reInvent reCap 2022

Editor's Notes

• #20: https://aws.amazon.com/blogs/aws/announcing-amazon-sagemaker-canvas-a-visual-no-code-machine-learning-capability-for-business-analysts/https://amzn-aws.slack.com/archives/C02FXMDAZAS/p1638296314148300 --- 1/Target customer: Amazon SageMaker Canvas makes it easy for business analysts to generate highly accurate ML predictions on their own without any ML experience. 2/Key customer problem(s) we're looking to solve: Expands ML access to business analysts in a no-code environment.3/Description of service (2 sentences MAX)2/With SageMaker Canvas, business analysts can easily access and import data from the cloud and on-premises data sources and quickly combine and cleanse data. From there, Canvas generates an ML model automatically. 4/How launch solves the customer problem(s). Include key capabilities and benefits unique to your service. Provides a no-code environment for business analysts to access data, generate ML models, and share ML models with data science teams.5/Use cases/examples (if applicable) In use by: BMW group – “With SageMaker Canvas, our business users can easily explore and build ML models to make accurate predictions without writing any code. SageMaker also allows our central data science team to collaborate and evaluate the models created by business users before publishing them to production.” Siemens Energy – “We found Amazon SageMaker Canvas a great addition to the Siemens Energy machine learning toolkit, because it allows business users to perform experiments while also sharing and collaborating with data science teams. The collaboration is important because it helps us productionalize more ML models and ensure all models adhere to our quality standards and policies.” 6/Other critical information to understand the service/feature (optional) GA, but not in Sydney yet. 
• #21: https://aws.amazon.com/blogs/aws/now-in-preview-amazon-sagemaker-studio-lab-a-free-service-to-learn-and-experiment-with-ml/https://amzn-aws.slack.com/archives/C02FXMDAZAS/p1638383770027700 --- If you are new to machine learning, and want to build machine learning skills, 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. All you need to get started is a valid email id; you don’t need to configure infrastructure or manage identity and access or even sign up for an AWS account. SageMaker Studio Lab accelerates model building through GitHub integration, and it comes preconfigured with the most popular ML tools, frameworks, and libraries to get you started immediately. SageMaker Studio Lab automatically saves your work so you don’t need to restart in between sessions; it’s as easy as closing your laptop and coming back later. FEATURES/BENEFITS No AWS account needed: To get started with SageMaker Studio Lab, use your email address to register for an account on studiolab.sagemaker.aws. Your SageMaker Studio Lab account is separate from an AWS account and doesn’t require a credit card. Choose compute power: SageMaker Studio Lab offers either CPU or GPU sessions for your project. You can choose to run notebooks with a 12-hour CPU session for complex algorithms, or a 4-hour GPU session for deep learning (DL) Persistent storage: SageMaker Studio Lab provides persistent sessions with 15 GB of free long-term storage, so you can save your work and pick up where you left off. When a session ends, your work is automatically saved in dedicated storage. Prepackaged ML frameworks: Choose the best Python package manager for your project, such as Pip, Conda, or Mamba. By default, SageMaker Studio Lab supports the Terminal and Git command lines and GitHub integration for collaboration. Setup is fast and easy, with no configuration required to run a Jupyter Notebook.
• #22: Once of the challenges with running a contact centre is that there is so much data generated – not just call flow information but also voice recordings; agent interactions and so on. In 2020 we announce real-time integration of Contact Lens (gotta love that name!) with Connect, giving you the ability to see the status of calls and interactions in progress in your contact centre. Now, using machine learning we’re giving you the ability to see more in less time by summarizing the important aspects of each customer call. This helps agents because they don’t have to keep notes in your CRM; instead the system can do it for them. That gets them back to doing what humans do best of all – dealing with other people. The ML does the tedious tasks for you. We also released a new unified agent application that brings together customer profiles, voice id and wisdom (which links the call to your knowledge base). As always, the agent application is a customized HTML app so you can still modify it, brand it and embed it where you need to. Ref: https://aws.amazon.com/blogs/aws/machine-learning-powered-amazon-connect-now-with-call-summarization/https://aws.amazon.com/about-aws/whats-new/2021/11/amazon-connect-unified-agent-application/ https://aws.amazon.com/about-aws/whats-new/2021/11/amazon-connect-unified-agent-application/
• #23: https://aws.amazon.com/blogs/machine-learning/expedite-conversation-design-with-the-automated-chatbot-designer-in-amazon-lex/https://amzn-aws.slack.com/archives/C02FXMDAZAS/p1638383702027000 --- 1/Target customer:  Amazon Lex users looking to develop new chatbots quickly and effectively.2/Key customer problem(s) we're looking to solve: Develop an automated chatbot using historical conversation transcriptions.3/Description of service (2 sentences MAX) The Amazon Lex Automated Chatbot Designer feature helps you automatically create chatbots within hours using historical conversation transcripts. 4/How launch solves the customer problem(s). Include key capabilities and benefits unique to your service.The feature uses NLU and DL techniques to analyse conversation transcripts and surface a chatbot design that includes user intents (such as “file a claim” for an insurance bot), sample phrases (such as “I’d like to file a claim”) associated with those intents, and a list of all the information (such as claim type or policy ID) required to fulfill them. You can iterate on this design and change chatbot prompts and responses instead of starting from scratch. 5/Use cases/examples (if applicable)6/Other critical information to understand the service/feature (optional)
• #24: Organizations, development teams, and individual developers who have chosen to use containers to host their applications may prefer, or perhaps are required, to source all images from Amazon Elastic Container Registry to take advantage of its high availability and security. To satisfy those requirements, customers have needed to take on the burden of manually pulling images from public registries into their private Amazon Elastic Container Registry repositories, and then keeping them in sync. This adds operational complexity and maintenance costs, thereby impacting developer productivity. Additionally, some registries may have limitations or restrictions on how frequently images can be downloaded. When reached, those limitations then begin impacting developers and the release velocity of their business, due to build errors when image pulls are throttled, or even rejected. Today, we have announced pull through cache repository support in Amazon Elastic Container Registry, for publicly accessible registries that do not require authentication. Pull through cache repositories offer developers the improved performance, security, and availability of Amazon Elastic Container Registry for container images that they source from public registries Pull through cache repositories provide the benefits of the built-in security capabilities in Amazon Elastic Container Registry, such as AWS PrivateLink enabling you to keep all of the network traffic private, image scanning to detect vulnerabilities, encryption with AWS Key Management Service (KMS) keys, cross-region replication, and lifecycle policies. When enabled, cross-region replication is designed to automatically distribute updated images to additional Regions. All you need to do is update the pull URL so that the image is downloaded from the relevant Region.
• #25: Karpenter is an open-source, flexible, high-performance Kubernetes cluster autoscaler built with AWS. It helps improve your application availability and cluster efficiency by rapidly launching right-sized compute resources in response to changing application load. Karpenter also provides just-in-time compute resources to meet your application’s needs and will soon automatically optimize a cluster’s compute resource footprint to reduce costs and improve performance. Before Karpenter, Kubernetes users needed to dynamically adjust the compute capacity of their clusters to support applications using Amazon EC2 Auto Scaling groups and the Kubernetes Cluster Autoscaler. Nearly half of Kubernetes customers on AWS report that configuring cluster auto scaling using the Kubernetes Cluster Autoscaler is challenging and restrictive. When Karpenter is installed in your cluster, Karpenter observes the aggregate resource requests of unscheduled pods and makes decisions to launch new nodes and terminate them to reduce scheduling latencies and infrastructure costs. Karpenter does this by observing events within the Kubernetes cluster and then sending commands to the underlying cloud provider’s compute service, such as Amazon EC2. eet your application’s needs and will soon automatically optimize a cluster’s compute resource footprint to reduce costs and improve performance. Its OS check it out https://github.com/aws/karpenter/blob/main/CONTRIBUTING.md
• #26: Amazon CodeGuru is a developer tool powered by machine learning that provides intelligent recommendations to detect security vulnerabilities, improve code quality and identify an application’s most expensive lines of code. Today we are announcing a new secrets detector feature that searches your codebase for hardcoded secrets. It can pinpoint locations in your code of usernames and passwords, database connection strings, tokens, and API keys from AWS and other service providers. When a secret is found in your code, CodeGuru Reviewer provides an actionable recommendation that links to AWS Secrets Manager where developers can secure the secret with a point-and-click experience. When you add a new repository to Amazon CodeGuru Reviewer, secrets detector will automatically search Python and Java source, in addition to configuration and documentation files, for secrets. As your codebase evolves, CodeGuru Reviewer continues to help you keep your secrets protected by integrating into your pull request workflow or CI/CD pipeline.
• #27: Introducing, “Amazon DevOps Guru for RDS” is a new machine learning powered capability for Amazon RDS that automatically detects and diagnoses relational database-related performance and operational issues within an application. Specific issues that DevOps Guru for RDS solves is for the over-utilization of resources or misbehavior of certain SQL queries. It delivers insights and recommendations for these issues, enabling developers to resolve them in minutes rather than days. It leverages machine learning models informed by years of experience operating thousands of databases at scale for Amazon.com. DevOps Guru for RDS helps customers quickly resolve database-related operational issues by immediately notifying developers (through Amazon Simple Notification Service (SNS) notifications and EventBridge) when issues occur and providing diagnostic information, details on the extent of the problem, and intelligent remediation recommendations. DevOps Guru for RDS is available for Amazon Aurora with PostgreSQL compatibility and MySQL compatibility today with support for additional Amazon RDS engines coming in 2022.
• #28: Supports two primary use cases – Dark launches, aka feature flags and A/B testing AWS AppConfig and AWS Systems Manager also support feature flags, but CloudWatch Evidently includes templating and dashboards of your features Supports front end, back end, web or mobile and even ML applications 9 programming languages supported
• #29: Amazon CloudWatch RUM will help you to collect the metrics that give you the insights that will help you to identity, understand, and improve this experience. You simply register your application, add a snippet of JavaScript to the header of each page, and deploy. The snippet runs when your users step through each page of your application, and sends the data to RUM for consolidation and analysis. You can use this tool on its own, and in conjunction with both Amazon CloudWatch ServiceLens and AWS X-Ray.
• #30: Gain better visibility on your infrastructure and large scale application performance with flexible querying and on-the-fly metric aggregations Create powerful visualisations that update as metrics update Use SQL or the visual query builder via namespaces and dimensions Scales queries across thousands of EC2 instances including hybrid Regions: All
• #31: Creating technology solutions is a lot like constructing a physical building. If the foundation is not solid, it may cause structural problems that undermine the integrity and function of the building. If you neglect the six pillars of security, reliability, performance efficiency, cost optimization, operational excellence, and sustainability when architecting technology solutions, it can become a challenge to build a system that delivers functional requirements and meets your expectations. When you incorporate these pillars, it will help you produce stable and efficient systems, allowing you to focus on functional requirements. Operational Excellence: The ability to run and monitor systems to deliver business value and continually improve supporting processes and procedures. Security: The ability to protect information, systems, and assets while delivering business value through risk assessments and mitigation strategies. Reliability: The ability of a system to recover from infrastructure or service failures, dynamically acquire computing resources to meet demand, and mitigate disruptions such as misconfigurations or transient network issues. Performance Efficiency: The ability to use computing resources efficiently to meet system requirements, and to maintain that efficiency as demand changes and technologies evolve. Cost Optimization: The ability to avoid or eliminate unneeded cost or suboptimal resources. Sustainability: Guidance on how AWS can help you reduce your footprint, and best practices you can use to improve the sustainability of your workloads. We are also launching a Customer Carbon Footprint Tool that will help customers identify their emissions while running in AWS.
• #33: aws.amazon.com/amplify/studio/ New: Amplify Studio Amplify Studio is an abstraction layer on top of the Amplify CLI that lets you create full-stack apps, front to back, on AWS using a visual development environment. With Amplify Studio, you can quickly build an app backend, create custom UI components, and connect a UI to the app backend with minimal coding. Select from dozens of popular React components, such as buttons, forms, marketing templates, and customize them to fit your style guide. Or, import UX designs from the popular design prototyping tool, Figma, as clean React code for seamless collaboration. Studio exports all UI and infrastructure artifacts as code, so you can maintain full control over your app design and behavior.
• #34: AWS Data Exchange for APIs is a new capability that lets you find, subscribe to, and use third-party APIs with a consistent access using AWS SDKs, as well as consistent AWS-native authentication and governance. This simplifies the lives of developers and IT administrators who have to integrate and secure the access to multiple third-party APIs. AWS Data Exchange for APIs is generally available in all AWS Regions where AWS Data Exchange is available. We’re looking forward to helping you simplify and centralize the management and governance of third-party APIs while we take care of the undifferentiated heavy lifting for you.
• #35: AWS CDK V2 – defines a consolidated construct Library so its easier to stay up to date AWS CDK v2 only includes stable APIs, which comply with Semantic Versioning (semver), so you can confidently update to new minor versions. The CDK follows the “release early, release often” philosophy to encourage community participation, and we will continue deliver new features  via experimental APIs for your feedback. However, going forward, experimental modules will be distributed separately from aws-cdk-lib, versioned clearly to indicate their pre-release status, and will only be merged into aws-cdk-lib when mature and stable.  In addition to simplified packing, the CDK includes developer productivity improvements such as a CDK API reference refresh with code snippets throughout, CDK Watch for faster inner-loop development iterations on the application code (AWS Lambda handler code, Amazon ECS tasks, and AWS Step Function state machines) in your CDK project. You can also preserve successfully provisioned resources by disabling automatic stack rollbacks, further reducing deployment and iteration time. To find issues earlier in your infrastructure code development cycle, you can use the new assertions library to run automated unit tests in any CDK-supported language.  Has a migration path from V1 created stack Migrating from V1 instructions - docs.aws.amazon.com/cdk/v2/guide/migrating-v2.html
• #36: https://constructs.dev To more easily share with the community your CDK Constructs You can find construct libraries published by the community, AWS and cloud service providers that solve for your use case: monitoring, containers, serverless, databases, utilities, deployment, websites, security, compliance, network, artificial intelligence (AI), cloud service integrations and more. Each library includes documentation, API reference and code samples in TypeScript, Python, Java and .NET. You can also find installation instructions for each programming language, dependency list, number of downloads, licensing information, and helpful links.
• #37: AWS Microservice Extractor for .NET simplifies the process of re-architecting applications into smaller code projects. It helps transform your .NET applications with an assistive tool that analyzes source code and runtime metrics to create a visual representation of your application and its dependencies. This tool delivers a holistic visualization of an applications source code, helps code refactoring and assists in extraction of the codebase into separate code projects that teams can develop, build, and operate independently to improve agility, uptime, and scalability. Benefits include: Faster identification of applications components to re-factor into service architecture: Microservice Extractor combines data from code analysis and runtime profiling to produce a visualization showing each component's dependencies and metrics. This simplifies the need to manually correlate outputs of various tools for code and runtime analysis. Facilitates refactoring so that you can apply Domain-Driven Design principles: Microservice Extractor helps you adopt industry best practices such as Domain Driven Design by enabling you to label the visualized graph to associate code with business processes. It highlights dependencies that need to be refactored to be able to extract parts of the application into separate code projects. Assisted refactoring of monolith codebases into smaller code projects: After refactoring the monolithic application to prepare it for extraction as independent code projects, this tool can be used to partition source code into units that teams may develop, build, deploy and operate as independent services with their choice of tools.
• #38: AWS Migration Hub Refactor Spaces addresses a common pair of practical problems when transforming applications: setting up an infrastructure for application refactoring and operating evolving applications at scale. Refactor Spaces simplifies application refactoring by:   Reducing the time to set up a refactor environment (cloud anti-corruption layer) Reducing the complexity to iteratively extract capabilities as new microservices and reroute traffic from old to new (Strangler Fig pattern) Simplifying the management of legacy apps and microservices as a single application with flexible routing control, isolation, and centralized management Helping development teams achieve and accelerate tech and deployment independence by simplifying development, management, and operations while apps are changing.
• #39: One of the challenges in any large network is IP address management; keeping track of what is allocated to where and to who. And you can build crazy big networks in AWS – especially as the number of accounts and VPCs grows. Consequently, one of the big asks of our customers has been “how do we do IP Address Management (IPAM) in AWS”? This is the answer – it’s an IP address management tool built right into the console; so it stops you having to mess around with spreadsheets. When someone creates a VPC they can allocate a pool of IP addresses from a source that you specify. In each Region in which you have resources needing IP addresses, you create a regional pool. Pools are collections of CIDRs and help you to organize your IP space. Unused address space from your top-level pools can be used to fill your regional pools. Further, if you have applications or environments with different security needs, you can create additional pools. For example, you could create different pools for ‘dev’ and ‘prod’ environments if they are subject to different connectivity requirements. If you have existing VPCs, IPAM will automatically catalogue your existing IP ranges, ready for you to use the tool. Ref: https://aws.amazon.com/blogs/aws/network-address-management-and-auditing-at-scale-with-amazon-vpc-ip-address-manager/
• #40: You’ve been able to use AWS as your global WAN for some time now. But the challenge has been that it’s a bunch of services that hook together but you needed to manage how they connected. CloudWAN gives you tools to automate your network management and it’s here to help make your networking life in AWS easier, especially at scale. So what does Cloud WAN actually give you? Rather than you manually configuring network separation, routes and connection points you can instead specify which VPCs, Direct Connects, VPNs belong to parts of your network (say, Dev or Prod) and then define policies on how they connect. To quote Hitchhikers Guide to the Galaxy: “No more tedious mucking about in hyperspace”. You get a single point of control; an opinionated service that does things for you based on a few clicks or lines of JSON – something our customers ask for all the time: “what would AWS do”; centralized monitoring and event managements; and built-in automation for new attachments based on tags. Of course, you also want partner integration and we have that too. Partners: Aviatrix Cisco Systems Fortinet Prosimo VMware Aruba Alkira Intercloud DXC Technologies Why is this in Preview? Because there are a few more features coming... Ref: https://aws.amazon.com/blogs/networking-and-content-delivery/introducing-aws-cloud-wan-preview/
• #41: Related but separate to this: You can now use the Direct Connect service as part of your WAN. You’ve been able to do part of this already – you could take traffic in (say) from a branch office in the US to a Direct Connect location; transport that across the world to another Direct Connection location (for example, Tokyo) and from there to your local branch office. But what you couldn’t do is have multiple branch offices in the US connected to the same Direct Connect location and have them communicate. This is what SiteLink does – you can now use Direct Connect as a transit network – most importantly, within the same POP. For those customers here in Perth, that means that if your three offices are connected to the Perth POP they can now communicate with each other; without having to add any other networking and without having to transit through Sydney. You’ll need to enable this in the Direct Connect console but that’s about it. When you combine this with Cloud WAN you can see how it makes it a lot easier to globally (or nationally within Australia) connect your locations. Ref: https://aws.amazon.com/blogs/networking-and-content-delivery/introducing-aws-direct-connect-sitelink/
• #42: 5G networks are cool – the ability to support thousands of devices in close proximity to each other; coupled with high bandwidth and low latency – we’ve come a long way from 2G and even 3G networks. But sometimes you need 5G where it isn’t; and you also need to get it up and running without help from your favourite mobile network carrier. That’s where Private 5G comes in. AWS provides the hardware and software you need and away you go! Today, only available in the US because it uses the citizen’s band radio spectrum; and it is in preview; but still: A sign of things to come. Ref: https://aws.amazon.com/about-aws/whats-new/2021/11/preview-aws-private-5g/ https://aws.amazon.com/private5g/
• #43: EBS Snapshots are a point in time copy of your data, and can be used to enable disaster recovery, migrate data across regions and accounts, and improve backup compliance. This new feature, EBS Snapshot Archive allows you to archive snapshots that are designed to be kept for longer than 90 days, usually for regulatory or compliance reasons. The new archive tier stores your snapshots up to 75% cheaper than the existing standard tier, however restoring the archived snapshot takes between 24 and 72 hrs depending on the snapshot size, so they’re really a good fit for snapshots that don’t’ need to be restored immediately.
• #44: Its been a great year for EBS customers as we can continue to deliver the most asked for features including a new data protection capability called , “Recycle Bin”. Recycle Bin lowers your risk of data loss due to accidental of deletion snapshots. Here’s how Recycle Bin works. Set up your retention rules which include a Recycle Bin retention period from 1 day to 1 year. The rules can be account-based or tag-based per region. Your deleted snap shots will be retained in the Recycle Bin for the period of time that you specify. Just be sure to recover your EBS Snapshots from the Recycle Bin before you preset retention period expires. Recycle Bin is also super flexible. For security you can restrict access to Recycle Bin Rules and resources using AWS Identity and Access Management roles. You can enable and configure Recycle Bin using the AWS Management Console, the AWS CLI, or the AWS SDKs. Recycle Bin is also available in all AWS commercial regions. Recycle Bin is free, so turn it on now and protect yourself from data loss resulting from accidental snapshot deletions.
• #45: We have combined the capabilities of the AWS Tape Gateway with our Edge computing device, AWS Snowball. The combined capability uses the Tape Gateway’s Virtual Tape Library (VTL) to deliver you a simple, integrated experience for tape data migration.  Then, AWS imports your data stored on Snowball Edge to Amazon S3 Glacier Flexible Retrieval or Amazon S3 Glacier Deep Archive based on the storage destination you selected when creating virtual tapes, for continued access via another AWS Tape Gateway VTL interface. ***dog for scale
• #47: The Amazon S3 Intelligent-Tiering storage class is designed to optimize storage costs by automatically moving data to the most cost-effective access tier when access patterns change. S3 Intelligent-Tiering automatically stores objects in three access tiers: a Frequent Access tier, an Infrequent Access tier with 40% lower-cost than the Frequent Access tier, and a new Archive Instant Access tier, S3 Glacier Instant Retrieval with 68% lower-cost than the Infrequent Access tier (Standard-IA), without performance impact, retrieval fees, or operational overhead. Usual 99.9% availability, 11 9’s durability. S3 Intelligent-Tiering monitors access patterns and moves objects that have not been accessed for 30 consecutive days to the Infrequent Access tier and now, after 90 days (30 + 60) of no access, to the new Archive Instant Access tier.
• #48: S3 Standard-Infrequent Access and S3 One Zone-Infrequent Access storage prices reduced up to 31% in 9 AWS Regions inc Sydney (-27%). S3 Glacier renamed S3 Glacier Flexible Retrieval (same async response service/times) (Naming alignment with new S3 Glacier Instant Retrieval – the new class with milliseconds response) No longer charges for Bulk Retrieval, 10% storage price reduction (all regions)
• #49: Now with AWS Backup support for Amazon S3 in public preview and VMware workloads in general availability, AWS is extending AWS Backup’s capabilities to more cloud and on-premises workloads. Previously, administrators would write custom scripts to combine S3 data across multiple AWS Regions and accounts with AWS Backup to get a consolidated view of their backups, as well as combine S3 reports with AWS Backup built-in reports to demonstrate compliance with application-level backup policies. They would also parse through S3 data to find the point-in-time they want to restore an application. Now, with AWS Backup support for S3 in public preview, customers can replace the complicated custom scripts they used to centrally manage their backups of their entire applications. Customers can also now replace parsing through S3 data with AWS Backup’s point-in-time restore functionality, allowing them to specify the time to restore—down to the second. With AWS Backup support for VMware workloads in general availability, customers can now protect their VMware workloads whether they run on premises or in the VMware Cloud on AWS (VMC). Up until now, customers running VMware workloads on premises and in the AWS Cloud maintained separate solutions to protect their data alongside AWS services already supported by AWS Backup. This required them to manage separate tools and policies to protect their data in VMware environments, as well as generate distinct reports to demonstrate compliance with backup policies. With AWS Backup for VMware, customers can extend AWS Backup’s centralized data protection, governance, and compliance features they already use to protect their AWS applications to their VMware workloads, whether running in AWS or in their own datacenters.