What is MLOps? and Top MLOps Strategy
AI and Machine Learning (ML) are everywhere. Amazon uses machine learning to recommend products. TGI Fridays made a virtual bartender using machine learning. Machine learning is used by car manufacturers to make cars drive themselves. This can be a long and painful process.
Use cases are limitless. The ML algorithms are not easy to develop, maintain or deploy. You need to have machine-learning operations (MLOps).
MLOps can be a difficult beast by itself. Even deploying a good MLOps Framework blindly can lead to chaos. You must plan the way that you will set up MLOps. An MLOps plan is essential.
What is MLOps?
Take a minute to read What is MLOps if you are new to MLOps, or machine learning generally. article. Both concepts are explained in simple terms and we show how businesses use them.
Machine learning models require specialized development and data preparation. They also need evaluation, maintenance, and evaluation. It’s not easy to get ML models that provide reliable business value. This requires continuous collaboration between machine learning engineers and software developers, as well as data specialists.
This new collaboration is complex and causes delays, friction, and errors. MLOps aims to change that. The tools, procedures, and workflows that businesses use to integrate reliable ML in software are the most important.
MLOps and DevOps
MLOps and DevOps are not the exact same thing. DevOps aims to improve the software development process. It allows software engineers and operations staff to work together in order to develop, deploy and update software.
MLOps is a different approach with a more complicated scope. The ML models are capable of incredible feats, but to communicate with the outside world they require traditional software. Imagine a giant human-piloted robot. The traditional software is the robotic pilot and the ML model is its underlying model.
The pilot must train, learn, study, and then train again. The robot must be constructed, tuned, and upgraded to include laser swords and cooler guns. The pilot trainers as well as the robot builders need to work together closely. Imagine the robot team replacing the Cool Sword with the Self-Destruct. This is a fantastic change. It reduces power consumption by 20%! If they forget to inform the pilot training team about this, then our rad anime mecha becomes a tragic warning tale about the importance of interdepartmental communications real quickly.
MLOps is a team of data engineers, machine-learning developers, and software engineering professionals who work together to implement machine-learning projects. Check out MLOps Motivation for a more detailed description with fewer anime references.
Key Components of MLOps Strategy
All stakeholders should have access to your MLOps Strategy. This is not a one-time process. An MLOps Strategy can and should change over time.
It should include the following:
Current Friction Points
Gather information from your team about any pain points that they are currently experiencing if your organization already uses ML models. You might come up with an MLOps plan that fixes future problems instead of current ones if you don’t have this information.
Ideal Workflow
How would the perfect MLOps solution look for your company? Do not worry about it being perfect the first time. This section will change as your team, business goals, and work scope change.
Budget
Constraints are important. You may not have unlimited funds to hire consultants and buy expensive software. You should at least know how much you can afford and what your ideal workflow will cost.
Short-Term Solutions
Put your pain points, ideal workflow, and budget together. Find the most difficult problems and then identify the best solutions. You might want to break your problem down into immediate and intermediate solutions if it is complex enough.
Originally Published on The Tech Trend
