LaunchDarkly Features

Configures and accurately measures an appropriate measure of engagement, such as average session length.

Accurately measures bounce rate.

Tracks user return rates and related metrics.

Tracks what proportion of users convert via a certain action.

Identifies user demographics like gender or age.

Enables the view of analytic data based on user segment.

Identifies users locations.

Enables you to define custom events for analysis.

Provides real-time reports.

Measures user acquisition analytics.

Provides a holistic summary of your data.

Displays a users progress throughout specific paths in an application.

Displays a users activity history.

Tracks where users are clicking on a web page.

Tracks mouse movement over a web page.

See where users experience the most difficulty on a web page.

Tracks sessions where users encountered errors and bugs.

Split web traffic to a page between two different URLs.

Offers insights into relationships between user information and user behavior.

Leave notes on sessions and bugs.

Collects user information (location, IP address, email, etc.).

Search sessions by keywords or IP address.

Ability to see analytics at the account level. This feature was mentioned in 27 LaunchDarkly reviews.

As reported in 28 LaunchDarkly reviews. Ability to see analytics at the user level.

Ability to compare usage across segments such as role, company size, etc. This feature was mentioned in 28 LaunchDarkly reviews.

Based on 28 LaunchDarkly reviews. See how users move though a product via grouped page sequences

View analytics for multiple products in a single dashboard, including cross-product engagement 26 reviewers of LaunchDarkly have provided feedback on this feature.

Breadth and functionality of integrations with third-party products. 26 reviewers of LaunchDarkly have provided feedback on this feature.

As reported in 195 LaunchDarkly reviews. Maintain, or facilitate maintenance of, tested and approved code in a deployment-ready state for manual pushes to production.

Based on 199 LaunchDarkly reviews. 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. 187 reviewers of LaunchDarkly have provided feedback on this feature.

Empowers users to smoothly deploy features in a variety of environments. This feature was mentioned in 432 LaunchDarkly reviews.

Allows teams to test features in production for select target groups without deploying. 430 reviewers of LaunchDarkly have provided feedback on this feature.

Presents users with a low-code interface to build and maintain feature management systems. 413 reviewers of LaunchDarkly have provided feedback on this feature.

Automatically adjusts resources base on application usage.

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

As reported in 193 LaunchDarkly reviews. Designate the necessary tasks and workflows for a team's unique development cycle.

Generate visual dashboards and reports around development cycle progress. 192 reviewers of LaunchDarkly have provided feedback on this feature.

Based on 183 LaunchDarkly reviews. Automate repository detection, version control, testing, and more.

Based on 440 LaunchDarkly reviews. Grants users a centralized dashboard for organized feature flag management.

As reported in 425 LaunchDarkly reviews. Grants users granular control over feature rollouts and rollbacks.

Allows users to track the status of deployed features and application performance via automated alerts. 414 reviewers of LaunchDarkly have provided feedback on this feature.

Give users in-app method of reporting bugs and leaving general performance feedback.

Give testers in-app method of reporting bugs and leaving general performance feedback.

Give team members method of reporting bugs and leaving comments on bug status.

Track history of bug status by application version, date, etc.

Store bug tracking data for an appropriate and useful amount of time.

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.

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

Provides high-frequency metrics data.

Provides reporting and analytics tools to quantify the results of the experiment. 155 reviewers of LaunchDarkly have provided feedback on this feature.

Based on 158 LaunchDarkly reviews. Allows for the testing of multiple variables at a time during a single test.

Based on 159 LaunchDarkly reviews. Allows multiple experiments to be deployed simultaneously.

Allows mobile web pages to be tested during A/B experiments. This feature was mentioned in 152 LaunchDarkly reviews.

Provides users with the ability to test and optimize prompts to improve LLM output quality and efficiency.

Offers tools for users to compare multiple LLMs side-by-side based on performance, speed, and accuracy metrics.

Gives users tools to integrate LLM functionality into their existing applications through SDKs and APIs, simplifying development.

Offers users the capability to deploy models quickly to production environments with minimal effort and configuration.

Provides users with live insights into model accuracy, latency, and user interaction, helping them identify and address issues promptly.

Offers users tools to set access permissions for different roles, ensuring only authorized personnel can interact with or modify LLM resources.

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

Supports ingestion and standardization of observability data via OpenTelemetry protocol.

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.

Works across multiple software systems or databases

Capability to perform complex tasks without constant human input 10 reviewers of LaunchDarkly have provided feedback on this feature.

Works across multiple software systems or databases This feature was mentioned in 11 LaunchDarkly reviews.

Improves performance based on feedback and experience This feature was mentioned in 10 LaunchDarkly reviews.

Based on 10 LaunchDarkly reviews. Engages in human-like conversation for task delegation

Anticipates needs and offers suggestions without prompting This feature was mentioned in 10 LaunchDarkly reviews.

As reported in 13 LaunchDarkly reviews. Capability to perform complex tasks without constant human input

Works across multiple software systems or databases This feature was mentioned in 14 LaunchDarkly reviews.

Based on 14 LaunchDarkly reviews. Improves performance based on feedback and experience

Anticipates needs and offers suggestions without prompting 14 reviewers of LaunchDarkly have provided feedback on this feature.

Tracks changes to prompts over time.

Helps users run test outputs across different models.

Tracks execution time of prompts across models.

Helps in monitoring token consumption and API call frequency.

Identifies expensive prompts to help teams optimize for cost efficiency.

Helps in A/B testing of prompts across models.

Helps to plug into CI/CD for automated testing, validation, and deployment of prompts.

Helps generating reliable and consistent AI outputs.

Engages in human-like conversation for task delegation

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