TL;DR
Simplismart has proved to be a one-stop solution for all your MLOps. Be it fine-tuning, inferencing, or observing you have it all in just few clicks. The platform has reduced months of training and deployment effort to just few minutes. Simplismart is bringing in the revolution in MLOps lifecycle. This blog gives a brief of the simplismart platform and its effective UI.
In the world of Machine Learning, operational efficiency is key to unlocking the full potential of AI-driven solutions. Simplismart brings a game-changing MLOps platform designed to streamline the entire MLOps lifecycle—from training to deployment and then to observability—all within a single, intuitive interface. In this blog post, we'll explore how Simplismart is revolutionising the approach organisations are taking to streamline ML operations. We'll draw parallels to Terraform's transformative impact in DevOps and Databricks in DataOps.
How Terraform operator Hashicorp Started and Streamlined DevOps:
Today we know Terraform as a DevOps behemoth, but it started just 12 years back. Founders Mitchell and Armon were given tasks related to the Deployment, Security and Networking of different kinds of hardware and virtual machines. Finding these tasks boring and repetitive, they sought to solve these issues by building Hashicorp. Hashicorp was an overnight success, reaching an ARR of $300k in less than a quarter of operations. As the next step, Hashicorp open-sourced Terraform. Which went on to become the industry standard for multi-cloud infrastructure and the "Language of DevOps".
Streamlining ML Operations:
Similar to how Terraform revolutionized DevOps by streamlining environment setup and dependency management with a single configuration, Simplismart transforms model deployment into a straightforward process. Hence, Simplismart saves a lot of developer bandwidth and eases the process of MLOps.
Simplismart makes model deployment as easy as making a cake.
Rather than grappling with writing over 1000 lines of code and investing days of effort, Simplismart condenses MLOps tasks into a concise 16-line YAML file. Simplismart frees up organizations from tedious tasks like model training, deployment, and tracking. This means they can focus more on being innovative and creating value instead of dealing with complicated processes.
With Simplismart, organizations can swiftly deploy and manage models, facilitating agile development cycles and enabling rapid iterations. What once demanded the expertise of five specialised engineers, can now be accomplished with just one, thanks to Simplismart's user-friendly platform and intuitive workflows.
Driving Innovation with Observability:
Just as Databricks revolutionised data management with its comprehensive observability features, Simplismart empowers organisations with deep insights into model performance and behaviour. Simplismart keeps a close eye on important things like how much the GPU and CPU are being used, the health of nodes, and how well the cluster is performing. This helps users see if their models are working efficiently and spot any issues early on so they can fix them quickly.
Let's have a deeper look into the Model Suite of Simplismart.
Step 1: Easily add our cloud accounts in the "Create Secret" section and add our keys.
Step 2: Then connect with our cloud account very easily, select a region and add our credentials. After this connect the DNS using Hosted Zone. Add Domain, Sub-Domain, Zone ID, and the cloud account.
Once done, move ahead and create deployment clusters.
Step 3: Easily specify the cluster name, cloud account, region, Hosted Zone. The Simplismart platform gives an option to easily configure deployments by selecting the Machine Type, Disk size, Node count, and Scaling Range. This had to be done by writing long config codes for everything and had been a very cumbersome task.
Step 4: Next, we can add our models very easily. The interface gives an option to directly paste the path from sources like HuggingFace. It easily helps manage the accelerator, the cloud account, the configuration and quantisation like FP32, FP16 or INT8. Once selected and added, the suite automatically optimises the model through a model optimiser core in the backend.
Final Step: We can then easily deploy our model by selecting the Kubernetes configuration and done!
Yes, it is as easy as this.
Once deployed, go to the control panel and check deployments that are created in a particular cluster. You can then get the HTTPS endpoint of the model deployed and start using it. You can easily monitor the model metrics on a Grafana dashboard, which enables you to control the model's health.
Unlocking the Potential of AI: In today's data-driven world, AI holds the promise of transforming industries and driving innovation at unprecedented speed. Yet, realising this potential requires a robust and streamlined approach to MLOps. With Simplismart, organisations can harness the power of AI with confidence, knowing that their ML operations are optimised for efficiency, scalability, and reliability.
Don't believe it, check out this post on how Vodex, a multi-million business developed its unit economics with Simplismart!
