When Your Outage Monitor Goes Down: Downdetector, Cloudflare, and the Real Cost of “No Dependencies”
If you have ever checked Downdetector during a major internet incident, you probably assume it is built to survive exactly that moment. So it is a little jarring to learn that during a Cloudflare outage, Downdetector itself went down too. At first glance, it sounds like an avoidable architectural mistake.
It is not. It is an economic decision wearing an engineering costume.
The Core Insight
The interesting lesson in the Downdetector story is not “avoid dependencies.” It is that dependencies are often a deliberate trade that buy you performance, security, and operational simplicity at a cost you do not see until the dependency fails.
In the source article, Gergely Orosz describes how Downdetector is built multi-region and multi-cloud. That part makes sense when you remember Downdetector is effectively a “meta-monitor”: it needs to keep reporting even when a cloud provider is the outage.
But Downdetector still relies on Cloudflare for critical edge layers:
- DNS
- CDN delivery
- Bot protection
That edge stack is not just a performance enhancement. It is a major piece of “keeping the lights on” for a consumer-facing site that can get slammed by traffic spikes precisely when the internet is on fire.
Replacing Cloudflare with a self-hosted equivalent is not a single project. It is an ongoing operational burden: distributed caching, global routing, DDoS resistance, bot mitigation, capacity planning for flash crowds, and the ability to change any of that quickly under pressure.
Downdetector’s engineering leadership (quoted in the piece) notes that redundancy at the DNS and CDN layers would require “enormous overhead,” and that Cloudflare’s bot protection is “world-class.” They also highlight a subtle operational detail: during the outage, Cloudflare’s dashboard was unavailable, but the API still worked, meaning Infrastructure as Code could have restored service faster.
That last point is the real engineering nugget: you cannot eliminate all upstream risk, but you can design your ops pathways to be resilient to partial failures (control plane vs API, web console vs automation).
Why This Matters
“Dependency-free” architectures are popular in postmortems, design reviews, and hiring interviews because they sound like purity. In practice, they are expensive. Most teams do not pay that bill up front, and many businesses cannot justify it.
Downdetector is a particularly sharp example because its usage spikes align with the worst possible time to be wrong about your edge strategy. But the same dynamic shows up in many products:
- A B2C app that depends on an identity provider and then cannot log users in during an auth outage.
- A SaaS product that depends on a single observability vendor, and loses the dashboards during an incident.
- A “multi-cloud” service that is still single-vendor at the DNS, CDN, or WAF layer.
The deeper reason this matters is that edge dependencies are often invisible until they are not. A product can be multi-region, have strong failover at the compute layer, and still be effectively single-point-of-failure if traffic cannot reach it or gets blocked.
There is also a business-model angle that engineers sometimes underweight. Downdetector is free for consumers and not heavily monetized per visitor. If removing Cloudflare increases cost substantially but does not increase revenue, the “more independent” architecture is not automatically better. It may be irrational.
This is not an argument for accepting fragility. It is an argument for aligning reliability investment with what you are actually optimizing for: user trust, regulatory obligations, contractual SLOs, brand damage, and the real cost of downtime.
Key Takeaways
- Dependencies are not inherently bad. The question is whether you understand the failure modes and the price of reducing that risk.
- “Multi-cloud” often stops at compute. Treat DNS, CDN, WAF, and bot protection as first-class resilience layers.
- During outages, the control plane may fail differently from the API. Design so automation can operate when dashboards cannot.
- If your traffic spikes during crises, your edge strategy is part of your incident response plan, not just performance tuning.
- Business model matters: independence that multiplies cost without increasing revenue may not be sustainable.
Looking Ahead
A practical way to use this story in your own system design is to turn it into a checklist for “edge dependencies.” Here is a concrete, executable approach:
- List your true upstream single points of failure. Include DNS, CDN, WAF, bot protection, and email or SMS providers if they affect login or alerts.
- Write down the blast radius for each one. What exactly breaks if this service is degraded: new sessions, static assets, API calls, admin actions, or all traffic.
- Decide which mitigation is worth it. Options include dual providers (expensive), conditional bypass modes (risky), degraded-but-available fallback pages (useful), and operational playbooks.
- Automate the “break glass” actions. If you need to disable bot protection or reroute traffic, ensure it is possible via API and exercised regularly. Do not require a web dashboard during a control-plane incident.
- Treat vendor failures as game days. Simulate partial outages: dashboard down but API up, regional degradation, or misfiring security controls that block legitimate users.
The contrarian risk point: redundancy itself can create complexity and new failure modes. Dual-CDN or multi-DNS setups are easy to get wrong, and you can end up with split-brain configuration, inconsistent caching behavior, or a security posture that is only as strong as the weakest provider.
The goal is not purity. The goal is to spend reliability budget where it buys the most user impact reduction per unit of complexity.
Sources
- Downdetector and the real cost of no upstream dependencies (The Pragmatic Engineer)
https://blog.pragmaticengineer.com/downdetector-and-the-real-cost-of-no-upstream-dependencies/
Based on analysis of Downdetector and the real cost of no upstream dependencies (The Pragmatic Engineer) https://blog.pragmaticengineer.com/downdetector-and-the-real-cost-of-no-upstream-dependencies/