These are a few of the best machine learning tools.
Hello I am building a real time streaming analytics system, that will be used to analyse and trade the stock markets. I am looking for a Kafka expert who can pipeline the data from the broker, and then set up machine learning in Spark ML for me. You will be paid hourly for your time. You will get on call with me and advise me while I work hands on. If you know deployment of the models then that is plus points.
I am developing a money transfer application and need to setup a highly scalable and high-performance transaction processing system with message queues for parallel processing of incoming request, and with multi-threaded processes for each queue. MQ SERIES and KAFKA are the 2 technologies we are considering. The application is written in .NET and runs over LINUX Machines in an AWS Data Center. Need to demonstrate / simulate up to 100,000 TPS Scalable Production Environment.
The platform is an IoT platform where we are using KAFKA and it needs enhancements and checks to make it stable.
About the project: Explore the setup and configuration of a secure and highly available instance of Apache Pulsar () on IBM Cloud (). The overarching goal is to enable clients to build enterprise cloud applications using Pulsar. Goals: 1. Start simple: Install and configure Apache Pulsar on IBM Cloud using a helm chart () [access will be provided to the IKS cluster ()], and using Red Hat operator [access will be provided to the Red Hat OpenShift on IBM Cloud cluster()]. Test with a simple producer/consumer. 2. Add message options: Configure message compression, batching, deduplication, etc. Test with a simple producer/consumer. 3. Add message security: Configure end-to-end Pulsar message encryption (). Test with a simple producer/consumer. 4. Highly available region: Install and config...
try to fetch bootstap server and register server dynamically