Altexsoft

JULY 23, 2020

It facilitates collaboration between a data science team and IT professionals, and thus combines skills, techniques, and tools used in data engineering, machine learning, and DevOps — a predecessor of MLOps in the world of software development. MLOps lies at the confluence of ML, data engineering, and DevOps. MLOps vs DevOps.

Artificial Inteligence 145

Artificial Inteligence Machine Learning DevOps Tools 145

Altexsoft

JULY 19, 2022

This basic principle corresponds to that of agile software development or approaches such as DevOps, Domain-Driven Design, and Microservices: DevOps (development and operations) is a practice that aims at merging development, quality assurance, and operations (deployment and integration) into a single, continuous set of processes.

Architecture 52

Architecture Data Analytics Data Engineering 52

Lacework

SEPTEMBER 18, 2023

Start now with cloud security, DevOps, and other training that allows for professional development as well as opportunities for the shop to mature. The main cloud providers (AWS Cloud, Google Cloud, Azure) have lots of free trainings online and there are many labs, on Github and elsewhere, to help your team build their skills.

Security 82

Security Software Review CTO Systems Review 82

Tandem

FEBRUARY 23, 2021

Over the next ten years, the IOT continued to expand across all industries and consumer segments. Early adopters in varied industries — from manufacturing, to healthcare, to agriculture — began experimenting with connected devices to gather data and optimize processes. It was a tedious, error-prone, and expensive endeavor.

MVC 52

MVC Weak Development Team IoT Software Engineering 52