Top Announcements of AWS re:Invent 2021

Top Announcements of AWS re:Invent 2021

Amazon made several announcements at AWS re:Invent 2021 that include new services and enhancements, whilst their partners fostered their offerings, turning the annual conference into one of the most significant events of the cloud technology marketplace. The following are the top announcements of this year.

1. AWS Private 5G

AWS Private 5G is a new managed service that helps organizations set up and scale private 5G mobile networks in their respective facilities within days instead of months. With the minimal number of clicks in the AWS console, customers define where they want to build a mobile network and the network capacity required for their devices. Subsequently, AWS delivers and maintains the small cell radio units, servers, 5G core, and radio access network (RAN) software, and subscriber identity module (SIM) cards required to build a private 5G network and link devices. Also, AWS Private 5G automates the setup and deployment of the network and scales capacity on-demand to support supplementary devices and enhanced network traffic. There are absolutely no per-device costs or fees to be paid in advance with AWS Private 5G and customers only have to pay for the network capacity and throughput they request.

2. Amazon SageMaker Canvas

Amazon SageMaker Canvas leverages the most powerful AutoML technology from Amazon SageMaker, which spontaneously trains and builds models depending on your dataset. This lets SageMaker Canvas to determine the best model based on your dataset so that you can generate single or bulk predictions. It supports numerous problem types such as binary classification, multi-class classification, numerical regression, and time series forecasting. These problem types allow you to address business-critical use cases, such as fraud detection, churn reduction, and inventory optimization without the need of having to write a single line of code. Also, this capability offers an intuitive user interface to swiftly connect to and access data from contrasting sources and prepare data for building ML models.

3. Amazon DevOps Guru for RDS

Amazon DevOps Guru for RDS is a new capability powered by Machine Learning for Amazon Relational Database Service (RDS) that systematically identifies and diagnoses database performance and operational issues, enabling users to address bottlenecks in minutes instead of days. This feature of Amazon DevOps Guru, uncovers issues related to operation and performance for all Amazon RDS engines and dozens of other resource types. Also, DevOps Guru for RDS extends upon the existing capabilities of DevOps Guru to determine, diagnose and offer correction recommendations for a range of issues related to performance of database, such as resource over-utilization and misbehavior of SQL queries. Whenever an issue arises, DevOps Guru for RDS instantly notifies developers and DevOps engineers by providing diagnostic information, info on the extent of the issue, and intelligent restoration recommendations to assist customers to promptly resolve the issue.

4. Amazon SageMaker Ground Truth Plus

Amazon SageMaker Ground Truth Plus enables users to create high-quality training datasets with ease, with no need to build labeling applications and manage the labeling workforce on your own. Consequently, you don’t even need to have deep expertise in Machine Learning or extensive knowledge of workflow design and quality management. You simply provide data together with labeling requirements and Ground Truth Plus sets up the data labeling workflows and manages them on your behalf in concordance with your requirements. Also, this latest service uses a multi-tier labeling workflow that includes ML techniques for active learning, pre-labeling and machine validation. This reduces the time required to label datasets for a range of use cases which include computer vision and natural language processing.

5. New EC2 instances featuring Trn1 and Graviton3 Processors

AWS Trainium-based Amazon EC2 Trn1 instances deliver the best price-performance for training deep machine learning models in the cloud for use cases like natural language processing, object detection image recognition, recommendation engines, intelligent search, etc. They support up to 16 Trainium accelerators, 800 Gbps of EFA networking throughput, and ultra-high speed intra-instance connectivity for the quickest ML training in Amazon EC2. These instances are deployed in EC2 UltraClusters that can be scaled to tens of thousands of Trainium accelerators with petabit scale and non-blocking networking. These Trn1 UltraClusters are 2.5x bigger than the former generation EC2 UltraClusters and assist as a powerful supercomputer to quickly train the most complicated deep learning models.

AWS Graviton3 Processors are the latest addition to the Graviton family of processors which are tailor-made by AWS to provide the best price-performance for workloads in Amazon EC2. They offer up to 25% better compute performance, 2x higher floating-point performance, and 2x faster cryptographic workload performance when compared to AWS Graviton2 processors. Also, Graviton3 processors render up to 3x better performance in comparison to Graviton2 processors for CPU-based machine learning workloads, along with additional support for bfloat16 and fp16 instructions. Furthermore, they support pointer authentication for improved security besides always-on 256-bit memory encryption available in AWS Graviton2.

6. Karpenter – An Open-Source High-Performance Kubernetes Cluster Autoscaler

Karpenter is an open-source, resilient, high-performance Kubernetes cluster autoscaler created with AWS. It helps improve the application availability and cluster efficiency of users by swiftly launching appropriately sized compute resources in response to the dynamic application load. Also, this autoscaler offers compute resources in a timely manner to meet your application’s requirements and will soon instinctively optimize a cluster’s compute resource footprint to minimize costs and enhance performance. Karpenter is created to work with any Kubernetes cluster irrespective of the running environment, comprising of all principal cloud providers and on-premises environments. As Karpenter is installed in a user’s cluster, it inspects the aggregate resource requests of unscheduled pods and generates decisions to institute new nodes and terminate them to minimize scheduling latencies and infrastructure expenses.

7. AWS Amplify Studio

This new visual development environment offers frontend developers with features to expedite the development of UI with minimal coding, whilst integrating Amplify’s powerful backend configuration and management capabilities. AWS Amplify Studio spontaneously translates designs made in Figma to human-readable React UI component code. Developers can now visually connect the UI components to app backend data within Amplify Studio. With regard to configuring and managing backends, Amplify Admin UI’s present capabilities will be part of Amplify Studio moving forward, offering an integrated interface to empower developers to build full-stack applications quicker. Furthermore, to speed up the UI development process, Amplify Studio provides developers a React UI library with several components such as newsfeeds, contact forms, and e-commerce cards.

8. Amazon Mask Severless (in preview)

This is a new type of Amazon MSK cluster that makes it simpler for developers to run Apache Kafka without needing to manage its capacity. Amazon MSK Serverless spontaneously provisions and scales compute and storage resources and provides throughput-based pricing, so that you can utilize Apache Kafka on demand and pay only for the data you stream and retain. With minimal clicks in the AWS management console, users can set up secure and highly available clusters that automatically scale as your application I/O scales. MSK serverless enables users to run existing applications without needing to change code or create new applications using prominent tools and APIs, as it is fully compatible with Apache Kafka. Also, this cluster supports native AWS integrations that offer capabilities like private connectivity with AWS PrivateLink, safe client access with AWS Identity and Access Management (IAM), and schema evolution control with AWS Glue Schema Registry.

9. Amazon EMR Serverless (in preview)

This is a new serverless option in Amazon EMR that makes it simple and economical for data engineers and analysts to run petabyte-scale data analytics in the cloud. As you are aware, Amazon EMR is a cloud big data platform utilized by customers to run large-scale distributed data processing jobs, interactive SQL queries, and machine learning applications using open-source analytics frameworks like Apache Hive, Apache Spark, and Presto. Now with the introduction of Amazon EMR Serverless, customers can run applications built with the aid of these frameworks with minimal clicks, without needing to configure, optimize and secure clusters. EMR Serverless instinctively provisions and scales the compute and memory resources needed by the application, and customers have to only pay for the resources they utilize. Also, with EMR Serverless, users need to just specify the open-source framework and version that they wish to use for their application and submit jobs using EMR Studio, API’s or JDBC & ODBC clients.

10. AWS Cloud WAN Preview

AWS Cloud WAN is a new managed wide-area networking (WAN) service that makes it easier for users to create, manage and track any global network that connects resources running across their cloud and on-premises environments. This service provides a simple way to link all your data centers, branch offices, and cloud resources into an integrated, centrally managed network, minimizing the operational costs and complexities involved with running a global network. Furthermore, with Cloud WAN, users can utilize a centralized dashboard and network policies to build a global network that covers multiple locations and networks, ultimately eliminating the need to individually configure and manage different networks using diverse technologies. As Cloud WAN automatically creates a global network across AWS Regions using the Border Gateway Protocol (BGP), users can now easily exchange routes round the globe.

Schedule a meeting with our AWS Cloud Solution Experts and accelerate your cloud journey with Idexcel.

AWS re:Invent Recap: Machine Learning Keynote

Here are the key announcements from the re:Invent 2020 Machine Learning Keynote:

  1. Faster Distributed Training on Amazon SageMaker is the quickest and most efficient approach for training large deep learning models and datasets. Through model parallelism and data parallelism, SageMaker distributed training automatically splits deep learning models and datasets for training in significantly less time across AWS GPU instances.
  2. Amazon SageMaker Clarify detects potential bias during all phases of the data preparation, model training, and model deployment, giving development teams greater visibility into their training data and models to resolve potential bias and explain predictions in greater detail.
  3. Deep Profiling for Amazon SageMaker Debugger gives developers the capability to train models at a quicker pace by monitoring system resource utilization automatically and providing notifications of training bottlenecks.
  4. Amazon SageMaker Edge Manager: provides developers the tools to optimize, secure, monitor, and maintain ML model management on edge devices like smart cameras, robots, personal computers, and mobile devices.
  5. Amazon Redshift ML empowers data analyst, development, and scientist teams to create, train, and deploy machine learning (ML) models using SQL commands. Teams can now build and train machine learning models from Amazon Redshift datasets and apply them to use cases.
  6. Amazon Neptune ML leverages Graph Neural Networks (GNNs) to make easy, fast, and more accurate predictions using graph data. The accuracy of most graph predictions increases to 50% with Neptune ML when compared to non-graph prediction methods. The selection and training of the best ML model for graph data are automated and lets users run ML on their graph directly using Neptune APIs and queries. ML teams can now create, train, and apply ML on Neptune data, reducing the development time from weeks down to a matter of hours.
  7. Amazon Lookout for Metrics applies ML to detect metrics anomalies in your metrics to perform proactive monitoring of the health of your business, issue diagnosis, and opportunity identification quickly that can save costs, increase margins, and improve customer experience.
  8. Amazon HealthLake leverages ML models to empower healthcare and life sciences organizations to aggregate various health information from different silos and formats into a centralized AWS data lake to standardize health data.

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 2019 – Global Partner Summit Announcements

AWS re:Invent 2019

1. Introducing AWS Retail Competency Partners: AWS Retail Competency Partners provide innovative technology offerings that accelerate retailers’ modernization and innovation journey across all areas in the enterprise. Read More

2. Introducing AWS Public Safety & Disaster Response Competency Partners: AWS Customers can quickly identify top-tier APN Consulting Partners who identify, build, and implement technology offerings aimed at improving organizational capacity to prepare, respond, and recover from emergencies and disasters, globally. Read More

3. New AWS Service Ready Program to help customers find tools that integrate with AWS services: AWS Partner Network (APN) announced AWS Service Ready Program, a new way for AWS customers to identify if a tool or application will integrate with AWS services running in their cloud environment. Read More

4. New APN Global Startup Program, helping startup APN Technology Partners grow their cloud-based business: AWS Partner Network (APN) announced the APN Global Startup Program, a dedicated go-to-market (GTM) program for eligible Startup APN Technology Partners. Read More

5. Introducing a new benefit for APN Consulting Partners, APN Immersion Days: AWS Immersion Day workshops provide a customizable AWS experience delivered by AWS Solution Architects and Account Managers to AWS customers. Read More

6. AWS Marketplace makes it easier for you to discover relevant third-party software and data products: AWS Marketplace, a digital catalog with over 7,000 software listings and data products, has announced Discovery API, a new API created for select partners. Read More

7. AWS Marketplace announces a simplified fee structure and the expansion of Seller Private Offers: Starting today, all registered sellers with a public listing in AWS Marketplace can extend a custom contract through Seller Private Offers. Read More

AWS re:Invent 2019

AWS re:Invent 2019

Event Details: At re:Invent 2019, you can expect deeper technical content, more hands-on learning opportunities, and more access to AWS experts than ever. Each year at re:Invent, we bring you over a thousand sessions, chalk talks, workshops, builders sessions, and hackathons that cover AWS core topics and highlight the emerging technologies that we are developing. This year, re:Invent will be no different.

[Know more about the Conference]

About Idexcel: Idexcel is a Professional Services and Technology Solutions provider specializing in Cloud Services, Application Modernization, and Data Analytics. Idexcel is proud that for more than 20 years it has provided services that implement complex technologies that are innovative, agile and successful and have provided our customers with lasting value.

Anand Allolankandy – (Senior Director, Cloud Services Practice at Idexcel) will be attending this event. For further queries, please write to

AWS re:Invent 2018

AWS re:Invent 2018

Event Details: At re:Invent 2018, you can expect deeper technical content, more hands-on learning opportunities, and more access to AWS experts than ever. The return of our two-hour workshops and our hackathon program means that you can dive into solving challenges and working on a team. The chalk talks and builders sessions give you the opportunity to interact in a small group setting with AWS experts as they whiteboard through problems and solutions. We have many more opportunities this year for you to interact, build, and learn, so you can get the most out of re:Invent.

Each year at re:Invent, we bring you over a thousand sessions, chalk talks, workshops, builders sessions, and hackathons that cover AWS core topics and embrace the emerging technologies we are developing. re:Invent 2018 will be no different. You will find sessions that cover topics that you have seen in past years: databases, analytics & big data, security & compliance, enterprise, machine learning, and compute, to name a few. This year, you will be able to cross-search these topics in the session catalog, so you can really drill down and find the sessions most pertinent to you.

[Know more about the Conference]

About Idexcel: Idexcel is a Professional Services and Technology Solutions provider specializing in Cloud Services, Application Modernization, and Data Analytics. Idexcel is proud that for more than 20 years it has provided services that implement complex technologies that are innovative, agile and successful and have provided our customers with lasting value.

Anand Allolankandy – (Sr. Director Technical Sales & Delivery at Idexcel) will be attending this event. For further queries, please write to