AWS 2020 re:Invent Recap: AWS Trainium

What Happened: 

The newest AWS custom-designed chip, AWS Trainium, was announced during Andy Jassy’s 2020 re:Invent keynote, with the projected best price performance for training Machine Learning (ML) models in the cloud. Meant for deep learning training workloads for applications, it includes capabilities of image classification, semantic search, translation, voice recognition, NLP (Natural Language Processing), and recommendation engines.

Why It’s Important: 

  • Lower Costs: AWS Trainium instances are specifically targeted for reducing the training costs, in addition to the existing savings through using AWS Inferentia, which focuses on the inference factors of ML applications.
  • Easy Integration: Since it shares the same AWS Neuron SDK as AWS Inferentia, it’s easier for developers with Inferentia experience to start working with AWS Trainium. SDK integrates with popular ML frameworks like Pytorch, MXNet, and Tensorflow, making it easier for developers to move GPU instances to AWS with minimal code changes.
  • Greater Capabilities: This chip is optimized for training deep learning models for applications using images, text, and audio, which means more opportunities to build solutions that solve operational business challenges across industries.

Why We’re Excited

AWS Trainium will be the most sophisticated and advanced training technology leveraged to deliver elegant solutions to address customer challenges and project requirements. Since it integrates with and complements AWS Inferentia, ML training capabilities will significantly increase with optimized speed, skill, and efficiency. As the most cost-effective option with the broadest set of capabilities and robust AWS toolset to support it, end-to-end workflows can be created to scale AI/ML training workloads faster and bring products or services to market at an accelerated rate.


AWS Trainium is available as an EC2 instance and will be available in Amazon Sagemaker in the 2nd half of 2021.

If you’re looking to explore these services further and need some guidance, let us know and we’ll connect you to an Idexcel expert!

AWS re:Invent Recap: Amazon SageMaker Pipelines

What happened?

The new service, Amazon SageMaker Pipelines, has been launched to provide continuous integration and delivery pipelines that automate steps of ML (Machine Learning) workflows. It’s the first CI/CD service for ML to build, store, and track automated workflows and also create an audit trail for training data and modeling configurations.

Why is it important?

  • Ease of Use: It has built in ML workflow templates that can be used to build, test, and deploy ML models quickly.
  • Compliance: Amazon SageMaker pipeline logs can be saved as audit trails to recreate models for similar future business cases that help support compliance requirements.
  • Better Capabilities: This service brings CI/CD practices to ML, which keeps the development & production environments separate, version control measures, on-demand testing, and end-to-end automation.
  • Automation: As the first Purpose-built CI/CD service for ML that incorporates automation of data loading, transformation, training, tuning, and deployment workflow steps, this increases productivity significantly.
  • Scalability: With the ability to create, automate, and manage end-to-end ML workflows at scale, there’s peace of mind knowing various are stored and be referred back to for audit purposes, compliance requirements, and future solution builds.

Why We’re Excited

Amazon SageMaker Pipelines offer a more efficient and productive solution to scale by reusing the workflow steps created and stored in a central repository. With built-in templates to deploy, train, and test models, our ML teams can quickly leverage CI/CD in our ML environments and easily incorporate models we’ve already created. With the SageMaker Pipelines model registry, we can track these model versions in one central location that gives us visibility and up to date record logs of the best possible solution options to meet client deployment needs.

If you’re looking to explore these services further and need some guidance, let us know and we’ll connect you to an Idexcel expert!

re:Invent 2020 Recap: Partner Keynote Announcements

In case you missed it, here are the major announcements and newest competencies from the re:Invent 2020 Partner Keynote on Wednesday, December 3rd, 2020:

  1. AWS Saas Boost supports accelerated modernization efforts by removing the heavy lifting of taking existing applications into the cloud. SaaS Boost is available open-source as a ready-to-use reference environment that enables Independent Software Vendors (ISVs) to accelerate the move to Software-as-a-Service (SaaS). For businesses of all sizes, AWS SaaS Boost helps ISVs migrate applications to AWS with minimal changes at a more rapid rate.
  2. AWS ISV Partner Path: Beginning in January 2021, any AWS Partner with a software solution that runs on or is integrated with Amazon Web Services (AWS) can join the new AWS ISV Partner Path that helps customers identify AWS-reviewed solutions. It aims to accelerate the engagementISVs have with AWS and shifts focus from partner-level badging to solution-level badging to meet customer needs.
  3. Managed Entitlements are now available in AWS Marketplace. This simple and automated license tracking helps make governance, compliance, and distribution of software license entitlement management easier. This lets buyers monitor their software license entitlements, providing visibility that helps ensure accurate license usage tracking. ISVs can use AWS License Manager to create and manage user licenses for products used on AWS and on-premises. This is effective immediately for over 7,000 products currently listed in AWS Marketplace.
  4. Private Marketplace APIs: AWS Marketplace now enables buyers to manage their Private Marketplace using a set of publicly accessible APIs. The Marketplace helps customers navigate these products and ISVs in their journey to transform, modernize, and govern by curating a catalog of approved third-party software solutions available.
  5. The AWS Service Catalog App Registry serves as the central repository to define and associate resources to better manage applications. Maintain a single source of truth with the integration of AppRegistry into application development processes to create application definitions and resource collections. Builders can define AWS CloudFormation stacks, metadata that describes partner-built AWS applications, descriptions, and attribute group associations. This helps ensure critical information like organizational ownership, data sensitivity, and cost center are up to date for IT leaders and business stakeholders. It also makes the procurement process simpler and more seamless for customers and ISVs.
  6. Professional Services in AWS Marketplace makes is easier to find and buy services to configure, deploy, and manage third-party software. Itallows partners to reach customers in new ways since they can now publish services in the same place as software, simplifying the contract process for buyers and sellers. For sellers, this new feature gives sellers an opportunity to reach new prospective customers by listing professional service offerings as individual products or bundle with existing software products in AWS Marketplace using pricing, payment schedule, and service terms independent from the software. For buyers, gaining access to professional services gives more choice to multiple trusted sellers and a much easier way to manage payment of both software and services provided.
  7. Newest Competencies Announced:
    • Mainframe Migration Competency: This recognizes AWS Partners with proven technology, customer success, mature practices, and a track record in migrating both mainframe applications, workload migrations, and data to AWS.
    • Public Safety & Disaster Recovery (expanded to include Technology Partners): This competency signifies specialized and dedicated AWS Technology Partners that help customers improve preparation, response, and recovery from emergencies and disasters.
    • Energy: This highly specialized designation will showcase AWS Partners who have completed a thorough technical validation with AWS and demonstrated continued success in supporting unique energy needs.
    • Travel & Hospitality: Partners with this competency help customers accelerate their digital transformation efforts across marketing and sales, customer experience, core operations, finance, human resources, and IT departments for travel and hospitality organizations build a resilient business and accelerate innovation.

AWS re:Invent 2020 Keynote Service Announcements

Andy Jassy Keynote Service Announcements

There were many major product launch and update announcements during Andy Jassy’s re:Invent Keynote presentation. We put together a list of these awesome technologies by service area to give you a quick overview on what they are and why they matter:


Habana Gaudi based Amazon EC2 Instances will be available the first half of 2021 Powered by New Habana Gaudi pre-processors from Intel, users can expect a 40% better price/performance over the current GPU based EC2 instances. Built specifically for ML training, these instances work seamlessly with TensorFlow and Pytorch.

AWS Trainium is an ML training chip custom designed by AWS to deliver most cost-effective training in cloud. It supports PyTorch, MXNet, and TensorFlow using the same Neuron SDK Inferentia uses. With both Trainium and Inferentia, customers will have an end-to-end flow of ML compute from scaling training workloads to deploying accelerated inference. AWS Trainium be available as an EC2 instance and in Amazon Sagemaker in the 2nd half of 2021.


Amazon ECS Anywhere lets you run ECS in your own datacenter. Using the same AWS style APIs, cluster management, and workload scheduling and monitoring tools, ECS Anywhere works on any infrastructure (cloud, on-prem, etc.) to enable accelerated transitions.

Amazon EKS Anywhere will also be available and lets you run EKS in your own data environment. Leverage your EKS experience to setup, upgrade, and operate on-prem kubernetes clusters. Amazon EKS distro is open sourced.


Amazon Elastic Block Storage Offers 2 New Levels:

  • GP3 can reduce expenses at 20% better cost per gigabyte. This lets customers independently increase IOPS and throughput without provisioning additional block storage capacity. Gp3 can provide predictable 3,000 IOPS baseline performance and 125 MiB/s regardless of volume size. Customers looking for higher performance can scale up to 16,000 IOPS and 1,000 MiB/s for an additional fee. This is great for applications that require high performance at lower costs such as MySQL, Cassandra, virtual desktops, and Hadoop analytics.
  • io2 Block Express, the first san built for the cloud, takes advantage of advanced communication protocols driven by the AWS Nitro System to allow for up to 256K IOPS & 4000 MBps of throughput and a maximum volume size of 64 TiB, all with sub-millisecond, low-variance I/O latency.

Aurora Serverless 2, scale to hundreds of thousands of transactions in a fraction of a second and enable up to 90% cost savings compared to provisioning for peak capacity. Multi AZ support, Global Database, Read-Replicas, Backtrack and Parallel query features available. SQL is available now and PostgresSQL will be available early next year.

AWS Proton will help in building microservices by building a stack and provisioning AWS services using parameters to push code, deploy, and set up monitoring and alarms. For example, if the central engineering team makes a change in the stack, down-service microservices teams can be notified. This helps optimize the deployment of serverless applications. It’s free of charge, as you only pay for the underlying services and resources.


Babelfish for Aurora PostgreSQL presents a new translation capability to complement Schema Conversion tool and AWS Database Migration Service. With new translation capability to easily run SQL server applications on Aurora PostgresSQL with little or no code changes. Schema and data can be migrated using SCT and DMS. Then, application configuration can be updated to point to Aurora instead of SQL server. This will be available open source.

AWS Glue Elastic Views Set up a materialized view to copy that data to a target store and manages all dependencies from those steps. If something changes, elastic takes that and applies it. If data structure changes, this alerts the person to make necessary adjustments. AWS Glue Elastic Views is serverless and scales capacity up or down automatically based on demand, so there’s no infrastructure to manage.

Amazon QuickSight Q As the first Business Intelligence (BI) service with Pay-per-Session pricing. Ask any question and get answers in seconds. Trained over many data points and business areas, Amazon Quicksight Q uses NLP to understand domain specific business language to auto generate data models that understand meanings and relationships of data.


SageMaker DataWrangler Aggregate and prepare ML features to speed up data preparation. Point it at a data store, make use of over 300 built-in transformations, which are suggested automatically. Import and inspect data to identify the various types, recommend transformations, and apply it to the entire data set, all infra-managed under the covers. This data preparation is made available for inference in real time.

SageMaker Feature Store is used with ML as a purpose-built feature store. This tool makes it much simpler to name, organize, and find and share SageMaker data with teams. It also enables ease of accessibility for both training and inference. Because it is located in Sagemaker, development teams will experience really low latency for inference building machine learning models.

Amazon SageMaker Pipelines is the first Purpose-built CI/CD service for ML that automates different steps of the ML workflow such as data loading, data transformation, training and tuning, and deployment. Create, automate, and manage end-to-end ML workflows at scale with the peace of mind knowing various versions are stored in a central repository.

Amazon DevOps Guru automatically detects operational issues early and provides recommended actions to take that address the problem.

Amazon Monitron is an end-to-end system that leverages machine learning (ML) to detect abnormal behavior in industrial machinery that alerts teams of the need for predictive maintenance to help reduce unplanned downtime.


Amazon Connect Wisdom uses ML to deliver real time product and customer info can integrate Salesforce and ServiceNow – as a call is happening, wisdom takes the call transcription to put the right info on the screen to the info needed around what to do when a given situation happens. This is a game-changer for customer support processes.

Amazon Connect Customer Profiles This presents a unified profile of a customer to the representative during a call. Databases will launch profiles (from Zendesk, Marketo, ServiceNow, etc.) and connects contact ID with a customer ID assigned consistently across all data stores. This helps normalize information from various platforms and displays it in a concerted and organized way. Agents have access to all information that might help change how they can have better, more holistic customer interactions.

Real-Time Contact Lens for upper level management is a sophisticated machine learning tool used to detect customer experience issues during live calls. Leverage ML expertise undercover to have better impact on calls and customer experience in real time. Criteria-based alerts are sent to ensure customers aren’t asked the same questions again, minimizing frustration to enable real-time resolution.


AWS Outposts offers a hybrid solution for access to the familiar and reliable AWS infrastructure, AWS services, APIs, and tools to any datacenter, co-location space, or on-premises facility to build, manage, and scale your on-premises applications for a hybrid solution. AWS Outposts are meant for workloads requiring low latency access to on-premises systems, local data processing, data residency, and migration of system-interdependent applications.

AWS Wavelength Zones are an AWS Infrastructure offering that provides optimized service for mobile edge computing applications. They enable application traffic from 5G devices to reach application servers without leaving the telecommunications network, so developers can now build the next generation of ultra-low latency applications.

If you’re looking to explore these services further and need some guidance, let us know and we’ll connect you to an Idexcel expert!

AWS re:Invent Recap: MacOS Instances for Amazon EC2

Andy Jessy Keynote Service Announcements

Developers will now have a virtual environment to leverage for designing apps for the Mac, iPhone, and other Apple devices, powered by Mac Minis.

What Happened: Amazon Expands App Development & Testing Capabilities with Native Mac Instances for AWS

On Monday’s reInvent Kickoff, Amazon announced the availability of macOS instances on AWS via the Amazon Elastic Compute Cloud (EC2), a welcomed alternative to Microsoft Windows and open-source Linux. Powered by Mac mini hardware and the AWS Nitro System, these Amazon EC2 Mac instances can be used to build, test, package, and sign Xcode applications for the Apple platform including macOS, iOS, iPadOS, tvOS, watchOS, and Safari.

Why It’s Important

Since no other major cloud provider has computing instances running MacOS, Apple Developers have a whole new world of opportunities to develop & test creative applications faster and AWS Partners will be able to provide more powerful development capabilities for clients. It’s a competitive win-win for everyone – AWS, AWS consulting partners, the development community as a whole, and the users who will eventually use the apps.

With this, the Mac minis operate as fully integrated and managed instances like other Amazon EC2 instances, enabling developers to natively run macOS in Amazon Web Services. With immediate access to the virtual macOS environments to build and test applications, development teams and organizations can innovate more quickly and bring products faster to market.

Apple developers benefit from the flexibility, scalability, security, reliability and cost benefits of AWS.


Mac instances are available On-Demand at a rate of $1.083 per hour or with Savings Plans. Currently offering macOS Mojave (10.14) and macOS Catalina (10.15) operating systems. Supported regions include the U.S. East (N. Virginia), U.S. East (Ohio), U.S. West (Oregon), Europe (Ireland), and Asia Pacific (Singapore) with more to come. Learn more in the featured AWS Video or contact an Idexcel expert to get started.