Best AIOps Tools for Azure DevOps

Find and compare the best AIOps tools for Azure DevOps in 2026

Use the comparison tool below to compare the top AIOps tools for Azure DevOps on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Cloudgeni Reviews

    Cloudgeni

    Cloudgeni

    $79 per month
    Cloudgeni serves as an intelligent AIOps platform tailored for cloud infrastructure, adept at analyzing incidents, compliance, drift, and financial operations issues, subsequently rectifying them through validated Infrastructure-as-Code pull requests. It consolidates cloud states, Infrastructure-as-Code, and operational signals into a unified context layer, enabling agents to grasp dependencies, pinpoint root causes, implement changes aligned with the organization's standards, validate these changes prior to deployment, and confirm the resolution of issues post-implementation. The platform's agents are equipped to handle various tasks, including compliance remediation, managing configuration drift, resource imports, DevOps activities, pull request evaluations, Infrastructure-as-Code pipelines, cost management, Site Reliability Engineering workflows, AI infrastructure governance, and bespoke automation solutions. Additionally, Cloudgeni seamlessly integrates with a multitude of platforms and tools such as AWS, Azure, GCP, OCI, Kubernetes, OpenShift, Terraform, OpenTofu, Terragrunt, Bicep, Pulumi, Helm, GitHub, GitLab, Azure DevOps, security instruments, observability solutions, and internal knowledge repositories, fostering a comprehensive ecosystem for cloud management. This versatility ensures that organizations can maintain optimal performance and security across their cloud environments while streamlining their operational processes.
  • 2
    BMC AMI Ops Reviews
    BMC AMI Ops is a mainframe AIOps and observability solution designed to help enterprises modernize operations, improve resilience, and reduce operational cost. The platform gives teams centralized visibility across mainframe systems, subsystems, applications, networks, storage, databases, batch workloads, and messaging environments. It helps operations teams detect issues earlier, reduce mean time to detect, avoid downtime, and maintain high service availability. BMC AMI Ops uses self-learning AI and machine learning models to continuously adapt to system behavior and improve anomaly detection accuracy. Embedded GenAI translates findings into context, impact, and guided remediation so teams can understand what happened and what to do next from inside the dashboard. The platform also supports OpenTelemetry-compliant streaming, allowing mainframe telemetry to connect with enterprise observability tools. BMC AMI Ops includes capabilities for CICS performance control, Db2 optimization, IMS visibility, MQ message management, Java workload monitoring, batch optimization, network visibility, storage oversight, and cost analytics. Automation features help reduce manual tasks, improve operational consistency, and lower CPU and MIPS consumption. By combining AI-driven monitoring, observability, automation, alert consolidation, and remediation guidance, BMC AMI Ops helps mainframe teams operate critical systems more efficiently and reliably.
  • Previous
  • You're on page 1
  • Next