Mobilunity

JANUARY 4, 2023

Key Skills and Responsibilities for Remote DevOps Engineer. DevOps Freelance engineers manage the delivery of new code and primarily collaborate with the IT team and developers. The Differences between AWS, Azure, and GCP Engineers. Google Cloud Storage is a feature of GCP for object storing.

DevOps 52

DevOps How To Azure Weak Development Team 52

DataRobot

SEPTEMBER 6, 2022

And lastly, engineers managing IT or production environments find it simple to connect the DataRobot AI Cloud platform to other tools. See DataRobot AI Cloud in Action. With an intuitive interface and out-of-the-box components, you can reach your goals and be efficient without deep data science expertise or coding skills.

Artificial Inteligence 52

Artificial Inteligence Analytics Data Machine Learning 52

Altexsoft

APRIL 26, 2022

Initially built on top of the Amazon Web Services (AWS), Snowflake is also available on Google Cloud and Microsoft Azure. As such, it is considered cloud-agnostic. This optimized data is stored in one of the cloud object storage such as S3 by AWS, Google Cloud Storage, or Microsoft Azure Blob Storage.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

O'Reilly Media - Ideas

OCTOBER 19, 2021

If you ask an engineer to show how they operate the application in production, they will likely show containers and operational dashboards—not unlike any other software service. As a commercial product, Databricks provides a managed environment that combines data-centric notebooks with a proprietary production infrastructure.

DevOps 142

DevOps Data Software Review Technical Advisors 142

The Agile Monkey

SEPTEMBER 14, 2018

Major cloud providers like Amazon Web Services , Microsoft Azure , or Google Cloud Platform have Functions as a Service (FaaS) products where you can deploy those smaller chunks of code.

Serverless 40

Serverless Lambda Microservices Google Cloud 40

Altexsoft

JULY 19, 2022

In between, there are data engineers managing the data infrastructure with ETL/ ELT processes and tools required to transform operational data into analytical ones. As the picture above clearly shows, organizations have data producers and operational data on the left side and data consumers and analytical data on the right side.

Architecture 52

Architecture Data Analytics Data Engineering 52