5 Warning Signs Your API Provider Might Go Down

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5 Warning Signs Your API Provider Might Go DownShib™ 🚀

Originally published on API Status Check TLDR: API outages rarely happen without warning signs....

Originally published on API Status Check

TLDR: API outages rarely happen without warning signs. Learn to spot five key indicators—creeping response times, elevated error rates, status page updates, social media buzz, and recent major changes—that often precede full outages, giving you precious minutes to prepare fallbacks and prevent customer-facing issues.

5 Warning Signs Your API Provider Might Go Down

Full outages rarely happen out of nowhere. Like earthquakes, they're usually preceded by smaller tremors — if you know what to look for.

After tracking 50+ APIs and analyzing hundreds of incidents, we've identified the warning signs that often precede major outages. Spotting these early can give you precious minutes (or hours) to prepare.

1. Response Times Creeping Up

The pattern: API responses that normally take 100ms start taking 300ms, then 500ms, then 2 seconds.

Why it matters: Increasing latency is often the first sign of infrastructure strain. The servers are still responding, but they're struggling. This frequently precedes:

  • Rate limiting kicking in
  • Timeouts
  • Complete unavailability

What to watch:

  • P95/P99 latency, not just averages
  • Latency by endpoint (some might degrade before others)
  • Time-of-day patterns (is it correlated with traffic?)

Real example: Before OpenAI's January 2026 Opus 4.5 incident, users reported gradually increasing response times for about 30 minutes before error rates spiked.

Your action: If you see sustained latency increases (not just a blip):

  1. Check their status page for any advisories
  2. Prepare to enable fallbacks
  3. Consider proactively reducing your request rate

2. Elevated Error Rates (Even Small Ones)

The pattern: Your error rate goes from 0.01% to 0.5%. Still low, but 50x higher than normal.

Why it matters: A small percentage of failing requests often indicates:

  • Partial infrastructure failure (some servers unhealthy)
  • Database issues (some queries failing)
  • Deployment in progress (canary servers having problems)

What to watch:

  • 5xx error rates (server-side problems)
  • Timeout rates (often precedes connection failures)
  • Retry success rates (if retries work, it's transient; if they don't, it's systemic)

Real example: GitHub's January 26, 2026 Windows runner incident showed elevated error rates for about an hour before the official incident was declared.

Your action:

  1. Log error details (specific error codes/messages can help diagnose)
  2. Implement exponential backoff if you haven't already
  3. Check Twitter/X for other developers reporting issues

3. Status Page Shows "Investigating" or "Monitoring"

The pattern: The status page changes from "Operational" to "Investigating" or shows a minor incident.

Why it matters: These interim states are often understated. By the time a provider posts "Investigating," they've already detected something significant. The incident frequently escalates before it resolves.

Status page decoder:

  • Investigating → "Something's wrong, we're figuring out what"
  • Identified → "We know what's broken but haven't fixed it"
  • Monitoring → "We think we fixed it but aren't sure"
  • Resolved → Actually resolved (usually)

Real example: Datadog's January 22, 2026 outage started as "Investigating web application performance" and escalated to a full critical incident within 15 minutes.

Your action:

  1. Subscribe to status page updates (email, webhook, RSS)
  2. Use apistatuscheck.com to see status changes in real-time
  3. When you see "Investigating," assume it might get worse before it gets better

4. Social Media Buzz Increases

The pattern: Tweets mentioning "[API] down" or "[API] slow" start appearing, even if the status page is green.

Why it matters: Users often notice issues before providers acknowledge them. Social media is frequently the first indicator of problems, especially for:

  • Geographic-specific issues (provider might not detect if their monitoring is in a different region)
  • Specific feature failures (main API works, but one endpoint is broken)
  • Authentication/rate limiting issues (not always detected by synthetic monitoring)

Where to watch:

  • Twitter/X: Search "[API name] down" or "[API name] issues"
  • Hacker News: Check for "Is X down for anyone else?"
  • Reddit: Relevant subreddits (r/webdev, r/devops, r/aws, etc.)
  • DownDetector: Crowdsourced outage tracking

Real example: During Supabase's January 28, 2026 incident, tweets appeared roughly 10 minutes before the official status page updated.

Your action:

  1. Set up Twitter alerts for "[your critical API] down"
  2. Join relevant Discord/Slack communities
  3. Trust user reports over green status pages

5. Recent Announcements of Major Updates

The pattern: Provider announced a big new feature, migration, or infrastructure change in the past 24-72 hours.

Why it matters: Change is the enemy of stability. Even well-tested deployments can have issues at scale. The most dangerous time for an API is right after:

  • Major version releases
  • Infrastructure migrations
  • Pricing/plan changes (traffic pattern shifts)
  • Acquisition announcements (team distraction)

Real examples:

  • Many OpenAI incidents correlate with new model rollouts
  • Heroku's reliability issues followed the Salesforce acquisition
  • Major cloud providers often have incidents during re:Invent/Build/Next announcements

Your action:

  1. Follow your critical providers' engineering blogs and changelogs
  2. Be extra vigilant for 72 hours after major announcements
  3. Consider delaying your own deployments during their deployment windows

Bonus: The "Everything Is Fine" Red Flag

Sometimes the most dangerous sign is... nothing.

Watch for:

  • Status page hasn't updated in months (is anyone watching?)
  • No incident history at all (either perfect or not tracking)
  • Status page is itself down (quis custodiet ipsos custodes?)

Transparency is a feature. Providers who acknowledge small issues are usually better at handling big ones.

Build Your Early Warning System

Don't wait for full outages to react. Set up monitoring for:

  1. Latency thresholds — Alert at P95 > 2x normal
  2. Error rate thresholds — Alert at > 0.5% errors
  3. Status page changes — Any status change, not just outages
  4. Social monitoring — Twitter search alerts

Or just use apistatuscheck.com — we monitor all of this for 50+ APIs and surface problems as they develop.

The Bottom Line

The best time to prepare for an outage is before the warning signs appear. The second best time is when you spot the first tremors.

By watching for these five indicators, you can often get 10-30 minutes of lead time — enough to enable fallbacks, alert your team, or proactively communicate with customers.

Stay vigilant out there. 🔍

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