How do I monitor my API for problems and downtime?

Your API going down is not a technical inconvenience. It is lost revenue, frustrated users, and a support queue that takes days to clear. Gartner puts the average cost of IT downtime at $5,600 per minute, and that number assumes you find out about the problem quickly. Without monitoring, you often find out from a customer complaint.

The good news: a complete monitoring setup costs less than $150/month to run and a few hours to configure. Once it is running, it watches your API around the clock and tells you about problems before your users do.

Most founders start by asking "is my API up or down?" That is a useful question, but not a complete one. An API can be technically online and still be broken, returning wrong data, timing out for half your users, or processing requests ten times slower than normal.

A complete monitoring setup tracks four things.

Response time is how long your API takes to answer a request. Under 200 milliseconds feels instant to a user. Above 2 seconds, they notice the delay. Above 5 seconds, most of them leave. Track this as an average and as a percentile. If 95% of requests are fast but 5% are slow, that slow 5% represents real users having a bad experience.

Error rate is the percentage of requests that return a failure instead of a valid response. A well-built API targets below 0.1% errors under normal conditions. When error rate climbs above 1%, something is wrong. When it climbs above 5%, something is seriously wrong.

Uptime is whether the API responds at all. Tools check this by sending a test request every 1–5 minutes from multiple locations worldwide. If three consecutive checks fail, the API is considered down. Monitoring from multiple locations matters because an API might be reachable from the US but unreachable from Europe.

Traffic volume shows how many requests your API is handling. A sudden spike can cause slowdowns. A sudden drop can mean a client integration broke and stopped sending requests entirely. Both are problems worth knowing about.

A 2024 Catchpoint report found 68% of API incidents were detected by end users before the engineering team. Monitoring fixes that ratio.

Less than the first hour of downtime.

For a straightforward API used by hundreds to low thousands of users, Better Uptime covers the basics at around $20/month. It checks your API every minute, alerts you via text and email when something fails, and gives you a public status page you can share with customers.

For a more complex setup, multiple APIs, detailed performance tracking, dashboards your team can share, tools like Datadog or New Relic run $50–$150/month depending on how many endpoints you are watching. They add deeper visibility: you can see which specific part of a request is slow, not just that the request is slow overall.

A Western agency typically charges $5,000–$15,000 to configure and document a monitoring stack as part of a larger infrastructure engagement. An AI-native team at Timespade sets up the same monitoring configuration, tool selection, alert thresholds, runbook documentation, for under $2,000. The tools themselves are the same. The difference is setup time, which AI-native workflows compress from days to hours.

Every monitoring tool operates on the same principle: send a real request to your API, measure the response, and compare it against what you expect.

The simplest version is a ping check. The monitoring tool calls a health endpoint on your API every 60 seconds and verifies it gets a valid response back. If it does not, that is a potential outage. If three consecutive checks fail, the alert fires.

More sophisticated checks go further. Instead of a generic health endpoint, they call real API functionality, the same requests your users send. They verify not just that the API responded, but that the response contains the right data. An API that responds with an empty list instead of actual results is technically online and technically broken at the same time. A generic ping would miss it. A content-validating check would catch it.

Geographic monitoring adds another layer. Your API might respond fine when called from a server in Virginia, where it is hosted, and time out for users in Singapore because of a routing problem. Monitoring from multiple regions reveals regional failures that single-location checks miss entirely.

The monitoring tool logs every check result. Over time this builds a record of your API's performance history, useful when a client asks why their integration failed last Tuesday, or when you are trying to figure out whether slowness started before or after you deployed a change.

Stripe, one of the most closely watched APIs in the industry, publishes its uptime history publicly. Their target is 99.99%, equivalent to less than 53 minutes of downtime per year. That standard is now the baseline expectation for any API used in a production product.

An alert should fire when a real user is already affected or is about to be. Alerts that fire too often train your team to ignore them. Alerts that fire too rarely let problems grow.

The thresholds that work for most APIs:

• Uptime: alert immediately after three consecutive failed checks. Three failures in a row, spaced 1–2 minutes apart, is a real outage, not a blip.
• Error rate: alert when errors exceed 1% over a 5-minute window. A single failed request is noise. Sustained errors above 1% are a problem worth waking up for.
• Response time: alert when the 95th percentile response time exceeds 2 seconds. This means 1 in 20 users is experiencing a noticeable delay.
• Traffic drop: alert when request volume falls more than 50% below the 7-day average for the same hour. A sudden traffic drop often means a major client's integration stopped working.

Alert routing matters as much as thresholds. An alert that emails a shared inbox at 3 AM and waits for someone to check email in the morning is not monitoring. It is logging with extra steps. Real monitoring sends an SMS or phone call to whoever is on-call, and escalates to a second person if the first does not acknowledge within 15 minutes.

PagerDuty and OpsGenie both handle on-call scheduling and escalation. They integrate with every major monitoring tool and cost $10–$20 per user per month. For a small team, the overhead is worth it. A properly configured escalation policy means a 3 AM outage gets resolved in 20 minutes instead of discovered at 9 AM.

The alert fired. Now what?

The sequence that minimizes damage starts with checking whether the problem is real and what its scope is. Open your monitoring dashboard before touching anything. Is this one endpoint or all of them? Is it affecting all users or users in a specific region? Has the error rate been climbing slowly for hours or did it spike suddenly?

A sudden spike in errors at the same time as a deployment almost always means the deployment caused it. The fastest fix is rolling back that change. A slow climb in response time over several days usually points to a database issue, growing data volume making queries slower, or a query that was always inefficient but only now handles enough records to become a problem.

Post the scope and status in your team channel immediately, even before you know the cause. "API is returning errors for ~15% of requests, investigating" is more useful than silence. If you have a public status page, update it within 5 minutes. Customers who can see that you know about the problem and are working on it are more patient than customers who have heard nothing.

Once resolved, write a brief incident record: what happened, when it started, what caused it, and what change prevents it from happening again. This does not need to be long. It needs to exist. A 2023 Atlassian report found teams that document incidents reduce their mean time to resolve future incidents by 35%, because they stop solving the same problem twice.

Timespade configures API monitoring as a standard part of every infrastructure build. Every project ships with uptime checks, error-rate thresholds, and an on-call routing setup, not as an add-on but as a baseline expectation. If your API is already live but running without monitoring, getting a proper setup in place is a one-day engagement, not a multi-week project.

If you want to walk through what your specific API needs, book a discovery call here.