Azure Performance Monitoring

AIMS provides automated 360° performance monitoring and analytics for Azure components. You get automated monitoring of parameters out of the box with no manual alert or threshold configuration.

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  • Why AIMS
  • Azure monitoring and analytics powered by AI
  • What is monitored on Azure?

Why use AIMS for Azure performance monitoring?

AIMS is the only performance monitoring and analytics solution for Azure that combines the latest AI and machine learning technology with a deep focus on integrations. With AIMS, you get AI to detect anomalies on your Azure components, and the ability to automatically correlate any issues in Azure to on-premises applications.

Fully automated

AIMS maps, learns and monitors your systems automatically

Artificial Intelligence

Automatically set dynamic thresholds down to the most granular level

Machine learning

The longer AIMS is installed, the more accurate it becomes

Extensive real-time analytics

Engage system owners, LoB owners and CxOs

Monitoring of Azure components is enabled from within AIMS by authentication towards Azure and is done in a couple of minutes.

See all AIMS capabilities

Azure monitoring and analytics powered by AI

Predictive anomaly detection

AIMS can predict anomalies within a single system and across systems. Using machine learning, AIMS detects when behavior is heading out of normal ranges and alerts you earlier – so you can take action to prevent performance issues, scaling issues and cost issues related to scaling.

Visualize Azure integrations

AIMS automatically generates a dynamic, 360° topological map of all systems participating in the integration flow. View systems from a bird’s-eye perspective to get a complete overview of your whole integration setup, or drill down to systems and individual apps.

Real-time Azure analytics

Drill down into any service, component or performance parameter using AIMS powerful analytics tools. Create health reports, identify the root cause of performance issues, verify SLA requirements, plan for scaling and more.

What is currently monitored on Azure?

Logic Apps

Workflow parameters; successful runs, workflow latency, workflow failed runs, trigger successful runs, trigger latency (average), trigger failed runs, action successful runs, action latency (average), action failed runs. Data per individual action / trigger soon to come

Service Bus

Queues (scheduled messages, transfer messages, transfer dead messages, messages, active messages, dead messages, total size), Topics (scheduled messages, transfer messages, transfer dead messages, active messages, dead messages, total size), list of connected Service Buses

Futureproof Guide for Microsoft Integrations

Read this expert guide and make sure your current Microsoft integration is ready to meet tomorrow's requirements – from BizTalk to hybrid to Azure.