ManageEngine OpManager Features

Continuously monitors network performance across the entire span of a network.

Sends alerts via pop-up notifications, texts, emails, or calls regarding network issues or failures.

Suggests potential remedies or improvements to slowdowns, errors, or failures.

Provides monitoring capabilities for multiple networks at once.

Monitor usage and activity on a diverse array of IT systems, e.g., servers, databases, and networks.

Generate real-time high-level and/or in-depth analytics regarding monitored systems activity.

Generate insights into IT systems utilizing event metrics, logging, traces, and metadata.

Integrate AI and/or machine learning capabilities to identify and address potential and active failures and errors.

Monitors and test apps to address issues before they affect end users.

Provides dynamic end-to-end maps of every single transaction.

Automatically adjusts resources base on application usage.

Monitors cloud microservices, containers, kubernetes, and other cloud native software.

Sets a standard performance baseline by which to compare live network activity.

Charts or graphs live and historical network performance for quick status checking and analysis.

Gives insights into which specific network paths are performing suboptimally.

Consolidate IT systems monitoring overviews to a single pane for quick insights.

Offer pre-built and custom reporting and dashboards for quick insights into system states.

Set expected baselines for system functions.

Create and distribute detailed alerts via email, phone, and messaging for potential and active failures and errors.

Automate how physical and virtual devices are configured, handled, tested, deployed, and operated inside a network.

Record and analyze the traffic on network.

Ensure that only certain users have access to a system.

Analyze network data to identify trends and patterns.

Infrom user of upgrades and repairs to network resources.

Presents information and analytics in a digestible, intuitive, and visually appealing way.

Clearly notifies team members with relevant information and anomalies in a timely manner.

Creates reports outlining load distribution, performance and other relevant metrics.

Allows users to track and control resource spend and loads across multiple servers.

Automatically allocates resources to optimize loads across servers.

Sets a standard performance baseline by which to compare live server activity.

Constantly monitors server to detect anomalies in real time.

Ability of the monitoring software to immediately alert the user in case of any issue.

Deploys remedial actions proactively. If this measure fails, then the user is alerted.

Automates all the key operations of a datacenter infrastructure.

Captures changes in hardware configurations, software installation, or virtual machines.

Tracks power, cooling, CPU usage, servers etc in real time and trigger alarms

Monitors CPU usage, disk activity and memory usage

Tracks and monitor building meters, UPSs , floor and rack PDU’s and environment sensor to notify unusual events

Tracks and manage rack, equipment, tray space to better utilize the capacity

Monitor the performance of network resources, such as switches, routers, and servers.

Automatically discover network assets.

Build map of network resources based on dependencies and connections.

Captures and analyzes each transaction by users of a website or application in real time.

Provides high-frequency metrics data.

Supports public, hybrid and private cloud environments.

Software can scale as the enterprises adds more servers to their portfolio virtually.

Notify user when network related error arise.

Supports cloud and LAN, including hybrid infrastructure

Provide API and custom sensors for easy integration.

Offers full observability of all network environments, including on-premises, cloud, SD-WAN, WLAN, and edge computing.

Automatically detects and maps all network devices and architectures, reducing manual effort and improving visibility.

Provides true real-time network monitoring to detect and resolve issues instantly, rather than relying on near-time data.

Uses AI-driven analysis of historical and real-time data to forecast network issues before they impact performance.

Combines packet and flow analysis techniques to provide a comprehensive view of network traffic and performance.

Ensures all monitored network data is securely encrypted both in transit and at rest.

Supports integration with Zero Trust frameworks and identity management solutions to enhance network security.

Unifies network performance monitoring with security intelligence to identify and mitigate threats in real-time.

Continuously analyzes and adjusts network configurations to optimize performance and reliability.

Automates routine network monitoring tasks, reducing operational overhead and human error.

Uses machine learning to identify network anomalies, preventing security and performance issues before they escalate.

Automates corrective actions for common network issues, reducing downtime and manual intervention.

Leverages AI to anticipate hardware failures, capacity issues, and performance bottlenecks before they occur.

Ingests and processes multiple telemetry types, such as logs, metrics, and traces.

Supports ingestion and standardization of observability data via OpenTelemetry protocol.

Displays relationships between services to visualize system dependencies.

Provides a consolidated view of system-wide telemetry in a single dashboard.

Allows users to explore and visualize distributed traces and span relationships.

Correlates logs, metrics, and traces to surface performance patterns and root causes.

Identifies likely causes of issues using system insights and correlation logic.

Automatically alerts users to anomalies or critical events using contextual data.

Provides observability into containerized workloads and Kubernetes clusters.

Enables observability across public cloud, private cloud, and on-prem environments.

Forecasts future system issues based on historical performance trends.

Summarizes incident root causes and potential fixes using generative AI.

Uses machine learning to detect unusual behavior across telemetry data.

Capability to perform complex tasks without constant human input

Ability to break down and plan multi-step processes

Works across multiple software systems or databases

Improves performance based on feedback and experience

Engages in human-like conversation for task delegation

Anticipates needs and offers suggestions without prompting

Makes informed choices based on available data and objectives

Capability to perform complex tasks without constant human input

Works across multiple software systems or databases

Improves performance based on feedback and experience

Anticipates needs and offers suggestions without prompting

Makes informed choices based on available data and objectives

Capability to perform complex tasks without constant human input

Ability to break down and plan multi-step processes

Works across multiple software systems or databases

Improves performance based on feedback and experience

Engages in human-like conversation for task delegation

Anticipates needs and offers suggestions without prompting

Makes informed choices based on available data and objectives

Capability to perform complex tasks without constant human input

Ability to break down and plan multi-step processes

Works across multiple software systems or databases

Improves performance based on feedback and experience

Engages in human-like conversation for task delegation

Anticipates needs and offers suggestions without prompting

Makes informed choices based on available data and objectives

Capability to perform complex tasks without constant human input

Ability to break down and plan multi-step processes

Works across multiple software systems or databases

Improves performance based on feedback and experience

Engages in human-like conversation for task delegation

Anticipates needs and offers suggestions without prompting

Makes informed choices based on available data and objectives

Capability to perform complex tasks without constant human input

Ability to break down and plan multi-step processes

Works across multiple software systems or databases

Improves performance based on feedback and experience

Engages in human-like conversation for task delegation

Anticipates needs and offers suggestions without prompting

Makes informed choices based on available data and objectives