Sold by: LaunchDarkly
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Accelerate innovation at AI scale by using LaunchDarkly for your front-end and back-end feature releases on AWS, including AI applications using Amazon Bedrock and AgentCore!
4.5
Overview
Unlock the full potential of your AWS-based applications with LaunchDarkly, the runtime control platform for the AI era, trusted by software teams to control AI-generated code and AI agents in production at any scale.
Accelerate your software development lifecycle, de-risk deployments, and move at AI speed while staying in control.
The LaunchDarkly platform delivers runtime control through two solutions: CodeControl and AgentControl.
CodeControl helps teams ship AI-generated code confidently. With CodeControl, teams can observe production behavior, make changes in real time, and limit exposure based on actual impact. Through a combination of industry-leading feature flags, progressive rollouts, real-time observability, experimentation, and automatic recovery, LaunchDarkly gives organizations the ability to move at AI speed without giving up control.
AgentControl helps teams keep AI agents in check in production, blocking bad behavior and steering responses in real time. Teams can configure prompts and models before launch, monitor and observe live performance and behavior, and automatically take action, without redeploying. When agents make curious decisions, or when small prompt or model changes cause big issues, AgentControl detects and corrects them as they happen.
With runtime control across code and agents, LaunchDarkly helps enable teams to ship AI-built software with confidence, govern agent behavior in production, optimize AI performance and cost, build self-healing systems, and experiment continuously. The result is faster release velocity, lower production risk, and the ability to continuously adapt software and AI systems without slowing down to stay safer.
For custom pricing, EULA, or a private offer, please contact aws-alliance@launchdarkly.com
Highlights
- Ship AI generated code confidently, with feature flags, progressive deliver, automatic rollback and runtime control.
- AgentControl helps keep agents on track, blocking bad behavior and steering responses in real time, enabling agents that improve continuously, and self-heal.
- Test in production with faster loops. Use AI to generate endless variations, measure what works in production, and continuously improve outcomes.
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Pricing
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Try this product free according to the free trial terms set by the vendor.
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
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Dimension | Description | Cost/12 months |
|---|---|---|
LaunchDarkly Pro Bundle | LaunchDarkly Professional Platform with 300K CMAU and 10M Exp events | $44,100.00 |
Dimensions summary
You buy one contract bundle: the LaunchDarkly Pro Bundle. It is a fixed package priced as a single unit, not a menu of separate options. The bundle includes a set usage allowance of 300K CMAU (client-side monthly active users) and 10M experimentation events. Pricing does not scale per seat or per connection here; you commit to the bundled capacity for the contract term. Because there is one dimension, there are no tiers or add-ons to compare on Marketplace. You pay for the package as defined by its included usage amounts.
Top-of-mind questions for buyers
A CMAU is one unique client-side user or device active in a month. Each distinct end user or device counts once, no matter how many times they connect. The bundle includes up to 300K such users per month as part of its fixed capacity.
Experimentation events tie to A/B and multivariate testing activity across features, models, and prompts. Each tracked experimentation action counts toward the 10M monthly total. The bundle includes this volume as part of the fixed package capacity.
The platform provides runtime control over code and AI agents. You get feature flags, targeting, progressive rollouts, and rollbacks. It also covers experimentation, observability such as logs and traces, and agent controls like prompt and model configuration. All run without redeploying code.
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Support
Vendor support
Support Homepage: https://support.launchdarkly.com/hc/en-us support@launchdarkly.com
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Updated weekly
By LaunchDarkly
By Split Software
By Bricks Software
Top
10
In Business Intelligence & Advanced Analytics, Generative AI, Continuous Integration and Continuous Delivery
Top
50
In Agile Lifecycle Management
Top
100
In Testing
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
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AI generated from product descriptions
Feature Flags and Progressive Delivery
Industry-leading feature flags with progressive rollouts enabling controlled deployment of code changes across environments
Real-time Runtime Control
Runtime control platform allowing real-time modifications to application behavior, configuration changes, and automatic recovery without redeployment
Production Observability and Experimentation
Real-time observability and experimentation capabilities for monitoring production behavior, measuring impact, and continuously testing variations
AI Agent Behavior Management
AgentControl solution for monitoring, observing, and automatically correcting AI agent behavior in production including prompt and model configuration adjustments
Automatic Rollback and Recovery
Automatic rollback mechanisms and self-healing capabilities to limit exposure and mitigate issues based on actual production impact
Feature Flagging and Deployment Control
Ability to set up feature flags and safely deploy to production, controlling which users see which features and when with zero downtime deployment capability.
Experimentation and A/B Testing
Support for A/B testing, canary releases, dark launches, and targeted rollouts to enable data-driven experimentation and feature validation.
Contextual Data Integration
Connection of feature flags to contextual customer data through Amazon S3 integration to enable seamless metric calculation and feature impact analysis.
Release Risk Mitigation
Reduction of cycle times and release risk through continuous integration/continuous delivery workflows and mean time to recovery optimization.
High-Volume Data Processing
Capability to serve feature flags to high-volume distributed systems, supporting more than 6 billion devices with reliable feature delivery at scale.
Feature Flag Management
Open-source feature flag platform enabling controlled feature releases and rollouts to manage deployment risk
Data Governance and Compliance Controls
Market-leading data governance, security, and compliance controls designed for enterprise-grade requirements including FedRamp and air-gapped deployment scenarios
Deployment Flexibility
Support for multiple deployment options including cloud-hosted private instances and self-hosted solutions
Developer Tools and Workflow Integration
Developer-focused tools for testing and deploying features to production environments with streamlined release process capabilities
Standard contract
No
No
No
Customer reviews
Prasanth N.
Effortless User Segmentation, Minor Data Challenges
Reviewed on Sep 07, 2026
Review provided by G2
What do you like best about the product?
I like LaunchDarkly for its ease of use, which makes setting up user segmentation for tracking app performance straightforward. It also simplifies cohort breaking as desired. The initial setup was simple, which made getting started quick and easy.
What do you dislike about the product?
I find it confusing to choose between similarly named features like "user - plan type" because there's no clear dictionary or guidance on how the data can be split based on the flag features we have. It would be helpful to have more clarity in this area.
What problems is the product solving and how is that benefiting you?
I find LaunchDarkly makes cohort splitting easier for tracking app performance, which is simple. It's easy to use, but could use a better dictionary for data splitting based on flag features, especially for similarly named features.
Information Technology and Services
Do not recommend from a Sys Admin perspective
Reviewed on Sep 04, 2026
Review provided by G2
What do you like best about the product?
I don't like anything about LD. I manage it; another team uses it. And collectively it's not great.
What do you dislike about the product?
LaunchDarkly has abysmal support and absolutely no strategy for retaining historical data during migrations. The ability to mass manage isn't there. As a system admin, this website is not ideal for management, and I don't recommend it.
What problems is the product solving and how is that benefiting you?
As an admin, they've only created problems for me.
Computer Software
Confident, Low-Risk Releases with Powerful Feature Flag Targeting
Reviewed on Sep 04, 2026
Review provided by G2
What do you like best about the product?
What I like best about LaunchDarkly is how much confidence it gives teams when releasing changes. Feature flags make it possible to ship code separately from releasing functionality, so we can merge work earlier, test in production-like conditions, and turn features on gradually for the right users or environments.
The targeting and rollout controls are especially valuable. Being able to enable a feature for internal users first, then a small percentage of customers, then broader segments, makes launches feel much less risky. If something behaves unexpectedly, the ability to toggle it off quickly without a redeploy is a huge operational safety net.
I also appreciate how useful it is beyond simple on/off flags. Experiments, user targeting, kill switches, and environment-specific flag management all fit into the same workflow, which helps product, engineering, and QA collaborate around releases instead of relying on ad hoc config changes or emergency hotfixes.
The targeting and rollout controls are especially valuable. Being able to enable a feature for internal users first, then a small percentage of customers, then broader segments, makes launches feel much less risky. If something behaves unexpectedly, the ability to toggle it off quickly without a redeploy is a huge operational safety net.
I also appreciate how useful it is beyond simple on/off flags. Experiments, user targeting, kill switches, and environment-specific flag management all fit into the same workflow, which helps product, engineering, and QA collaborate around releases instead of relying on ad hoc config changes or emergency hotfixes.
What do you dislike about the product?
The main downside is that LaunchDarkly can add operational overhead if teams are not disciplined about flag cleanup. It is easy for temporary release flags to become permanent clutter, and over time that can make the codebase harder to reason about.
What problems is the product solving and how is that benefiting you?
LaunchDarkly solves the problem of risky, all-or-nothing releases. Before using it, every production deployment carried more pressure because a feature going live often meant the code was live for everyone at once. Now we can deploy code behind feature flags, release gradually, and turn features on for internal teams, beta users, or small customer segments first.
That has improved both speed and reliability. We can merge and deploy work earlier without waiting for every feature to be launch-ready, which reduces release bottlenecks and lets QA, product, and engineering validate behavior in real environments. Percentage rollouts and targeting rules also make it easier to catch issues before they affect the full customer base.
It also gives us a practical safety net. If a feature causes unexpected behavior, we can disable it quickly without rolling back an entire deployment or pushing an emergency hotfix. That shortens incident response time from a code-release cycle to a configuration change, which is a major benefit for customer-facing systems.
Another problem it solves is coordination across teams. Product managers can manage launch timing, engineers can keep risky changes isolated, and support teams can understand which customers have access to which experience. Overall, LaunchDarkly helps us release more frequently, reduce deployment risk, and experiment with less operational overhead.
That has improved both speed and reliability. We can merge and deploy work earlier without waiting for every feature to be launch-ready, which reduces release bottlenecks and lets QA, product, and engineering validate behavior in real environments. Percentage rollouts and targeting rules also make it easier to catch issues before they affect the full customer base.
It also gives us a practical safety net. If a feature causes unexpected behavior, we can disable it quickly without rolling back an entire deployment or pushing an emergency hotfix. That shortens incident response time from a code-release cycle to a configuration change, which is a major benefit for customer-facing systems.
Another problem it solves is coordination across teams. Product managers can manage launch timing, engineers can keep risky changes isolated, and support teams can understand which customers have access to which experience. Overall, LaunchDarkly helps us release more frequently, reduce deployment risk, and experiment with less operational overhead.
Pydi R.
Powerful Feature Flag Enablement with Boolean, Multivariate, Number & JSON Support
Reviewed on Sep 04, 2026
Review provided by G2
What do you like best about the product?
I like feature flag enablement because it supports Boolean values and multivariate flags have more than two variations it can have strong number and json variations.
What do you dislike about the product?
I think during release process we have platform dependency where latency or outages can cause or impact our release
What problems is the product solving and how is that benefiting you?
Right now it's solving control feature rollout deployments
Priya P.
Solid tool that lets you release frontend safer
Reviewed on Sep 02, 2026
Review provided by G2
What do you like best about the product?
LaunchDarkly's main purpose for me is to toggle new UI features without having to do another deploy. When you want to test a feature with QA or a select group of users before rolling it out to everyone, it's very helpful. Frontend integration is pretty easy and once your flags are created it makes releasing easy.
What do you dislike about the product?
Only negative is that there can easily be too many old flags if your team doesn't keep them cleaned up. Dashboard also has slight learning curve at first.
What problems is the product solving and how is that benefiting you?
LaunchDarkly allows us to release frontend with less risk. We can quickly turn features off/on, test out changes on select users, and not have to deploy anything we don't need to. Allows for more control when releasing new frontend features.
Recommendations to others considering the product:
To improve the user experience, consider implementing a feature to automatically archive old flags after a certain period. Additionally, providing more intuitive onboarding tutorials could help new users navigate the dashboard more efficiently.