In our latest conversation, we dialogue with Satish Raj, VP of Engineering, Cloud Platform at Imprivata. He has 20 years of experience in software engineering and management. An innovator with expertise in new product development, leading adoption of technologies/tools, driving change and transforming engineering organizations. As Technology has di…

Atul Rawat highlights one important aspect of the software industry: The rising cost of Software Maintenance in today’s episode of KnolBytes. Atul is Vice President, Operations at Knoldus with more than 20 years of experience in IT/ITeS as a Techno-functional & Business Management Professional. IT budgets these days are not just measured by their n…

In our latest conversation, we held a dialogue with Bhavya Aggarwal, CTO at Knoldus. He has 16+ years of experience in leading complex technical projects and is an expert in Java & Scala. Success rates of IT projects are relatively low in the industry and Bhavya talks about how success can be ensured based on his vast experience. He highlights the …

This week, we sat down with Mayank Bairagi and Sahil Sawhney. Sahil is a Lead DevOps Consultant at Knoldus and is experienced in delivering Architectural solutions for customers and mentoring the new talent that comes in. He keeps a keen eye on the cutting edge DevOps trends in the industry. Mayank has 11+ years of experience in the industry and ha…

We sat down for a conversation with our Data Scientists a.k.a our MachineX wizards, Shubham Goyal and Pranjut Gogoi who has extensive experience in building AI algorithms for their customers. Our Data Scientists talked about the current state of Data Science & AI in the industry and whether it lives up to the hype after all. The podcast will answer…

To serialize an object means to convert its state to a byte stream so that the byte stream can be reverted back into a copy of the object. Have you ever wondered how, when and where spark uses serialization while distributed computing? Let's gather in this podcast to understand the core of how spark use serialization.…

DAG is a graph denoting the sequence of operations that are being performed on the target RDD”. Spark uses DAG to carry out the in-memory computations. So, what happens internally when we perform any transformation and action on RDD? How does Spark handle it through DAG? We are going to answer these questions through this podcast. Listen now…