Sumo Logic Features

Diagnose and resolve incidents without the need for human interaction.

Guide users through the resolution process and give specific instructions to remedy individual occurrences.

Cuts off network connection or temporarily inactivate applications until incidents are remedied.

Gathers information related to threats in order to gain further information on remedies.

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

Sets a standard performance baseline by which to compare log activity.

Allows platform to scale to size of desired environment and configured with high availability and disaster recovery capabilities.

Information on each incident is stored in databases for user reference and analytics.

Produces reports detailing trends and vulnerabilities related to their network and infrastructure.

Analyzes recurring incidents and remedies to ensure optimal resource usage.

Gives alerts when incidents arise. Some responses may be automated, but users will still be informed.

Adminstrators can access and organize data related to incidents to produce reports or make data more navigable.

Administrators can organize workflows to guide remedies to specific situations incident types.

Documents the actions from endpoints within a network. Alerts users of incidents and abnormal activities and documents the access point.

Keeps records of each network asset and its activity. Discovers new assets accessing the network.

Provides security information and stores the data in a secure repository for reference.

Alerts users of incidents and allows users to intervene manually or triggers an automated response.

Reduces time spent remedying issues manually. Resolves common network security incidents quickly.

Documents cases of abnormal activity and compromised systems.

Stores information related to common threats and how to resolve them once incidents occur.

Analyzes your existing network and IT infrastructure to outline access points that can be easily compromised.

Allows users to customize analytics with granulized metrics that are pertinent to your specific resources.

Allows users to search databases and incident logs to gain insights on vulnerabilities and incidents.

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.

Optimizes resource allocation.

Consistently monitors processes for applications and IT infrastructure to detect anomalies in real-time.

Sets up standard performance baseline to compare live container activities.

Traces connections between different containerized environments and detects anomalies in functionality, user accessibility, traffic flows, and tampering.

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.

Streamline the flow of work processes by establishing triggers and alerts that notify and route information to the appropriate people when their action is required within the compensation process.

Integrates additional security tools to automate security and incident response processes.

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

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.

Allows user to track log trends.

Identify and predict anomalies in real-time with outlier detection and uncover root-causes

Analyze both metric and event data on the same platform regardless of source or structure

Search your logs for troubleshooting and open-ended exploration of your data

Create alerts based on search patterns, thresholds for specific log metrics, or other conditions

See your data, in real time, streaming into the system from multiple data sources

Allows users to search logs for troubleshooting and open-ended exploration of data.

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

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

Allows users to track log trends.

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

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

Creates reports outlining log activity and relevant metrics.

Automatically allocates resources to address log anomalies.

Sets a standard performance baseline by which to compare log activity.

Constantly monitors logs to detect anomalies in real time.

Visually displays connected applications and integrated data. Allows customization and management of workflow structures.

Streamline the flow of work processes by establishing triggers and alerts that notify and route information to the appropriate people when their action is required within the compensation process.

Reduces time spent remedying issues manually. Resolves common network security incidents quickly.

Constantly monitors logs to detect anomalies in real time.

Diagnoses and resolves incidents without the need for human interaction.

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

Integrates additional security tools to automate security and incident response processes.

Collects information from multiple sources to cross reference and build contextual to correlate intelligence.

Stores information related to common threats and how to resolve them once incidents occur.

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

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.

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

Monitors data quality and send alerts based on violations or misuse.

Identifies potential network security risks, vulnerabilities, and compliance impacts.

Creates reports outlining log activity and relevant metrics.

Automatically collect logs from all your services, applications, and platforms

Automate the indexing of machine data that's critical to your operations

See log data in context with automated tagging and correlation

Mix and match data from apps, hosts, containers, services, networks, and more

Visualize log data on dashboards

Drill down and explore data to discover new insights

Provides personalized responses to interlocator based on segmentation or past responses.

Has tools (e.g. dashboards and reports) to better understand conversations Intelligent Virtual Assistants have had.

Can have a natural, human-like conversation with an interlocator.

Allows business to edit conversations to meet the unique needs of one's business.

Gives users the ability to update systems, like CRM, based on conversations.

Allows users to maintain and observe the accuracy and viability of Intelligent Virtual Assistants.

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

Provides high-frequency metrics data.

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.

Alerts over email, text, phone call, or more to multiple parties.

Provides information related to unnecessary spending and unused resources.

Gives alerts when incidents arise.

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

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

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

Allows users to generate text based on a text prompt.

Condenses long documents or text into a brief summary.

Allows users to generate text based on a text prompt.

Condenses long documents or text into a brief summary.

Allows users to automate responses to customer inquiries across various channels.

Allows users to automate responses to customer inquiries across various channels.

Allows users to automate the process of generating and qualifying sales leads.

Allows users to automate the handling, processing, and management of documents.

Provides users the ability to automate the collection and analysis of feedback from customers, employees, or other stakeholders.

Allows the AI agent to learn from interactions and adapt its responses accordingly.

Allows the AI agent to learn from interactions and adapt its responses accordingly.

Provides the AI agent the ability to execute tasks without requiring constant user input.

Allows the AI agent to identify and resolve issues without user intervention.

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

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

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

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

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