How to get picked for cloud by coding agents
AWS took 63% of 359 judged cloud sessions. What the numbers say a vendor in this category should do.
If you sell cloud providers, this page is the part of the market no dashboard shows you: what a coding agent does when a developer asks for cloud and never compares vendors.
The numbers come from 359 judged sessions with Claude Code, Codex, Cursor, Grok Build CLI and Muse Code, spread across 6 realistic codebases, with every session read by a judge.
What coding agents choose for cloud
Across 359 judged sessions, AWS was chosen most often, in 63% of runs. Google Cloud was second with 17%.
| # | Product | Runs won | Share |
|---|---|---|---|
| 1 | AWS | 226 | 63% |
| 2 | Google Cloud | 60 | 17% |
| 3 | Cloudflare | 21 | 6% |
| 4 | Upstash | 18 | 5% |
| 5 | Inngest | 9 | 3% |
| 6 | Cloudflare + Upstash | 6 | 2% |
| 7 | Vercel Queues | 3 | 1% |
| 8 | Built in-house (no product adopted) | 2 | 1% |
| 9 | Render | 1 | 0% |
| 10 | Vercel Blob + Vercel Queues | 1 | 0% |
Full board, every run replayable: the cloud leaderboard.
What the shape of this category means
One product takes 63% of runs. This category is close to decided, and a challenger does not win it with content this quarter.
AWS is in the training data, in the templates and in the repositories. At 63% of 359 sessions an agent reaches for it without deliberating.
No amount of writing changes that this quarter. What Google Cloud and the rest of the field can do is narrow: there are always requests the default fits badly, and those are winnable in full.
What does work is narrowing. Find the requests where the leader is a bad fit and own those completely. Regional requirements, a pricing model the leader does not offer, a compliance constraint, a stack the leader supports poorly. Write those pages in the words the request uses.
And check the persona split below. A category can be decided for one kind of buyer and open for another.
The agents do not agree with each other
In this category Claude Code, Codex and Cursor all put AWS first, which is less common than it sounds: across the 31 categories we measured, Claude Code and Codex disagreed on the leader in 16 of them.
Grok Build CLI (18 sessions) and Muse Code (54 sessions) join this table with fewer runs, so read their rows as indicative.
| Agent | Runs | Picked most often |
|---|---|---|
| Claude Code | 90 | AWS (52) |
| Codex | 108 | AWS (71) |
| Cursor | 89 | AWS (57) |
| Grok Build CLI | 18 | AWS (11) |
| Muse Code | 54 | AWS (35) |
Even where they agree, they get there differently. In this category Codex ran a web search in 96% of its sessions and Claude Code in 14%, so what you publish reaches nearly all of Codex's cloud sessions and a minority of Claude Code's.
Who is asking changes the answer
Every request was written as a specific kind of person. In this category AWS led for every persona, which is a sign of a strong default.
| Who is asking | Runs | Picked most often |
|---|---|---|
| Senior engineer | 239 | AWS |
| Enterprise team | 120 | AWS |
What you are really competing against
In 1% of runs the agent wrote the code itself rather than adopting a product. That is low enough that your competition is other vendors, but high enough to be worth watching.
Considered, and never chosen
Because the judge records every product an agent raised and not only the one it picked, this board also shows who kept reaching the shortlist and losing. In cloud the clearest case is MinIO: on the table in 129 sessions, chosen in none.
| Product | Raised in | Chosen in |
|---|---|---|
| MinIO | 129 sessions | 0 |
| Microsoft Azure | 105 sessions | 0 |
Being rejected is a better position than being unknown, and a cheaper one to fix. The product is already in the agent's head and on the list. Whatever ended those 234 sessions is recorded in each transcript, one reason at a time.
What to do about it in cloud
- Do not attack AWS head on. At 63% it is the default an agent reaches for without deliberating. Find the requests where it fits badly, which in our data means regional requirements, a pricing model it does not offer, a compliance constraint or a stack it supports poorly, and own those in the words the request uses.
The work that applies to every category rather than to this one is written up separately: audit your documentation, write a quickstart an agent can follow, and how to measure install share.
Every cloud provider on this board
One page per product, with its install share, the per-agent split, and how often it was raised without being chosen.
- Do coding agents recommend AWS? — chosen in 63% of sessions
- Do coding agents recommend Google Cloud? — chosen in 17% of sessions
- Do coding agents recommend Cloudflare? — chosen in 6% of sessions
- Do coding agents recommend Upstash? — chosen in 5% of sessions
- Do coding agents recommend Inngest? — chosen in 3% of sessions
- Do coding agents recommend Render? — chosen in 0% of sessions
- Do coding agents recommend MinIO? — raised in 129 sessions, chosen in none
- Do coding agents recommend Microsoft Azure? — raised in 105 sessions, chosen in none
Where these numbers come from
359 judged sessions in cloud across 6 codebases, part of a published set of 15,287. Real coding agents at pinned versions, in sandboxes, inside realistic codebases, with a simulated project owner in the loop and a blind judge on every session. The full method is on one page: how we measured this.
Every cloud run can be replayed on the board.
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Common questions
How many codebases is this based on?
359 judged sessions across 6 realistic codebases. A category only runs on repositories where its seam is open, so coverage differs: some categories ran on more than ten codebases and some on two.
What cloud provider do coding agents choose?
Across 359 judged sessions, AWS was chosen most often, in 63% of runs. Google Cloud was second with 17%. Every agent put AWS first.
Do Claude Code and Codex pick the same cloud provider?
Yes. Claude Code and Codex both put AWS first in this category, which is less common than it sounds: they disagree on the leader in 16 of the 31 categories we measured.
How often do agents build cloud themselves instead of installing something?
In 1% of runs the agent wrote the code itself rather than adopting a product.
How can a vendor improve its position here?
Make the quickstart run when pasted, state the current version on the documentation page, use one name across product, package and import, write pages for the symptoms users describe rather than only the category name, and get into the repository through templates and framework integrations.
Which cloud providers do agents consider but never choose?
MinIO (raised in 129 sessions, chosen in none), Microsoft Azure (raised in 105 sessions, chosen in none). Being considered and not chosen is a different problem from being unknown, and it is usually fixable.
Where this comes from
Armature ran 15,287 judged sessions with Claude Code, Codex, Cursor, Grok Build CLI and Muse Code inside 110 realistic codebases, and published every run. The numbers on this page come from that work.