic analyticsYesAfter consent Search dataYesImported Search Console data Celery / jobsYesJobs and releases Self-hostedNoHosted
SentryErrors, tracing when enabled ErrorsYesCore Django SDK job Performance / tracesYesTracing and profiling when enabled Traffic analyticsNoNot the Django SDK’s job Search dataNoNot included Celery / jobs—Not stated Self-hosted—Not stated
DatadogDistributed traces ErrorsPartPart of the wider platform Performance / tracesYesDistributed traces Traffic analyticsPartReal-user monitoring is separate Search dataNoNot included Celery / jobs—Not stated Self-hosted—Not stated
New RelicPython transaction traces ErrorsPartReported with APM traces Performance / tracesYesTransaction traces Traffic analyticsPartBrowser monitoring is separate Search dataNoNot included Celery / jobs—Not stated Self-hosted—Not stated
Scout APMSlow views and N+1 queries ErrorsYesWith traces and logs Performance / tracesYesTraces and N+1 detection Traffic analyticsNoNot this product’s job Search dataNoNot included Celery / jobsYesCelery and other queues Self-hosted—Not stated
AppSignalErrors and view performance ErrorsYesDocumented Performance / tracesYesView performance Traffic analyticsNoNot this product’s job Search dataNoNot included Celery / jobs—Not stated Self-hosted—Not stated
Elastic APMErrors and transactions in Elastic ErrorsYesDocumented for Django Performance / tracesYesTransactions Traffic analyticsNoNot this product’s job Search dataNoNot included Celery / jobs—Not stated Self-hostedPartAPM server you run, or Elastic Cloud
HoneybadgerErrors, lighter APM, uptime ErrorsYesCore Performance / tracesPartLighter APM Traffic analyticsNoNot this product’s job Search dataNoNot included Celery / jobsPartCron and heartbeat checks Self-hosted—Not stated
OpenTelemetryPortable request traces ErrorsPartSpans, not grouped errors Performance / tracesYesRequest traces Traffic analyticsNoNot included Search dataNoNot included Celery / jobs—Not stated Self-hostedPartYou operate the pipeline
Prometheus + GrafanaMetrics and dashboards you control ErrorsNoCounts, not tracebacks Performance / tracesPartMetrics, not traces Traffic analyticsPartOnly if you emit custom events Search dataNoNot included Celery / jobs—Not stated Self-hostedPartDashboards you control

Traces / N+1 depth is the reason to shortlist Scout or AppSignal. Portfolio multi-site priority, consented traffic, and Search Console import are the reason to shortlist FetchNode. Neither column is a score.

When FetchNode fits

Choose FetchNode for the portfolio question, not for deep APM

FetchNode fits an independent Django developer, freelancer, or small agency looking after several production websites. The job is to see which website needs attention, then open the error, request, job, or release evidence behind it.

That view puts errors, traffic analytics and imported Search Console data in one dashboard. Search Console remains the source of those rows. Traffic analytics run after the site grants consent. Keep Scout, AppSignal, Sentry, Datadog, New Relic, or Elastic when you need distributed tracing, host metrics, profiling, or long-term log search.

See how a multi-website review works, the current plans and limits, or the live demo.

Errors, traffic analytics and your Search Console data in one dashboard

FetchNode puts your Django errors, traffic analytics and imported Search Console data in one dashboard, so you see which site needs you first.

  1. Errors

    Sentry-style grouping

    Traceback, route, and release

  2. Traffic analytics

    GA-style, after consent

    Pageviews, sessions, and sources

  3. Imported Search Console data

    Your Google search rows

    Not a replacement for Search Console

FetchNode dashboard

One website view

  • Open exceptionGrouped
  • SessionsAfter consent
  • Search queryImported
Everyday check What FetchNode does What it does not do
Sentry-style error tracking Groups Django exceptions and browser errors with the traceback, route, release, and affected users. Session replay, distributed tracing, profiling, source maps, or a drop-in Sentry SDK. It is not a drop-in replacement for Sentry.
Traffic analytics After analytics consent: pageviews, sessions, sources, and configured conversions, next to the errors on the same site. Advertising reports, audiences, or the rest of the Google Analytics catalog.
Your Search Console data Imports clicks, impressions, CTR, position, queries, and landing pages into the dashboard. Search Console remains the source. The import is aggregated and delayed, and a query is not a named visitor.

Read the boundaries in Django error monitoring, Django analytics, and Search Console for Django. Repeated-query observations are a lead, not a Scout-style N+1 diagnosis: use the N+1 guide when query count is the question.

What each option is good at

Django performance monitoring tools, in plain language

Each note follows that vendor’s public Django or Python documentation as reviewed on 7 November 2026. It is a fit description, not a benchmark.

PUBLISHED BY FETCHNODE

FetchNode: the website priority, plus the three everyday checks

Use FetchNode when the first question is which Django website needs a person today. Errors, request timing, repeated-query observations, jobs, releases, and uptime sit beside consented traffic, configured conversions, and imported Search Console metrics.

Look elsewhere first for distributed tracing, host metrics, profiling, session replay, or long-term log search. Agent access is also available from specialist tools. Sentry publishes its own MCP server.

ERRORS AND TRACING

Sentry: Django errors, with tracing and profiling when you enable them

Sentry’s Django docs describe error monitoring as the core product and show how to turn on tracing, profiling, logs, and application metrics. The SDK can monitor middleware, signals, database queries, Redis commands, and cache access. Sampling is a production decision; the setup example is not a recommendation to trace every request.

Choose Sentry when many languages or a deep issue workflow matter more than a small Django portfolio view. Review what the SDK collects before you enable user data.

Official Sentry Django documentation

PLATFORM TRACING

Datadog: Django as one service in a tracing platform

Datadog’s Python tracer documents Django as a supported integration for distributed tracing. Which Django framework spans are on by default depends on the tracer version, so read the current migration notes before you rely on ORM, cache, or template spans.

It fits when Django is one of several services and you already use Datadog for infrastructure or logs. For a single Django site whose main question is customer impact, the platform is broader than that job.

Official Datadog Python tracing docs

PYTHON APM

New Relic: transaction traces for Django and other Python apps

New Relic’s Python agent documents Django among the frameworks it instruments, and describes traces that separate application time from database queries and external calls. Confirm the agent’s current Python version support before you install it.

It fits when Django already lives in a New Relic account that covers other services. Browser monitoring, if you need it, is a separate New Relic product.

Official New Relic Python agent introduction

DJANGO PERFORMANCE

Scout APM: traces, N+1 queries, and background jobs

Scout’s Django page documents errors, logs, and code-level traces, automatic N+1 detection in the Django ORM, Celery and other task queues, and transaction-level memory bloat detection. It says the agent requires Python 3.8 or newer on Linux or macOS.

Shortlist Scout when the recurring question is which view, query, or worker is slow. Check that runtime requirement against your hosts.

Official Scout Django page

MANAGED APM

AppSignal: errors and view performance for Django

AppSignal’s Django page centers on error tracking, view performance, anomaly detection, and metric dashboards. Confirm host metrics, uptime, and logs against the current plan before you count on them.

It fits teams that want a managed APM rather than assembling traces and dashboards. It is not a Search Console or consent-based traffic product.

Official AppSignal Django page

ELASTIC STACK

Elastic APM: Django errors and performance in Elastic

Elastic’s Python agent documents Django support for error logging and performance metrics, and sends them to an APM server you run or to Elastic Cloud. The same docs say Django running in ASGI mode is not currently supported. Check the supported Django and Python versions for the agent you install.

Choose it when the rest of the estate already lands in Elasticsearch and Kibana. It is not the open-source metrics path; that is OpenTelemetry or Prometheus.

Official Elastic APM Django support

DEVELOPER SUITE

Honeybadger: errors, logs, lighter APM, and uptime

Honeybadger’s Django page describes error tracking, logging, a lighter APM, uptime checks, cron or heartbeat monitoring, and status pages. It also says that APM layer can sit beside New Relic or Datadog.

Evaluate it when you want those incident tools from one developer-focused vendor. Verify the depth of each module rather than treating every combined suite as the same product.

Official Honeybadger Django page

OPEN SOURCE

OpenTelemetry, Prometheus + Grafana, and open-source error trackers

OpenTelemetry’s Django instrumentation (Apache-2.0) creates spans for requests. You still choose an exporter and a backend such as Jaeger or Grafana Tempo. Prometheus collects time-series metrics and evaluates alert rules; Grafana draws the dashboards. Teams often export Django metrics with a library such as django-prometheus. That stack does not by itself create a grouped traceback workflow.

For open-source error tracking rather than APM, compare GlitchTip and Bugsink. Both are Sentry-compatible error trackers. They are not request-level APM.

OpenTelemetry Django instrumentation Prometheus overview Grafana Django dashboard

Evaluate your shortlist on the same Django website

Choose one problem you recently investigated. Give each shortlisted tool the same staging scenario, then record what you could prove and what remained unclear. Use a separate test project so the exercise does not become customer telemetry.

  1. 1. Reproduce one known exception

    Can you find the correct stack frame, distinguish repeated occurrences, and connect the failure to a release? Record missing context rather than counting dashboard widgets.

  2. 2. Investigate one slow request

    Can you distinguish time in Django code from database or external-service time? List the evidence you need for the next fix and check whether the tool actually supplies it.

  3. 3. Repeat with a second website

    Can you tell which website needs attention and explain why? Record the setup steps you had to repeat and any context lost when switching projects.

  4. 4. Inspect capture and limits

    Review the actual captured fields, retention, alert behavior, and current plan limits. Measure request cost in your own environment before making an overhead claim.

For a repeatable test sequence, use the production monitoring checklist. The setup guide shows the manual path if you try FetchNode.

Use a vendor-neutral monitoring evaluation worksheet

Select and copy the blank notes below for each shortlisted tool. No signup or submission. Not tested is not the same as unsupported. Record the plan and date rather than turning an untested feature into a yes/no score.

This is an evaluation template, not a published benchmark or a claim that FetchNode wins every test. Keep staging measurements separate from customer production evidence. For a background-job scenario, start with the Celery diagnostic worksheet.

Start monitoring your first Django website

Review exceptions, slow routes, uptime, and measured conversions across your Django websites. Inspect the generated setup changes before deploying them.

No credit card required · Inspectable, guided setup · Explore interactive demo without signup →

A useful stack can have two tools

Combine distinct jobs, not duplicate alerts

You do not have to force one platform to answer every question. A small team might use FetchNode for the website priority, consented traffic, and Search Console import, and still open Sentry or Scout when a trace is the missing evidence. Another team might keep Prometheus and Grafana for host metrics.

Write down one owner and one response rule for each signal. If two products page the same person for the same failure, consolidate the alert even when you keep both data sources.

Turn the choice into a 12-point monitoring checklist

Smaller hosts

Lightweight APM options for Django, FastAPI and Python apps

Datadog, Dynatrace, and New Relic are built to trace many services, usually with a language agent and a host collector. A Django, FastAPI, or other Python app on Dokku, Heroku, Fly.io, Hetzner, or a VPS often needs a narrower job: query counts, slow requests, background jobs, and user-facing errors. The three options below are the lighter shortlist. What each one covers is already in the cards above. This page does not publish CPU or memory benchmarks — measure overhead on a staging copy of your own app.

FetchNode

In-process Django package

The Python package runs inside the Django process. There is no separate host agent to install. Use it for a portfolio of Django sites. It is not a FastAPI or multi-language tracer.

Scout APM

Request and query traces

Shortlist Scout when the question is which view, query, or worker is slow, including N+1 detection. Check the Python and OS requirements on Scout’s Django page against the host you run.

AppSignal

Managed app monitoring

Shortlist AppSignal when you want managed errors and view performance without operating a trace backend. Confirm the current agent install on AppSignal’s Django page.

Django APM FAQ

Questions before you install another agent

What is the best APM for Django?

There is no single best APM for Django. Choose Scout APM or AppSignal when the main job is request and query performance, including N+1 queries. Choose Sentry or Honeybadger when grouped errors come first and performance is a supporting feature. Choose Datadog or New Relic when Django is one service in a wider tracing platform. Choose Elastic APM when you already run the Elastic Stack. Choose OpenTelemetry or Prometheus with Grafana when you want to operate the pipeline yourself. Choose FetchNode when you maintain several Django websites and want errors, consented traffic, and imported Search Console data in one view.

What is a Django APM?

A Django APM records where a request spent its time: the view, database queries, templates, cache, and outbound calls. Django APM tools and Django performance monitoring tools overlap with error trackers, but the APM label does not mean a product also covers uptime, consented traffic, conversions, or Search Console.

Which Django performance monitoring tools should I compare?

Compare Sentry, Datadog, New Relic, Scout APM, AppSignal, Elastic APM, Honeybadger, OpenTelemetry, Prometheus with Grafana, and FetchNode against one production question. Check Django and Python support, what the agent captures by default, retention, and current pricing on each vendor site. This page does not publish prices or benchmarks.

What are the open-source Django APM options?

OpenTelemetry publishes Django instrumentation that creates request spans, and you choose the backend. Prometheus with Grafana is the usual open metrics path, often fed by a Django exporter such as django-prometheus, and it does not replace grouped exception tracking. GlitchTip and Bugsink are open-source, Sentry-compatible error trackers, not full APM products. Elastic APM is a separate choice: its Python agent documents Django support and sends data to an APM server you run or to Elastic Cloud.

Can FetchNode show errors, traffic analytics and Search Console data together?

FetchNode puts your Django errors, traffic analytics and imported Search Console data in one dashboard. It groups Django exceptions, and after analytics consent it records pageviews, sessions, sources and conversions. It imports your Google Search Console clicks, impressions, queries and landing pages. Search Console remains the source. Sentry remains the fit when you need session replay, distributed tracing or profiling.

Is Sentry enough for Django monitoring?

Sentry’s Django SDK documents error monitoring, tracing, profiling, logs, and application metrics. It can be enough when exception triage and request performance are the work. It is a weaker default when you also want consented traffic, conversions, and imported Search Console data in the same website view, or a priority across several Django sites.

Can I use two Django monitoring tools together?

Yes. FetchNode can sit beside Sentry, Scout, Datadog, New Relic, or a metrics stack. Give each tool one job and one alert owner so the same failure does not page you twice.

From evidence to action

Choose the workflow before choosing the tool.

For FetchNode, the workflow spans website priority, available customer context, an optional agent investigation and measured follow-up. Keep the specialist depth your system needs.

  1. 01

    Start with the evidence.

    Choose a website and inspect the available signals, their time window and any missing context.

  2. 02

    Give your agent a specific task.

    Your coding agent can retrieve project-scoped context through MCP and work in your repository.

  3. 03

    Review, deploy and measure.

    Review the proposed changes and checks. After deployment, use new measurements to assess the result.

See how your coding agent can help

A focused place to start

See whether one Django view covers the checks you repeat

Explore a populated project before installing anything, or connect one website on the free plan. Keep a specialist APM when the trace is the missing evidence.

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