Remove Azure Remove Engineering Management Remove Google Cloud Remove Scalability
article thumbnail

How to Hire Freelance DevOps in 2023

Mobilunity

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
article thumbnail

The Good and the Bad of Snowflake Data Warehouse

Altexsoft

This demand gave birth to cloud data warehouses that offer flexibility, scalability, and high performance. 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. Great performance and scalability.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

MLOps and DevOps: Why Data Makes It Different

O'Reilly Media - Ideas

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. Today, a number of cloud-based, auto-scaling systems are easily available, such as AWS Batch. Software Development Layers.

DevOps 143
article thumbnail

Serverless; the next big thing

The Agile Monkey

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. In addition to the cost reduction, lambda functions enable virtually unlimited scalability.

article thumbnail

Data Mesh Architecture: Concept, Main Principles, and Implementation

Altexsoft

Through all these shifts, data mesh is called to solve the problems of centralized data platforms by giving more flexibility and independence, agility and scalability, cost-effectiveness, and cross-functionality. Data mesh can be utilized as an element of an enterprise data strategy and can be described through four interacting principles.