Machine learning is no longer just a nice-to-have. Companies of all sizes are using it to understand customers better, spot problems early, predict demand, and make everyday decisions faster. But here’s the honest truth: building a great model on your laptop is only half the story. Getting that model to work reliably day after day in the real world—without crashing, slowing down, or giving wrong answers—is the hard part.
That’s exactly why MLOps as a Service has become so popular. It’s professional help that takes care of the complicated bits so you can focus on what your business actually needs from AI. One company that does this really well is DevOpsSchool. Their MLOps as a Service gives you everything you need from start to finish: planning, building, teaching your team, and keeping things running smoothly.
Let’s walk through it together in plain language—what MLOps actually is, why it matters right now, the everyday problems it solves, and how a service like this can make your life easier.
What is MLOps, Really?
MLOps is just a short way of saying “Machine Learning Operations.” It’s the set of practices that help teams take a machine learning model from a notebook experiment to a live, working system that people can trust.
Think of it like this: Regular software teams use DevOps to write code, test it quickly, and push updates without breaking everything. MLOps does the same thing—but for machine learning models. It handles extra challenges like changing data, models that “forget” how to work over time, and the need to keep experimenting safely.
Without MLOps, you often see the same frustrating pattern: Data scientists create amazing models → they hand them over → operations teams struggle to run them → nobody knows why the predictions suddenly got worse → everyone gets stressed.
MLOps fixes that by bringing automation, clear processes, and teamwork to the whole journey.
Why More Companies Are Choosing MLOps as a Service
Most businesses don’t have the time, people, or budget to build a full MLOps system from scratch. And honestly, they don’t need to. That’s where “as a Service” comes in. You get expert help without hiring a huge new team or learning every tool yourself.
Here are the four biggest reasons companies go this route:
- They want models in production fast—not sitting in a folder for months.
- They need the system to stay accurate even when customer behavior or market conditions change.
- They want to avoid expensive mistakes like wrong predictions or security leaks.
- They want their current team to learn how to manage it long-term, not depend on outsiders forever.
DevOpsSchool has been helping companies with exactly this for years. They work with startups, mid-size businesses, and big enterprises in healthcare, banking, retail, manufacturing, and tech—across India, the USA, Europe, and beyond.
What You Actually Get with DevOpsSchool’s MLOps as a Service
Their service is built around four clear pieces that cover the entire machine learning lifecycle:
- Consulting – They sit with you, understand your goals, and design the simplest, most effective plan for your business.
- Implementation – They build the pipelines, connect your data sources, set up monitoring, and get models running in production safely.
- Training – They teach your data scientists, engineers, and operations people so everyone knows how to keep things going.
- Ongoing Support & Monitoring – They watch your models 24/7, alert you to problems like data drift, and help retrain when needed.
You don’t have to pick every piece. You can start small and grow as your AI projects grow. That flexibility is one reason companies keep coming back.
Real Benefits You’ll Notice Every Day
When MLOps is done right, the improvements are practical and easy to see.
| What You Get | What It Means for Your Business |
|---|---|
| Faster model launches | New features or predictions go live in days, not months |
| Models that stay accurate | Less “surprise” bad results when data changes |
| Much less manual work | Automation handles updates, testing, and deployments |
| Everyone works better together | Data scientists and operations teams stop fighting |
| Lower long-term costs | No need to keep hiring specialists for every new project |
A retail company, for example, can keep product recommendations fresh during big sales seasons. A bank can keep fraud detection sharp as new tricks appear. These are the kinds of wins that pay for themselves quickly.
The Most Common Problems—and How MLOps Fixes Them
Here are the things that go wrong most often—and how a good MLOps setup stops them:
- Models get worse over time (data drift) → Automatic monitoring spots it early and triggers retraining.
- Deployments take forever → CI/CD pipelines push updates in minutes instead of weeks.
- Data comes from everywhere and it’s messy → Clean, reusable pipelines pull everything together properly.
- Team doesn’t know enough → Hands-on training fills the gaps quickly.
DevOpsSchool builds all of these safeguards into their service so you avoid the usual headaches.
Who’s Behind This? Meet Rajesh Kumar
The person leading the charge at DevOpsSchool is Rajesh Kumar. He’s not just another trainer—he has more than 20 years of real-world experience in DevOps, DevSecOps, SRE, DataOps, AIOps, MLOps, Kubernetes, and cloud platforms.
Rajesh has worked as a Principal DevOps Architect and Director of Engineering. He’s trained thousands of professionals and helped big names like Verizon, Nokia, Cognizant, Vodafone, and many others build reliable systems. Participants always say the same thing: his classes are clear, full of practical examples, and he answers every question patiently.
You can read more about him and see his work at Rajesh Kumar. When you work with DevOpsSchool, you’re learning from someone who’s been doing this for real companies for two decades.
What People Say About Working with DevOpsSchool
Real feedback tells the story better than any sales page:
- “The sessions were very interactive. Rajesh cleared all doubts and gave great hands-on practice.” – Abhinav
- “Best training I’ve attended. Everything was well explained and organized.” – Sumit
- “Thank you, Rajesh. I learned so much and now I feel confident.” – Multiple participants
These are everyday professionals who walked away ready to apply what they learned.
Why Choose DevOpsSchool?
DevOpsSchool has built a solid name as one of the best places for practical training and services in DevOps, MLOps, Kubernetes, cloud, and more. They’re not about fancy slides—they’re about helping you get results you can see and measure.
If you’re serious about making machine learning a real, dependable part of your business, they’re a great partner to start with.
Ready to Make MLOps Easy?
If this sounds like the help you need, just reach out. They’ll talk through your current setup, your goals, and the simplest next steps.
Here’s how to contact them:
✉️ Email: contact@DevOpsSchool.com
📞 Phone & WhatsApp (India): +91 84094 92687
📞 Phone & WhatsApp (USA): +1 (469) 756-6329
You don’t have to figure out MLOps alone. A short conversation could save your team months of trial and error—and get your models working reliably much sooner.
