Overview Leaderboard Methodology
Industry Report

Container Deployment Platforms

Platforms and services that manage containerized application deployment, scaling, and lifecycle across clusters and cloud providers.

Brands tracked: 38
Brands analyzed: 38
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 293
Total responses: 1,505
Top Brand Overall?
Google
88/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Microsoft
93

Highest score on the LBA metric in this industry.

Authority Leader?
Google
83

Highest score on the Authority metric in this industry.

TOM Leader?
Google
93

Highest score on the TOM metric in this industry.

Google is the default answer in AI responses for Container Deployment Platforms

Google and Amazon together dominate AI responses for Container Deployment Platforms. Both brands consistently surface unprompted, with the model treating them as the default answers for most category queries. Brands outside the top two face a structural disadvantage: users are usually given these two before the model even considers alternatives.

Brand Leaderboard All 38 Container Deployment Platforms brands ranked

Ranked by overall AI Visibility Score (smoothed geometric mean of LBA, Authority, and TOM with an LBA-based floor on Authority and TOM, see methodology). Click any brand for the full report.

# Brand LBA Authority TOM Overall
1
Google
google.com
 88
83
93
88
2
Amazon
amazon.com
 89
66
86
80
3
Kubernetes
kubernetes.io
 90
61
81
77
4
Microsoft
microsoft.com
 93
55
78
74
5
Red Hat OpenShift
redhat.com
 86
47
79
69
6
OpenShift
openshift.com
 82
47
79
67
7
Rancher
rancher.com
 87
18
50
44
8
Nomad
nomadproject.io
 82
8
29
29
9
Render
render.com
 77
12
21
28
10
Terraform
hashicorp.com
 78
8
29
28
11
Docker
docker.com
 87
9
22
27
12
Tanzu
vmware.com
 67
7
33
27
13
Fly.io
fly.io
 83
8
18
25
14
Heroku
heroku.com
 80
8
12
22
15
Railway
railway.com
 79
8
13
22
16
Argo CD
argoproj.io
 87
9
9
21
17
Mirantis
mirantis.com
 76
8
8
18
18
Portainer
portainer.io
 75
8
8
18
19
CapRover
caprover.com
 71
7
7
17
20
Giant Swarm
giantswarm.io
 69
7
7
17
21
Rafay
rafay.co
 71
7
7
17
22
D2iQ
d2iq.com
 63
6
6
16
23
Dokku
dokku.com
 64
6
6
16
24
Humanitec
humanitec.com
 65
7
7
16
25
Platform9
platform9.com
 66
7
7
16
26
Okteto
okteto.com
 61
6
6
15
27
Qovery
qovery.com
 60
6
6
15
28
Akuity
akuity.io
 57
6
6
14
29
Coolify
coolify.io
 57
6
6
14
30
Jelastic
jelastic.com
 58
6
6
14
31
Kubermatic
kubermatic.com
 58
6
6
14
32
Northflank
northflank.com
 54
5
5
14
33
Spectro Cloud
spectrocloud.com
 57
6
6
14
34
Civo
civo.com
 53
5
5
13
35
Gardener
gardener.cloud
 45
5
5
12
36
Koyeb
koyeb.com
 41
4
4
11
37
Cycle
cycle.io
 21
2
2
6
38
Z
Zeet
zeet.co
 18
2
2
5

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 293 shared Container Deployment Platforms prompts. The same prompts, same model, same iterations. So differences in scores reflect actual differences in AI visibility, not differences in measurement.

Overall AI Visibility Score
Smoothed geometric mean of LBA, Authority and TOM. Authority and TOM are floored at LBA × 0.1 before the geometric mean (the same floor used in the per-metric cards above, so brand cards and the composite tell the same story). Formula: composite = ((LBA + 5)(Authority + 5)(TOM + 5))^(1/3) - 5. The floor keeps brands the model clearly recognises but doesn't yet recommend from collapsing to zero, while a single genuinely weak metric still pulls the composite down. Full methodology.
Shared industry prompts
For Authority and TOM, all brands in the industry are scored against the same 293 category prompts (e.g. "best SEO tools for agencies"). This makes brand-to-brand comparisons valid - everyone faces identical inputs. LBA prompts are per-brand because they ask brand-specific questions.
Latent Brand Association (LBA)
5 brand probes + 1 control prompt, each run 5 times in recall mode (no web search). LBA = quality × meta × stability × share × recognition × 100. Read the full LBA methodology →
LLM Authority
50 organic category prompts (discovery, comparison, problem and transactional intents), each run once in recall mode and once in retrieval mode. Score = frequency × log-decayed prominence × intent weight, then 50/50 averaged across the two modes. Read the full Authority methodology →
Top of Mind (TOM)
15 high-volume discovery prompts (sourced from Keywords Everywhere search-volume data), each run 5 times in pure recall mode (no web). Score = frequency × (0.5 + 0.5 × log-prominence), volume-weighted. Read the full TOM methodology →