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cloudf.one vs AWS Device Farm: SG production accounts vs CI test infrastructure

if you are comparing cloudf.one vs AWS Device Farm, you are usually staring at two products that both say “real Android devices in the cloud” and trying to figure out why the prices and use cases look so different.

they look related on paper. they are not solving the same problem.

AWS Device Farm is a CI testing service. you upload a build, it runs your test suite on a fleet of physical devices, you get logs and screenshots back, and the devices reset between sessions. it is built for QA pipelines and per-minute billing.

cloudf.one is a persistent phone rental. you rent a real Samsung in our Singapore datacenter, on a real local SIM, with a real SG mobile IP, and you keep it. log in to apps, warm accounts, run sessions, leave it running. it is built for ops, not for ephemeral CI runs.

picking the wrong one for your workflow is expensive in opposite directions. AWS for ongoing ops will cost a fortune. cloudf.one for a one-off CI suite is overkill on the wrong axis.

what AWS Device Farm actually does

AWS Device Farm is part of the AWS testing stack. it provides physical devices and emulators in AWS’s own racks, instrumented for automated testing.

the core capabilities.

• upload an APK or iOS build, run automated test frameworks (Appium, Espresso, XCTest, Calabash)
• pick from a fleet of real device models across Android and iOS versions
• run remote interactive sessions for manual debugging
• get screenshots, logs, video, and performance metrics back
• per-minute pricing on devices, with parallelism for bigger suites
• integration with CodeBuild, CodePipeline, and the rest of AWS

if your team is shipping a mobile app and needs cross-device QA before each release, AWS Device Farm is built for that. it does its job well. for the broader category, our real device cloud phones for mobile app testing breakdown explains where each kind of device cloud fits.

the ephemeral problem

the design principle that makes AWS Device Farm great for QA is the same one that makes it useless for ops.

devices are wiped between sessions. you do not own the phone. you rent compute time on a phone that will be reset for the next user once your suite finishes. login state, app cache, push tokens, account warming, history, none of it persists.

that is exactly what you want for CI. you do not want test runs polluting each other. you do not want yesterday’s stale account state breaking today’s regression suite.

it is the opposite of what you want for ops. account warming requires the same device, same SIM, same IP, same install state, day after day. wiping that between sessions means starting over every time, which means there is no warming.

cloudf.one is persistent by default. the phone you rent today is the phone you have next week. apps stay installed. accounts stay logged in. the SIM does not change unless you ask. that is what makes it fit for ops, and what makes it the wrong tool for ephemeral CI.

the IP problem

AWS Device Farm’s devices live in AWS racks. the network path is AWS infrastructure. the IPs are AWS ASN ranges, well-known and aggressively scored as datacenter traffic by every fraud engine on the internet.

for QA, that is fine. nobody cares whether your test rig looks like a residential SG user. you are testing your own app on your own build.

for ops, it is a hard stop. if you need traffic that originates from a Singapore mobile carrier IP, AWS cannot give you that. there is no carrier SIM in the device. there is no SG mobile range to route through. the IP is what it is.

cloudf.one is the other extreme. each phone has a real local SIM. the IP is a real Singtel, StarHub, M1, or Vivifi mobile range, depending on the plan. for any workflow that depends on Singapore mobile trust (TikTok, Instagram, WhatsApp, fintech, ad verification), this is not optional. it is the reason the work exists.

a deeper version of the geo argument lives in cloudf.one vs Genymotion Cloud, which covers another cloud Android service that is also great for testing but not built for SG ops.

pricing models pull in opposite directions

the two products price for opposite use cases.

AWS Device Farm: per-minute billing, around $0.17 per device-minute as of late 2025, plus an unmetered option for higher volume. cheap for short test suites. expensive if a device runs all day, every day. a single phone running 8 hours a day, 30 days a month, comes out around $2,400 per device per month. multiply by however many devices you need.

cloudf.one: flat monthly subscription per phone. real handset, real SIM, all in. no per-minute meter, no spike pricing, no surprise bill. one phone running 24/7 for a month costs the same as one phone running an hour for a month.

the math falls cleanly into two camps. CI runs that use a few minutes per device per day are dramatically cheaper on AWS. ops that need a phone running continuously are dramatically cheaper on cloudf.one. the line between the two is the cumulative device-hours per month.

use case fit

a clean way to read this.

AWS Device Farm fits when:

• you ship a mobile app and need cross-device QA in CI
• test runs are short and frequent
• you need broad device coverage (different OEMs, OS versions)
• the work is automated, not interactive
• IP geography does not matter
• device persistence is undesirable

cloudf.one fits when:

• you run accounts on real Singapore mobile networks
• the workflow is interactive or persistent
• account warming, login state, or app trust matters
• one phone runs for hours or days at a time
• the IP must be local SG mobile
• you need ADB control for ops, not just CI

if your work straddles both, you almost certainly need both, not one stretched across both jobs.

the CI vs ops distinction matters

the line that gets blurred is between testing an app and operating it.

AWS Device Farm tests apps. you wrote the app, you want to know whether it crashes on Android 12 on a Samsung Galaxy. perfect fit.

cloudf.one operates accounts within apps. you did not write TikTok. you want a real account, on a real SG phone, running real sessions, surviving real platform-side detection. AWS cannot give you that because the device is ephemeral and the IP is wrong.

teams that try to use AWS for ops eventually discover this the expensive way. test infrastructure is not ops infrastructure. they overlap on hardware but they diverge on everything else.

the AWS Device Farm documentation is explicit about its CI focus. the product is positioned for the test pipeline, not for persistent device rental. that is honest positioning, and it should drive the buying decision.

when teams actually use both

mature mobile teams often run both products in parallel.

• AWS Device Farm in the CI pipeline, triggered on every PR
• cloudf.one for the team running production accounts, ad ops, or SG-specific workflows
• engineers test on AWS, marketing and ops run on cloudf.one
• QA leads pick AWS for cross-device coverage, growth leads pick cloudf.one for warming

this is not double-spending. it is matching infrastructure to the actual job. CI does not need persistent SG SIMs. ops does not need parallel test runs across 50 device models. each tool wins on its surface.

teams that try to consolidate end up either with terrible CI (because cloudf.one is not a test runner) or terrible ops (because AWS wipes between sessions). the consolidation impulse is wrong here. the tools are doing different jobs by design.

the simple decision

if the question is whether your CI pipeline should target AWS Device Farm, the answer is almost certainly yes. it is the right product for that.

if the question is whether your account ops or SG mobile workflow should run on AWS Device Farm, the answer is no. the device model is wrong, the IP is wrong, and the per-minute billing turns into a bill nobody approves.

cloudf.one is built for the second job. real device, real SIM, real SG mobile, persistent rental, flat monthly fee. that is the workflow it covers.

try the layer you do not have

if your team already runs AWS Device Farm for testing and needs real SG account ops or persistent app work, cloudf.one offers a free one hour trial on a real Singapore phone with no card. open the device, run your app on a local mobile IP, and see whether the response from the platform changes.

start the free trial

FAQ

can AWS Device Farm run TikTok ops

technically you can install TikTok and log in. the practical answer is no. the IP is AWS datacenter, the device wipes between sessions, and per-minute pricing makes long warming cycles unaffordable. it is the wrong shape of product for the job.

does cloudf.one support automated testing like Appium

ADB is exposed on every rented phone, so you can drive Appium, Frida, or whatever your stack uses. it works. it is just not priced or designed for short, parallel CI runs across many device models. for that, AWS Device Farm is the right tool.

what about iOS

AWS Device Farm covers iOS. cloudf.one is Android-only because the operational model (real SIMs, ADB control, replaceable hardware) does not transfer to iOS. for iOS QA, AWS or BrowserStack is the answer.

is AWS Device Farm cheaper

for short, automated test runs, almost always yes. for persistent device rental, no, by a lot. the per-minute meter is built for QA, not for daily ops sessions that run for hours.

can I keep an AWS Device Farm device “private” between runs

AWS offers private device fleets at higher tiers, which retain state between sessions for a single account. that is closer to cloudf.one’s model, but the IP is still AWS, the carrier SIM is still missing, and the geography is still wrong for SG-specific work.

do I need to choose one

no. mature teams run both. AWS for CI, cloudf.one for ops and SG-specific workflows. each tool wins on its own surface. running both usually costs less than forcing either to do the other’s job.