Energy, Cost, and Performance: Rethinking Data Center Design

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Data centers consume a massive amount of energy, and this demand is growing rapidly as facilities are increasingly designed to support AI and GPU-heavy workloads. Decisions made early—during design and planning—have long-term consequences. Good choices can save energy, money, and operational headaches, while poor ones often lock in inefficiencies that are difficult and expensive to… Continue reading Energy, Cost, and Performance: Rethinking Data Center Design

Docker and Podman orchestration, limitation and emergence of Kubernetes

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Continuation from here . Here’s the summary. To optimize a data center, effective control over computing resources is essential, and containers are vital for this. They encapsulate applications with all necessary components, allowing them to run on any server that supports containers. This on-demand operation aligns with serverless architecture, enabling resource allocation efficiently to balance… Continue reading Docker and Podman orchestration, limitation and emergence of Kubernetes

Docker or Podman, whichever fits for your use case

Joyanta Biswas1 Comment

Let me clarify few terms here. Docker and Containers are related but distinct technologies. A Container is the core technology that packages your application code along with the necessary dependencies into a single unit. It requires a runtime to operate on a virtual machine or server. Docker is a tool that provides this runtime to… Continue reading Docker or Podman, whichever fits for your use case

Hardware role for ML

Joyanta Biswas1 Comment

Continuation from here https://joyantablog.wordpress.com/2025/04/08/neural-network-dive-deeper/ Let’s continue exploring the hardware magic behind long machine learning tasks like training and inference. In my previous post, I discussed how tools like TensorFlow and PyTorch offload resource management and expose optimal approaches through libraries and APIs. This enables you to focus on understanding the methods and functionalities, applying them… Continue reading Hardware role for ML

Neural network, Dive Deeper

Joyanta Biswas1 Comment

Continuation from here . What discussed so far how micro services helps implementing server-less architecture for Neural network based architecture. In this article I will talk few interesting topics like parallel computing, how ML library tools helps implementing smart resource management, and finish by giving a touch hardware solutions from NVIDIA helps accelerating ML progress.… Continue reading Neural network, Dive Deeper

MicroService concept, philosophy and ML importance

Joyanta Biswas1 Comment

Continuation from here. In that article, I explored how a microservice-based solution can address several limitations of serverless computing. For instance, AWS Lambda’s time limit for running long tasks can be mitigated by moving to containerized solutions. In this article, I’ll dive deeper into the microservice concept and explain why it’s crucial for enabling true… Continue reading MicroService concept, philosophy and ML importance

Serverless Computing and AI/ML — Balancing Performance, Cost, and Sustainability

Joyanta Biswas1 Comment

In this post, I’d like to share some thoughts on serverless computing, especially in the context of AI/ML. I’ve kept the content light on technical jargon so it’s easier to follow, even if you’re not deeply familiar with these concepts. Feel free to comment and share your thoughts! Running powerful computing systems isn’t just about… Continue reading Serverless Computing and AI/ML — Balancing Performance, Cost, and Sustainability