API Monitoring Tools: The Best API Monitoring Software and API Endpoint Monitoring Services Compared
Thirteen tools compared on the things that decide whether an API check is worth running: what it can assert about the response, how it authenticates, where it runs from, and how the bill scales. We build Uptimehub, and we have been specific about the jobs the others do better.
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In short
API monitoring tools call your REST or HTTP endpoints on a schedule and check that the response is actually correct, not just that something came back. The category splits three ways. Uptime tools such as Uptimehub, UptimeRobot, Better Stack and Uptime.com run scheduled endpoint checks with status code and response body assertions, and they are the cheapest way to know an API is healthy. Code-first tools such as Checkly and Postman let developers define checks as code or as collections, which suits teams that want monitoring in the same repo as the API. Observability platforms such as Datadog and New Relic fold synthetic API checks into tracing and logs, which is powerful and priced accordingly. If all you need is proof that an endpoint answers correctly and fast from several regions, the uptime tools do that job for roughly a tenth of the price of an observability platform.
Side by side
API monitoring software compared
The column to read first is response assertions. Everything in this table can tell you an endpoint answered. Far fewer can tell you it answered correctly, and that is where nearly every expensive API incident hides. Verified dollar figures are in the pricing table below rather than here, because list prices move and a stale number is worse than none.
| Tool | Best for | Check types | Response assertions | Multi step flows | Pricing model | Free tier |
|---|---|---|---|---|---|---|
| Uptimehub | Endpoint health and SLA evidence without an observability bill | HTTP, API, keyword, SSL, DNS, TCP, cron | Yes, status code, body keyword and latency | No, single request checks only | Per monitor, from $9/mo | No, paid only |
| Checkly | Developer teams that want checks defined as code | API checks, Playwright browser checks | Yes, full assertion syntax on body, headers, timing | Yes, Playwright scripts | Per plan, metered by check runs | Yes, 10k API check runs/mo |
| Postman Monitors | Teams whose API contracts already live in collections | Collection runs against any endpoint | Yes, JavaScript test scripts | Yes, chained requests in a collection | Per user seat, metered by monitoring requests | Yes, 1,000 requests/mo |
| Datadog Synthetic Monitoring | Companies already paying for Datadog observability | API, multistep API, browser | Yes, plus correlation with traces | Yes, multistep API and browser tests | Per test run, on top of the platform | Trial only |
| New Relic Synthetics | Teams correlating API failures with APM traces | Ping, simple and scripted API, browser | Yes, scripted checks in JavaScript | Yes, scripted API tests | Usage based on data ingest and checks | Yes, 100 GB ingest and 500 checks |
| UptimeRobot | The cheapest way to watch a lot of endpoints | HTTP, keyword, ping, port, heartbeat | Keyword matching, limited assertions | No | Tiered by monitor count, listed in EUR | Yes, 50 monitors at 5 min |
| Better Stack | On-call teams that run a formal rota | HTTP, keyword, ping, port, heartbeat | Yes, keyword and status code | No | Per monitor block, plus responder seats | Yes, 10 monitors |
| Site24x7 | Buyers who want one vendor for everything | REST API, SOAP, web, server, network | Yes, response and JSON assertions | Yes, transaction monitors on higher tiers | Tiered plans plus add-on credits | Trial only |
| Pingdom (SolarWinds) | Classic uptime reporting inside a larger IT suite | HTTP, transaction, page speed | Yes, on transaction checks | Yes, transaction checks | Tiered by checks and transaction volume | Trial only |
| Uptime.com | Enterprise procurement that wants formal SLA reports | HTTP, API, transaction, DNS, SSL, malware | Yes, multi step API assertions | Yes, transaction and multistep API | Tiered by checks and features | Trial only |
| Sematext Synthetics | Predictable per monitor billing with browser checks | HTTP and browser monitors | Yes, response conditions | Yes, browser scripts | Per monitor, pay as you go | Trial only |
| Uptime Kuma | Self hosters who want no vendor and no bill | HTTP, keyword, JSON query, ping, port, heartbeat | Yes, keyword and JSON query | No | Free and open source, you host it | Free, self hosted |
| Prometheus Blackbox Exporter | Infrastructure teams already running Prometheus | HTTP, TCP, DNS, ICMP probes | Yes, regex on the body | No | Free and open source, you host it | Free, self hosted |
The real split
Uptime tools, code first tools and observability platforms
Most shortlists in this category go wrong at the first step, because three quite different kinds of product all describe themselves as API monitoring. Sorting them out before you compare features saves a lot of time and usually a lot of money.
Uptime and endpoint tools answer one question well: is this endpoint responding correctly, right now, from several places on earth. They run scheduled requests, assert on status codes and response content, measure latency and alert when something breaks. Uptimehub, UptimeRobot, Better Stack, Sematext and Uptime Kuma sit here. Setup is minutes, the bill is small and predictable, and the ceiling is real: single requests, not scripted journeys.
Code first tools treat monitoring as part of the codebase. Checkly and Postman both let developers express checks in the language and tooling they already use, version them alongside the API, and run them through CI. That is the right shape if the people who own the API also own the monitoring, and it is friction if they do not. The bill is metered by check runs or by seats rather than by endpoints.
Observability platforms put synthetic API checks next to traces, logs and infrastructure metrics. Datadog and New Relic do this well, and the payoff is diagnosis rather than detection: you see the failing check and the database saturation that caused it in one timeline. The cost is a platform relationship, not a subscription, and the synthetic module is a small part of what you sign up for.
The practical rule: buy detection cheaply and buy diagnosis only when you have something to diagnose. A team running a dozen endpoints gets more value from checking each one every minute from six regions with real body assertions than from a scripted flow that runs every fifteen minutes because each run is metered. That is the reasoning behind our own API monitoring and uptime monitoring checks being priced per monitor rather than per run.
What breaks
Why a 200 OK is not a health check
APIs fail politely. A cache returns yesterday's data with a perfect status line. A downstream service times out and the gateway hands back an empty array. An auth token expires and every request gets a 200 with an error object inside it because someone wrapped the response envelope years ago. A schema change drops a field your biggest customer parses. None of that trips a status code check, and all of it costs you support tickets.
The fix is not complicated, it is just specific. Every endpoint check should assert on three things instead of one:
- The status code, which catches hard failures and nothing else.
- A value in the response body, ideally a field that only exists when the request genuinely succeeded, so an empty or error shaped payload fails the check.
- A latency ceiling, because an endpoint that answers correctly in nine seconds has already broken the client that gave up at five.
Then pick the endpoint carefully. A dedicated health route that returns a hard coded OK proves your web server is running and nothing more. Monitor something that exercises the real path: a read that touches the database, a search that hits the index, an authenticated call that proves your token issuance still works. If you sell an API, monitor the exact call your busiest customer makes, with the same headers they send. Our guide to monitoring an API walks through choosing those endpoints, and the API response time benchmarks post covers where to set the latency threshold.
Tool by tool
Where each API monitoring tool actually wins
Checkly
The strongest developer-first option in the category. Checks are written as code, versioned in your repo and deployed through CI, and the assertion syntax on API checks is genuinely good: status, headers, response time and any JSONPath in the body. The browser side runs real Playwright scripts, so a login and checkout flow is a first class citizen rather than a bolt on. The tradeoff is that everything is code, which is a feature for a platform team and an obstacle for anyone who wanted to add a check between meetings. Billing is metered by check runs, so a one minute frequency on many endpoints climbs faster than a per monitor plan.
Uptimehub vs ChecklyPostman Monitors
If your API is already documented as a Postman collection with tests written against it, monitors are close to free work: point a schedule at the collection you already maintain and the same assertions now run hourly. That is a real advantage for contract correctness. It is a weak fit as your outage alarm, because the included monitoring requests are counted per team and are modest, the run frequency is coarser than a dedicated uptime tool, and the platform is priced per user seat, so the bill tracks how many developers you have rather than how many endpoints you watch.
Datadog Synthetic Monitoring
When an API check fails here you can jump straight into the traces, logs and infrastructure metrics from the same failure window, which is a genuinely different class of answer than a red dot on a dashboard. Multistep API tests handle auth flows where one call feeds the next. It only makes sense if you are already on the platform. Buying Datadog to find out whether an endpoint is up is like buying a car to charge your phone, and the per test run billing means high frequency checks are a line item somebody eventually questions.
Uptimehub vs Datadog Synthetic MonitoringNew Relic Synthetics
Similar logic to Datadog: the value is correlation with APM, not the checks themselves. New Relic is unusual in that the free allowance is large enough to be useful, with 100 GB of ingest and 500 synthetic checks included, so a small team can run real monitoring at no cost. The usage based model is the thing to model carefully before you commit, because ingest, users and checks are billed on separate meters and a noisy service can move all three at once.
UptimeRobot
The default cheap starting point, and the free tier at 50 monitors is still the most generous around. For API monitoring specifically the ceiling arrives quickly: keyword matching in the body is about as deep as the assertions go, so a structurally wrong JSON payload that happens to contain the right word passes. Fine for is it up, thin for is it correct.
Uptimehub vs UptimeRobotBetter Stack
Monitoring, on-call scheduling and a status page in one product, which is a strong combination for a team that actually runs a rota. Worth reading the pricing page carefully: monitors are billed in blocks and uptime access for a responder is billed per seat on top, so the bill moves with both the size of your estate and the size of your team.
Uptimehub vs Better StackSite24x7
The broadest feature list here by some distance: REST and SOAP API checks with JSON assertions, plus servers, networks, cloud and real user monitoring, all from Zoho. If consolidating vendors is the goal it is a sensible buy. The cost of that breadth is a licensing model built from plans plus add-on credits, which is hard to forecast, and a product surface far larger than an API team needs.
Uptimehub vs Site24x7Pingdom (SolarWinds)
One of the oldest names in uptime and still a competent product with good reporting and real transaction checks. Two practical notes for anyone shortlisting it in 2026: the pricing page did not return a readable quote to us, so budget by request rather than by list, and the product now sits inside the wider SolarWinds portfolio, which changes the buying conversation from a card payment to a procurement cycle.
Uptimehub vs Pingdom (SolarWinds)Uptime.com
Positioned for buyers who need formal SLA reporting and a broad check catalogue, including multistep API checks where one response feeds the next request. Strong on the compliance and reporting side. Entry pricing starts at $9 a month, but the tiers that carry the API and transaction features are a very different number, and the site does not expose that ladder without going through a plan selector.
Uptimehub vs Uptime.comSematext Synthetics
An unusually clean pricing model in a category full of meters: $2 per HTTP monitor and $7 per browser monitor, pay as you go, with unlimited users. If you want to know exactly what next month costs and you dislike per seat billing, it deserves a look. The wider Sematext platform is logs and infrastructure monitoring, so the synthetics piece is one module rather than the whole company.
Uptime Kuma
The best free option, and better at API checks than most people expect: it supports JSON query assertions, not just keyword matching, so you can assert on a specific field in the payload. The structural catch is unchanged. A monitor hosted on your own infrastructure shares failure modes with the thing it monitors, and it cannot check your service from six places at once unless you run six of it.
Uptimehub vs Uptime KumaPrometheus Blackbox Exporter
The right answer if Prometheus and Alertmanager are already the backbone of your alerting and you want probe results in the same place as everything else. It probes HTTP, TCP, DNS and ICMP and supports regex matching on the response body. It is a component, not a product: you write the config, run the exporter, build the dashboards and set up the alert routes, and external checks still need to run somewhere outside your cluster to be worth anything.
What it costs
API monitoring pricing, checked on each vendor's own page
Every figure below was read on the vendor's own pricing page in July 2026. Where a vendor lists in euros we have kept euros rather than converting, and where a page would not give us a readable number we say so instead of guessing.
| Tool | Published price | What that buys |
|---|---|---|
| Uptimehub | From $9/mo (Starter, 20 monitors at 1 minute) | All check types, 6 regions and a branded status page in every plan |
| Checkly | Hobby $0, Starter $24/mo, Team $64/mo, Enterprise custom | Hobby 10 monitors and 10,000 API check runs/mo; Team 75 monitors and 100,000 API check runs/mo. Prices shown reflect annual billing |
| Postman | Free $0, Solo $9, Team $19, Enterprise $49 per user/mo billed annually | Free includes 1,000 monitoring requests/mo per team; paid tiers 10,000/mo per team |
| Site24x7 | Web Uptime $9/mo, Web Perf $36/mo, Enterprise Plus Web $899/mo, MSP $54/mo, all paid annually | Web Uptime covers 25 websites; Web Perf adds 8 transaction monitors |
| Better Stack | 10 monitors included, then $25/mo per additional 50 monitors ($21 billed yearly). Responder seats $34/mo ($29 yearly) | Free tier covers 10 monitors and 1 status page |
| New Relic | Usage based: 100 GB ingest free then $0.40/GB, Data Plus $0.60/GB. Extra synthetic checks $0.005 each | Free tier includes 500 synthetic checks; platform users billed separately |
| Sematext Synthetics | Pay as you go: $2 per HTTP monitor, $7 per browser monitor, $5/mo minimum | Unlimited users and unlimited APIs on every tier |
| UptimeRobot | Listed in EUR: Solo EUR9, Team EUR33, Enterprise EUR69/mo | Free tier is 50 monitors at 5 minute checks |
| Uptime.com | Website monitoring from $9/mo ($108/yr) | Higher tiers sit behind a plan selector and were not published as a list |
| Datadog Synthetics | Billed per test run on top of the platform. The page did not expose a figure to us, so we are not quoting one | API tests and browser tests are metered separately |
| Pingdom | Pricing page returned an error to us, so we are not quoting a figure | Compare the model: tiered by checks and transaction volume |
| Uptime Kuma / Blackbox Exporter | $0 licence | You pay in hosting, patching and the hours to build alert routing |
Read down that column and the four billing models are easy to separate. Checkly and Postman meter check runs and requests, so raising frequency on a critical endpoint costs more every month. Better Stack charges for monitors and for the seats that can see them. New Relic bills ingest, users and checks on three meters at once. Per monitor pricing, which is what we do, is the only model where the bill is a function of how many things you watch and nothing else, so a one minute check costs the same as a five minute one. The full breakdown of how these models diverge at scale is in the uptime monitoring cost guide.
How to choose
What to compare before you commit
Does it read the response body, or only the status code?
This is the question that separates real API monitoring from a ping with extra steps. A broken API returns 200 with an empty array, a stale cache, or an error object wrapped in a success envelope more often than it returns a 500. Ask whether the tool can assert on a JSON field, a regex or an exact value, and whether a failed assertion alerts the same way a timeout does.
Can it authenticate the way your clients do?
Most endpoints worth monitoring are behind auth. Check for custom headers, bearer tokens, API keys, basic auth and, if you need it, a token refresh step before the real request. A tool that can only hit public URLs will monitor your marketing site and nothing that earns money.
Where do the checks run from, and what confirms a failure?
A single probe in one data center will page you for its own network blips. Look for several geographic regions and, more importantly, for a confirmation step: a good tool retries from a different region before declaring an outage. Multi region also catches faults that only affect one part of your customer base, which single location checks report as all clear.
How is it billed: per monitor, per check run, per seat or per GB?
These four models scale in completely different directions. Per check run punishes frequency, which is exactly the thing you want to increase on a critical endpoint. Per seat punishes bringing more of your team into the tool. Per GB is unpredictable when a service starts misbehaving. Per monitor is the only one where the bill rises only when you genuinely watch more things.
Do you actually need multi step and contract testing?
Chained requests, OAuth dances and schema validation are excellent capabilities and they carry a real price premium. Many teams pay for them and monitor a single health endpoint anyway. Be honest about which of your failures would have been caught only by a scripted flow, and if the answer is none, buy the simpler tool and spend the difference on check frequency.
How noisy is the alerting, and where does it land?
An API check running every minute across a dozen endpoints will generate alerts, and the ones your team learns to ignore are worse than no monitoring. Look for retry and confirmation logic, maintenance windows, per monitor thresholds, and delivery into the place your team already watches rather than a mailbox nobody opens at 3am.
What history and reporting does it keep?
Response time trend data is what turns monitoring from an alarm into evidence. You want retained per check history, latency percentiles rather than only averages, and an availability figure you can put in front of a customer. If you sell against an uptime commitment, confirm the retention period covers your reporting cycle before you buy.
One honest boundary before you shortlist us: Uptimehub does not run scripted browser journeys or chained multi request flows. If your monitoring has to log in, add to a cart and complete a checkout, look at Checkly or a transaction capable suite instead. What we do is run every check type that matters for endpoint availability, from six regions, every minute, at a flat per monitor price, and publish the result on a branded status page without an extra line item. If your shortlist is wider than APIs, our uptime monitoring tools comparison covers the same ground for websites and services, and status page software compares the public reporting side.
FAQ
Questions buyers ask when comparing API monitoring tools
API monitoring is the practice of calling your REST or HTTP endpoints on a fixed schedule from outside your infrastructure to confirm they return the right status code, the expected content and an acceptable response time. It runs whether or not anyone is using the API, which is what makes it useful for catching machine facing failures that no human would notice until a customer integration breaks.
For endpoint health and SLA evidence at low cost, Uptimehub, UptimeRobot and Better Stack cover it. For developer teams who want checks defined as code, Checkly is the strongest option, with Postman a natural fit if your contracts already live in collections. If you need API failures correlated with traces and logs, Datadog and New Relic are the platforms to look at, at a much higher price.
Pick the endpoints that represent real functionality rather than a health route that only proves the web server is running. Call each one on a schedule from several regions, assert on the status code, on a value in the response body and on a latency threshold, and require a confirming check from a second region before alerting. Record every confirmed failure so you can report availability as a percentage later.
API testing runs before release to prove new code behaves correctly, usually in CI against a build. API monitoring runs continuously in production to prove the deployed service still behaves correctly right now. The assertions can look identical. The difference is when they run and what a failure means: a failed test blocks a deploy, a failed monitor means customers are affected already.
Availability as a percentage of successful checks, response time as percentiles rather than an average, error rate broken down by status code, and correctness measured by assertions on the response body. Add certificate expiry and DNS resolution, because both take an API fully offline and neither shows up in application metrics until it is too late.
Dedicated endpoint monitoring runs from roughly $9 to $60 a month for a small estate, with per monitor plans the most predictable. Code first tools land between $24 and $64 a month at team size. Observability platforms are usage based and routinely reach hundreds or thousands a month, because the synthetic checks are a small module attached to a much larger bill.
Yes, and you should, because the public parts of an API rarely break in the ways that matter. Most tools support custom headers, bearer tokens, API keys and basic auth. Create a dedicated read only credential for the monitor rather than reusing a production key, scope it to a harmless endpoint, and make sure the check never writes data or consumes rate limits a real client needs.
Last updated July 2026
Watch your endpoints, not your invoice
API checks with status code, response body and latency assertions, running every minute from six global regions, from $9 a month. Priced per monitor, never per check run and never per seat, so raising your check frequency costs nothing extra.