Cloud Deployment Container
Splice Machine’s Cloud Deployment Containers were designed to greatly facilitate the injection of intelligence into mission-critical cloud applications. This new deployment method allows developers to locally develop Internet of Things (IoT) and artificial intelligence (AI) applications that use streaming and machine learning (ML) technologies on their laptops, and then seamlessly deploy their ML models as containers on a virtual private network with Splice Machine’s Cloud Service. By deploying the same containerized code to the cloud, companies can easily train, test, and deploy machine learning at scale in mission-critical production applications. This deployment capability enables Apache MLlib pipelines to be deployed as containers as well as Spark Streaming applications that can transactionally stream directly into Splice Machine.
With Splice Machine Cloud Deployment Containers, standard applications written in traditional programming languages such as Java or newer languages such as Python, Node, or Scala can be easily migrated to the cloud and then extended with streaming and machine learning.
This enables companies to deploy smarter, predictive applications quickly and easily on the cloud and generate business and customer value in various use cases and verticals, such as supply chain, field service, healthcare, fraud detection and more.
|Categories||IoT > IoT Networking and Connectivity|
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