Overview Leaderboard Methodology
Industry Report

Managed Kubernetes & Container Services

Managed container orchestration platforms that provide hosted Kubernetes clusters, container registries, and related developer tooling for deploying containerized applications.

Brands tracked: 32
Brands analyzed: 32
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 253
Total responses: 1,287
Top Brand Overall?
Google
95/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Microsoft
100

Highest score on the LBA metric in this industry.

Authority Leader?
Google
96

Highest score on the Authority metric in this industry.

TOM Leader?
Google
100

Highest score on the TOM metric in this industry.

Google is the default answer in AI responses for Managed Kubernetes & Container Services

Google and Amazon together dominate AI responses for Managed Kubernetes & Container Services. 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 32 Managed Kubernetes & Container Services 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
 89
96
100
95
2
Amazon
amazon.com
 87
84
100
90
3
Microsoft
microsoft.com
 100
62
87
81
4
DigitalOcean
digitalocean.com
 87
33
63
57
5
OpenShift
openshift.com
 87
19
48
44
6
Red Hat OpenShift
redhat.com
 82
19
48
43
7
IBM
ibm.com
 80
18
45
41
8
Oracle
oracle.com
 77
9
24
27
9
Linode
linode.com
 78
8
13
22
10
Rancher
rancher.com
 86
9
9
21
11
Mirantis
mirantis.com
 72
7
7
18
12
Tanzu
vmware.com
 69
7
7
17
13
Vultr
vultr.com
 71
7
7
17
14
Alibaba Cloud
alibabacloud.com
 67
7
7
16
15
OVHcloud
ovhcloud.com
 65
7
7
16
16
Platform9
platform9.com
 63
6
6
16
17
Scaleway
scaleway.com
 65
7
7
16
18
Spectro Cloud
spectrocloud.com
 67
7
7
16
19
Tencent Cloud
tencentcloud.com
 67
7
7
16
20
Azure DevOps
azure.com
 62
6
6
15
21
Giant Swarm
giantswarm.io
 62
6
6
15
22
Huawei Cloud
huaweicloud.com
 61
6
6
15
23
Kubermatic
kubermatic.com
 59
6
6
15
24
Qovery
qovery.com
 59
6
6
15
25
Rafay
rafay.co
 58
6
6
15
26
Civo
civo.com
 56
6
6
14
27
D2iQ
d2iq.com
 56
6
6
14
28
Northflank
northflank.com
 50
5
5
13
29
Porter
portermetrics.com
 53
5
5
13
30
Kublr
kublr.com
 39
4
4
10
31
Cycle
cycle.io
 28
3
3
8
32
Z
Zeet
zeet.co
 29
3
3
8

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 253 shared Managed Kubernetes & Container Services 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 253 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 →