---
title: "What to Do When Your Cloud Provider's Metrics Are Degraded"
description: "When a provider like Fly.io reports degraded metrics, the risk is often misunderstood. Here's what it means and how to protect your production workloads."
date: "2026-02-24"
author: "ScribePilot Team"
category: "general"
keywords: ["Fly.io incident", "degraded metrics", "cloud reliability", "observability outage", "edge cloud monitoring"]
coverImage: ""
coverImageCredit: ""
---
What to Do When Your Cloud Provider's Metrics Are Degraded
Picture this: you check your cloud provider's status page and see "Metrics Are Degraded" in yellow. Not red. Not "Major Outage." Just... degraded. You shrug, maybe, and move on. That instinct is exactly why a Fly.io incident like this, or the same event on any edge-cloud platform, can catch teams off guard. A metrics degradation event isn't a minor inconvenience. It's an operational blind spot, and it deserves a serious response.
Let's break down what degraded metrics actually mean, why they can be more dangerous than a brief full outage, and what your team should do the next time it happens.
Degraded Metrics vs. a Full Outage: Why the Distinction Matters
When a provider reports a full outage, everyone scrambles. Slack channels light up. Incident response kicks in. There's clarity: things are broken, and you act accordingly.
Degraded metrics are sneakier. Your application might be running fine, or it might not, and you can't tell the difference. Here's what typically breaks down during a metrics degradation event:
- Monitoring dashboards go stale or show gaps. You're looking at data that's minutes or hours old, or simply incomplete.
- Alerting pipelines stop firing. If your alerts depend on provider-side metrics (CPU, memory, request latency), they go silent. Not because everything is healthy, but because the data feeding them has stopped.
- Auto-scaling stops responding. Scaling policies that rely on real-time metrics won't trigger. Your app could be drowning in traffic with no additional instances spinning up.
- SLA tracking becomes unreliable. If you're reporting uptime or latency to your own customers, a gap in metrics means a gap in your SLA evidence.
The Real Impact on Production Workloads
For teams running production workloads on platforms like Fly.io, degraded metrics create a cascade of secondary problems. Your on-call engineer sees a quiet dashboard and assumes things are stable. Meanwhile, a memory leak goes undetected, or a region starts dropping requests without triggering a single alert.
The hot take here: a metrics outage can be worse than a brief service outage. A service outage is loud. It gets attention and gets fixed. A metrics gap is silent, and the damage it hides might not surface until your users start complaining on Twitter.
This is especially true on edge-cloud platforms, where workloads are distributed across many regions. If metrics from one or two regions go dark, the aggregate dashboard might still look "mostly green," masking localized failures.
What You Should Do: Before, During, and After
Don't wait for the next status page update to figure out your plan. Here's what we recommend:
Before an incident happens:- Set up external monitoring. Use a third-party tool (Datadog, Grafana Cloud, even a simple uptime checker like Uptime Robot) that doesn't depend on your provider's metrics pipeline. If the provider's observability goes down, yours shouldn't.
- Build an incident response playbook that specifically covers "provider observability degradation" as a scenario. It's different from a full outage and requires different steps.
- Track SLA data independently. Don't rely solely on your provider's dashboards for compliance evidence.
- Switch to external monitoring immediately. Trust your own instruments over the provider's stale data.
- Manually verify critical services. Hit your health check endpoints directly. Check logs from your own logging stack.
- Communicate proactively with your users. If you can't confirm things are healthy, say so. "We're investigating potential impact" is better than silence followed by an apology.
- Audit the gap. Look for anomalies during the window when metrics were unavailable. Errors, latency spikes, and failed requests may have gone unrecorded.
- Review your alerting dependencies. If every alert in your system relies on provider-side metrics, that's a single point of failure. Fix it.
The Bigger Picture
Every cloud provider, from the hyperscalers to edge platforms like Fly.io, will experience observability incidents. It's not a question of if. The question is whether your team treats "metrics are degraded" with the same urgency as "services are down." If the answer is no, you've got a gap in your incident response that's waiting to bite you.
Build your monitoring like you don't trust your provider. Because one day, for a few hours, you won't be able to.