Comparisons

DenkOps vs Fly.io.

Fly.io runs your app on machines close to your users, across a global set of edge regions, with a deep CLI to match. DenkOps is simpler and EU-focused: an always-on slot with a durable disk and flat pricing, built MCP-first for agents. Here's an honest comparison, including where Fly.io is genuinely ahead.

Start on DenkOps →
01 · The spec, side by side

Read the table.
Then pick.

SpecDenkOpsFly.io
Max run timeUnlimitedUnlimited (per machine)
Persistent diskDurable /persist on every slotVolumes (opt-in, per machine, per region)
Cold startNone (always-on slot)None if kept warm; auto-stop machines add a start delay
Egress defaultBlocked by default, whitelist to allowOpen by default
Pricing modelFlat per slotPer-resource usage (compute, volumes, egress)
Agent / MCP focusMCP-first, deploy from Claude CodeGeneral-purpose, CLI-driven
RegionsEU only30+ global edge regions, multi-region in one app
CLI maturityLightweight, deploy-from-chat focusflyctl: deep, mature, fine-grained control

Those last two rows are real advantages for Fly.io: if your app needs to run in several regions close to users worldwide, or you want a deeply scriptable CLI for machines and volumes, Fly.io is ahead of DenkOps today.

02 · Honest fit

Neither platform
is right for everything.

When DenkOps is the right choice
  • → You're deploying an AI agent or MCP server and want the simplest possible deploy flow
  • → A single EU region is enough, you're not chasing global latency
  • → You want outbound traffic locked down by default rather than open
  • → You want one flat number on the invoice instead of per-resource usage billing
When Fly.io is the right choice
  • → Your users are spread globally and you need the app close to each of them
  • → You want fine-grained control over machines, volumes and regions via a mature CLI
  • → You're comfortable managing fly.toml configuration and want that level of control
  • → You need multi-region failover built into the platform itself
03 · FAQ

Questions people
actually ask.

Is DenkOps a good Fly.io alternative?

Yes, for a single-region API, agent or MCP server that wants a simple, flat-priced slot and a deploy-from-Claude-Code flow. Fly.io is the stronger pick for true multi-region deployment across global edge locations.

Does DenkOps support multi-region deploys like Fly.io?

No. DenkOps runs slots in EU regions. Fly.io's core product is deploying across many regions worldwide with routing to the nearest one, a broader, global-edge capability by design; DenkOps is built for a simple, always-on slot in EU regions instead.

Is Fly.io's CLI better than DenkOps for deploying?

flyctl is mature and full-featured for fine-grained control over machines, volumes and regions. DenkOps trades some of that control for a simpler flow, deploy by saying "deploy on DenkOps" from Claude Code, especially suited to agent and MCP workloads.

Why use DenkOps instead of Fly.io for an AI agent?

DenkOps is MCP-first: deploy and debug an agent from Claude Code with natural language, get a durable disk and unlimited run time by default, and outbound traffic blocked unless whitelisted. Fly.io is a great fit if that agent needs to run close to users worldwide.

04 · Next step

Try it on your own service.

Push what you already have and see how it runs on an always-on slot with a durable disk and zero-trust egress. If you're deploying an API or backend rather than an agent, start with API & backend hosting. Deploying an agent or MCP server instead? See deploy AI agents on DenkOps.

Start on DenkOps →
# any language, any framework
$ ls
main.py requirements.txt
 
› deploy on DenkOps
→ live at https://my-service.denkops.app
slot: always-on · /persist mounted · egress: blocked by default