Showing 3 open source projects for "environment-modules"

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    Gemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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    99.99% Uptime for MySQL and PostgreSQL Databases

    Sub-second maintenance. 2x read/write performance. Built-in vector search for AI apps.

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  • 1
    LocalStack

    LocalStack

    Develop and test your cloud apps offline

    LocalStack is a fully functional local AWS cloud stack that enables you to develop and test your cloud and serverless apps offline. It spins up an easy-to-use testing environment on your local machine that has the same APIs and works the same way as the real AWS cloud environment. It can spin up a number of different core Cloud APIs on your local machine, including API Gateway, Kinesis, DynamoDB, Firehose, Lambda and many others. LocalStack was built on some of today’s best-of-breed mocking/testing tools, combining them and making them interoperable, and adding important functionality such as error injection and pluggable services. ...
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  • 2
    AWS SAM CLI

    AWS SAM CLI

    CLI tool to build, test, debug, and deploy Serverless applications

    ...During deployment, SAM transforms and expands the SAM syntax into AWS CloudFormation syntax, enabling you to build serverless applications faster. To get started with building SAM-based applications, use the SAM CLI. SAM CLI provides a Lambda-like execution environment that lets you locally build, test, debug, and deploy AWS serverless applications.
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  • 3
    StreamAlert

    StreamAlert

    StreamAlert is a serverless, realtime data analysis framework

    StreamAlert is a serverless, real-time data analysis framework that empowers you to ingest, analyze, and alert on data from any environment, using data sources and alerting logic you define. Computer security teams use StreamAlert to scan terabytes of log data every day for incident detection and response. Incoming log data will be classified and processed by the rules engine. Alerts are then sent to one or more outputs. Rules are written in Python; they can utilize any Python libraries or functions. ...
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