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LaunchDarkly + AWS
Get on the path to cloud confidence.
Migrate, innovate, and accelerate with AWS and LaunchDarkly.
Deliver extraordinary experiences for customers.
Derisk, modernize, and move faster on AWS with LaunchDarkly. Unify feature flags, release observability, experimentation, and AI configuration management to ship safer AI agents and code.
LaunchDarkly + AWS
Innovation that spans industries.
The LaunchDarkly + AWS partnership delivers results in industries from healthcare to entertainment to retail—and everything in between.
Software
Velocity with safety.
Decouple deploy from release on AWS, allowing continuous integration and deployment while gating new features with flags. This reduces downtime risk and enables mid-deployment rollbacks without redeploys.
Cross-service coordination.
Use LaunchDarkly targeting to coordinate releases across dozens of microservices running in AWS Lambda or ECS, ensuring dependent services update in lockstep rather than risking cascading failures.
Experimentation at scale.
Embed experimentation into the delivery pipeline by attaching experiments to any feature flag. This enables rapid iteration on pricing flows, collaboration features, or UI changes, with statistically rigorous results trusted by both engineering and product teams.
Financial services
Fraud detection & risk models.
Deploy new fraud detection models on AWS using LaunchDarkly feature flags to gate releases by customer segment. Teams can validate accuracy and performance in production before broad rollout, reducing false positives and customer friction.
Regulatory compliance.
Use Guarded Releases with automated rollback and CloudTrail Lake audit logs to ensure every update to trading platforms or payment systems can be traced, audited, and reversed instantly if thresholds are breached.
Customer engagement experiments.
Financial institutions can run A/B tests on digital banking features (like mobile onboarding flows or savings recommendations) with full isolation between test and control groups, measuring engagement while preserving compliance boundaries.
Healthcare
Clinical decision support.
Gradually roll out new diagnostic algorithms or patient monitoring dashboards to a subset of clinicians. If issues arise (e.g., model drift, latency spikes), roll back instantly to the prior version without interrupting care delivery.
HIPAA-ready governance.
Enforce strict access controls for feature management with SSO/MFA, ensure PHI-sensitive features are only available in compliant regions, and provide audit trails to satisfy HIPAA and FedRAMP requirements.
Iterative healthcare tools.
Test new note-taking or telehealth tools with small patient cohorts, collecting usability and reliability metrics before scaling system-wide, reducing the risk of introducing instability into critical care workflows.
Entertainment
Content moderation.
LaunchDarkly flags allow teams to trial new moderation models (e.g., toxicity detection in chat) on AWS in real time, targeting by geography or user tier to comply with local policies and measure impact before full rollout.
Personalized recommendations.
Streaming and gaming companies can test algorithm changes on a subset of users, monitoring engagement and churn before extending to their global user base. Real-time rollback prevents widespread quality drops.
A/B testing at scale.
Media platforms can run parallel experiments on ad placement, subscription offers, or UI changes, measuring effects on revenue per user, session length, and retention—all without pausing deployments or requiring parallel code branches.
Retail
Personalized shopping journeys.
Retailers can release new recommendation algorithms or targeted promotions to defined cohorts, tracking conversion lift in real time and rolling back if results degrade.
Demand forecasting.
New inventory prediction models can be incrementally rolled out by region or store type, validated against live sales data, and optimized iteratively without exposing all customers to risk.
Optimized conversions.
LaunchDarkly flags allow checkout flow updates or upsell features to be toggled in production. Teams can measure drop-off rates and revenue impact immediately, iterating rapidly without redeploys.
Migrate and modernize faster.
From release control to self-healing systems, these are the problems teams solve using runtime control — right from their existing tools.
Break migrations into manageable pieces.
Use migration-specific feature flags to progressively introduce new cloud infrastructure, databases, APIs, and other services in small increments.
Go beyond infrastructure routing.
Control migrations at the application layer to flexibly target using any parameter. Roll out specific backend components to specific audiences.
Monitor migration metrics.
Closely monitor performance, consistency, and business metrics across each step of a migration. Improve visibility and increase the likelihood of success.
Ebook
3 ways to end the misery of tech migrations
Safely migrate and modernize across cloud services, databases, and APIs.
Safely control and speed up deployment of AI apps on AWS.
Use LaunchDarkly and Amazon Bedrock to rapidly iterate on new models and prompts, instantly roll back issues, and customize and optimize experiences across audiences.
Move from pilot to production faster.
Accelerate safe deployment with progressive rollouts, instant rollback, and reduced production risk.
Demonstrate real business impact.
Optimize prompts, models, and tools directly against business metrics with full visibility into cost, performance, and behavior.
Stay ahead of innovation.
Seamlessly adopt new models and workflows while keeping production stable and experimentation rapid.
Explore additional AWS integrations.
Amazon Bedrock
Deploy, measure, and improve prompts, models, tools, and agents in production with LaunchDarkly AI Configs.
Learn more
AWS CloudTrail Lake
LaunchDarkly sends an event to AWS CloudTrail if a feature flag is updated or a new account member is added.
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Amazon Kinesis Data Streams
Export log stream data for real-time processing to perform complex queries and analysis on your LaunchDarkly data.
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