| Audyense Score | 29AS*Bajo | 80ASSólido |
| Posicionamiento | aqua cloud is an AI-driven test management system that aids development teams in organizing tests, scaling testing scenarios, and transitioning seamlessly from manual to automated | Analítica de logs, observabilidad y SIEM nativos de la nube |
| Plan gratuito | Sí | Sí |
| Implementación | Nube / SaaS | Nube / SaaS |
| Mejor encaje | Startup, PYME, Mediana empresa | PYME, Mediana empresa, Empresa |
| Planes de precio | - Free or entry planFree
- Higher tiersCustom pricing
| - FreeFree
- Essentials$0
- Enterprise SuiteCustom pricing
|
| Generative AI (AI Copilot) | SíDocumented in the independently researched profile. | — |
| Capture bug reporting | SíDocumented in the independently researched profile. | — |
| Test management | SíDocumented in the independently researched profile. | — |
| Requirements management tool | SíDocumented in the independently researched profile. | — |
| User Acceptance testing | SíDocumented in the independently researched profile. | — |
| Application testing | SíDocumented in the independently researched profile. | — |
| Built-in bug tracking | SíDocumented in the independently researched profile. | — |
| Automation management. | SíDocumented in the independently researched profile. | — |
| AI features | — | SíAI/ML analytics such as LogReduce, anomaly detection, and an AI assistant (Copilot). |
| Alerting & on-call | — | ParcialRobust monitors, scheduled queries, and webhook alerting; on-call routing via PagerDuty/Opsgenie integrations. |
| Application performance monitoring (APM) | — | ParcialAPM available via OpenTelemetry-based tracing; historically less mature than dedicated APM tools. |
| CI/CD pipelines | — | ParcialNot a CI/CD tool; monitors pipelines via Jenkins, GitHub, and GitLab app integrations. |
| Distributed tracing | — | SíOpenTelemetry-based distributed tracing included in the observability suite. |
| Incident management | — | ParcialSecurity incidents via Cloud SIEM; broader incident workflows through integrations. |
| Infrastructure monitoring | — | SíMetrics plus Kubernetes, Docker, host, and cloud infrastructure monitoring. |
| Log management | — | SíCore capability: real-time ingestion, search, and analytics across many sources. |
| Public API | — | SíExtensive, well-documented REST API for sources, dashboards, searches, and configuration. |
| Self-hosting / on-prem | — | NoSaaS/cloud-only; no on-prem or self-hosted deployment option. |
| Integraciones verificadas | — | 200+ |
| Valoración agregada | 9.5 · No reviews yet | 4.3 · 403 reviews |
| Integraciones | — | AWS CloudTrailKubernetesDockerJenkinsPagerDutyOpsgenie+9 más |
| Seguridad y cumplimiento | — | SOC 2 Type IIISO 27001HIPAAPCI DSS+3 más |
| Pros | - +Independent review documents a concrete business workflow
- +Documented capability: Generative AI (AI Copilot)
- +Documented capability: Capture bug reporting
- +Documented capability: Test management
- +Documented capability: Requirements management tool
| - +Ingesta en tiempo real desde una amplia variedad de fuentes, incluidos logs directos de CDN y de la nube
- +Lenguaje de búsqueda y consultas potente, familiar para los usuarios de Splunk (SPL)
- +API REST extensa y bien mantenida para fuentes, paneles y automatización
- +Amplio catálogo de aplicaciones e integraciones, además de funciones nativas de seguridad/SIEM
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| Contras | - −Pricing and usage limits should be checked against the exact plan
- −Implementation effort depends on the team's data and process maturity
- −Reported outcomes should be validated with the buyer's own data
| - −Los costos pueden aumentar de forma significativa a medida que crecen el volumen de logs y el uso de la plataforma
- −Algunos reseñadores consideran que la interfaz/experiencia de usuario está desactualizada o es poco ágil
- −El rendimiento puede degradarse al consultar conjuntos de datos muy grandes
- −El modelo de precios basado en créditos e ingesta resulta complejo de estimar y negociar
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Audyense