Built with BigQuery: How to accelerate data-centric AI development with Google Cloud and Snorkel AI
Built with BigQuery: How to Accelerate Data-Centric AI development with Google Cloud and Snorkel AI.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
A Simplified Guide to Cloud Data Platform Architecture
Since the 2006 launch of Amazon Web Services (AWS), the world’s first hyper-scale public cloud provider, thousands of data-driven businesses have shifted on-premise data storage and analytics workloads into the cloud by architecting or adopting a cloud data platform. As the volume, variety, and velocity of enterprise data continues to grow in 2023, cloud data platforms with legacy tech and complex architectures are becoming increasingly time-consuming and costly to manage.
Get Ready For The Cloud API War
About a decade ago, cloud computing became the norm in enterprise IT deployments. Infrastructure as a Service (IaaS) and Integrated Platform as a Service (iPaaS) vendors were fiercely competing to deliver the private and public cloud products that would power the next generation of app development, processing, storage, and networking. And since APIs are at the heart of cloud computing, the race was on to deliver the API that developers and sysadmins would most favor. The Cloud API War had begun.
Responding to changes in cloud resources with Eventarc and Cloud Run
Eventarc - Use Cloud Run to react to events about changes in the provisioned cloud resources.
Announcing Koyeb Pulumi Provider
Today, we are glad to share that you can interact with your Koyeb resources in your infrastructure using Pulumi. Pulumi is a modern infrastructure as code platform that allows you to define, deploy, and manage cloud infrastructure on any cloud using your favorite programming languages.
Cloud Object Storage-based Architectures are Natively Scalable and Available
There is a long history of clustering architectures with respect to building distributed databases for two primary reasons. The first is scalability. If a cluster of nodes has reached its capacity to perform work, adding additional nodes are introduced to handle the increased load. The second is availability. The ability to ensure that if a node fails, let’s say during ingestion and/or querying, remaining nodes would continue to execute due to state replication.
Beyond Data Insights: The Transformative Power of the Data Cloud
Just as iTunes and Spotify transformed the music industry, Snowflake’s Data Cloud is transforming companies and industries.
What's your API strategy for the cloud?
Shouldn’t your API manager be as cloud native as your applications? Don’t trust security and governance to tech dinosaurs or legacy solutions. Get ahead of the crowd with a cloud native platform built to meet you wherever you are on your digital transformation journey — on prem, hybrid, or entirely in the cloud. No other solution offers the same flexibility for your application modernization. Get started with Kong.
Patrick Moorhead | Your Cloud Sucks!
The world is going to be hybrid and multi-cloud and we don't necessarily need more than that.
Implement a Multi-Cloud Open Lakehouse with Apache Iceberg in Cloudera Data Platform
Since we announced the general availability of Apache Iceberg in Cloudera Data Platform (CDP), Cloudera customers, such as Teranet, have built open lakehouses to future-proof their data platforms for all their analytical workloads. Cloudera partners are also benefiting from Apache Iceberg in CDP. For example, Modak Nabu is helping their enterprise customers accelerate data ingestion, curation, and consumption at petabyte scale.