Showing 6 open source projects for "deploy"

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  • 1
    The Lift Web Framework
    ...Lift's Comet support is unparalled and Lift's ajax support is super-easy and very secure. Because Lift applications are written in Scala, an elegant JVM language, you can still use your favorite Java libraries and deploy to your favorite Servlet Container and app server. Use the code you've already written and deploy to the container you've already configured! As of Lift 3.0, you'll need to be running Java 8 to use Lift. For those using Java 6 or Java 7, you'll need to use Lift 2.6 until you can upgrade your Java installation.
    Downloads: 0 This Week
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  • 2
    GitBucket

    GitBucket

    A Git platform powered by Scala

    ...GitBucket is a Git web platform powered by Scala offering, easy installation, intuitive UI, high extensibility by plugins, API compatibility with GitHub. You can also deploy gitbucket.war to a servlet container which supports Servlet 3.0 (like Jetty, Tomcat, JBoss, etc). To upgrade GitBucket, replace gitbucket.war with the new version, after stopping GitBucket. All GitBucket data is stored in HOME/.gitbucket by default. So if you want to back up GitBucket's data, copy the directory to the backup location. ...
    Downloads: 2 This Week
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  • 3
    Lagom

    Lagom

    Reactive Microservices for the JVM

    The opinionated microservices framework for moving away from the monolith. Lagom helps you decompose your legacy monolith and build, test, and deploy entire systems of Reactive microservices. Lagom is an open source framework for building systems of Reactive microservices in Java or Scala. Lagom builds on Akka and Play, proven technologies that are in production in some of the most demanding applications today. Lagom's integrated development environment allows you to focus on solving business problems instead of wiring services together. ...
    Downloads: 4 This Week
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  • 4
    Marathon

    Marathon

    Deploy and manage containers (including Docker) on top of Apache Mesos

    A container orchestration platform for Mesos and DC/OS. Deploy and manage containers (including Docker) on top of Apache Mesos at scale. Marathon is a production-grade container orchestration platform for Mesosphere’s Datacenter Operating System (DC/OS) and Apache Mesos. Marathon has first-class support for both Mesos containers (using cgroups) and Docker. Marathon runs as an active/passive cluster with leader election for 100% uptime.
    Downloads: 0 This Week
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  • Streamline Azure Security with Palo Alto Networks VM-Series Icon
    Streamline Azure Security with Palo Alto Networks VM-Series

    Centrally manage physical and virtualized firewalls with Panorama

    Improve your security posture and reduce incident response time. Use the VM-Series to natively analyze Azure traffic and dynamically drive policy updates based on workload changes.
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  • 5
    Graphcool Framework

    Graphcool Framework

    Graphcool is an open-source backend development framework

    ...Graphcool separates the business logic from stateful storage components, allowing the stateful parts (database, subscription engine) to scale independently and giving flexibility in how you compose your system. Users could deploy Graphcool either locally (e.g. via Docker) or on a managed cloud offering. The framework also provided features like schema evolution, migrations, data loaders for performance, and built-in tooling to manage endpoints and deployments.
    Downloads: 0 This Week
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  • 6
    Apache PredictionIO

    Apache PredictionIO

    Machine learning server for developers and ML engineers

    Apache PredictionIO® is an open source Machine Learning Server built on top of a state-of-the-art open source stack for developers and data scientists to create predictive engines for any machine learning task. Quickly build and deploy an engine as a web service on production with customizable templates; respond to dynamic queries in real-time once deployed as a web service; evaluate and tune multiple engine variants systematically; unify data from multiple platforms in batch or in real-time for comprehensive predictive analytics; speed up machine learning modeling with systematic processes and pre-built evaluation measures; support machine learning and data processing libraries such as Spark MLLib and OpenNLP; implement your own machine learning models and seamlessly incorporate them into your engine; simplify data infrastructure management.
    Downloads: 0 This Week
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