Mackenzie is the Global Startup Evangelist at AWS. His days are spent traveling the globe to meet startups, share their stories, and connect engineering teams together. Every day there are a large number of startups launching on AWS across every imaginable industry. It’s Mackenzie’s mission to find stories of startups that are helping to improve the world and share these stories with a wide audience.
With the increasing importance of Big Data and Machine Learning (AI/ML) to global businesses and industries, Kubernetes has emerged as a popular platform to run data workloads due to improved agility, scalability, and portability. Kubernetes offers improved portability for data workloads between different environments, such as on-premise data centers, public clouds, and edge locations. It provides a unified environment for managing both stateful and stateless applications, making it easier to run a wide range of data workloads and supports frameworks like Spark, Flink, PyTorch, TensorFlow, and others, making it easier to run data processing jobs and orchestrate ML pipelines in cloud-native or on-prem environments.
EMR is a fully-managed big data processing service offered by Amazon Web Services (AWS). EMR allows users to easily process large amounts of data using popular open-source data-processing frameworks like Apache Spark, Hadoop, and Hive. However, deploying and scaling data workloads on Kubernetes remains a challenge for many customers. Please join us for an EMR on EKS Builders Workshop at a location near you.
Why Attend?
During the workshop, you will gain hands-on experience and learn:
1. How Kubernetes simplifies infrastructure managementÂ
2. How Amazon EMR on EKS can reduce cost and optimize performance for big data workloadsÂ
3. Best Practices for implementing EMR on EKS inclusive of blue-prints for accelerating time to value
Indira Balakrishnan is a Principal Solutions Architect in the AWS Analytics Specialist SA Team. She is passionate about helping customers build cloud-based analytics solutions to solve their business problems using data-driven decisions. Outside of work, she volunteers at her kids’ activities and spends time with her family.
Kinnar Kumar Sen is a Sr. Solutions Architect at Amazon Web Services (AWS) focusing on Flexible Compute. As a part of the EC2 Flexible Compute team, he works with customers to guide them to the most elastic and efficient compute options that are suitable for their workload running on AWS. Kinnar has more than 15 years of industry experience working in research, consultancy, engineering, and architecture.
Sekar Srinivasan is a Sr. Specialist Solutions Architect at AWS focused on Big Data and Analytics. Sekar has over 20 years of experience working with data. He is passionate about helping customers build scalable solutions modernizing their architecture and generating insights from their data. In his spare time he likes to work on non-profit projects, especially those focused on underprivileged Children’s education.
Parul Saxena is a Big Data Specialist Solutions Architect at Amazon Web Services, focused on Amazon EMR, Amazon Athena, AWS Glue and AWS Lake Formation, where she provides architectural guidance to customers for running complex big data workloads over AWS platform. In her spare time, she enjoys traveling and spending time with her family and friends.Â
Saurabh Bhutyani is a Principal Big Data Specialist Solutions Architect at AWS. He is passionate about new technologies. He joined AWS in 2019 and works with customers to provide architectural guidance for running scalable analytics solutions and data mesh architectures using AWS analytics services like Amazon EMR, Amazon Athena, AWS Glue, AWS Lake Formation, and Amazon DataZone.
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