Session Archives
You can view all previous sessions of the M-Power Academy here.
This session provides deep insights into how AWS analytics services offer the flexibility of running big data and analytics workload through its offerings such as EMR, Glue and Redshift. It also covers a number of exciting services introduced as part of 'Reinvent 2021’ such as running Spark work on Kubernetes viz. EMR on EKS, a full featured notebooks IDE called as EMR Studio, managed Apache Airflow and enhancements to Glue and Redshift
This session will provide an overview of MLOps, its features and benefits in transforming your business. It will also give an overview of the orchestration frameworks and tools, provide a Demo and cover the various data integration options possible with AWS services.
The session will cover how cutting-edge AWS applications such as Amazon ECS Anywhere provide a simple yet powerful way to manage containerized applications on premises and anywhere else outside AWS. It will also explore how Amazon ECS deployment of Circuit Breaker can automatically discover and roll back unhealthy service deployments, which ensures that resources consumed in failed tasks are saved and keeps indefinite deployment delays at bay. Finally, the session will also explain how a new functionality, dubbed as Amazon ECS Exec, allows all Amazon ECS users to “exec” into a container running inside a task deployed on either Amazon EC2 or AWS Fargate.
This session provides deep insights into how AWS analytics services offer the flexibility of running big data and analytics workload through its offerings such as EMR, Glue and Redshift. As part of 'Reinvent 2021’, it also covers a number of exciting services such as running Spark work on Kubernetes viz. EMR on EKS, a full featured notebooks IDE called as EMR Studio, managed Apache Airflow and enhancements to Glue and Redshift.
AWS experts will provide a comprehensive overview of how to attain optimal price performance using AWS Graviton2 Processors. They will explain how they deliver 7x more performance with its 4x more compute cores, 5x faster memory, and 2x larger caches compared to the first-generation Graviton processors. The experts will talk about the superior performance of services such as Amazon ElastiCache, Amazon RDS and Amazon EC2 that can be powered by AWS Graviton2 processors. Through a series of hands-on use-cases and demos, they will also cover benchmarking applications, migrating RDS instances to AWS Graviton2 and deploying multi-architecture EKS clusters with Graviton2.
This hand-on session on Amazon Redshift will provide a comprehensive overview of Redshift’s capabilities. Watch DNB Solutions Architect Akshaya Rawat and Solutions Architect Tejal Rathod deep-dive into new features of Amazon Redshift like RA3, AQUA, and data sharing. Let them guide you through an architecture overview, and share some of the best practices to run Amazon Redshift-hosted data warehouses efficiently in your business.
Data warehousing, Amazon Redshift
In this session, attendees will learn a unified way of pre-processing data and orchestrating ML workflows in Sagemaker Studio. ML builders who want to leverage the big data processing using EMR can now work within the Sagemaker Studio. Experts will demonstrate how to integrate easily with big data tools and leverage the pre-processing of data using EMR. Furthermore, attendees will learn how to build complete workflows for training and deploying ML models, and metadata management with CI/CD using Sagemaker Pipelines. At the end of the session, the speakers will conduct a Q&A session.
Amazon Sagemaker Studio, Amazon Elastic Map Reduce, Simple Storage Service
2022 will keep the security sector on their toes, as the threat landscape for the year continues to unveil itself, revealing new vulnerabilities to attacks. This makes security a complex and nuanced topic that must be adjusted to suit the needs and priorities of different organisations. In this session, Jasmine Maheshwari, Senior Solutions Architect, AWS, will discuss holistic approaches to security and simplify the meaning of security for all teams in an organisation. The session will also share guidelines on how to create a phased approach for security posture improvement in an organisation.
This session, conducted by Venugopal Pai, Solutions Architect, AWS, explores different AWS services that deliver high performance, highly available applications for an organisation’s end users - particularly, Amazon Cloudfront and AWS Global Accelerator.
Amazon Cloudfront enables organisations to securely deliver content with low latency and high transfer speeds. Built for high performance, security and developer convenience, Cloudfront is the perfect vehicle to demonstrate how attendees can speed up the delivery of content, while fending off DDOS attacks.
Vengopal will also show attendees how to improve the availability and performance of your applications for local or global users with AWS Global Accelerator. This networking service improves the performance of an organisation’s traffic by 60 percent using AWS’ global network infrastructure.
For any product or service, availability is a key factor in their success. Gaining the highest availability with the lowest latency can be a hard task, as bugs, hardware failures, network issues, unusual traffic spikes and other reasons can hamper an organisation achieving the four 9s of availability - 99.99 percent.
In this session, Jasmine Maheshwari, Senior Solutions Architect, AWS, will explain why this is so crucial for fintechs or any organisation with mission critical applications to achieve. The session will also guide you through important architectural aspects such as availability, monitoring, change management, resiliency, DR - factors to help you achieve this coveted level of performance.
AWS Global Accelerator and Cloudfront
From making more accurate predictions, to gaining deeper insights from your data, improving customer experiences to reducing operational overheads, AWS’ Machine Learning services, infrastructure and implementation resources are there to support you at every stage of the journey.
This session, curated for data scientists and developers, guides you on how to prepare, build, train and deploy high-quality Machine Learning models swiftly, by utilising a broad set of capabilities that are purpose-built for ML.
Accelerate innovation in your organisation through purpose-built tools for every step of ML development, including labeling, data preparation, feature engineering, statistical bias detection, auto-ML, training, tuning, hosting, explainability, monitoring, and workflows. Learn about the most comprehensive ML service, Amazon Sagemaker - the "middle layer" in what AWS commonly refers to as the 3-tier AI/ML stack. This 200-level session highlights the main features of Amazon Sagemaker covering end-to-end ML deployment. It starts with Sagemaker Studio and covers GroundTruth, Data Wrangler, Feature Store, Experiments, Debugger, Clarify (for explainability), and more.
The second session in this event is all about teaching modern day ML users to leverage existing Big Data tools, which enable data engineering teams to explore and visualise large datasets. In order to do so, a unified analytics solutions (for e.g. Spark/Hive/metastore integrated with ML tools, such as python notebooks) is required to explore and prepare big-data datasets to build, train and deploy Machine Learning models in a single pane of glass.
Another big challenge is managing many experiments which keep running across the teams with CI/CD practices. Learn how to orchestrate these workflows for production for model building. This includes pre-processing, training, evaluation and registering the models with the respective model versions with lineage and metadata information. This also includes model deployment appropriate approvals and tests to validate the accuracy before deploying the models in production.
This session, by Vishnu Kota, Solutions Architect, Amazon Internet Services Private Limited and Sumir Kumar, AWS WWCS Geo Solution Architect, Amazon Internet Services Private Limited, introduces attendees to Sagemaker Studio, then demonstrates how you can use Sagemaker Studio notebooks to easily and securely connect to Amazon EMR clusters to prepare vast amounts of data for analysis and reporting. Finally, the speakers will introduce and demonstrate Sagemaker Pipelines to automate the ML CICD workflow steps of pre-processing, training, deployment and managing the model metadata.
Deliver apps quickly and efficiently to your customers by introducing automation into the stage of app development through Continuous Integration, Continuous Delivery and Continuous Deployment. ‘Continuous integration and continuous delivery’ (CI/CD) techniques enable teams to increase agility to quickly release high-quality products. In this session, Vishal Gupta, Solutions Architect, AWS and Vivek Ghildiyal, Solutions Architect, AWS, talk about how CI/CD helps in building a successful product by enabling teams to scale by automating safe, repeatable deployments. This includes code, as well as infrastructure maintenance and deployment. Along the way, the speakers will also discuss how companies can integrate security controls into the CI/CD pipeline.”
In session 2, Chandrashekar Munibudha, Principal Solutions Architect, AISPL, will dive deep into the practice of Chaos Engineering - the discipline of experimenting on a distributed system to induce artificial failures. It is a process that builds confidence in your system’s capabilities to withstand turbulent conditions during production. In this session, Chandrashekar will present an overview of chaos engineering and AWS Fault Injection Simulator. AWS Fault Injection Simulator is a fully managed chaos engineering service that helps you improve application resiliency by making it easy and safe to perform controlled chaos engineering experiments on AWS. The session will include a demo of how to use AWS Fault Injection Simulator to make applications more resilient to failure.
Achieve greater scalability, more flexibility, and quicker time to release through serverless workflows. Chandrashekar Munibudha, Principal Solutions Architect, AISPL, will guide you on how to coordinate business workflows among distributed services using a simple, yet powerful, fully-managed service called AWS Step Functions. The session will also discuss how to build resilient, modern applications, and reduce costs using Step Functions.
AWS Step Functions is a serverless function orchestrator that makes it easy to sequence AWS Lambda functions and multiple AWS services into business-critical applications. Through its visual interface, you can create and run a series of check-pointed and event-driven workflows that maintain the application state. The output of one step acts as an input to the next. Each step in your application executes in order, as defined by your business logic.
The fourth event in the LevelUP series will focus on the domain of containers. The event will feature two engaging sessions conducted by experienced solutions architects from AWS.
In this session, Kayalvizhi Kandasamy, a Senior Solutions Architect at AWS, who works with digital native companies to support their innovations, will take you through the benefits of Amazon EMR on Amazon EKS, which
essentially enables you to use Amazon EMR to run Apache Spark workloads on Amazon EKS. The speaker will deep-dive into the technical aspects of it with clarity. You will discover how you can simplify the running of Big Data frameworks on Kubernetes without the hassles of managing open source code and deliver better performance while consolidating the infrastructure.
In this session you will explore the networking, storage, security, scaling, observability and logging aspects of Amazon Elastic Kubernetes Service (Amazon EKS). EKS is a managed container service to run and scale Kubernetes applications in the cloud. The speaker, Jayesh Vartak, a Solutions Architect at AWS, who focuses on containers, application modernization, infrastructure, big data and analytics, will delve into the EKS architecture and its essential elements. You will also learn about scaling sample application using HPA (Horizontal Pod Autoscaler), using CloudWatch Container Insights for metrics and logging, and about EKS’ seamless integration with IAM (Identity and Access Management) for RBAC (Role based Access Control).
The fifth event in the levelUp series will be in the domain of Analytics. The event will feature three distinct sessions, conducted by Solutions Architects from AWS.
Learn how to extract meaningful insights about your customers from volumes of raw Big Data in the first session of the event. Speakers Priya Jathar and Tejal Rathod, Solutions Architects, AWS will share how DNB customers are turning Big Data into meaningful business insights. They will also cover an Analytics pipeline overview, and focus on the key aspects of data processing, deriving analysis, and visualising insights. The session will wrap with demos on data preparation and visualisation.
In this session, the speakers will be utilsing different solutions from AWS, including Analytics Pipeline on AWS, Big Data Processing, Big Data Analysis, Big Data Visualisations, AWS Analytics Services like AWS DataBrew, AWS Glue, Amazon Redshift, Amazon Athena, and Amazon QuickSight.
Every organisation has a different threshold for handling Big Data. As the tools and solutions for working with big datasets evolve, so does the data. Your organisation may require an overarching system to manage large volumes of data that can be analysed for business purposes - which is Big Data Architecture. You will also need to establish big data architectural components before embarking on a Big Data project. Implementing best practices or key principles in your architecture strategy will help create a well-rounded approach that ensures your data addresses a wide range of business needs.
This session will provide an overview of ‘Analytics pipeline 101’ on AWS through broadly seen technical architecture patterns in the Big Data space using AWS Analytics Services. Watch Priya Jathar and Tejal Rathod, Solutions Architects, AWS walk through analytics architecture patterns like Batch/Streaming/Ad-hoc analytics, Serverless analytics, ML Integrations, and Data Mesh. This session also covers customer implemented solutions from industries like gaming and retail, to name a few.
In this session, the speakers will be utilsing different solutions from AWS, including AWS Modern Data Architecture, AWS Analytics Architecture patterns, AWS Analytics Services, Analytics in Payments, Gaming, Retail and Logistics industry verticals.
Data Lakes enable organisations to store all their structured and unstructured data at any scale, and run different types of analytics to make better, more insightful decisions. However, the ingestion of streaming data into data lake has limitations due to limited support of transactions and incremental data processing on traditional data lake platforms. In this session, Dipta Shekhar, Enterprise Solution Architect, AWS and Akshaya Rawat, Solutions Architect, AISPL introduce the concept of transactional data lake platforms and explain how they solve the problem. The session presents an example transactional data lake platform on AWS using Apache Hudi.
The sixth and final event in the levelUP series will dive even deeper into all things analytics. The event will feature two sessions, conducted by a seasoned Solutions Architect from AWS.
When it comes to developing, visualising, and debugging data engineering and data science applications, EMR Studio’s integrated development environment makes it easyfor any data scientist or data engineer. In this session, Sumir Kumar, Solutions Architect, AISPL, will cover the use of Jupyter Notebooks, debug with tools like Spark UI and YARN Timeline Service, and collaborate with peers using GitHub and BitBucket - all within the EMR Studio IDE.
The session will further guide you on how to schedule your notebooks as part of a data pipeline. Additionally, you’ll learn how to manage the big data platform by integrating EMR studio with corporate identity. You’ll also be able to define different roles for different data engineering members with appropriate access to the data lakes and metadata.
The session will feature three demos:
• First demo
Develop, visualise, and collaborate big data applications with EMR Studio environment and notebooks.
• Second demo
Running Spark/Hive jobs on EMR clusters and debugging Spark/Hive jobs using the Spark UI, Tez UI, and YARN Timeline Service.
• Third demo
Parameterise the notebooks and schedule them as part of a data pipeline without any additional tools.
Empower your enterprise by automating the process of converting data into insights, which in turn can boost your business, facilitate your goals, and help you understand and retain customers. Session two of this event teaches you how to do that by diving into Managed Analytics.
AWS customers worldwide use open-source distributions including Spark, Elasticsearch, Apache Kafka, and more for analytics. Learn how to deliver insights more quickly and cost-effectively by moving your big data processing, log analytics and search, andreal-time streaming and analytics to the fully managed AWS analytics services in your lake house architecture.
Furthemore, the session will help you understand what AWS Lake house architecture is, the benefits of moving to managed big data analytics services, how to move to managed operational analytics, and how to move to managed real-time analytics. Finally, the speaker - Sumir Kumar, Solutions Architect, AISPL - will conduct a live demo during the session.
Amazon EMR Studio, AWS analytics services , AWS Lake house architecture
