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    LaunchDarkly

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    Deployed on AWS
    Free Trial
    AWS Free Tier
    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

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    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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    Delivery method

    Deployed on AWS
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    Pricing

    Free trial

    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.
    Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator  to estimate your infrastructure costs.

    12-month contract (1)

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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

    Vendor refund policy

    All fees are non-cancellable and non-refundable except as required by law.

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    Usage information

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    Delivery details

    Software as a Service (SaaS)

    SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.

    Support

    AWS infrastructure support

    AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.

    Product comparison

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    Accolades

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    Top
    10
    In Business Intelligence & Advanced Analytics, Generative AI, Continuous Integration and Continuous Delivery
    Top
    50
    In Agile Lifecycle Management
    Top
    100
    In Testing

    Customer reviews

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    Sentiment is AI generated from actual customer reviews on AWS and G2
    Reviews
    Functionality
    Ease of use
    Customer service
    Cost effectiveness
    6 reviews
    Insufficient data
    Insufficient data
    0 reviews
    Insufficient data
    Insufficient data
    Insufficient data
    Insufficient data
    Positive reviews
    Mixed reviews
    Negative reviews

    Overview

     Info
    AI generated from product descriptions
    Cross-Platform Feature Flag Management
    Feature flags are cross-platform supported with multi-lingual capabilities and real-time consistent updates across all services.
    Production Testing and Experimentation
    Ability to test ideas in production on real users with measurement of impact and A/B testing capabilities including experiments on different prompts, parameters, or models.
    AI Configuration Management
    Runtime control over AI prompts and models enabling safe shipping, testing, and optimization of AI experiences in production without code redeployments.
    User Targeting and Segmentation
    Targeting engine that customizes applications to different user groups based on any attribute for personalized user experiences.
    Real-Time Feature Deployment
    Real-time delivery of feature updates and configuration changes across front-end and back-end services without requiring code changes or redeployments.
    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 new features to production environments with streamlined release process capabilities

    Contract

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    Standard contract
    No
    No
    No

    Customer reviews

    Ratings and reviews

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    4.5
    751 ratings
    5 star
    4 star
    3 star
    2 star
    1 star
    70%
    27%
    2%
    1%
    0%
    4 AWS reviews
    |
    747 external reviews
    External reviews are from G2  and PeerSpot .
    James L.

    Clear Customer Journey Visibility with Powerful Filters and a Polished UI

    Reviewed on Jun 08, 2026
    Review provided by G2
    What do you like best about the product?
    I can view all aspects of the events in a customer’s journey. This is especially helpful when I need to find specific moments around an issue by using filters, such as the name of a button the user clicked. From there, it’s easy to extend the search to other customer journeys and see whether they encountered the same issue as well. Overall, this is straightforward to do because the UI is very well presented.
    What do you dislike about the product?
    It’s unfortunate that we’ve lost the ability to share individual session captures with external users. There are times when we want to provide customers with evidence of an issue or of a user’s actions, but in Launch Darkly this isn’t possible.

    We hoped we could work around it by adding customers as users on the platform with custom access levels. However, that also isn’t possible with Launch Darkly, which seems to offer an all-or-nothing level of sharing when it comes to sessions. This is disappointing, especially because it’s something we were very used to when using Highlight.io.

    Additionally while the Dashboards are fine, we would prefer this data to be exported to Grafana where we would be able to use their panels to display and transform the data as we would like. We are working on this ourselves at the moment.
    What problems is the product solving and how is that benefiting you?
    Speaking from the position of the support team, Launch Darkly allows a singular platform that we can use to troubleshoot the customer and end user journey issues. It also provides the tools for our developers to enhance the level that we can do this via custom fields. It's integration with Linear makes it easy for Issues to be raised linked to the journey and the Dashboards allow a holistic view across the front end so we can be proactive with bug investigation and fixes.
    Computer Software

    Easy Setup and a Straightforward Learning Curve

    Reviewed on Jun 03, 2026
    Review provided by G2
    What do you like best about the product?
    LaunchDarkly is relatively easy to set up and has a straightforward learning curve compared to the other platforms we explored.
    What do you dislike about the product?
    So far, I haven't come across any major drawbacks, at least with the features I've worked with and explored.
    What problems is the product solving and how is that benefiting you?
    Most of my exploration has been around feature flags and user lifecycle–based experiment setup.
    Avi Cherny

    Feature flags have enabled safe gradual rollouts and now reduce risk and save engineering time

    Reviewed on Jun 03, 2026
    Review from a verified AWS customer

    What is our primary use case?

    My main use case for LaunchDarkly  is feature flagging and gradual rollouts. Instead of releasing a new feature to all users at once, we can first enable it for internal users, then for a small group of customers, and only later roll it out to everyone.

    When we released a new feature, we first turned it on only for internal users. After that, we enabled it for a small percentage of real customers, which helped us test that feature in production without taking too much risk. If something went wrong, we could simply turn the flag off in LaunchDarkly  without doing a full rollback.

    We use flags for gradual deploying and testing, then rolling out. For example, we enabled a feature, tested it in a specific environment, then turned off this flag.

    What is most valuable?

    The best feature LaunchDarkly offers is the flag that allows rollouts.

    What I appreciate about LaunchDarkly is that the setup was easy, it had a clean user experience, and the control allowed us to manage the features without deploying them to everyone. We could deploy it gradually and then roll out easily. I particularly value the ability to click to turn the feature on and off.

    LaunchDarkly has positively impacted my organization by reducing the risk of releasing new features because we did not have to expose everything to all users at the same time. It eventually resulted in faster releases and more confidence. It also saved engineering time because in some cases, we did not need to do a rollback or hot fixes; we could simply disable the feature flag. Additionally, it reduced the QA time since they could only test a specific area.

    What needs improvement?

    LaunchDarkly can be improved by managing old flags. We have an issue with old flags; it became very messy very fast and we need to be very disciplined about managing these flags. I also heard from the manager that it was very expensive when the usage grew.

    Perhaps LaunchDarkly could mark old flags somehow or add a tag to these flags when they are not in use or have not been used for a long time. We found ourselves after a short period of time having too many flags.

    For how long have I used the solution?

    I have been working in my current field for above ten years.

    Which solution did I use previously and why did I switch?

    I used LaunchDarkly in my previous company for several months.

    What other advice do I have?

    Overall, LaunchDarkly saved our engineering time and helped us manage features very smoothly, allowing us to gradually deploy and roll out.

    My advice for others looking into using LaunchDarkly is to manage the flags carefully, as it can become messy very fast.

    I believe LaunchDarkly is a very useful tool for teams wanting to release features quickly and safely; it gives a lot of control and helps reduce the risk around production releases. I would rate this product an eight out of ten.

    Which deployment model are you using for this solution?

    Public Cloud

    If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

    Information Technology and Services

    Clean, Intuitive Dashboard with Powerful Targeting and Fast Flag Propagation

    Reviewed on Jun 03, 2026
    Review provided by G2
    What do you like best about the product?
    The dashboard is clean and intuitive enough for PMs to manage rollouts without needing dev help. Flag targeting and the segment builder are powerful, although complex rule sets can get cluttered and harder to scan. Integration with our existing system was straightforward, and the SDK coverage spans every major language we use. Flag evaluation is effectively near-zero latency on the client side, propagation is sub-second, and we haven’t seen any measurable overhead in the app.

    Pricing feels acceptable for what you get. I haven’t fully explored the AI features yet, so I’m holding off on judging those for now. Overall, it’s a strong choice for teams that ship continuously, but budget-conscious orgs or teams with a low release cadence should compare alternatives first.
    What do you dislike about the product?
    It’s unable to handle complex rules. The product itself seems like it was designed for non-dev users in the first place, but in real-life environments you often need to deal with more complex situations; otherwise, we’re not able to cover the majority of the system.

    It’s also important to point out a major issue with segment integration with the backend system: there’s a bug where it can’t retrieve the correct value while segment targeting is being processed. Although we tried to contact LaunchDarkly support, the problem seems to remain unresolved.
    What problems is the product solving and how is that benefiting you?
    LaunchDarkly provides ease of maintenance and helps solve the risk of shipping code directly to all users at once. With feature flags, we can decouple deployment from release—code goes out, but features stay off until we’re ready. We can roll out to 1% of users, watch metrics, then either expand the rollout or kill it instantly without a redeploy. It also lets us run A/B experiments without engineering overhead each time, and it gives non-technical team members control over feature visibility. The result is faster releases, fewer incidents, and less pressure on every deploy. Overall, the system has a user-friendly UI.
    Micah B.

    Easy to Understand, Comprehensive, and Flexible Feature Flagging with LaunchDarkly

    Reviewed on Jun 02, 2026
    Review provided by G2
    What do you like best about the product?
    LaunchDarkly is easy to understand while still being extremely comprehensive and flexible. I’ve used it at multiple workplaces, and I’m always happy to see it already in use as a service at an organization.
    What do you dislike about the product?
    Not much to complain about—any shortcomings I initially thought it had were overcome once I learned more about the product.
    What problems is the product solving and how is that benefiting you?
    Segmented rollouts let us release features to specific user groups, using feature flags so we can quickly revert if needed. It also makes it easy to target particular user segments when a feature requires it.
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