Category · Infrastructure · live data
| # | Brand | Coverage | Presence | Avg rank | SoV | Score |
|---|---|---|---|---|---|---|
| 01 | Datadog |     | 79% | 5.4 | 3.4% | 57 |
| 02 | Dynatrace | | 79% | 5.4 | 3.4% | 57 |
| 03 | OpenTelemetry | | 81% | 5.0 | 3.8% | 63 |
| 04 | GitLab CI/CD | | 68% | 6.3 | 2.8% | 46 |
| 05 | Red Hat Advanced Cluster Management | | 68% | 6.3 | 2.8% | 46 |
| 06 | Rancher | | 68% | 6.3 | 2.8% | 46 |
| 07 | IBM Instana | | 67% | 6.5 | 2.6% | 44 |
| 08 | Portainer | | 67% | 6.5 | 2.6% | 44 |
| 09 | Grafana | | 67% | 6.6 | 2.5% | 42 |
| 10 | Prometheus | | 67% | 6.6 | 2.6% | 43 |
| 11 | OpenShift | | 65% | 7.0 | 2.3% | 38 |
| 12 | GitHub Actions | | 65% | 7.0 | 2.3% | 38 |
| 13 | Northflank | | 66% | 6.9 | 2.3% | 39 |
| 14 | Elastic Observability | | 65% | 7.0 | 2.3% | 38 |
| 15 | Harness | | 56% | 7.2 | 2.1% | 35 |
| 16 | CircleCI | | 64% | 7.2 | 2.1% | 35 |
| 17 | Honeycomb | | 54% | 7.8 | 1.7% | 28 |
| 18 | SigNoz | | 54% | 7.8 | 1.6% | 27 |
| 19 | New Relic | | 54% | 7.9 | 1.6% | 26 |
| 20 | Jaeger | | 65% | 7.0 | 2.3% | 38 |
Presence = share of prompts where the brand is cited · Avg rank = mean position when cited · SoV = share of voice across the category · First measured edition; trends begin next edition.
Which cloud & devops brands are most cited by AI assistants?
Datadog ranks #1 with a score of 57/100, ahead of Dynatrace (57/100) and OpenTelemetry (63/100). Measured across ChatGPT, Perplexity, Gemini and Claude for the query “best DevOps and cloud infrastructure platform 2026”.
Do AI assistants agree on which cloud & devops brands to recommend?
Engine opinions diverge significantly in cloud & devops: no brand is cited identically by all four assistants. Gemini in particular surfaces brands the other engines do not mention. This reflects differences in each engine training data and retrieval sources rather than a single correct ranking.
Which cloud & devops brands are invisible to AI assistants?
4 of 20 brands are cited by one engine or fewer, including Harness, Honeycomb, SigNoz. Being functionally invisible to AI assistants ahead of a high-intent buyer query is a growing risk for vendors with otherwise solid market presence.
How is the AI visibility score calculated, and how is it different from SEO?
The score (0–100) combines five dimensions: coverage across engines, presence rate, average rank when cited, share of voice, and citation consistency. Unlike SEO, it measures whether a model names your brand inside its synthesized answer — not whether a link ranks on a results page. Full methodology at /methodology/.