The use of machine learning models by development/operations (DevOps) teams is known as machine learning operations (MLOps). MLOps combines Machine Learning, DevOps, and data engineering into a set of practices. MLOps aims to reliably and efficiently deploy and maintain machine learning systems in production. Machine Learning, DevOps, and Data Engineering come together in MLOps. An MLOps Engineer is a traditional Software Engineer who has specialized in the deployment and production aspects of the overall Data Science process. Who Needs MLOps?

DevOps is a set of cultural philosophies, practises, and tools that improves an organization’s ability to deliver high-velocity applications and services, allowing it to evolve and improve products at a faster rate than traditional software development and infrastructure management processes. Organizations can better serve their customers and compete in the market because of this speed.  How DevOps Works?  Development and operations teams are no longer “silos” in a DevOps model. These two teams are sometimes combined into a single team where

SRE stands for site reliability engineering, and it’s a software engineering approach to IT operations. To manage systems, solve problems, and automate operations tasks, SRE teams use software. SRE delegated tasks previously performed by operations teams (often manually) to engineers or operations teams, who use software and automation to solve problems and manage production systems. When it comes to building scalable and highly reliable software systems, SRE is a valuable practice. It allows you to manage large systems using code,

What is AIOps? Big data, modern machine learning, and other advanced analytics technologies are used in AIOps platforms to improve IT operations (monitoring, automation, and service desk) functions directly and indirectly by providing proactive, personalized, and dynamic insight. Multiple data sources, data collection methods, analytical (real-time and deep) technologies, and presentation technologies can all be used at the same time with AIOps platforms.  The definition of AIOps is fluid because it is an emergent space. However, the following are the

What is DevOps? DevOps is the combination of individuals, process and technology to provide value to customers continuously. DevOps enables formerly siloed roles—development, IT operations, quality engineering and security— to collaborate to provide better as well as more reliable products. By adopting a DevOps culture together with DevOps practices and tools, teams gain the flexibility to higher reply to customer requirements, increase confidence within the applications they build, as a result growth becomes speedy which leads to achieve business goals