Stop paying $50/mo for "Synthetic Monitoring." I just built a free alternative.
I run a dev agency and I got tired of the "200 OK" lie.
My client's server status was green (100% Uptime), but their Checkout Button was broken because of a silent JavaScript error. They lost sales for 6 hours while the dashboard said "All Systems Operational."
I looked at enterprise tools like Datadog and New Relic. They charge huge fees for "Synthetic Monitoring" (using a headless browser to actually click buttons).
So this weekend, I built my own suite.
I am releasing these 3 tools as a Free Forensic Suite for the community:
-
The Login Validator
It doesn't just ping the URL. It types dummy credentials and checks if the "Submit" button actually works. (Tests from US/EU regions). -
The Checkout Defender
It simulates a user flow: Product Page -> Add to Cart -> Checkout. If the Stripe/PayPal iframe fails to load, it alerts you. -
The API Deep-Check
Validates the actual JSON data structure, not just the status code.
The Ask:
I'm keeping this in "Private Beta" to manage server load.
Drop a comment below if you want to stress-test your SaaS. I'll DM you the access link.
(I’m looking for feedback specifically on the Checkout visualization—does it work with your specific gateway?)
Solid build. The "loss leader for agency work" positioning is actually one of the smartest go-to-market moves I've seen on IH lately. You're not trying to compete on pricing with Datadog — you're using a genuinely useful free tool to build trust and funnel leads into higher-value services.
I'm building a mobile app (not SaaS), so the checkout monitoring doesn't directly apply to me, but I ran into a similar philosophy problem: how do you prove your tool actually works before someone pays? Your answer of "only charge when it works" (from the other thread) and this approach of "give away the monitoring, sell the expertise" are both smart takes on the same trust gap.
One thing I'd add — have you considered letting users define custom user flows beyond login/checkout? Like "click Product > Add to Cart > Apply Coupon > Check total is correct"? That kind of composable flow testing is where enterprise tools really fall short for indie hackers with simpler but unique flows.
You read my mind on the 'Agency Flywheel' strategy.
It’s hard to sell a $5,000 optimization package to a cold lead. It’s easy to sell it to a user who just saw—with their own eyes—that their 'Add to Cart' button is broken. The free tool builds the trust; the agency delivers the fix.
Re: Custom Composable Flows:
You actually nailed our latest update. We just rolled out a 'Multi-Step Logic Builder' that supports up to 10 sequential actions in a single flow.
You aren't limited to just 'Login'. You can script exactly what you described:
Search for 'Product A'
Click Result
Add to Cart
Input Coupon 'SAVE10'
Assert: Grand Total == $90
If step 5 fails (e.g., coupon logic breaks), the whole monitor alerts you. It’s basically 'Integration Testing as a Service' for Indie Hackers.
Appreciate the kind words on the strategy!
This hits a real problem. “200 OK” while the actual flow is broken is way more common than people admit. Curious — how do you handle JS errors that appear only after user interaction or delayed loads?
Spot on. That 'Zombie State' (200 OK but UI is frozen) is exactly what kills conversion rates.
To answer your question on delayed/JS errors:
Since we run a full headless browser (Playwright), we catch those in two ways:
Explicit Wait for Outcomes: We don't just sleep(2000). We use await page.waitForSelector('#success-message'). If the user clicks 'Pay' and that specific success element doesn't render (due to a silent JS crash), the test fails—even if the API returned 200.
Console Listeners: We attach listeners to page.on('pageerror') and page.on('console'). If an unhandled Promise rejection or a 404 on a critical JS chunk happens after the load, we capture that stack trace and include it in the alert.
It’s heavy on resources (which is why most tools don't do it), but it’s the only way to catch those React/Vue 'White Screens of Death.'
Do you have a specific flow (like a heavy SPA) that’s been tricky to monitor?
Nice build. The value prop is immediately clear because you’re solving a costly blind spot (green uptime while checkout is broken). One suggestion: publish a short “false-positive playbook” for dynamic DOM changes (A/B tests, feature flags, cookie banners). If you can show low-noise alerting, that becomes a real differentiator vs generic uptime tools.
That is a killer suggestion. 'Alert Fatigue' is why most devs turn off PagerDuty after a week.
I’m actually working on a 'Resilience Guide' right now—specifically how to use data-testid attributes so your monitoring doesn't break every time Marketing changes a button color.
I’ll definitely add a section on handling A/B test DOM shifts. Thanks for the roadmap idea!
Really solid weekend build. The loss leader for agency work positioning is smart - I have seen a few founders do this well where a free tool becomes the top-of-funnel for higher-ticket services.
One thing I would push back on slightly: the CAPTCHA limitation might actually be your biggest feature gap long-term. Enterprise clients will need bot-friendly test accounts or IP whitelisting, and the ones willing to set that up are exactly the ones who would pay for a premium tier. Could be a natural segmentation point.
Also curious - are you seeing any false positives with the Playwright checks? Things like A/B tests or feature flags that change the DOM structure between runs? That is where most synthetic monitoring tools get noisy.
Spot on regarding the CAPTCHA bottleneck.
You’re right—the Free Tier hits a wall if the login is aggressively gated (Cloudflare Turnstile/reCAPTCHA).
How we handle it for Agency Clients:
For high-ticket clients, we whitelist the monitoring IP or inject a specific 'Test Header' that the WAF recognizes to bypass the challenge. That’s exactly where the natural segmentation lies, as you said.
Re: Flaky Tests:
To fight DOM drift (A/B tests), we avoid generic CSS selectors like .btn-primary. We encourage users to add data-testid="login-btn" attributes. If that’s missing, we use Playwright’s 'Locate by Role' which is resilient to layout shifts.
Appreciate the deep dive—rare to see this level of nuance in comments!
The Test Header injection approach for agency clients is clever — using the WAF's own segmentation logic as the bypass mechanism is cleaner than IP whitelisting (no VPN/proxy dependency, and the header can rotate per-client). The natural segmentation point you identified is real: if someone's willing to configure a custom header, they're already in the "serious monitoring" category.
On the data-testid guide — that's genuinely needed. Most dev teams don't think about test resilience until they're debugging a broken CI pipeline at 2am. Making it a proactive habit during component build is the right call.
The 'Locate by Role' fallback in Playwright is underrated for this. Semantic HTML becomes a monitoring asset, not just an accessibility checkbox.
Vajid, this is a smart approach! Testing real user flows is crucial, and your tools seem super practical for catching issues that traditional monitoring misses. Excited to see how the suite performs in real scenarios.
Thanks, Ryan!
The goal was to make 'Synthetic Checks' accessible to everyone, not just enterprises with $500/mo budgets.
Have you had a chance to run it against your own checkout flow yet? Would love to know if it catches anything unexpected.
The "200 OK lie" is such a real problem. I've seen the same thing with documentation — server says everything is fine, but the actual user-facing content is completely stale and misleading.
Really smart move validating the JSON structure and not just status codes. That's where most monitoring tools fall short. The checkout flow simulation is clever too — simulating the actual Stripe/PayPal iframe load is way more useful than just pinging the endpoint.
Are you planning to open source any of it, or keeping it as a managed service? Either way, solid weekend build.
Stale Documentation" is a perfect analogy. The server says one thing, the reality is another.
Right now, I’m keeping it as a Managed Free Service because setting up the headless browser infra (Playwright + dependencies) is a bit annoying for self-hosting. But if the server costs get too crazy, I might just open-source the repo and let people deploy it on their own VPS!
makes sense - loss leader for agency work is smart positioning. we tried freemium first with VibeCheck but honestly free tier was too limiting to build trust. how are you handling the DO costs right now, ballpark per month?
Thanks! And that's a great point about VibeCheck—if the free tier feels too "cheap," people don't trust it for critical ops. That's why I'm trying to keep the "free" limits high (hourly checks) rather than crippling the features.
Re: Ballpark Costs:
To be 100% transparent, my current bill is $0/mo because I’m running on DigitalOcean startup credits ($5k).
If I were paying cash? It would be roughly $40-50/mo for the droplets to run the Playwright workers at this volume. The "Loss Leader" math still works out since one agency client covers that for years.
Hey Vajid! That "200 OK but broken checkout" thing is so frustrating. I've had to debug similar issues where everything looks fine on the surface but users can't actually complete their purchase.
I'd love to test the Checkout Defender. I work with Razorpay a lot (it's big here in India) and would be curious to see how it handles that since most tools focus on Stripe/PayPal.
Quick question - does the API Deep-Check look at nested JSON or just the top level? I've seen bugs where the structure looks fine but nested values are messed up.
Would be great to get beta access and give you some feedback on what I find. Thanks for building this!
Hey DJha! Razorpay is exactly what I need to test next. Since they handle the modal/redirect differently than Stripe, I’d love to see if my Playwright bot catches it correctly.
To answer your question: Yes, the API Deep-Check supports nested JSON. You can define a path like data.user.status and verify it equals active.
I’ll DM you the link. If you can break the Razorpay check, that would be actually helpful for me to fix the edge cases!
Here are the links to the full suite. Since you asked about Razorpay and Nested JSON, I’d recommend starting with #2 and #4:
🛒 Checkout Defender: https://app.pingsla.com/tools/checkout
(I'm really curious if this handles the Razorpay redirect correctly—let me know!)
🔌 API Deep-Scan: https://app.pingsla.com/tools/api-check
(This supports nested JSON validation).
🔐 Login Validator: https://app.pingsla.com/tools/login-check
🔍 Infra Audit: https://app.pingsla.com/tools/audit
Let me know if you manage to break it!
Man, the "200 OK lie" is so real. I've been on the other side of this—monitoring showed green while actual users were hitting silent failures. The gap between "page loaded" and "flow actually works" is exactly where things break quietly. Your Checkout Defender idea especially hits home. Payment gateways can fail in ways that don't throw errors but just... stop converting.
The "200 OK lie" resonates hard. I ran into the exact same pattern with tech stack detection — BuiltWith charges $295/mo for what's essentially HTTP header parsing + some JavaScript fingerprinting. Looked at the price tag, looked at what it actually does, and just built my own API over a weekend in Go.
Your API Deep-Check point is spot on too. Status codes are table stakes. The real value is validating the actual response structure. I do something similar where I validate that detection results actually contain meaningful data, not just a 200 with an empty tech array.
Curious about your headless browser approach for the Login Validator — are you running Playwright or Puppeteer? The infrastructure costs for that must be non-trivial at scale, which probably explains the enterprise pricing you're undercutting.
You hit the nail on the head regarding costs. That’s why Datadog charges $50/mo.
The Stack: I’m running Playwright (not Puppeteer) on DigitalOcean droplets. To keep costs down for the free version, I’m not running checks every 60 seconds. It’s a "Health Check" interval (every 10-15 mins) rather than real-time monitoring.
Re: CAPTCHAs: This is the biggest hurdle. For now, I recommend whitelisting the bot's User-Agent or IP in your WAF, or using a "Test User" account that bypasses 2FA. If you put a CAPTCHA on your login page, my bot will fail (as it should!).
Dude, this is straight up the kind of energy the IH community needs. It's insane how these SaaS companies look at a simple script and think, "Yeah, let's slap a $50/mo recurring price tag on it." Love that you just built the damn thing yourself.
It actually reminds me of why I built my own tool, I got tired of seeing these bloated "risk analysis" platforms charging an arm and a leg for API calls that should be straightforward. So I rolled my own backend that does the heavy lifting without the monthly subscription headache. Just solid logic, no fluff.
Haha, exactly! I looked at the "Enterprise" pricing page and just closed the tab. There is no reason a simple script execution should cost a monthly subscription.
Your DAC_Risk_Engine sounds like the same philosophy—logic over fluff. Keep building! 🚀
"Thanks so much! 🙏 And honestly, your reaction to the Enterprise pricing page is exactly why we built DAC_Risk_Engine the way we did.
Since you clearly get the 'logic over fluff' philosophy, I'd love to pick your brain for a second—because understanding what actually matters to people like you helps us keep it real.
When you looked at that Enterprise pricing page, what was the biggest thing that turned you off? Was it:
The fact that it's a monthly subscription at all?
The lack of transparency about what you're actually paying for?
Or the feeling that you're being forced to pay for a bunch of features you'd never use?
And more importantly if you were to build or buy your ideal risk engine, what's the one thing it absolutely must do (or absolutely must NOT do) to make it worth your time?
Genuinely curious your take would really help shape where we take this."
Happy to help.
To answer your question directly: It’s the 'Black Box Pricing' that kills me.
If I have to 'Talk to Sales' just to find out if I can afford it, I bounce. I want to know: 'Is this $50/mo or $5,000/mo?'
My Ideal Risk Engine:
It needs to be Composable. I don't want a monolith. I want an API I can query: GET /risk-score?user=123. If I have to install a heavy SDK that slows down my frontend, it’s a dealbreaker.
Hope that helps clarify the dev mindset!
The "200 OK lie" problem is so real. On mobile apps it shows up differently but the pattern is the same. Your crash-free rate can be 99.8% while a critical button does nothing because of a logic bug that doesn't throw exceptions.
I don't run a SaaS with checkout flows, but I've had similar silent failures. A "save" button that quietly failed to persist data. An onboarding flow that looked fine but dropped users due to a race condition. Status dashboards are great at catching what you expect to break, terrible at catching what you didn't expect.
The Checkout Defender concept is clever. For anyone selling digital products, the gap between "payment page loads" and "payment actually works" is exactly where revenue leaks happen. Good weekend build.
You nailed it—"Dashboards catch what you expect; reality catches what you didn't."
That "Save button" silent failure is a nightmare. Even though you don't have a Checkout flow, the API Deep-Scan might actually help you there.
You can set it to validate that the "Save" endpoint returns a specific success: true or a simplified new_object_id in the JSON, rather than just a 200 OK. If the race condition hits and returns a 200 but no data, the audit will fail.
🔌 API Deep-Scan: https://app.pingsla.com/tools/api-check
Let me know if that helps catch the "ghosts" in your onboarding flow!
curious how you handle reliability at free tier - with VibeCheck we noticed monitoring infra gets expensive fast when you need real uptime guarantees. are you self-hosting or using edge compute? what made you go free vs freemium?
Great question. You are right—Playwright checks are heavy and expensive compared to simple curls.
Re: Infra:
I am currently self-hosting on DigitalOcean (not Edge Compute). Playwright binaries are too bloated for most standard edge functions right now.
Re: Free vs Freemium:
Right now, this is a "Loss Leader" for me. I run a dev agency (Rizqtek), so I treat the server cost as a marketing expense to build trust.
Eventually, I will introduce a "High Frequency" tier (e.g., check every 1 minute) which will be paid. But for now, the "On-Demand Audit" and "Hourly Health Check" are sustainable on the current droplets.
If you want to stress-test the infra:
🔍 Infra Audit: https://app.pingsla.com/tools/audit
This is cool. I respect weekend builds that solve real operational pain.
Appreciate that, Sumeet!
Operational pain is the best motivator. Let me know if you get a chance to break the tools—I’m still hunting for edge cases.
🛒 Checkout Defender: https://app.pingsla.com/tools/checkout
This hits a real nerve. I've had the exact same experience — uptime dashboard showing green while actual user flows were broken. The disconnect between "server is responding" and "the product actually works" is where real money gets lost.
The Login Validator idea is particularly clever. Most monitoring tools check if the page loads, not if the interactive elements actually function. A form that renders but has a broken submit handler looks fine to every traditional check.
Curious about the implementation though — how are you handling sites with CAPTCHAs or bot protection on login pages? That's usually where headless browser testing gets tricky. Also, what's the check frequency? Running Playwright/Puppeteer checks every 5 minutes adds up fast on server costs, which I imagine is why the enterprise tools charge what they do.
I'd be interested in testing the API Deep-Check on a few endpoints I maintain. The JSON structure validation is way more useful than status codes alone — had a bug once where my API returned 200 OK with an empty array instead of actual data. Technically "working," practically broken.
I’m running Playwright (not Puppeteer) on DigitalOcean. To keep it free/cheap, I don't run checks every 60 seconds. It’s a "Health Audit" (on-demand or hourly) rather than real-time monitoring.
Re: CAPTCHAs:
This is the biggest trade-off. If a site has a strict CAPTCHA on the login form, my bot will fail (as it should!). I usually recommend whitelisting the bot's User-Agent or using a dedicated "Test User" that bypasses 2FA.
For your API Bug (Empty Array):
That "200 OK but empty data" bug is exactly what the API Deep-Scan catches. You can define a rule like "Response JSON must contain data.id".
You can test it here:
🔌 API Deep-Scan: https://app.pingsla.com/tools/api-check
Let me know if it catches that empty array bug for you!
так це правда
100%. The pain of "Silent Downtime" is the same in every language. 😅
Feel free to test the tools if you need them:
https://app.pingsla.com/tools/audit
Love the "Checkout Defender" concept. Silent JS errors are the worst — your server is fine but revenue is bleeding.
I've seen this exact scenario: client had "100% uptime" but Stripe iframe failed for 8 hours. Lost $3k in sales.
How does the headless browser handle rate limiting from payment providers? Do you need to whitelist IPs or does it fly under the radar?
Either way, smart to build this. The $50/mo tools are overkill for most indie hackers who just need "does the critical path still work?"
Would love to try this out for irel.ai checkout flow.
Ouch, the $3k loss is painful. That’s exactly the scenario I built this for.
Re: Rate Limits: Since I’m not spamming the checkout (just checking if the iframe/elements load), I haven’t hit Stripe’s rate limits yet. The bot acts like a "slow" user. It doesn't actually submit the payment, it just verifies the payment form is interactive.
Sending you the link now—would love to see if it works on irel.ai
Hey nivcmo, that $3k loss story is painful. That is exactly why I built this.
Here is the full suite to audit your stack:
🛒 The Checkout Defender: https://app.pingsla.com/tools/checkout
(Run this on your Stripe flow first. It should detect if the iframe fails to load).
🔐 Login Validator: https://app.pingsla.com/tools/login-check
🔌 API Deep-Scan: https://app.pingsla.com/tools/api-check
🔍 Infra Audit: https://app.pingsla.com/tools/audit
Let me know if it works for irel.ai!
This actually seems useful. Real user flow checks are way more accurate than just pinging URLs.
Exactly. Pings are for servers; Flows are for businesses.
If you want to see the difference in action, try the Checkout Defender. It’s the most "real" test in the suite because it actually clicks the payment button.
🛒 Test here: https://app.pingsla.com/tools/checkout
You posed a good problem, but I'd like to solve it in another way. instead of managing a lot of structures.
I'm tired of it even with managing two authentication systems in frontend and backend.
I feel that pain. Syncing auth between FE/BE is enough of a headache without adding more complexity.
The goal with this suite was actually to reduce management. It’s designed as an external "sanity check"—you configure the URL once, and then ignore it. It only bothers you if the flow actually breaks.
It’s less about "managing structure" and more about having a backup alarm when the main structure fails.
Sounds nice , I am just a new founder If I have grown my app to atleast 200 people then I will definietly need this :)
Congrats on starting the journey!
I would argue the opposite, though. When you have 200 users, losing 1 isn't a disaster. When you have 0 users, losing your first signup because the Login button didn't work is fatal.
Since the tool is free, I’d recommend setting up the Login Validator just to be safe. You don’t want your first true fan to bounce because of a silent error!
🔐 Login Validator: https://app.pingsla.com/tools/login-check
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