Fly.io vs Google Cloud Run
A side-by-side, data-driven comparison of Fly.io and Google Cloud Run — pricing, free tiers and capabilities.
Fly.io focuses on running containers close to users across its own global edge network with persistent-app defaults, whereas Cloud Run is a managed GCP service centered on request-driven autoscaling and scale-to-zero within Google Cloud regions.
At a glance
- Google Cloud Run has a free tier — note: Perpetual monthly free allowance: 2M requests, 180,000 vCPU-seconds, 360,000 GiB-seconds of memory, and 1 GiB of North America egress; Fly.io does not.
- Fly.io includes a managed database; Google Cloud Run does not.
Specs side by side
| Fly.io | Google Cloud Run | |
|---|---|---|
| Category | Container hosting | Container hosting |
| Pricing model | usage-based | usage-based |
| Free tier | No | Yes |
| Managed database | Yes | No |
| Regions | 30+ | 40+ (GCP regions) |
| Self-hostable | No | No |
| Docker-native | Yes | Yes |
| Git deploy | No | Yes |
| Open source | No | No |
Pros & cons
Our editorial assessment — not vendor-stated facts. Last reviewed 2026-07-16.
Fly.io
Pros
- Runs full Docker containers globally, not just functions, so it fits stateful and long-running apps
- CLI- and config-driven workflow makes provisioning multi-region deployments straightforward
- Usage-based billing charged per second, with no required monthly plan commitment
- Places compute close to users, which suits latency-sensitive applications
- Includes stateful primitives (volumes, managed Postgres, private networking) that many edge/PaaS platforms lack
Cons
- Has had publicized reliability incidents in recent years (some community reports attribute past outages to internal service-discovery systems); check Fly's status page and recent incident history before committing
- Uptime SLA is offered only to Enterprise-plan customers; standard pay-as-you-go usage carries no contractual uptime guarantee
- Billing can be hard to predict once you scale across instances and regions, and some users report unexpected charges
- CLI- and config-first, region-centric model has a steeper learning curve than conventional click-to-deploy PaaS
Google Cloud Run
Pros
- Scale-to-zero means no charge when the service is idle
- Deploys any container image without framework or language lock-in
- Generous perpetual free monthly allowance for low-traffic workloads
- Deep integration with the broader Google Cloud platform and services
- Automatic HTTPS, request-based autoscaling, and managed infrastructure
Cons
- Cold starts can add latency when scaling from zero unless minimum instances are set
- GCP's IAM, networking, and project setup add a learning curve versus simpler PaaS tools
- Network egress and cross-service traffic can add costs beyond compute
- Per-request/usage billing makes costs harder to predict for sustained high traffic
- No built-in managed database; state must come from separate GCP services
Bottom line
Pick Fly.io for latency-sensitive apps that need multi-region by default. Pick Google Cloud Run for bursty or event-driven container workloads on GCP.
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Frequently asked questions
- What is the difference between Fly.io and Google Cloud Run?
- Fly.io: Runs full-stack apps and Docker containers as lightweight VMs in many regions, with a focus on low-latency, globally-distributed deployments. Google Cloud Run: Google Cloud Run is a managed compute platform that runs stateless containers and scales them automatically, including down to zero when idle. It is part of Google Cloud and bills on a usage-based, pay-per-use model.
- Does Fly.io have a free tier?
- No.
- Does Google Cloud Run have a free tier?
- Yes. Perpetual monthly free allowance: 2M requests, 180,000 vCPU-seconds, 360,000 GiB-seconds of memory, and 1 GiB of North America egress.
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