AWS Online Tech Talks

Type: Use Case How To | Level: 300

In today’s world where predictions are made by machine learning (ML) algorithms at scale, it’s increasingly important for tech organizations to be able to explain to their customers and internal teams why they made a certain decision based on an ML model’s prediction. Explaining ML models and understanding the reasoning behind the predictions is often difficult, but critical for responsible use of ML. In this webinar, learn how to identify the importance of various features in overall model predictions as well as for individual inferences using Shapley values and detect any shifts in feature importance over time after the model is deployed to production.

What you'll learn:

• Understand which features contributed most to your model’s overall prediction-making process
• Explain individual model predictions
• Monitor your model for changes in behavior

Speaker(s): Denis Batalov, AI/ML Tech Leader, AWS WWSO AI/ML

Who Should Attend: Data scientists, ML practitioners

Type: Service How To | Level: 200

When you build a search or log analytics solution to store business critical data, it’s important to have a comprehensive security toolkit that includes features for authentication, authorization, encryption, auditing and regulatory compliance. Access to sensitive enterprise data must be secure, easily configurable and auditable. Amazon OpenSearch Service incorporates native SAML support for OpenSearch Dashboards, fine-grained access control for your data access and cluster permissions needs, detailed security auditing including watching interactions on highly sensitive fields or documents, and more. In this webinar, learn how to use these features to audit and protect your business data in compliance with industry standards.

What you'll learn:

• Learn how to create and implement a comprehensive security strategy for your Amazon OpenSearch Service domains
• Integrate your existing identity provider with OpenSearch Dashboards
• Understand how backwards compatible security patches help protect you from newly discovered vulnerabilities

Speaker(s): Jimish Shah, Sr. Technical Product Manager, OpenSearch, AWS

Who Should Attend: Security Administrators, Infrastructure Administrators, Application Developers, DevOps personnel

Type: Service Deep Dive | Level: 300

Organizations building modern applications are increasingly turning to serverless API architectures powered by GraphQL and NoSQL databases to increase development velocity and decrease operational overhead. In this talk we will review key GraphQL and NoSQL concepts, how to use AWS AppSync and Amazon DynamoDB to create a serverless GraphQL API, and discuss the pros and cons of two approaches to using DynamoDB with GraphQL, single-table vs multi-table design.

What you'll learn:

• Understand the differences between single-table and multi-table design patterns when connecting a GraphQL API to an Amazon DynamoDB database
• Learn how to get started quickly with a serverless GraphQL API powered by AWS AppSync and Amazon DynamoDB
• Learn how to get started quickly with a serverless GraphQL API powered by AWS AppSync and Amazon DynamoDB

Speaker(s): Brice Pellé, Principal Product Manager, AWS AppSync; Alex Debrie, AWS Serverless Hero

Who Should Attend: API Developers, GraphQL Developers, Backend Developers, Front-end Application Developers, Full-Stack Application Developers, Solution Architects, CTOs

Type: Use Case How To | Level: 300

Join us to learn more about how to leverage the efficiencies and benefits of Containers in a hybrid environment. Carlos Santa Gadea, Sr. Product Manager with AWS will discuss more about how you can satisfy compliance, data gravity, and other business requirements by running your workloads on infrastructure you own while enjoying simple and familiar container tooling. Learn how you can run containerized data processing workloads at edge locations on your own hardware to allow you to stay close to your end customers and maintain reduced latency. We’ll also cover machine learning, image processing, big data, among other application workloads, without the need to transfer your data to the cloud or manage a third party orchestration software.

What you'll learn:

• Understand the ability to run containerized applications in customer owned infrastructure
• Learn how to maintain reduced latency while working with big data, image processing and other workloads
• Learn how to avoid transferring data or needing to leverage third party orchestration software

Speaker(s): Carlos Santa Gadea. AWS Sr. Product Manager

Who Should Attend: Developers, Infrastructure teams

Type: Service Intro | Level: 200

Join us to learn about the types of object, block, and file storage that AWS offers to help you deliver the best price/performance for your applications. Whether you are building cloud native apps, or migrating mission critical storage from your SAN to the cloud, AWS has the broadest and deepest cloud and edge storage. Learn about S3/EFS/FSx/EBS, and discover how to choose the best AWS storage service for your applications. We will cover object storage and archiving with S3, and elastic, scalable, managed file storage with EFS. Learn how FSx delivers fully managed high performance, scale-out file storage for Windows, Lustre, NetApp ONTAP, and Open ZFS. EBS high performance block storage for mission critical applications like Oracle, SQL and SAP HANA will be covered, as well as how to choose EBS volumes for your applications. AWS Outposts solutions will also be presented to show you how you can leverage AWS storage services at the edge.

What you'll learn:

• General introduction to AWS cloud Storage offerings.
• Which storage to choose based on your applications/workloads.
• How AWS cloud storage delivers the best price/performance.

Speaker(s): Rajesh Vijayaraghavan, Sr. Storage Specialist, AWS

Who Should Attend: Infrastructure managers, software engineers, storage/cloud IT managers

Type: Use Case How To | Level: 200

In machine learning (ML), data labeling is the process of identifying raw data (images, text files, videos, etc.) and adding one or more meaningful and informative labels to provide context so that a ML model can learn from it. In this AWS Online Tech Talk, you'll learn how you can use Amazon SageMaker data labeling offerings to identify raw data and add informative labels to create high-quality training datasets for your ML models.

What you'll learn:

• Discover common data labeling challenges and use cases
• Learn how Amazon SageMaker data labeling offerings accelerate the process of creating datasets for training ML models
• Walk through a demo of Amazon SageMaker data labeling offerings

Speaker(s): Manish Goel, Sr. Product Manager, AWS; Vedant Jain, Senior AI/ML Specialist SA, AWS

Who Should Attend: Data Scientists, ML Engineers, Data Operations Managers, and Program Managers

Type: Service How To | Level: 200

Technical and infrastructure failures, human error, cyberattacks, and natural disasters happen. These disruptions are inevitable, but they do not have to spell disaster for your critical IT systems. With AWS Elastic Disaster Recovery, organizations of all sizes can build resilience and prepare for fast, reliable recovery to AWS. In this Tech Talk, learn how you can continuously replicate servers to AWS using affordable storage, minimal compute, and point-in-time recovery to minimize downtime and data loss, meet stringent recovery objectives, and significantly reduce costs versus on-premises disaster recovery.

What you'll learn:

• Deploy a single, unified process to test, recover, and fail back a wide range of applications without specialized skillsets.
• Recover applications within minutes, at their most up-to-date state or from a previous point in time.
• Save costs by removing idle recovery site resources and pay for your full disaster recovery site only when needed.

Speaker(s): Ken Sze, Worldwide Disaster Recovery Specialist Solution Architect, AWS

Who Should Attend: Disaster Recovery Manager, Cloud Architect, Cloud Engineer, Manager / Director of Cloud Operations, IT Admin, Manager / Director of IT, IT Infrastructure Analyst, Business Continuity Director

Type: Solutions Best Practices | Level: 300

Amazon Aurora is a MySQL and PostgreSQL-compatible relational database built for the cloud, that combines the performance and availability of traditional enterprise databases with the simplicity and cost-effectiveness of open source databases. It provides the security, availability, and reliability of commercial databases at 1/10th the cost. Amazon Aurora is fully managed by Amazon Relational Database Service (RDS), which automates time-consuming administration tasks like hardware provisioning, database setup, patching, and backups. In addition to all the managed features, Amazon Aurora also provides industry leading features like automatic read scaling, fast databases cloning, Global Database, serverless and many more. In this session, you will learn about the distributed storage architecture that makes Aurora uniquely scalable. You will also learn about Aurora features like Serverless v2, Global Database, cloning, backtrack and more.

What you'll learn:

• You will learn Amazon Aurora’s value proposition over traditional relational databases (commercial and open source).
• You will learn the distributed storage architecture that makes Aurora uniquely scalable.
• You will also learn about Aurora features like Serverless v2, Global Database, cloning, backtrack and more.

Speaker(s): Aditya Samant, Sr. Database Specialist Solutions Architect, AWS

Who Should Attend: IT Architects, Database Architects, Database Developers, DBAs and DevOps engineers using Amazon Aurora databases

Type: Service Deep Dive | Level: 300

Learn how Amazon Kinesis Data Firehose enables you to reliably load your streaming data into data lakes, data warehouses, and analytics services built on AWS, with AWS Partners, and using open-source tools. This talk includes a demonstration showcasing how Kinesis Data Firehose easily captures, transforms, and delivers streaming data to a data lake built on Amazon S3. Learn to simplify Amazon S3 analytics workflows using Kinesis Data Firehose, Apache Parquet, and dynamic partitioning.

What you'll learn:

• Learn how to ingest terabytes of data for real-time processing from AWS and 3rd party data sources with the serverless offering of Amazon Kinesis Data Firehose
• Learn how to analyze streaming data with no-code serverless ETL to transform and parition data stored in S3
• Explore how to reduce costs of Amazon S3 analytics queries and to simplify Amazon S3 analytics workflows using Amazon Kinesis Data Firehose, Apache Parquet, and dynamic partitioning

Speaker(s): Mostafa Mansour, Head of Product for Amazon Kinesis Firehose, AWS

Who Should Attend: IT specialists, developers, data engineers, dev ops, data scientists, data analysts, big data developers

Type: Service How To | Level: 200

In this session you will learn the basics of how AWS Key Management Service (AWS KMS) works and how AWS KMS can help you protect sensitive data across AWS integrated services and inside your customized applications. We will also provide some performance, protection, and policy tips for navigating AWS KMS advanced features in attribute bases access control, encryption key caching, and improved policy management. You will also learn about AWS KMS functionality that can be used for a broad range of use cases, including data protection, key management, digital signing, and the newly launched HMAC feature.

What you'll learn:

• Learn the basics of how AWS Key Management Service (AWS KMS) works.
• See how AWS KMS can be deployed in the context of access control, separation of duties, data protection, and auditability.
• Learn about advanced AWS KMS functionality to enhance and expand your data protection strategies.

Speaker(s): Jeremy Stieglitz, Principal Product Manager, AWS

Who Should Attend: Builders and security practitioners that must address data encryption requirements to enhance their security and/or address compliance and audit requirements.

Type: Use Case How To | Level: 200

Data-first organizations are increasingly curious about a data mesh architecture. Learn how to design, build, and operationalize a data mesh architecture on AWS, one that helps businesses navigate their data challenges, optimize analytics processes, and deliver insights to the business faster.

What you'll learn:

• Learn the fundamentals of a data mesh architecture
• Understand the benefits (and challenges) of a data mesh
• Learn how to overcome and manage governance challenges associated wit data mesh

Speaker(s): Nivas Shankar, Principal Product Manager, AWS Lake Formation

Who Should Attend: Data Engineers, Data Modelers, Data Architects, Data Stewards, and Data Admins, ETL Developers

Type: Use Case How To | Level: 200

Containers and cloud-native architectures enable customers to ship software quickly and frequently. Amazon ECS and AWS Fargate are both fully managed services which enable customers to modernize and accelerate their software development lifecycle. In this session, we will look at how to build end-to-end automation including CI/CD, set up ECS Fargate clusters, managed containers lifecycle and ensure observability and security across all stages.

What you'll learn:

• In this session, we will look at how to build end-to-end automation including CI/CD, set up ECS Fargate clusters, managed containers lifecycle and ensure observability and security across all stages.
• Be able to use ECS Fargate to run containerized workloads
• Understand core aspects of CI/CD, observability and security needed for container workloads

Speaker(s): Arvind Soni, WW Head of GTM ECS, Amazon

Who Should Attend: Core Infrastructure Engineers, DevOps Engineers,

Type: Service Deep Dive | Level: 300

Resolving complex customer issues is often time consuming and requires agents to gather information from various knowledge bases to answer questions accurately and quickly. This leads to agent fatigue from information overload and long resolution times resulting in poor customer experience. Join the session to learn how to build a real-time agent assist solution to generate next best actions. Using ML-powered services, this agent assist solution provides relevant recommendations, real-time transcription, intent detection, and NLP based search.

What you'll learn:

• Learn about AWS CCI solutions and how to use AWS AI services to transform customer experiences.
• Give your contact center supervisor the tools to draw powerful insights, improve your agents' and customers' experience
• Build an agent assist solution to unlock CX insights, reduce call handle time, improve service and operational efficiency.

Speaker(s): Babu Srinivasan, Sr. Specialist SA - AI Services

Who Should Attend: COO, VP/Director Customer Service/Customer Success, VP/Director Shared Services, Customer Experience manager, Contact Center Director/Supervisor/manager, Customer support manager, Developer, IT Professional/Leader, Business User

Type: Service How To | Level: 200

As part of a resilience plan, it is important to proactively protect your mission critical applications from the risk of downtime. This includes understanding your applications’ ability to maintain availability and recover from disruptions. AWS Resilience Hub provides you with a central place to define, validate, and track the resilience of your applications on AWS. In this Tech Talk, we will show you how you can avoid unnecessary downtime caused by software, infrastructure, or operational disruptions. Learn how you can identify and resolve issues before they occur in production.

What you'll learn:

• Define your applications’ resilience targets (RTO and RPO) and help validate that these targets can be met prior to deployment.
• Identify resilience weaknesses and implement recommended remediation.
• Build a comprehensive view of your overall application portfolio resilience status through the Resilience Hub dashboard and resilience score.

Speaker(s): Tony Politano, Principal PMT, AWS

Who Should Attend: Disaster Recovery Manager, Cloud Architect, Cloud Engineer, Manager / Director of Cloud Operations, IT Admin, Manager / Director of IT, IT Infrastructure Analyst, Business Continuity Director

Type: Use Case How To | Level: 100

Industrial operations create massive amounts of data that can be harnessed and optimized through artificial intelligence (AI). AI has the potential to drive efficiency and scale for industries via process, throughput, and quality improvements, among other benefits. In this Tech Talk, learn how AWS customers are leveraging purpose-built industrial AI services to accelerate the data-to-decision lifecycle. We will discuss use cases of AI and machine learning (ML) in the industrial sector, how AWS customers are applying the technology, and how to get started rapidly with AI services from AWS.

What you'll learn:

• Learn about how you can use AI and ML to solve common industrial challenges
• Hear how AWS customers are leveraging purpose-built industrial AI services from AWS to accelerate the data-to-decision lifecycle
• Learn how to get started quickly by working with AWS Partners

Speaker(s): Chelsea Render, Sr. Product Marketing Manager, AWS

Who Should Attend: Business decision makers including line of business owners and managers, operations and production leaders; Technical decision makers in Engineering, Technology, Product, Architecture; IT professionals engaged with industrial operations

Type: Use Case How To | Level: 100

Computer vision (CV) can be a powerful tool to automate tasks that have traditionally required human inspection, such as evaluating manufacturing quality, improving supply chain logistics, and optimizing traffic management. In this Tech Talk, learn how AWS customers are improving their industrial operations with computer vision, and how you can get started quickly with AI services from AWS.

What you'll learn:

• Discover how you can use computer vision to automate manual inspection tasks, even at the edge
• Learn about purpose-built CV services from AWS, such as Amazon Lookout for Vision and AWS Panorama
• Hear how customers are working with AWS Partners to build CV applications quickly

Speaker(s): Michael Hoarau, Industrial AI Solutions Architect, AWS

Who Should Attend: Business decision makers including line of business owners and managers, operations and production leaders; Technical decision makers in Engineering, Technology, Product, Architecture; IT professionals engaged with industrial operations

Type: Service Deep Dive | Level: 400

Gravition EC2 provides a wide selection of instance types optimized to fit different use cases. Instance types comprise varying combinations of CPU, memory, storage, and networking capacity. Developers join us for a hands-on demo where you will learn how to choose the appropriate mix of resources for your applications and to scale your resources to the requirements of your workload.

What you'll learn:

• learn how to choose the appropriate mix of resources for your applications
• Learn hot to scale your resources to the requirements of your workload
• Learn how to run cloud native applications securely, and at scale.

Speaker(s): Michael Fischer, Prin SSA, EC2 Graviton OSS, AWS

Who Should Attend: Cloud Architect, Developer, IT Professional

Type: Solutions Best Practices | Level: 200

Amazon Relational Database Service for SQL Server (RDS SQL Server) is a managed database service that handles the undifferentiated heavy lifting of operating databases (i.e. patching, automated backups and failovers) to ensure high availability, durability and security, so you can focus on innovation and delivering business solutions. This session is a collection of learnings from 10+ years of helping AWS customers who migrated from self-managed SQL Server to managed Amazon RDS SQL server. Whether you are self-managing your own SQL server databases on-premise or an existing AWS customer, we will walk you through best practices, use cases, demos and considerations throughout the migration journey and after you have launched on RDS SQL Server.

What you'll learn:

• Provide helpful tips and tricks on how to migrate from self-managed to RDS SQL Server
• Learn how to optimize performance and cost with RDS SQL Server
• Learn best practices on migrating to RDS SQL Server

Speaker(s): Manish Punjabi, Head of RDS Commercial GTM Specialist at AWS; Sandeep Singh, Database Solution Architect at AWS

Who Should Attend: DBAs, Developers and engineers interested in migrating from SQL Server to RDS SQL Server

Type: Service How To | Level: 200

Amazon SageMaker Studio Lab is a free ML development environment that provides the compute, storage (up to 15GB), and security—all at no cost—for anyone to learn and experiment with ML. Join us for a hands-on demo where you start with an email address and end with an ML model in cloud. If you don't have an account yet, make sure to register at https://studiolab.sagemaker.aws for free so you can follow along.

What you'll learn:

• Learn and experiment with ML using a no-setup, free development environment
• Find out how you can setup an account and choose compute power
• Discover pre-packaged ML frameworks

Speaker(s): Michele Monclova, Principle Product Manager , AWS AI Platforms; Mia Chang ML Specialist SA, AWS WWSO AI/ML

Who Should Attend: Students, ML Learners, ML beginners

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