Buyer’s Guide - October 2026

The 11 best API monitoring tools in 2027

Q: How often should API checks run?

Common intervals range from 30 seconds to 5 minutes for critical endpoints. On per-run pricing (Datadog, Checkly, New Relic overages), frequency directly multiplies cost; on per-node pricing (Netdata, from $4.5/node/month on annual plans) it does not. Also note that retries on failure count as extra runs on some platforms.

Q: What is the difference between API monitoring and API observability?

Monitoring answers ‘is it working right now’ with checks and alerts; observability answers ‘why is it slow or failing’ with metrics, logs and traces. Synthetic tools (Checkly, UptimeRobot) do monitoring; APM and observability platforms (Datadog, New Relic, SigNoz) do observability. Netdata covers both: endpoint checks plus per-second metrics, logs and OpenTelemetry traces on one agent.

Q: Do I need synthetic monitoring if I already have APM?

Yes, they answer different questions. APM sees what your instrumented services experience; synthetics catch failures users hit first, including DNS, CDN, certificate and routing problems outside your code. They are complementary, and a synthetic failure is best diagnosed with APM data. Platforms that combine both (Netdata, Datadog, New Relic) avoid stitching two tools together.

API monitoring splits into two jobs: probing endpoints from outside for uptime and correctness, and watching the latency and error rates of real API traffic from inside. This ranking grades 11 tools on check depth, latency visibility, alerting, cost shape and probe coverage, and flags where each one stops short.

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The 11 best API monitoring tools in 2027 product interface

Why this list exists

API monitoring sits at the intersection of two disciplines, and most roundups quietly mix them. The first is external synthetic checking: probing your endpoints from outside for uptime, response correctness and latency. The second is internal API observability: per-endpoint latency, error rates and traces from the traffic itself. A tool that is excellent at one can be useless at the other.

The mistake buyers make is picking from the wrong half. A pure uptime pinger confirms the port answered but misses the failure mode that actually hurts: an API returning HTTP 200 with a broken payload. Conversely, an enterprise APM suite is overkill when what you needed was a JSON assertion on a health endpoint every 30 seconds. Before you shortlist, decide which problem you are solving.

Three dimensions decide the outcome:

Check depth vs observability depth. Do you need response-body validation (JSONPath, schema, regex) and multi-step flows, or do you need to know why an endpoint is slow, the job of API performance monitoring tools, which pull metrics, logs and traces from the serving side? Few tools do both.
Pricing shape. Per-check-run models multiply with frequency, locations and retries, so checking faster literally costs more. Per-monitor, per-node and self-hosted models do not punish you for checking often.
Probe geography. Vendor-operated global locations distinguish regional failures from local ones. Self-hosted and agent-based checks only see from where you deploy them.

We do not quote competitor list prices on this page. Pricing pages change often, and a stale number is worse than none; each card links the vendor’s official pricing page and describes the shape of the bill instead. For a narrower view of the external-checking half alone, see our ranked list of the best synthetic monitoring tools.

The shortlist was assembled from practitioner discussion (r/devops and r/selfhosted threads on API uptime), existing comparison articles from Uptrace, Last9, SigNoz, Moesif and Thunderbit, and each vendor’s official documentation and pricing pages. Tools had to actively ship and either probe API endpoints externally or expose API traffic latency and errors internally; the strongest do both.

Check depth and latency/error visibility carry the most weight (20% each) because they define whether the tool catches real failures rather than silence. Cost predictability and alerting quality follow at 15% each, since a tool you cannot afford to run frequently, or one that alerts late, fails at the job. Global probe coverage, setup effort and broader observability context each contribute 10%.

Tester credit

Compiled by the Netdata team - Updated October 14, 2026

Sources verified

Scoring criteria

Endpoint check depth 20%
Response body, header and schema validation, multi-step flows, not just port checks
Latency and error-rate visibility 20%
Granularity of latency and error metrics for API traffic; per-second and RED-style score highest
Alerting and anomaly detection 15%
On-call routing, escalation, and catching degradation before hard failure
Cost predictability 15%
Per-run models scale with frequency and locations; per-node and self-hosted do not
Global probe coverage 10%
Multiple geographic vantage points to separate local from regional failure
Setup and maintenance effort 10%
Time to first check, config-as-code, operational burden
Broader observability context 10%
Correlating API failures with host metrics, logs and traces in one place

Vendor 01 / 11 · #netdata

Netdata

Per-second infrastructure monitoring with built-in protocol-level synthetic checks, ML anomaly detection, and metrics, logs and traces on the same agent.

Best for

Teams that want API endpoint checks unified with the infrastructure serving those APIs, so a failing check is root-caused in the same tool
Cost-sensitive teams that run many checks frequently and do not want per-check-run billing
Self-hosters and privacy-conscious teams who want telemetry to stay on their own nodes

Pricing

Per-node pricing: Netdata Cloud Business from $4.5/node/month on annual plans, with the per-node price decreasing as node count grows
Agents are open source under GPLv3+; you download, run and operate them yourself, on your own infrastructure
Community plan is free for personal, non-commercial use with up to 5 active connected nodes; businesses use the open-source Agent or Netdata Cloud Business (14-day trial)
Not billed: metrics volume, Logs Monitoring (querying logs in place), users, data retention, containers

Pros

Protocol-level synthetic checks for HTTP endpoints, ping, TCP ports, DNS queries and certificate expiry, with per-second precision
Per-second collection with unsupervised ML anomaly detection on the node, flagging latency and error-rate regressions before hard failure
One agent collects metrics, logs and OpenTelemetry traces (OTLP over gRPC and HTTP), stored and indexed on your own infrastructure
Digital Experience Monitoring, introduced October 2026, adds Real User Monitoring (live traffic globe, sessions, top pages, errors per page) and Browser Synthetic Checks running scripted journeys around the clock
Adding checks, dashboards, users or retention does not increase the per-node bill
Default multi-tier dbengine retains up to about 2 years of metrics on-node

Where teams pair it

Synthetic checks run from your own agents, not a vendor-operated global probe network; independent geographic vantage points mean deploying agents in multiple regions yourself
RUM and Browser Synthetic Checks are new (October 2026); vendors with years in browser synthetics offer more mature features such as session replay
API checks are protocol-level; scripted multi-step flows like Postman collections, k6 scripts or Playwright journeys are the dedicated synthetic tools’ strength

Verdict

Netdata is the only entry here that covers both halves of API monitoring in one product and one bill: external checks against your endpoints, and per-second visibility into the latency and error rates of the API traffic itself, with logs and OpenTelemetry traces for root cause on the same agent. Per-node pricing means check frequency and count never move the bill, which is exactly where per-run competitors get expensive. The honest caveats: probes run from your own agents rather than a managed global network, and scripted multi-step API test flows remain the dedicated synthetic tools’ territory. For teams that want checks and diagnosis in one place at a predictable price, it leads this list.

Try Netdata -> See synthetic checks ->

Vendor 02 / 11 · #checkly

Checkly

Playwright-first synthetic monitoring as code, purpose-built for API and browser checks with a developer-centric workflow.

Best for

Dev and QA teams that want monitoring defined as code in their repos and CI/CD
Teams needing both API checks and Playwright browser checks from one tool
Product teams monitoring critical user journeys, not just endpoints

Pricing

Usage-based: API checks and browser checks billed per check run; browser runs cost more than API runs
Uptime monitors (URL, TCP, DNS, ICMP, SSL, gRPC, heartbeat) billed by monitor count
Free hobby tier, then paid tiers; the bill grows with check frequency, locations and retries (retries count as runs)
Team collaboration and private locations sit on higher tiers

Pros

Monitoring-as-code SDK: checks live in version control and deploy through CI/CD
Playwright-native browser checks alongside API checks with latency broken down by phase
Alerting wired to incident tools (PagerDuty, Slack, Opsgenie) and status pages
Frequently cited by practitioners as the dedicated synthetic tool of choice

Cons

Per-run billing means frequent checks from many locations multiply the bill; flaky checks and retries add runs
No infrastructure metrics, logs or traces: when an API check fails you need another tool to find out why
No self-hosted option; checks run on Checkly’s cloud locations or paid private locations

Verdict

Checkly is the strongest dedicated synthetic tool on this list. The monitoring-as-code workflow fits how platform teams already work, and the API check validation is deep. It deliberately ignores the internal side, so root-causing a failed check requires a separate observability stack, and per-run pricing punishes high-frequency, multi-location checking. If external checking is the whole job, it is the first tool to trial.

Visit Checkly -> Checkly pricing ->

Vendor 03 / 11 · #datadog

Datadog

Enterprise observability platform whose Synthetics module runs API, multi-step and browser tests tied into APM, logs and metrics.

Best for

Enterprises that want synthetic API tests, APM, logs, RUM and infrastructure in one vendor
Teams with complex multi-step API workflows needing chained assertions
Organizations with budget for a premium platform and consolidated vendors

Pricing

Synthetic monitoring is billed per test run, with browser tests metered separately from API tests; annual-commitment and on-demand rates apply
The bill grows with check frequency, number of locations, retries and parallel testing slots
Infrastructure and APM are priced separately per host, so synthetics sit on top of a per-host bill
Custom metrics and other products are metered separately

Pros

API tests, multi-step API tests and browser tests with response assertions, from managed global locations
Synthetic failures link into APM traces and logs for root cause inside the same platform
Very broad integration catalog beyond API monitoring
Mature alerting, SLOs and dashboards

Cons

Per-test-run pricing climbs quickly with frequency and locations; the per-run trap is well documented by practitioners
Total platform cost is a common complaint across comparison articles and community threads
Many separately metered products make bills hard to predict

Verdict

Datadog offers the broadest combined coverage here: synthetic API checks wired into APM, logs and RUM, from managed global locations. The trade-off is cost shape. Per-run synthetics stacked on per-host infrastructure pricing makes frequent, multi-location API checking expensive, and the bill is hard to forecast. Enterprises consolidating vendors will accept that; lean teams checking endpoints every 30 seconds will feel it.

Read full Netdata vs Datadog -> Datadog pricing ->

Vendor 04 / 11 · #betterstack

Better Stack

Uptime and incident management platform with REST API monitoring, heartbeats, status pages and on-call, priced modularly.

Best for

Small and mid-size teams wanting uptime checks, status pages and incident management in one place
Teams replacing a separate on-call tool alongside API uptime monitoring
Startups that value a generous free tier for non-critical endpoints

Pricing

Freemium, modular model: uptime monitoring, logs, incident management and status pages priced independently
Monitors bought in blocks; on-call responder seats licensed per user while read-only members are free
Free tier with a small monitor count and longer check intervals; faster checks and phone/SMS alerts on paid tiers
The bill grows with monitor count and on-call responder seats

Pros

REST API monitors with response validation, plus heartbeats (cron monitoring) and status pages
Strong incident management: on-call scheduling, escalations and postmortems built in
Consistently praised for price/performance and a generous free tier in reviews
Log management and error tracking available in the same platform

Cons

Free-tier check intervals are measured in minutes rather than seconds; faster checks require a paid plan
No infrastructure metrics or traces: a failing API check does not show you why
Modular pricing stacks as you add logs, error tracking or more responders

Verdict

Better Stack pairs solid API uptime checks with genuinely good incident workflow, which is rare among the dedicated checkers on this list. It is a strong value pick for teams whose primary need is knowing fast and waking the right person. What it will not do is observe the API’s internals; latency-by-endpoint analysis of real traffic requires another tool alongside it.

Read full Netdata vs Better Stack -> Better Stack pricing ->

Vendor 05 / 11 · #grafana-synthetic-monitoring

Grafana Cloud Synthetic Monitoring (k6)

Grafana Cloud’s synthetic monitoring, powered by k6, runs scripted API and browser checks into Grafana dashboards and SLOs.

Best for

Teams already on Grafana who want API checks next to existing dashboards and SLOs
Engineering teams that want scripted checks (k6, multiHTTP) rather than simple pings
Organizations wanting open-source-aligned tooling with a managed option

Pricing

Usage-based within Grafana Cloud: checks billed by test executions per month plus the active series and data points they generate
k6 load testing billed by virtual user hours
Free tier includes a monthly allowance of checks and k6 usage; the bill grows with frequency, script complexity and locations
Grafana Cloud itself meters metrics, logs and traces by usage

Pros

k6-scripted checks: full JavaScript control over API test flows, plus multiHTTP and browser checks
Results land in Grafana with SLO tracking and alerting through the existing stack
Built-in pricing calculator shows expected executions per check before you commit
Backed by the k6 open-source project and large community

Cons

Composite pricing (executions, series, data points, log usage) is harder to predict than per-node models
Requires Grafana Cloud or self-managed Grafana plus Prometheus to be useful; not standalone
Setup is more involved than dedicated uptime tools; scripting checks takes developer effort

Verdict

For Grafana-centric teams, k6-powered synthetic monitoring is the natural choice: scripted API checks, SLO tracking and alerting without leaving the ecosystem. The composite usage pricing and the requirement to already run the Grafana stack hold it back for simpler needs. If your dashboards live elsewhere, the setup cost is hard to justify for endpoint checks alone.

Read full Netdata vs Grafana -> Grafana pricing ->

Vendor 06 / 11 · #newrelic

New Relic

Full-stack observability platform with synthetic API monitors in a usage-based model built around per-GB data ingest.

Best for

Teams wanting APM, synthetics, logs and infrastructure under one usage-based roof
Organizations with moderate ingest volumes that benefit from the free monthly allowance
Teams that value a flexible query language (NRQL) for latency and error analysis

Pricing

Per-GB ingest model with a free monthly data allowance; overage billed per GB
Synthetic checks included per edition up to a monthly allowance, with per-check charges beyond it; ping monitors included at no extra cost
User seats billed separately (full platform vs core users)
The bill grows with ingest volume, check volume beyond the allowance, and seats

Pros

Synthetic monitors for API endpoints from managed locations, including scripted browser monitors
APM traces, distributed tracing and logs give root-cause context for failing endpoints
Perpetual free tier with a monthly data allowance, no time limit
NRQL enables flexible per-endpoint latency and error-rate analysis

Cons

Ingest-based pricing makes high-volume telemetry expensive; exceeding the free allowance stops ingestion on the free tier
Per-check overage pricing for synthetics runs higher per run than dedicated synthetic vendors
Seat-based pricing adds cost as teams grow

Verdict

New Relic combines external synthetic checks with genuine APM depth, and NRQL is one of the better query languages for slicing API latency and errors. The cost shape is the deterrent for check-heavy use: ingest plus seats plus check overages means the meter runs on three axes at once. Teams with moderate volumes get real value from the free allowance; high-traffic APIs change that math.

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

Vendor 07 / 11 · #postman

Postman

The API development platform’s Monitors feature schedules your existing Postman collections as API checks with assertions and alerts.

Best for

Dev and QA teams that already maintain Postman collections and want scheduled checks without a new tool
Pre-production and staging API validation by the people who wrote the tests
Small teams needing basic uptime and response validation

Pricing

Per-user, per-month seat pricing with annual discounts; free plan for individuals
Monitoring metered by monthly API call allowances per plan, with overage blocks available
The bill grows with team seats and monitoring call volume
Plan packaging changes often; verify the current plan page

Pros

Reuses existing collections and assertions, so monitoring setup takes minutes when tests already exist
Runs checks from multiple regions and validates response bodies, status codes and headers
Integrates with CI/CD and alerts via email, Slack and incident-tool integrations
Huge ecosystem and familiarity among API developers

Cons

Monitoring features are lighter than dedicated tools; alert options are basic
Call allowances are consumed quickly by frequent checks; overages add cost
No infrastructure or traffic-level observability: it tests the API from outside only

Verdict

If your API tests already live in Postman collections, Monitors is the fastest path from test suite to scheduled checks, and the multi-region runs with body assertions cover correctness well. The monitoring feature set is thinner than dedicated synthetic tools, and call allowances evaporate at high check frequency. Treat it as an extension of your API development workflow, not as production observability.

Visit Postman -> Postman pricing ->

Vendor 08 / 11 · #site24x7

Site24x7

ManageEngine’s monitoring suite with REST API monitors and multi-step API transaction checks from 130+ global locations.

Best for

IT teams wanting API checks alongside website, server and network monitoring from one vendor
Organizations needing many geographic probe locations
Budget-conscious buyers who prefer per-monitor pricing over per-run

Pricing

Per-monitor licensing: plans bundle a set of monitors; REST API transaction monitors consume additional monitor licenses based on their step count
Website/API monitoring is a separate pack from infrastructure and APM packs; all-in-one bundles cost more
The bill grows with monitor count, step counts and location coverage
Free tier available for small setups

Pros

REST API monitors with JSONPath/regex/XPath assertions and JSON schema validation, from 130+ global locations
REST API transaction monitors chain multiple endpoints to test multi-call workflows without a browser
SSL/certificate, DNS, ping and port checks alongside API monitors
Per-monitor licensing is more predictable than per-run billing for frequent checks

Cons

Monitor-license accounting (steps per license, packs per domain) makes true cost hard to model
UI and alerting feel dated compared with developer-first tools
Deep root-cause analysis requires the APM pack at a higher price point

Verdict

Site24x7 is the sleeper pick for external API checking: schema validation, chained multi-endpoint transactions and one of the largest probe networks here, at per-monitor pricing that does not punish frequency. The dated interface and pack-based licensing are the costs of that value. Internal API observability means buying into their APM pack, at which point the all-in-one price narrows the gap with bigger platforms.

Read full Netdata vs Site24x7 -> Site24x7 pricing ->

Vendor 09 / 11 · #prometheus-blackbox-exporter

Prometheus + Blackbox Exporter

The open-source monitoring stack: Blackbox Exporter probes HTTP/TCP/ICMP endpoints on a schedule and Prometheus alerts on the results.

Best for

Platform teams already running Prometheus who want endpoint checks without a new vendor
Organizations with data-sovereignty requirements that rule out SaaS probes
Teams comfortable with config-as-code and self-operated monitoring

Pricing

Open source and self-hosted: you run and operate it; the cost is your infrastructure and engineering time
No license fees or per-check charges; cost grows with the scale of the Prometheus fleet you operate
Grafana (also open source) is typically added for dashboards

Pros

Blackbox Exporter probes HTTP (status, body regex, TLS expiry), TCP, ICMP and DNS from your own infrastructure
Results are ordinary Prometheus metrics: alert with Alertmanager, graph in Grafana, correlate with service metrics
Massive community, proven at scale, no vendor lock-in
A common r/devops pattern: blackbox exporter for external latency plus service-exposed metrics

Cons

Probes run from your own infrastructure; independent external vantage points mean deploying exporters in multiple regions yourself
You own the operation: scaling, retention, high availability and upgrades
No JSON schema validation beyond regex; complex multi-step flows need custom scripting

Verdict

For Prometheus-native teams, Blackbox Exporter is the obvious answer: endpoint availability, latency and TLS checks become first-class metrics next to everything else you already alert on. The price is operational: no managed probes, no schema validation, and every scaling and HA problem is yours. If you already run the stack well, adding API checks costs an afternoon; if you do not, it costs much more.

Read full Netdata vs Prometheus -> Prometheus project ->

Vendor 10 / 11 · #uptimekuma

Uptime Kuma

Popular self-hosted uptime monitor with HTTP(S) checks including JSON query validation, keyword checks, ports, DNS and a built-in status page.

Best for

Self-hosters and small teams wanting a friendly UI for endpoint uptime without a SaaS bill
Homelab and internal-service monitoring where data must stay in-house
Teams wanting a quick status page for internal APIs

Pricing

Open source (MIT) and self-hosted: you run and operate it; the cost is a small server and your maintenance time
No license fees, monitor caps or seats; cost grows only with the infrastructure you host it on
Optional sponsorship model, not a license

Pros

HTTP(S) monitors with keyword and JSON query validation, TCP ports, ping, DNS records and certificate expiry checks
90,000+ GitHub stars, actively maintained with releases in 2026
90+ notification integrations and a built-in status page
Single-container deployment, running in minutes

Cons

Checks run from one location, wherever you host it; no distributed probe network
Uptime-focused: no per-endpoint latency analytics over time, no traces, no infrastructure correlation
You own the monitor’s own availability; alert delivery depends on your host staying up

Verdict

Uptime Kuma is the best self-hosted uptime UI available, and its JSON query validation puts it a step above simple pingers for API correctness. It is not an observability platform: no latency analytics, no distributed probes, and the monitor itself is a single point of failure you maintain. For internal APIs and small fleets where data must stay in-house, it is hard to beat for the effort.

Read full Netdata vs Uptime Kuma -> Uptime Kuma project ->

Vendor 11 / 11 · #uptimerobot

UptimeRobot

Long-established hosted uptime monitor with HTTP/keyword/API checks, SSL and DNS monitoring, and a well-known free tier.

Best for

Individuals and small teams needing simple hosted uptime checks for a handful of endpoints
Non-critical endpoints where 1-5 minute check intervals are acceptable
Buyers wanting the simplest possible setup with no infrastructure

Pricing

Tiered plans priced by monitor count and check interval
Free tier is capped by monitor count and longer check intervals, and limited to personal, non-commercial use
Paid tiers add faster check intervals, more monitors, SMS alerts and longer log retention
The bill grows with monitor count and interval granularity

Pros

HTTP(S), keyword, port, ping, DNS and SSL expiry monitors with multi-location checks
API monitoring with response validation on paid tiers, plus slow-response alerts
Very simple setup and a familiar name in uptime monitoring
Free tier for personal, non-commercial use

Cons

Free tier is personal, non-commercial use only, with longer check intervals; businesses must pay
Latency analysis is basic compared with tools that break latency down by phase
No internal observability: no metrics, logs or traces for the API’s host

Verdict

UptimeRobot remains the simplest hosted answer to ’tell me when this endpoint is down,’ and multi-location checks on paid tiers cover the basics well. Latency analysis is shallow, the free tier excludes business use, and there is no view into why an API is slow. For non-critical endpoints at 1-5 minute intervals it is adequate; anything more demanding outgrows it quickly.

Read full Netdata vs UptimeRobot -> UptimeRobot pricing ->

Frequently asked questions

What is the best API monitoring tool?

Netdata leads this ranking because it covers both halves in one tool at per-node pricing: external endpoint checks, and internal visibility into the latency and error rates of real API traffic. Checkly is the strongest dedicated synthetic tool; Datadog is the broadest enterprise option. Which one fits you depends on which half of the problem you are solving: external checks (uptime, correctness, latency from probes) or internal observability (per-endpoint latency, errors and traces). The methodology section above lists the exact criteria and weights used.

What is the difference between API monitoring and uptime monitoring?

Uptime monitoring confirms an endpoint answers; API monitoring validates the response, including status codes, body content, schema and latency thresholds. The failure mode that matters is an API returning HTTP 200 with a broken payload, which pure uptime pingers miss entirely. Tools like Checkly, Site24x7 and Netdata validate response bodies; simple ping-style checks, such as basic UptimeRobot monitors, do not.

Are there free API monitoring tools?

Yes, in two forms. Open-source, self-hosted options you run and operate yourself include Uptime Kuma, Prometheus with Blackbox Exporter, and Gatus; open source is a distribution model with a real operating cost, not the absence of cost. Hosted free tiers exist but are capped: UptimeRobot’s free tier is personal, non-commercial use with longer check intervals, and Better Stack and Postman offer limited free allowances. Netdata’s agents are open source under GPLv3+, and the Community plan is free for personal, non-commercial use with up to 5 active connected nodes; businesses use the open-source Agent or Netdata Cloud Business.

What should I monitor on a REST API?

Externally: availability and status codes, response correctness via JSONPath or schema assertions, response latency against thresholds, error rates, and TLS certificate expiry. Internally: per-endpoint latency percentiles, error rates (RED), and traces for failing requests. Check frequency is a trade-off: more frequent checks catch incidents sooner, but on per-run pricing models they directly multiply cost.

How often should API checks run?

Can Netdata monitor APIs?

Yes. Netdata runs protocol-level synthetic checks for HTTP endpoints, ping, TCP ports, DNS queries and certificates, with per-second precision and ML anomaly detection. Beyond checks, the same agent collects per-second metrics from the API-serving processes, logs, and OpenTelemetry traces with RED analysis, all in one platform. Digital Experience Monitoring adds Real User Monitoring and Browser Synthetic Checks for what users experience in the browser. Checks run from your own agents rather than a vendor-operated probe network, so geographic diversity depends on where you deploy them.

What is the difference between API monitoring and API observability?

How much does API monitoring cost?

Costs range from capped hosted free tiers and self-hosted open source (no licence fee, but real infrastructure and operations cost), through per-node pricing such as Netdata’s from $4.5/node/month on annual plans, to per-run bills that scale with every check, location and retry. Because list prices change often, pricing shape matters more than the number: per-check-run (Datadog, Checkly, New Relic overages), per-monitor tiers (UptimeRobot, Site24x7, Better Stack), per-seat plus call allowances (Postman), usage-based cloud (Grafana), per-node (Netdata), and open-source self-hosted, where you pay with infrastructure and operations time. On per-run models the bill grows with check frequency, locations and retries; on per-monitor models it grows with monitor counts. Each card above links the vendor’s official pricing page.

Do I need synthetic monitoring if I already have APM?

The 11 best API monitoring tools in 2027

How we evaluated API monitoring tools

Netdata

Checkly

Datadog

Better Stack

Grafana Cloud Synthetic Monitoring (k6)

New Relic

Postman

Site24x7

Prometheus + Blackbox Exporter

Uptime Kuma

UptimeRobot

Frequently asked questions

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