AWS — re:Invent 2023 Top Announcements Summary and Highlights (My Favorites)

Ashish Patel
Awesome Cloud
Published in
7 min readNov 28, 2023


AWS re:Invent 2023 Key Announcements Highlights!

Awesome Cloud — AWS re:Invent 2023 Top Announcements

GenAI was main focus of the AWS re:Invent 2023.

Amazon Aurora Limitless Database

Amazon Aurora Limitless Database (preview), a new capability supporting automated horizontal scaling to process millions of write transactions per second and manage petabytes of data in a single Aurora database.

Amazon Aurora read replicas allow you to increase the read capacity of your Aurora cluster beyond the limits of what a single database instance can provide. Now, Aurora Limitless Database scales write throughput and storage capacity of your database beyond the limits of a single Aurora writer instance. The compute and storage capacity that is used for Limitless Database is in addition to and independent of the capacity of your writer and reader instances in the cluster.

With Limitless Database, you can focus on building high-scale applications without having to build and maintain complex solutions for scaling your data across multiple database instances to support your workloads. Aurora Limitless Database scales based on the workload to support write throughput and storage capacity that, until today, would require multiple Aurora writer instances.

Read more about it here.

Amazon ElastiCache Serverless for Redis and Memcached

A new serverless option allows customers to create a cache in under a minute and instantly scale capacity based on application traffic patterns. ElastiCache Serverless is compatible with two popular open-source caching solutions, Redis and Memcached.

ElastiCache Serverless constantly monitors your application’s memory, CPU, and network resource utilization and scales instantly to accommodate changes to the access patterns of workloads it serves. You can create a highly available cache with data automatically replicated across multiple Availability Zones and up to 99.99 percent availability Service Level Agreement (SLA) for all workloads, which saves you time and money.

With ElastiCache Serverless, there are no upfront costs, and you pay for only the resources you use. You pay for the amount of cache data storage and ElastiCache Processing Units (ECPUs) resources consumed by your applications.

Read more about it here.

Zero-ETL integrations with AWS Databases and Amazon Redshift & Amazon OpenSearch

Zero-ETL is a set of integrations that eliminates the need to build ETL data pipelines. Zero-ETL integrations with Amazon Redshift enable customers to access their data in place using federated queries or ingest it into Amazon Redshift with a fully managed solution from across their databases.

zero-ETL integrations with Amazon Redshift:

  • Amazon Aurora MySQL-Compatible Edition (generally available)
  • Amazon Aurora PostgreSQL-Compatible Edition (preview)
  • Amazon RDS for MySQL (preview)
  • Amazon DynamoDB (limited preview)

By bringing different database services closer to analytics, AWS is streamlining access to data and enabling companies to accelerate innovation, create competitive advantage, and maximize the business value extracted from their data assets. Read more about it here.

Amazon DynamoDB zero-ETL integration with Amazon OpenSearch: It provides customers advanced search capabilities, such as full-text and vector search, on their Amazon DynamoDB data. Read more about it here.

Amazon OpenSearch zero-ETL integration with Amazon S3: A new way to query operational logs in Amazon S3 and S3-based data lakes without needing to switch between services. You can now analyze infrequently queried data in cloud object stores and simultaneously use the operational analytics and visualization capabilities of OpenSearch Service. Amazon OpenSearch Service direct queries with Amazon S3 provides a zero-ETL integration to reduce the operational complexity of duplicating data or managing multiple analytics tools by enabling customers to directly query their operational data, reducing costs and time to action. Read more about it here.

Amazon Q

Amazon Q (preview), a new generative AI–powered assistant that is specifically designed for work and can be tailored to your business to have conversations, solve problems, generate content, and take actions using the data and expertise found in your company’s information repositories, code, and enterprise systems.

Read more about it here.

Amazon Q generative SQL in Amazon RedShift: Amazon Redshift introduces Amazon Q generative SQL in Amazon Redshift Query Editor, an out-of-the-box web-based SQL editor for Redshift, to simplify query authoring and increase your productivity by allowing you to express queries in natural language and receive SQL code recommendations. Furthermore, it allows you to get insights faster without extensive knowledge of your organization’s complex database metadata.

Read more about it here.

Amazon RDS for Db2

Amazon RDS for Db2, a fully managed Db2 database engine running on AWS infrastructure. AWS takes care of the infrastructure heavy lifting, meaning, database runs on a fully managed infrastructure.

Amazon RDS offers the same Db2 database as the one you use on-premises today. Your existing applications will reconnect to RDS for Db2 without changing their code.

Read more about it here.

Amazon S3 Express One Zone storage class

Amazon S3 Express One Zone storage class is purpose-built to deliver the fastest cloud object storage for performance-critical applications that demand consistent single-digit millisecond request latency. S3 Express One Zone can improve data access speeds by 10x and reduce request costs by 50% compared to S3 Standard and scales to process millions of requests per minute for your most frequently accessed datasets. It enables workloads such as machine learning training, interactive analytics, and media content creation to achieve single-digit millisecond data access speed with high durability and availability.

Read more about it here.

Amazon EKS Pod Identity simplifies IAM permissions

You can use Amazon EKS Pod Identity to simplify your applications that access AWS services. This enhancement provides you with a seamless and easy to configure experience that lets you define required IAM permissions for your applications in Amazon Elastic Kubernetes Service (Amazon EKS) clusters so you can connect with AWS services outside the cluster.

Amazon EKS Pod Identity helps you solve growing challenges for managing permissions across many of your EKS clusters.

Read more about it here.

Amazon SQS FIFO queues throughput increase and DLQ redrive

Maximum throughput has been increased up to 70,000 transactions per second (TPS) per API action in selected AWS Regions, supporting sending or receiving up to 700,000 messages per second with batching.

Dead letter queue (DLQ) redrive support to handle messages that are not consumed after a specific number of retries in a way similar to what was already available for standard queues.

Read more about it here.

AWS Lambda scales up to 12 times faster

AWS Lambda functions now scale 12 times faster when handling high-volume requests. Each synchronously invoked Lambda function now scales by 1,000 concurrent executions every 10 seconds until the aggregate concurrency across all functions reaches the account’s concurrency limit. In addition, each function within an account now scales independently from each other, no matter how the functions are invoked. These improvements come at no additional cost, and you don’t need to do any configuration in your existing functions.

Read more about it here.

Amazon CloudWatch Logs automated anomaly detection

Amazon CloudWatch has added new capabilities to automatically recognize and cluster patterns among log records, extract noteworthy content and trends, and notify you of anomalies using advanced machine learning (ML) algorithms trained using decades of Amazon and AWS operational data.

Read more about it here.

Use natural language to query Amazon CloudWatch logs and metrics

To make it easy to interact with your operational data, Amazon CloudWatch is introducing natural language query generation for Logs and Metrics Insights.

This feature provides three main capabilities for CloudWatch Logs and Metrics Insights:

  • Generate new queries from a description or a question to help you get started easily.
  • Query explanation to help you learn the language including more advanced features.
  • Refine existing queries using guided iterations.

Read more about it here.

Amazon CloudWatch Application Signals for automatic instrumentation

Amazon CloudWatch Application Signals helps you automatically instrument applications based on best practices for application performance. There is no manual effort, no custom code, and no custom dashboards. You get a pre-built, standardized dashboard showing the most important metrics, such as volume of requests, availability, latency, and more, for the performance of your applications.

In addition, you can define Service Level Objectives (SLOs) on your applications to monitor specific operations that matter most to your business. An example of an SLO could be to set a goal that a webpage should render within 2000 ms 99.9 percent of the time in a rolling 28-day interval.

Read more about it here.

Amazon CloudWatch log class for infrequent access logs at a reduced price

This new log class offers a tailored set of capabilities at a lower cost for infrequently accessed logs, enabling customers to consolidate all their logs in one place in a cost-effective manner.

Read more about it here.

Amazon CloudWatch to consolidate hybrid, multicloud, and on-premises metrics

You can now consolidate metrics from your hybrid, multicloud, and on-premises data sources using Amazon CloudWatch and process them in a consistent, unified fashion.

You can query, visualize, and alarm on any and all of the metrics, regardless of their source. In addition to giving you a unified view, this new feature will help you to identify trends and issues that span multiple parts and aspects of your infrastructure.

Read more about it here.

IAM Access Analyzer: Find unused access, check policies before deployment

A new analyzer continuously monitors roles and users looking for permissions that are granted but not actually used, and a policy checker validates that newly authored policies do not grant additional (and perhaps unintended) permissions.

Read more about it here.

Mutual authentication (mTLS) for Application Load Balancer

You can now offload client authentication to Application Load Balancer, ensuring only trusted clients communicate with backend applications.

This new capability is built on S2N, AWS’s open source Transport Layer Security (TLS) implementation that provides strong encryption and protections against zero-day vulnerabilities, which developers can trust.

Read more about it here.

Amazon Managed Service for Prometheus agentless metric collection for Amazon EKS

This new capability discovers and collects Prometheus metrics from Amazon Elastic Kubernetes Service (Amazon EKS) automatically and without an agent.

One of the significant benefits is that the collector is fully managed, automatically right-sized, and scaled for your use case. This means you don’t have to run any compute for collectors to collect the available metrics. This helps you optimize metric collection costs to monitor your applications and infrastructure running on EKS.

Read more about it here.



Ashish Patel
Awesome Cloud

Cloud Architect • 4x AWS Certified • 6x Azure Certified • 1x Kubernetes Certified • MCP • .NET • Terraform • DevOps • Blogger []