Confluent

FEBRUARY 6, 2019

Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way. It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way.

Machine Learning 106

Machine Learning Artificial Inteligence Scalability Data Engineering 106

Confluent

SEPTEMBER 26, 2019

Leveraging Rockset , a scalable SQL search and analytics engine based on RocksDB , and in conjunction with BI and analytics tools, we’ll examine a solution that performs interactive, real-time analytics on top of Apache Kafka and also show a live monitoring dashboard example with Redash. In the most critical use cases, every seconds counts.

Analytics 20

Analytics Serverless Blockchain Microservices 20

Confluent

JUNE 26, 2019

Due to this, many architects use middleware as a backbone for microservice communication to create decoupled, scalable, and highly available systems. producers and consumers) in a reliable, scalable, and fault-tolerant way. Kafka handles backpressure, scalability, and high availability for them.

Microservices 109

Microservices Software Review Technical Review Architecture 109

Confluent

OCTOBER 10, 2019

Most scenarios require a reliable, scalable, and secure end-to-end integration that enables bidirectional communication and data processing in real time. with the datacenter (on premises, cloud, and hybrid) to be able to process IoT data. Most MQTT brokers don’t support high scalability. How do you integrate both?

IoT 20

IoT Internet Weak Development Team Scalability 20