Checkly alternatives in 2026

If you are shopping for Checkly alternatives, you have probably already decided that synthetic monitoring belongs in your stack: scripted browser checks that log in, click through a checkout, and tell you the app is broken before your customers do. Checkly does that well. It pioneered Monitoring as Code, it runs real Playwright scripts on a global probe network, and its pricing is more honest than most. So the question is rarely "is Checkly bad?" It usually is one of three other things. The per-run browser-check pricing climbs faster than you want at scale, you would rather have synthetics living inside the same platform as your logs and traces, or you want to own the whole thing and self-host. This guide walks the realistic options in 2026, with a clear-eyed read on where each one wins, where it loses, and one honest note about a tool that authors the browser flows rather than hosting them.

A quick definition so we are talking about the same thing. Synthetic monitoring runs scripted, automated transactions against your production app on a schedule, from one or more locations, and alerts when they fail or slow down. It is the opposite of real user monitoring (RUM), which watches actual people. Synthetics catch the broken signup form at 3am when no real user is awake to hit it. Uptime monitoring is the shallow end of that pool (is the URL returning a 200?) and full multi-step browser checks are the deep end. Most tools below cover some slice of that spectrum, and the slice they cover is what separates them.

What Checkly actually is, so you can replace the right part

Checkly is a synthetic and API monitoring platform built around three primitives. API checks fire HTTP requests and assert on status, body, and latency. Browser checks run Node.js scripts written against the open-source Playwright framework, driving a real browser through navigation, form fills, and assertions. Playwright Check Suites go further and run your existing Playwright test suites natively, with custom dependencies and shared storage state. Everything is defined as code: you commit checks to Git, run them through the Checkly CLI, and deploy them like any other artifact. That Monitoring-as-Code model is the thing people genuinely love.

The pricing shape, as of 2026 and per Checkly's published plans, is what tends to push teams to look around. The free Hobby plan includes ten uptime monitors, around 1,000 browser/Playwright runs per month, 10,000 API runs per month, and alerting over email, Slack, and webhooks. The Detect Starter plan is listed at $24/month billed annually with roughly 25,000 API check runs and 3,000 browser/Playwright runs. The Team plan steps up to about 100,000 API runs and 12,000 browser runs. The lever that matters: extra browser/Playwright runs are billed around $4.00 per 1,000, while extra API runs are far cheaper at roughly $1.80 per 10,000. Always re-check the live pricing page before you budget, because vendor numbers move.

Do the napkin math and the reason for this article appears. One browser check at a five-minute cadence is about 8,640 runs a month. Run a dozen critical flows that often and you are well past the included browser runs on most plans, paying overage on the expensive primitive. High-frequency, multi-location browser checks are the line item that grows, and every alternative below is in some way a response to that one fact.

How to think about Checkly alternatives

Before the table, here is the mental model I use when evaluating this category. Sort every option along two axes.

First axis: scope. Does it do uptime only, or full scripted browser journeys, or the whole observability stack (logs, metrics, traces, incidents, status pages)? A tool that only pings URLs is not a Checkly replacement, no matter how cheap. A full observability platform might be overkill if all you wanted was five login flows watched.

Second axis: ownership and where the checks run. Fully hosted SaaS with a managed global probe network is the Checkly model. Self-hosted open source means you run the probes and own the data. There is also a third, often-missed option: author the flow yourself, run it on infrastructure you already pay for (CI, a cron box), and skip the dedicated synthetics SaaS entirely. That last one is where the honesty section later in this piece lives.

Keep both axes in mind as you read. A "cheaper" tool that drops scripted browser checks is not cheaper. It is a different product.

The main contenders, compared

Here is the landscape at a glance. Treat every price as directional and verify against the vendor before you commit, because synthetic-monitoring pricing changes often and depends heavily on run frequency and locations.

The columns that matter most are "scripted browser checks" and "self-host." If a tool cannot run a multi-step scripted journey, it is an uptime tool wearing a synthetics label. If you need to own the data for compliance reasons, self-host narrows the field to Grafana's open-source k6, OneUptime, and a couple of others.

Datadog Synthetic Monitoring

If your team already lives in Datadog, this is the most natural Checkly alternative, and arguably the most capable on raw features. Datadog supports both a no-code recorder and code-defined browser tests, runs them from managed and private locations, and (this is the real differentiator) links a failing browser check directly to the APM trace and the related logs. When a checkout step fails, you are one click from the span that threw and the log line that explains it. For root-cause speed, nothing in this list beats a unified platform.

The honest catch is cost and gravity. Datadog's synthetics are priced per browser test run and per API test run, and the bill compounds with everything else you already pay Datadog for. Public write-ups in 2026 describe 50 browser checks at a five-minute cadence from a few locations costing several hundred dollars a month on checks alone, before APM, logs, or infrastructure. And once your synthetics live inside Datadog, leaving gets harder. Choose this when trace-linked debugging is worth the premium and you have already committed to the platform. Skip it if you want synthetics as a standalone, portable concern.

Grafana Cloud Synthetic Monitoring (k6)

Grafana's synthetic monitoring is powered by k6, the open-source load-testing tool Grafana now owns. Its pitch is unusually clean: one k6 script can run in CI, as a load test, and as a production synthetic monitor, with no rewrite. A k6 scripted check runs a single iteration of your test at frequent intervals, and the results land as Prometheus metrics and Loki logs, so alerting and dashboards reuse the Grafana machinery you already operate.

For teams already standardized on Grafana Cloud and k6, this is close to a no-brainer, and it is one of the few options here with a genuine open-source path: k6 itself is OSS, so you can self-host the script execution. The trade-off is that the experience is metrics-first and assumes comfort with the Grafana stack and with writing k6 JavaScript. If you are not already a Grafana shop, the onboarding tax is real, and the browser-check ergonomics are less polished than Checkly's purpose-built Playwright story. Pricing follows Grafana Cloud's usage model (active series, logs ingested), with a free tier that includes a starter allotment. Verify the synthetic-monitoring specifics for your volume.

New Relic Synthetics

New Relic deserves a spot mostly because of its free tier, which is the most generous of the full-platform players. As of 2026 the Free edition includes one full-platform user, 100GB/month of data ingest, and around 500 synthetic checks per month. That is genuinely enough to watch roughly ten critical endpoints at a 30-minute cadence from multiple locations without paying anything — a real on-ramp, not a 14-day trial.

New Relic supports scripted browser monitors as well as simple ping and uptime checks, all inside the same observability platform that holds your APM and logs. The honest limits show up as you scale: the free tier caps checks well below paid plans, omits ticketed support, and drops some alerting workflow features. Pricing above the free tier is usage-based on data ingest plus per-user fees, which can surprise teams that ingest a lot. Pick New Relic when you want synthetics, APM, and logs in one place and you value a free tier you can actually run production monitoring on. Look elsewhere if you want pure, lightweight synthetics without the rest of the platform.

Better Stack, Pingdom, and UptimeRobot: the uptime-leaning options

These three cluster together because their center of gravity is uptime and incident response, with synthetic capability varying from "solid" to "thin." Be precise about which one you are buying.

Better Stack combines uptime monitoring, on-call scheduling, incident management, and status pages into one fast, modern product. The selling point teams repeat is speed: sign-up to first alert in under ten minutes, and when an alert fires the response workflow already exists in the same tool. Its scripted browser-check depth is lighter than Checkly's Playwright story, so think of it as "uptime plus incidents plus status page" rather than "deep synthetics." Excellent if the operational workflow matters more to you than complex multi-step journeys.

Pingdom is the veteran, and its strength is genuinely synthetics-adjacent: a large global probe network (100+ locations), detailed waterfall reports, real user monitoring, and transaction monitoring that handles multi-step flows. If page speed and user experience are your obsession, Pingdom is a credible Checkly alternative. It is a commercial SaaS with no self-host option, and the recorder-based authoring is less code-native than Checkly's Git-driven model.

UptimeRobot is the pragmatic budget pick. It concentrates on one job, reliable uptime monitoring with fast alerts and predictable pricing, and does it well, with a famously generous free tier. What it is not is a full synthetic-monitoring platform; scripted multi-step browser journeys are not its strength. If all you actually need is "tell me when the site is down" across a lot of monitors cheaply, it is the right answer and you do not need Checkly at all.

OneUptime and the self-hosted route

If owning your data and your stack is the priority, OneUptime is the open-source option that goes furthest. It pairs synthetic monitoring with the full incident lifecycle (on-call scheduling, incident management, and status pages) and you can self-host the whole thing. For regulated environments where checks and results cannot leave your infrastructure, or for teams that philosophically prefer to run their own tooling, this is the cleanest Checkly alternative in the list.

The trade-off with any self-hosted monitoring is the one every self-hosted tool carries: you now operate the monitor. You own the probe locations, the uptime of the thing that watches your uptime, the upgrades, and the scaling. That is a real engineering cost, and the irony of your monitoring going down is not hypothetical. Choose self-host when data ownership or cost-at-scale clearly outweighs the operational overhead. If you would rather pay someone to keep the watchers running, stay with a hosted option.

The honest part: BrowserBash is not a synthetic-monitoring platform

This blog is published by the team behind BrowserBash, so the fair thing is to be blunt about what it is and is not. BrowserBash is a free, open-source (Apache-2.0) command-line tool that drives a real Chrome browser from a plain-English objective using an AI agent. You describe the flow — "log in, add the pro plan to the cart, go to checkout, confirm the total shows tax" — and an agent walks the page step by step, no selectors, and returns a verdict plus structured values. It is browser-scoped on purpose: it automates web browsers, not the whole operating system. For true desktop or OS-level automation, general computer-use models or RPA tools are the right fit. For anything that lives in a browser, BrowserBash is cheaper, faster, and more deterministic because it reads the DOM rather than guessing at screenshot pixels.

Here is the honest line: BrowserBash does not host a global probe network, it does not run on a schedule by itself, and it does not page your on-call engineer. It is not a drop-in replacement for Checkly's hosted synthetic-monitoring service. What it replaces is the authoring of the browser flow, and that is the part everyone underestimates. Writing and maintaining Playwright browser checks is the labor inside Checkly, Datadog, and Grafana that nobody enjoys. BrowserBash lets you express the flow in English, run it locally to confirm it passes, and run the same objective in CI on every deploy. You bring the schedule (cron, GitHub Actions, your CI's scheduled pipelines) and the alerting (Slack, PagerDuty, whatever you already have); BrowserBash brings the resilient, selector-free browser execution.

Getting started is one install. It runs Ollama-first, so with a capable local model the bill is $0 and nothing leaves your machine:

npm install -g browserbash-cli

# Verify a critical production flow in plain English
browserbash run "go to https://app.example.com, log in with the test account, \
open billing, and confirm the current plan reads 'Pro'"

For CI-driven synthetic checks — the closest BrowserBash gets to "monitoring" — use agent mode. It emits NDJSON and returns machine-readable exit codes (0 success, non-zero failure) so a scheduled pipeline can treat a failed login flow exactly like a failed test and trigger your existing alerting:

# Scheduled CI job: run as an agent, fail the build (and your alerts) on a broken flow
browserbash run "verify the signup form accepts a new email and shows the welcome screen" \
  --agent

You can also version your flows the way Checkly versions checks. BrowserBash reads Markdown test files (*_test.md) with {{variables}} and masked secrets, so a flow becomes a reviewable artifact in your repo and the same file runs across environments:

# Run a versioned Markdown flow with environment variables injected
browserbash testmd run checkout_test.md \
  --var BASE_URL=https://staging.example.com \
  --var PLAN=pro

Add --record when you want a .webm video, a screenshot, and a trace of exactly what the agent saw — useful when a flow fails and you need the same forensic detail Checkly gives you in a failed-check report. One honest caveat to set expectations: tiny local models (8B and under) get flaky on long multi-step journeys, so the sweet spot is a Qwen3- or Llama 3.3 70B-class model, or a hosted model via Anthropic or OpenRouter. There is more on running these flows in CI in the BrowserBash tutorials and the learn guides.

When to choose which

Let me make this decision-shaped rather than a feature dump.

Stay on Checkly if pure synthetic monitoring with a Monitoring-as-Code workflow is exactly what you want and the browser-run pricing fits your cadence. It is the most focused tool in the category and the IaC story is genuinely good. The only reason to leave is the per-browser-run cost at scale or a desire to consolidate.

Choose Datadog or New Relic if you want synthetics living next to your APM, logs, and traces. Datadog wins on trace-linked debugging and loses on cost and lock-in; New Relic wins on the free tier and loses on data-ingest pricing at scale. Both beat Checkly on root-cause speed and lose to it on focus.

Choose Grafana Cloud if you already run Grafana and k6 and want one script to serve CI, load tests, and synthetics. It is the strongest pick for metrics-first teams and the open-source-friendliest of the hosted options.

Choose Better Stack, Pingdom, or UptimeRobot by exact need: Better Stack for uptime plus incident workflow and status pages, Pingdom for page-speed and UX depth on a big probe network, UptimeRobot for cheap, predictable uptime when you do not need deep scripted journeys.

Choose OneUptime if self-hosting and data ownership outweigh the cost of operating your own monitor.

Add BrowserBash (alongside any of the above, not instead of the hosted scheduler) when the bottleneck is writing and maintaining the browser flows, when you want to run those same flows as gates in CI for free on local models, or when you want a fast, selector-free way to verify a production journey on demand without provisioning a check. It wins on browser-task authoring cost and CI ergonomics; it explicitly does not win on hosted scheduling, global probes, or paging, and it is the wrong tool for any OS-level automation. Browse the case studies to see where teams slot it in, and the pricing page to confirm the free, open-source terms.

A pragmatic two-tier setup

The pattern I see working in 2026 is not "pick one tool." It is two tiers. Tier one is a lightweight, cheap, always-on uptime layer (UptimeRobot, Better Stack, or your existing observability platform's basic checks) answering "is it up?" continuously. Tier two is a smaller set of deep, scripted browser journeys for the handful of flows that actually make you money: signup, login, checkout, the critical dashboard. You run tier two less frequently because each run is expensive, whichever platform hosts it.

BrowserBash fits tier two's authoring and CI side cleanly. You write the deep flows in English, keep them as Markdown artifacts in Git, run them as agent-mode gates on every deploy, and let a hosted synthetics tool (or a scheduled CI job plus your alerting) handle the always-on cadence. That keeps the expensive hosted browser-run count low and the flows readable by your whole team. The expensive part of synthetic monitoring was never the scheduler. It was the brittle scripts, and that is the part worth rethinking first.

FAQ

What is the best free alternative to Checkly?

It depends on what you mean by free. For a genuine free synthetic-monitoring tier on a full platform, New Relic is the standout, with roughly 500 synthetic checks per month and 100GB of data ingest at no cost. For free uptime monitoring across many monitors, UptimeRobot is hard to beat. And for authoring and CI-gating the browser flows themselves at zero cost on local models, BrowserBash is free and open source, though it is not a hosted scheduler.

Is Checkly the only Monitoring-as-Code option?

No, but it popularized the term. Grafana Cloud's synthetic monitoring uses k6 scripts defined as code, Datadog and New Relic both support code-defined browser tests, and OneUptime can be configured as code while you self-host it. BrowserBash takes a related but distinct approach: flows are versioned Markdown files with variables and masked secrets, run from the CLI or CI rather than from a hosted control plane.

Why does Checkly get expensive at scale?

The cost driver is browser/Playwright check runs, which are billed far higher than API runs: on the order of a few dollars per thousand browser runs versus cents per thousand API runs as of 2026. A single browser check at a five-minute cadence is roughly 8,640 runs a month, so a dozen high-frequency multi-step flows can push past included allotments and into overage quickly. Lowering cadence, trimming flows, or moving authoring and CI gating off-platform are the usual levers.

Can BrowserBash replace a synthetic monitoring platform?

Not on its own, and the team behind it says so plainly. BrowserBash has no global probe network, no built-in scheduler, and no paging, so it does not replace the hosted service Checkly or Datadog run for you. What it replaces is the hard part, authoring and maintaining the browser flows, which you can then run as CI gates with machine-readable exit codes and pair with your own schedule and alerting.

Ready to make your browser flows easier to write and cheaper to run in CI? Install the CLI with npm install -g browserbash-cli and start in minutes. An account is optional: create one at https://browserbash.com/sign-up only if you want the cloud dashboard for run history.