meshIQ Features

Processes batch, real-time, and streaming data workloads in singular, multi-tenant, or cloud systems

Expands functionality while maintaining balanced loads. Serves growing demand without reducing functionality.

Provides additional AI analytics to drive insights.

Provides Administration tools/console that are easy to use and learn for routine maintenance tasks

Creates new or streamlines existing workflows to better handle IT support tickets and service.

Utilizes data to proactively identify and prioritize IT issues.

Supports trust actions( recommend, manual or automated) to take a decision.

Software is able to alert the user immediately in case of a fault in the processing line.

Provides operational access to job scheduling on a 24/7 basis. This gives IT users a flexible point of access to control workloads.

Actively monitor status of work stations either on-premise or remote.

Allows users to track and control cloud spend across cloud services and providers.

Efficiently scales resource usage to optimize spend whith increased or decreased resource usage requirements.

Automatically scales resources based on demand and optimizes for performance and cost.

Automates IT related to the running of batch Jobs.

Application Programming Interface Specification for how the application communicates with other software. APIs typically enable integration of data, logic, objects, etc. with other software applications.

Provides true integration with multi vendor tools to ensure business continuity.

Allows sender and reciever to operate independently at separate times.

Supports programming languages such as Java, C, or Python. Support for front-end languages such as HTML, CSS, and JavaScript.

Functions through a cloud-based messaging service without on-premise infrastructure.

Has minimal delay between input and feedback.

Maintain, or facilitate maintenance of, tested and approved code in a deployment-ready state for manual pushes to production.

Integrate with other development and testing software, such as continuous integration or test automation tools.

Plug-in capable for added resources, features, and functions within the product itself.

Utilizes artificial intelligence to analyze big data.

Utilizes machine learning to analyze big data.

Monitors logs and activities from a wide range of IT systems.

Integrates with other development and testing software, such as continuous delivery or test automation tools.

Plug-in capable for added resources, features, and functions within the product itself.

Enables full control over test types and parameter definitions for effective automated testing.

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.

Allows messages and data to integrate directly into applications using APIs.

Breadth of standard integrations to first, second, and third-party data providers.

Allows for additional features and functionalities in the form of pre-packaged integrations and plug-ins.

Ability to control file/folder access by user or group, external sharing permissions, editing policies, device location restrictions, sharing by device, etc.

Detects anomalies in functionality, user accessibility, traffic flows, and tampering.

Actively monitor status of work stations either on-premise or remote.

Designate the necessary tasks and workflows for a team's unique development cycle.

Generate visual dashboards and reports around development cycle progress.

Automate repository detection, version control, testing, and more.

Integrates with a variety of IT systems.

Automatically alerts necessary parties via email, text, or call when issues are identified.

Generate sreports and dashboards highlighting trends and key metrics around issues and issue resolution.

Fully automates repetitive or tediuos tasks to ease developer workload.

Designates the necessary tasks and workflows for a team's unique development cycle.

Generates visual dashboards and reports around development cycle progress.

Tracks infrastructure resource needs and alerts administrators or automatically scales usage to minimize waste.

Monitors performance and statistics related to memory, caches and connections.

Detects anomalies in functionality, user accessibility, traffic flows, and tampering.

Constantly monitors system to detect anomalies in real time.

Enables monitoring of security and compliance standards across cloud infrastructure.

Creates reports outlining resource, underutilization, cost trends, and/or functional overlap.

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

Ability to project spend based on contracts, usage trends, and predicted growth.

Directly identifies, or increases identification speed for, root causes for IT system issues.

Proactively identifies trends on IT systems that could lead to failures or errors.

Provides paths, suggestions, or other general assistance towards issue resolution.

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

Provides high-frequency metrics data.

Allows users to generate text based on a text prompt.

Condenses long documents or text into a brief summary.

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

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

Capability to perform complex tasks without constant human input

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

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

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

Anticipates needs and offers suggestions without prompting

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

Utilizes machine learning to automatically detect and alert on unusual patterns in infrastructure metrics.

Provides AI-generated insights and actionable recommendations to optimize resource performance and cost.

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