Back to Basics Video Series

Basic architectural building blocks and best practices

'Back to Basics' is a video series that explains and examines basic cloud architecture pattern best practices. Each episode is hosted by an AWS SA (Solutions Architect) and focuses on a specific architectural building block independent of a specific cloud solution.
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Watch | Back to Basics: Best Practices for Selecting Inference Options to Deploy SageMaker ML Models

Learn how to choose the best Amazon SageMaker inferencing option for deploying your machine learning models based on your requirements like latency, throughput, payload size, and traffic patterns. Using a real-world fraud detection example, we'll walk through how to set up a SageMaker Real-Time Inference endpoint, make requests, and get predictions in real-time to meet low latency and high throughput needs.

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  • Machine Learning | Serverless

    New

    Back to Basics: Best Practices for Selecting…

    Back to Basics

    Learn how to choose the best Amazon SageMaker inferencing option for deploying your machine learning models based on your requirements like latency, throughput, payload size, and traffic patterns.

    In this episode, join Jyoti as she discuss four deployment options:
    1️⃣ SageMaker Real-Time Inference: Ideal for low latency, high throughput use cases like fraud detection, ad serving, and personalized recommendations. Supports payload up to 6MB and 60s processing time.
    2️⃣ SageMaker Serverless Inference: Best for intermittent or unpredictable traffic with ability to tolerate cold starts. Automatically scales resources. Supports payload up to 4MB and 60s processing time.
    3️⃣ SageMaker Asynchronous Inference: Queue requests with large payloads up to 1GB or long processing times up to 15 mins. Cost-effective by scaling endpoints to zero. Great for computer vision and object detection.
    4️⃣ SageMaker Batch Transform: For offline processing of large datasets in GBs or longer processing times up to days. Highest throughput option for data pre-processing, churn prediction, predictive maintenance.

    Using a real-world fraud detection example, we walk through how to set up a SageMaker Real-Time Inference endpoint, make requests, and get predictions in real-time to meet low latency and high throughput needs.

    Additional Resources:

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  • Machine Learning

    New

    Back to Basics: Infrastructure as Code…

    Back to Basics

    As enterprises embrace generative AI, robust infrastructure becomes crucial for scalable, reliable deployments. Join Neelam as she explores using Infrastructure as Code (IaC) and the AWS Cloud Development Kit (CDK) to streamline your GenAI application infrastructure.

    You'll learn:
    ✅ Challenges of deploying GenAI apps without IaC
    ✅ Benefits of IaC: version control, consistency, automation
    ✅ Architecting with AWS CDK - VPC, web app, and GenAI backend stacks
    ✅ Defining infrastructure in your preferred programming language
    ✅ Hosting web apps with Amazon ECS and load balancing
    ✅ Orchestrating GenAI inference with SageMaker, Bedrock or EKS
    ✅ Decoupled APIs for text gen, image gen using API Gateway & Lambda
    ✅ Best practices for avoiding over-abstraction and leveraging AWS services

    Whether you're building text summarization, chatbots, or image generation apps, IaC with AWS CDK provides the scalable, versionable foundation to power your GenAI innovation.

    Stop wrestling with manual deployments - unlock agility, consistency and productivity by codifying your GenAI infrastructure.

    Additional Resources:

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  • Databases | Analytics

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    Back to Basics: Building Data Domains for…

    Back to Basics

    Break down data silos and empower your teams with self-service access to curated datasets - all while maintaining governance with Amazon DataZone. In this episode, join Brian as he explores how organizing data into purposeful domains simplifies discovery and access.

    You'll learn:
    ✅ Benefits of self-service data environments
    ✅ Structuring data into functional domains (patient, clinical, finance)
    ✅ Value stream domains for business processes (patient care, operations)
    ✅ Roles of data producers (curating, publishing) and consumers (discovering, accessing)
    ✅ Using metadata catalogs and tagging for efficient dataset discovery
    ✅ Implementing access controls and approval workflows
    ✅ Integrating DataZone with existing workflows via APIs
    ✅ Best practices: training, data quality, monitoring

    Whether you're a medical organization, research facility, or any data-driven enterprise, self-service data environments powered by Amazon DataZone can accelerate data access and insights - without compromising governance.

    Eliminate gatekeepers, streamline processes, and unlock your data's full potential with just a few clicks.

    Additional Resources:

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  • Databases | Serverless

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    Back to Basics: Disaster Recovery Patterns for…

    Back to Basics

    Get expert tips on data recovery for Amazon DynamoDB & Aurora, plus patterns to maintain consistency across microservices! Join Cheryl as she covers:
    ✅ Recovering deleted/corrupted data in DynamoDB using Point-in-Time Recovery
    ✅ Restoring Aurora databases to any point within 35 days
    ✅ Using Aurora's Backtrack to "rewind" your DB cluster (MySQL)
    ✅ Implementing idempotency pattern with AWS Lambda Powertools to prevent double charges

    Whether you're an online jeweler with fluctuating traffic or any business using microservices, you'll learn strategies to quickly recover from data issues while ensuring ACID compliance.

    Don't miss these pro tips for keeping your serverless apps resilient!

    Additional Resources:

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  • Architecture Best Practices | DevOps | Infrastructure

    New

    Back to Basics: Design Patterns for Building…

    Back to Basics

    As your AWS cloud footprint expands, implementing a secure and scalable multi-account structure becomes crucial. In this episode, join Prateek as he dives into proven design patterns using AWS Organizations to meet your enterprise's growing needs.

    You'll learn:
    ✅ Why a single AWS account falls short as you scale
    ✅ Benefits of an AWS multi-account architecture
    ✅ Foundational Organization Units (OUs) for security, networking, shared services
    ✅ Separate OUs for sandbox, workloads, exceptions, CI/CD
    ✅ Aligning accounts to product lifecycles (dev, pre-prod, prod)
    ✅ Baking in security and compliance from the start
    ✅ Tips on structuring OUs for business agility

    Whether you're an enterprise starting your cloud journey or experiencing rapid growth, this blueprint will help you design a future-proof multi-account AWS setup.

    Avoid operational bottlenecks, security risks, and resource constraints - unlock seamless scalability with AWS Organizations!

    Additional Resources:

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  • Business Resiliency | Management & Governance |…

    New

    Back to Basics: Achieving End to End…

    Back to Basics

    SSL/TLS encryption is critical for secure data transmission, but managing certificates can be a major operational burden. Join Amit as he explores different options to offload TLS termination to AWS services, simplifying your app deployments.

    You'll learn:
    ✅ Benefits of offloading TLS to AWS load balancers
    ✅ Using Application Load Balancers (ALB) for L7 protocols like HTTP/gRPC
    ✅ ALB features: SSL offload, mTLS, connection tracking
    ✅ Network Load Balancers (NLB) for L4 protocols like TCP/UDP
    ✅ NLB modes: SSL offload, passthrough for end-to-end encryption
    ✅ Benefits like source IP preservation, centralized cert management
    ✅ Using service meshes like AWS Cloud Map for TLS offload
    ✅ Factors to consider: app requirements, security needs, operational overhead

    Whether you're building web apps, microservices or managing legacy workloads, offloading TLS can greatly simplify your deployments and operations.

    Stop worrying about cert distribution, validation logic - let AWS handle the heavy lifting while you focus on core app development!

    Additional Resources:

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  • Application Integration | Developer Tools

    New

    Back to Basics: Modernize Your…

    Back to Basics

    Struggling with a monolithic frontend codebase? Discover how a micro-frontend (MFE) architecture can transform your app development - enabling scalability, flexibility, and faster innovation.

    Join Amey as he explores:
    ✅ What are micro-frontends and their benefits
    ✅ Different MFE composition patterns (build-time, server-side, run-time)
    ✅ Example e-commerce app with independent MFEs for search, payments, etc.
    ✅ Leveraging AWS services: Amplify, AppSync, CloudFront, OpenSearch
    ✅ Choosing front-end tech stacks per MFE requirements (React, Angular, Vue)
    ✅ Decoupling deployment pipelines for autonomous team ownership
    ✅ End-to-end MFE development lifecycle with AWS Amplify

    Stop wrestling with tightly-coupled frontends! MFEs promote modularity, scalable performance, and tech flexibility for your digital experiences.

    Whether you're an e-commerce business, SaaS platform or any customer-facing app, micro-frontends can empower your teams to innovate faster while reducing operational complexity.

    Ready to up level your frontend architecture? Let's break that monolith!

    Additional Resources:

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  • Analytics

    New

    Back to Basics: Building a Serverless Apache…

    Back to Basics

    Struggling to derive real-time insights from your data? Learn how to build a serverless analytics pipeline on AWS to gain actionable insights like determining your most effective ads - without managing any infrastructure!

    Join Zaiba as she covers:
    ✅ Common challenges with real-time data analysis
    ✅ Serverless architecture using AWS services like MSK Serverless, Kinesis Data Analytics, and OpenSearch Serverless
    ✅ Benefits of going serverless - no infrastructure management, auto-scaling, and pay-per-use
    ✅ Key considerations: avoiding emulators, accelerating dev loops, MSK Serverless configs
    ✅ Choosing the right services based on your throughput needs
    ✅ Monitoring with CloudWatch alarms

    Whether you're an e-commerce business, IoT company, or any data-driven org, this pattern eliminates heavy lifting so you can focus on extracting value from your real-time data streams.

    Ready to unlock powerful insights without the ops burden? Let's dive in! 👇

    Additional Resources:

    Check out more resources for architecting in the #AWS cloud:

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  • Machine Learning | Analytics

    New

    Back to Basics: Generative BI Pattern…

    Back to Basics

    Imagine effortlessly extracting insights from your data using just natural language. Join Neelam as she explores how Generative Business Intelligence (GenBI) powered by AWS can revolutionize self-service analytics for your organization.

    You'll learn:
    ✅ What is Generative BI and its benefits
    ✅ Importance of a modern data architecture as a foundation
    ✅ Using Amazon QuickSight for data visualization
    ✅ Leveraging natural language with QuickSight Q for data analysis
    ✅ Generating visualizations from plain language queries
    ✅ Sharing insights via data-driven narratives and stories
    ✅ Reviewing user feedback to improve GenBI performance
    ✅ Best practices like human oversight for trustworthy insights

    Whether you're in retail, finance, healthcare or manufacturing, GenBI empowers business users to derive rapid insights without specialized skills.

    No more wrestling with complex BI tools - ask questions in plain language and get compelling visuals in seconds! Accelerate data-driven decisions with the power of AI.

    Ready to democratize analytics across your enterprise? Let's get started!

    Additional Resources:

    Check out more resources for architecting in the #AWS cloud:

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