Showing 3 open source projects for "php sharing cloud"

View related business solutions
  • Try Google Cloud Risk-Free With $300 in Credit Icon
    Try Google Cloud Risk-Free With $300 in Credit

    No hidden charges. No surprise bills. Cancel anytime.

    Use your credit across every product. Compute, storage, AI, analytics. When it runs out, 20+ products stay free. You only pay when you choose to.
    Start Free
  • Powerful App Monitoring Without Surprise Bills Icon
    Powerful App Monitoring Without Surprise Bills

    AppSignal starts at $23/month with all features included. No overages, no hidden fees. 30-day free trial.

    Tired of monitoring tools that punish you for scaling? AppSignal offers transparent, predictable pricing with every feature unlocked on every plan. Track errors, monitor performance, detect anomalies, and manage logs across Ruby, Python, Node.js, and more. Trusted by developers since 2012 with free dev-to-dev support. No credit card required to start your 30-day trial.
    Try AppSignal Free
  • 1
    omegaml

    omegaml

    MLOps simplified. From ML Pipeline ⇨ Data Product without the hassle

    omega|ml is the innovative Python-native MLOps platform that provides a scalable development and runtime environment for your Data Products. Works from laptop to cloud.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 2
    Jina

    Jina

    Build cross-modal and multimodal applications on the cloud

    ...Polyglot gateway that supports gRPC, Websockets, HTTP, GraphQL protocols with TLS. Intuitive design pattern for high-performance microservices. Seamless Docker container integration: sharing, exploring, sandboxing, versioning and dependency control via Jina Hub. Fast deployment to Kubernetes, Docker Compose and Jina Cloud. Improved engineering efficiency thanks to the Jina AI ecosystem, so you can focus on innovating with the data applications you build.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 3
    MLflow

    MLflow

    Open source platform for the machine learning lifecycle

    MLflow is a platform to streamline machine learning development, including tracking experiments, packaging code into reproducible runs, and sharing and deploying models. MLflow offers a set of lightweight APIs that can be used with any existing machine learning application or library (TensorFlow, PyTorch, XGBoost, etc), wherever you currently run ML code (e.g. in notebooks, standalone applications or the cloud).
    Downloads: 7 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB