Pinterest launched a next-generation CDC-based database ingestion framework using Kafka, Flink, Spark, and Iceberg. The system reduces data availability latency from 24+ hours to 15 minutes, processes ...

Abstract: Since the rapid development of deep learning (DL) technology, large-scale GPU clusters receive a large number of DL workloads daily. To speed up the completion time, the workloads usually ...

For users, few things are more frustrating than encountering unavailable services or unexpected downtime. Load balancing significantly reduces these occurrences through its built-in redundancy and ...

If we use the FlightServiceClient to connect to a list of server instances, and a we call execute_query and then successive get_next_batch calls, will all these calls be to the same endpoint ...

Ever since Edison’s Pearl Street station came online, it’s been challenging to match the amount of electricity being generation with the customer’s fluctuating load. It’s a delicate balance requiring ...

Built on eBPF technology, the Isovalent Load Balancer is designed to run in any environment, from servers and virtual machines in the data center, to the public cloud, to Kubernetes containers. Since ...

Today, at its annual Data + AI Summit, Databricks announced that it is open-sourcing its core declarative ETL framework as Apache Spark Declarative Pipelines, making it available to the entire Apache ...

A step-by-step guide to deploying, configuring, and testing a multi-AZ, multi-region SQL Server FCI in the Azure cloud, complete with a PowerShell script that handles the networking configuration.

In a multi-isolated network environment, how should the collector cluster mode be configured when deploying as an installation package? From the documentation, I see that the only configuration ...