What’s New at AWS? Live From re:Invent 2022 – Day 3

Overview

AWS has been a leading cloud computing provider for about one and a half decades. In fact, AWS has been a pioneer with the 1st position on Gartner’s Magic Quadrant for the last 12 consecutive years. Every year AWS does a yearly conclave – AWS re:Invent – to touch base with the Cloud Computing industry and more importantly to announce how AWS is keeping up to speed by launching path-breaking services.

We at CloudThat, have been at par with the same with our path-breaking learning capabilities. Following the company’s ethos of relentless learning, I want to keep you guys posted on what is happening at AWS re:Invent 2022.

Day 1 in a brief

Day 1 at AWS re: invent 2022 was exciting with insightful sessions and path-breaking releases.

Check out the overview Blog : AWS re:Invent 2022 Highlights – CloudThat

What’s New Day 1: What’s New at AWS? Live From re:Invent 2022 – Day 1 – CloudThat Resources

Check out the live feed at: CloudThat (@cloudthat) • Instagram photos and videos

Day 2 in Brief

With tons of Service releases, day 2 was pretty exciting

Check out  what’s New Day 2: AWS re:Invent 2022 Cloud Conference – Day 2 (cloudthat.com)

Check out the live feed at: CloudThat (@cloudthat) • Instagram photos and videos

Day 3

Day 3 of AWS re:Invent 2022, witnessed the release of many new services. Let’s dive in:

1. Amazon Athena for Apache Spark
   Apache spark runs 3x faster on AWS.  It runs interactive analytics with Apache Spark. This feature can run Apache Spark workloads, use Jupyter Notebook as the interface to perform data processing on Athena, and programmatically interact with Spark applications using Athena APIs. Read more. 
2. Amazon SageMaker
   Amazon SageMaker is a machine learning service that Amazon wholly manages. Data scientists and developers can use SageMaker to construct and train machine learning models fast and efficiently, then deploy them directly into a production-ready hosted environment. The newly released functionality of Amazon SageMaker supports Geospatial ML, which means that it can predict dangerous road conditions due to rising water levels. It is also expanding in other sectors such as Automotive, Retail, Agriculture & Urban Planning. It is making the lives of data scientists and engineers to build, train, and deploy models using geospatial data. Read more. 
   
3. AWS Lake Formation
   This new feature is released to govern, secure, and share data in data lakes and warehouses. The policy access is centralized, which can be easily enforced across all services. The access management is simplified and defines fine-grained access permissions. It has enhanced integration capabilities with Amazon Redshift, EMR, SageMaker, and Athena. Read more.
   
4. Amazon DataZone
   Amazon DataZone is a new data management service that quickly helps customers catalog, discover, share and govern data stored in AWS cloud, on-premises, or any other third-party sources. Engineers, Data Scientists, and business users can access data throughout their organization to help them derive useful insights to cater to their business needs. Read more.
5. Amazon Kinesis Data Stream Data Viewer
   It is used for capturing item-level modifications of any DynamoDB table. Our applications can access the Kinesis stream and view changes in near real-time. Data Viewer is a new capability added to Amazon Kinesis Data Streams that allows viewing data directly from the AWS Management Console. Read more. 
   
6. Amazon RDS multi-AZ with two standbys
   Amazon RDS Multi-AZ with two standby is available on MySQL (8.0.28) and PostgresSQL (13.4). Its amazing features make it the potential choice for most workloads where high availability cannot be compromised. It supports automatic database failover, which takes less than 35 secs to ensure your application is highly available. Compared to Multi-AZ with one standby, you can achieve a 2x improvement in write latency. You can gain read scalability by distributing traffic between two readable standby instances. Scalability and performance can be maximized by routing queries to write servers and appropriate standby read replica instances. 
   
7. Amazon Aurora Serverless V2
   Amazon Aurora Serverless V2 is a cloud-based database service that provides a fully managed and scalable solution for running relational databases. This service automatically scales up or down based on the workload, eliminating the need for manual provisioning and scaling of database capacity. Aurora Serverless V2 also offers fast failover, high availability, and low latency performance, making it a popular choice for applications requiring high database performance levels. It is a fully managed service that is easy to set up and use, allowing developers to focus on building applications without worrying about managing the underlying infrastructure. Read more. 
8. Amazon MemoryDB for Redis Data Tiering
   Amazon MemoryDB for Redis is a data tiering solution that allows you to use Redis as a cache for data stored in Amazon Aurora. This can improve the performance of your application by allowing it to access frequently used data directly from the in-memory cache, instead of querying the database. MemoryDB for Redis is fully managed, so you don’t have to worry about provisioning or scaling the cache. It also automatically synchronizes data between Redis and Aurora so you can use Redis as a real-time view of your data. This can be useful for applications requiring low-latency data access, such as real-time analytics or online gaming. MemoryDB for Redis is compatible with the open-source Redis API so that you can use it with existing Redis client libraries and tools. Read more. 
9. Amazon RDS Optimized Writes
   Introducing RDS Optimized Writes – Up to 2x improvement in write transaction throughput. Optimized Writes are a great fit for write-heavy workloads that generate many concurrent transactions.  Read more.
10. DPaaS: Data Pipeline as a Service
    DPaas allows users to create, manage, and monitor data pipelines that extract data from various sources, transform and clean it, and load it into a destination system, such as a data warehouse or a database. DPaaS is a fully managed service, so you don’t have to worry about provisioning or maintaining the infrastructure required to run your data pipelines. It also offers a range of tools and features that make it easy to build, manage, and monitor your data pipelines, including a visual pipeline editor, automatic error handling, and real-time monitoring and alerting. It is a cloud-based solution for managing data flow between different systems and services. Read more. 
11. Amazon GuardDuty RDS ProtectionAmazon GuardDuty is an intrusion detection service that monitors for malicious activity and unauthorized behavior to protect your AWS accounts and workloads. Amazon GuardDuty RDS Protection now identifies potential threats to the data stored in the Amazon Aurora database. Read more.
12. Amazon RDS Blue/Green Deployments
    AWS has announced the general availability of Amazon RDS blue-green deployments, a new feature for Amazon Aurora with MySQL compatibility, Amazon RDS for MySQL, and MariaDB that allows you to make database updates faster, easier, and more secure. This new fully managed feature is available in almost all AWS regions except China and AWS GovCloud.
    Here is a detailed blog on a Step-by-step guide for Blue/Green Deployments.
13. AWS DMS Schema Conversion
    AWS DMS Schema Conversion is a new feature of Amazon Web Services Database Migration Service (DMS) that allows you to convert the schema of a database from one database engine to another. This can be useful when migrating your database to AWS or switching to a different database engine, such as moving from Oracle to Amazon Aurora. DMS Schema Conversion automatically converts the schema of your source database to the target database engine, including the tables, indexes, and primary keys. It also provides a preview of the converted schema, so you can review and make any necessary changes before applying the conversion.
    

Machine Learning with AWS

AWS brings machine learning closer to data with these 5 ML services that are helpful for data analytics:

• Amazon Aurora
• Amazon Neptune
• Amazon Redshift
• Amazon Athena
• Amazon QuickSight

AWS and CloudThat

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We are on a mission to build a robust cloud computing ecosystem by disseminating knowledge on technological intricacies within the cloud space. To get started, go through our Consultancy page and Managed Services Package that is CloudThat’s offerings.

About CloudThat

CloudThat is a pioneer in the Cloud Computing training realm, we are a Microsoft Gold Partner, AWS (Amazon Web Services) Advanced Consulting Partner, and Training partner. Also, we are Google Cloud Partners delivering best-in-industry training for Azure, AWS, and GCP (Google Cloud Platform). We are on a mission to build a strong cloud computing ecosystem by disseminating knowledge on technological intricacies within the cloud space.