Kubernetes Bangalore Meetup March 2024

Join Kubernetes Bangalore (K8sBLR) for an insightful event focused on Cloud Native Platforms. We will delve into Kubernetes, Cloud Native solutions and discussing their impact on Cloud Computing. From Containers to Docker, we will explore how these technologies are shaping the future of development and deployment.
Don't miss this opportunity to network with fellow tech enthusiasts, while learning about the latest trends in Open Source solutions. Whether you are an expert in Kubernetes or just starting your journey in Cloud Computing, this meetup is perfect for anyone looking to deepen their understanding of modern PaaS offerings.
RSVP now to secure your spot at this exclusive event!

Target Audience:
If you are interested to learn about Kubernetes, and all the exciting new happenings in this space, then please join us in our in-person event

Agenda:
01:40 PM - 02:00PM - Registration/ Welcome
02:00 PM - 02:40 PM - Apiserver Network Proxy (Imran Pochi,Microsoft)
02:45 PM - 03:15 PM - Resource usage tracking for data and AI workloads
Resource usage tracking for data and AI workloads with Yunikorn(Manikandan Ramaraj)
03:15 PM - 03:30 PM. - Tea/Snacks
03:30 PM - 04:00 PM - Scaling Apache Airflow data pipelines towards enterprise AI journey using Kubernetes (Satya Nayak & Amogh Desai)
04:00 PM - 04:30 PM - Virtual clusters on Kubernetes (TBD)
04:30 PM - 05:00 PM - Kubernetes in air-gapped Environments using Zarf (Vibhav Bobade, Uffizzi)

• Ligtning Talks
• Open Floor

Speakers :
Amogh Desai - Senior Software Engineer at Cloudera and Apache Airflow Committer
Seasoned engineer with a 3-year track record in cloud-native product development for data engineers, including familiarity in big data technologies. Apache Airflow Committer contributing across project domains. Skilled in Python, Golang, AngularJS, Helm Charts, Kubernetes, Apache Spark, and other big data technologies. Passionate about open source and driving innovation in tech.

Satya Sundar Nayak - Engineering Manager at Cloudera
Satya Sundar Nayak leads the Cloudera Data Engineering (CDE) team. In his role, he oversees the development and management of the CDE platform, empowering data scientists to execute intricate data pipelines seamlessly through the utilization of Apache Airflow and Apache Spark on Kubernetes. With an extensive background spanning more than 18 years in the fields of fintech, BiData, and analytics, Satya brings a wealth of industry expertise to his leadership position. Beyond his professional pursuits, he is a passionate fitness enthusiast, a dedicated sports lover, and an avid reader.

Manikandan Ramaraj - Manikandan Ramaraj is currently a Staff Software Engineer at Cloudera and PMC Member of Apache YUNIKORN working on resource management. He has been contributing to several Apache projects like YUNIKORN (YK), YARN, Submarine for several years, especially focussing on YK in recent times. He has over 17+ years of experience with expertise in building Data Infrastructure & High Volume SMS operators, Ad Server & Exchanges.

Topics:
Amogh Desai & Satya Nayak: Scaling Apache Airflow data pipelines towards enterprise AI journey using Kubernetes

• 1. How we use Apache Airflow for various use cases
• 2. How K8s enhances Airflow
• 3. Shortcomings of K8s with Airflow
• 4. How we handle these shortcomings by integrating with 5. Apache Yunikorn and designing improvements for NFS
• 6. Learnings and challenges in the process

Manikandan Ramaraj: Resource usage tracking for data and AI workloads with Apache YuniKorn
Data processing and AI applications normally consist of multiple jobs in pipelines. Tracking resource usage for these workloads is not simple. A workload's resource usage could change each run if the data being processed changes. Observing the usage for different runs over time is important for users and cluster admins.

Attendee Benefits:

• How we use Apache Airflow for various use cases
• How K8s enhances Airflow
• Shortcomings of K8s with Airflow
• How we handle these shortcomings by integrating with 5. Apache Yunikorn and designing improvements for NFS
• Learnings and challenges in the process