Learn how Amazon Bedrock AgentCore agents in one account can generate answers from an Amazon Bedrock knowledge base backed by Amazon Redshift Serverless in another account, without copying source data. This post covers the architecture, security boundary, and two orchestration models: a code-based Strands agent and a declarative AgentCore harness.

Need to cache frequently accessed data in memory? That is ElastiCache Need a fully managed NoSQL database that scales instantly? That is DynamoDB Need to warehouse and analyze massive datasets? That is Redshift Need to move and transform data between those services automatically? That is AWS Glue

In this post, we will show you five Amazon Redshift architecture patterns that you can consider to optimize your Amazon Redshift data warehouse performance at scale using features such as Amazon Redshift Serverless, Amazon Redshift data sharing, Amazon Redshift Spectrum, zero-ETL integrations, and Amazon Redshift streaming ingestion.

Amazon Redshift Serverless now defaults to AI-driven scaling for new workgroups, automatically optimizing compute resources based on workload patterns while supporting lower entry costs with 8–512 RPU range.

Amazon Redshift Serverless now offers AI-driven scaling and optimization, allowing users to balance performance and cost across five different optimization profiles ranging from cost-saving to performance-maximizing configurations.

Amazon Redshift now allows you to get started with Amazon Redshift Serverless with a lower data warehouse base capacity configuration of 4 Redshift Processing Units (RPUs). Amazon Redshift Serverless measures data warehouse capacity in RPUs, and you pay only for the duration of workloads you run in RPU-hours on a per-second basis. Previously, the minimum base capacity required to run Amazon Redshift Serverless was 8 RPUs. You can start using Amazon Redshift Serverless for as low as $1.50 per hour and pay only for the compute capacity your data warehouse consumes when it is active. Amazon Redshift Serverless enables users to run and scale analytics without managing data warehouse clusters. The new lower capacity configuration makes Amazon Redshift Serverless suitable for both production and development environments, particularly when workloads require minimal compute and memory resources. This entry-level configuration supports data warehouses with up to 32 TB of Redshift managed storage, offering a maximum of 100 columns per table and 64 GB of memory. Amazon Redshift Serverless with 4 RPU Minimum Capacity Option is generally available in the AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), US West (N. California), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Asia Pacific (Mumbai), Europe (Ireland), Europe (Stockholm). To get started, see the Amazon Redshift Serverless https://aws.amazon.com/redshift/features/, https://aws.amazon.com/redshift/redshift-serverless/, https://docs.aws.amazon.com/redshift/latest/mgmt/serverless-capacity.html, https://docs.aws.amazon.com/redshift-serverless/latest/APIReference/Welcome.html, and https://aws.amazon.com/redshift/pricing/.  

In this post, we show you the upgrade process from DC2 instances to Amazon Redshift Serverless. By using Amazon Redshift Serverless, you can run and scale analytics without managing data warehouse infrastructure.

    Amazon Redshift Serverless now preserves zero-ETL and Amazon S3 event integrations during snapshot restores 0 views Eyal Estrin unread, 12:00 AM (20 minutes ago)    to https://aws.amazon.com/about-aws/whats-new/2026/07/redshift-serverless-zetl-autocopy-restore/ https://docs.aws.amazon.com/redshift/latest/mgmt/serverless-snapshot-restore.html https://docs.aws.amazon.com/redshift/latest/mgmt/behavior-changes.html#serverless-restore-integrations-patch202 Eyal Estrin Author | Cloud Architect | AWS • Azure • GCP Insights Social: @eyalestrin Connect: https://linktr.ee/eyalestrin Blog: https://security-24-7.com Reply all Reply to author Forward

In this post, we review how to set up Redshift Serverless to use geospatial data contained within a data lake to enhance maps in ArcGIS Pro. This technique helps builders and GIS analysts use available datasets in data lakes and transform it in Amazon Redshift to further enrich the data before presenting it on a map.

https://aws.amazon.com/redshift/ now allows you to get started with Amazon Redshift Serverless with a lower data warehouse https://docs.aws.amazon.com/redshift/latest/mgmt/serverless-capacity.html of 4 Redshift Processing Units (RPUs) in the Asia Pacific (Hong Kong), Asia Pacific (Seoul), Canada (Central), Europe (London), South America (Sao Paulo), AWS GovCloud (US-East), and AWS GovCloud (US-West) regions. Amazon Redshift Serverless measures data warehouse capacity in RPUs. 1 RPU provides you 16 GB of memory. You pay only for the duration of workloads you run in RPU-hours on a per-second basis. Previously, the minimum base capacity required to run Amazon Redshift Serverless was 8 RPUs. You can start using Amazon Redshift Serverless for as low as $1.50 per hour and pay only for the compute capacity your data warehouse consumes when it is active. For predictable workloads, Amazon Redshift Serverless https://docs.aws.amazon.com/redshift/latest/mgmt/serverless-billing-reserved.html#serverless-billing-reserved-works with 1-year and 3-year terms provide additional price-performance benefits. Amazon Redshift Serverless enables users to run and scale analytics without managing data warehouse clusters. The new lower capacity configuration makes Amazon Redshift Serverless suitable for both production and development environments, particularly when workloads require minimal compute and memory resources. This entry-level configuration supports data warehouses with up to 32 TB of Redshift managed storage, offering a maximum of 100 columns per table and 64 GB of memory. To get started, see the Amazon Redshift Serverless https://aws.amazon.com/redshift/redshift-serverless/, https://docs.aws.amazon.com/redshift/latest/mgmt/working-with-serverless.html, and https://docs.aws.amazon.com/redshift-serverless/latest/APIReference/Welcome.html.

https://aws.amazon.com/redshift/redshift-serverless/, which allows you to run and scale analytics without having to provision and manage data warehouse clusters, is now generally available in the AWS Asia Pacific(Taipei) region. With Amazon Redshift Serverless, all users, including data analysts, developers, and data scientists, can use Amazon Redshift to get insights from data in seconds. Amazon Redshift Serverless automatically provisions and intelligently scales data warehouse capacity to deliver high performance for all your analytics. You only pay for the compute used for the duration of the workloads on a per-second basis. You can benefit from this simplicity without making any changes to your existing analytics and business intelligence applications. With a few clicks in the AWS Management Console, you can get started with querying data using the Query Editor V2 or your tool of choice with Amazon Redshift Serverless. There is no need to choose node types, node count, workload management, scaling, and other manual configurations. You can create databases, schemas, and tables, and load your own data from Amazon S3, access data using Amazon Redshift data shares, or restore an existing Amazon Redshift provisioned cluster snapshot. With Amazon Redshift Serverless, you can directly query data in open formats, such as Apache Parquet, in Amazon S3 data lakes. Amazon Redshift Serverless provides unified billing for queries on any of these data sources, helping you efficiently monitor and manage costs. To get started, see the Amazon Redshift Serverless https://aws.amazon.com/redshift/redshift-serverless/, https://docs.aws.amazon.com/redshift/latest/mgmt/working-with-serverless.html, and https://docs.aws.amazon.com/redshift-serverless/latest/APIReference/Welcome.html.

Amazon Redshift now allows you to get started with Amazon Redshift Serverless with a lower data warehouse base capacity configuration of 4 Redshift Processing Units (RPUs). Amazon Redshift Serverless measures data warehouse capacity in RPUs, and you pay only for the duration of workloads you run in RPU-hours on a per-second basis. Previously, the minimum base capacity required to run Amazon Redshift Serverless was 8 RPUs. You can start using Amazon Redshift Serverless for as low as $1.50 per hour and pay only for the compute capacity your data warehouse consumes when it is active. Amazon Redshift Serverless enables users to run and scale analytics without managing data warehouse clusters. The new lower capacity configuration makes Amazon Redshift Serverless suitable for both production and development environments, particularly when workloads require minimal compute and memory resources. This entry-level configuration supports data warehouses with up to 32 TB of Redshift managed storage, offering a maximum of 100 columns per table and 64 GB of memory. Amazon Redshift Serverless with 4 RPU Minimum Capacity Option is generally available in the AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), US West (N. California), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Asia Pacific (Mumbai), Europe (Ireland), Europe (Stockholm). To get started, see the Amazon Redshift Serverless feature page, use cases, user documentation, API Reference, and pricing.

Discover more about what's new at AWS with Amazon Redshift Serverless announces the general availability of dual-stack mode supporting IPV6

https://aws.amazon.com/redshift/redshift-serverless/, which allows you to run and scale analytics without having to provision and manage data warehouse clusters, is now generally available in the AWS Europe (Milan) and Africa (Cape Town) regions. With Amazon Redshift Serverless, all users, including data analysts, developers, and data scientists, can use Amazon Redshift to get insights from data in seconds. Amazon Redshift Serverless automatically provisions and intelligently scales data warehouse capacity to deliver high performance for all your analytics. You only pay for the compute used for the duration of the workloads on a per-second basis. You can benefit from this simplicity without making any changes to your existing analytics and business intelligence applications. With a few clicks in the AWS Management Console, you can get started with querying data using the Query Editor V2 or your tool of choice with Amazon Redshift Serverless. There is no need to choose node types, node count, workload management, scaling, and other manual configurations. You can create databases, schemas, and tables, and load your own data from Amazon S3, access data using Amazon Redshift data shares, or restore an existing Amazon Redshift provisioned cluster snapshot. With Amazon Redshift Serverless, you can directly query data in open formats, such as Apache Parquet, in Amazon S3 data lakes. Amazon Redshift Serverless provides unified billing for queries on any of these data sources, helping you efficiently monitor and manage costs. To get started, see the Amazon Redshift Serverless https://aws.amazon.com/redshift/redshift-serverless/, https://docs.aws.amazon.com/redshift/latest/mgmt/working-with-serverless.html, and https://docs.aws.amazon.com/redshift-serverless/latest/APIReference/Welcome.html.

Amazon Redshift now allows you to get started with Amazon Redshift Serverless with a lower data warehouse https://docs.aws.amazon.com/redshift/latest/mgmt/serverless-capacity.html of 8 Redshift Processing Units (RPUs) in the AWS Asia Pacific (Seoul) and Canada (Central) regions. Each RPU provides 16 GB of memory. Amazon Redshift Serverless measures data warehouse capacity in RPUs, and you pay only for the duration of workloads you run in RPU-hours on a per-second basis. Previously, the minimum base capacity required to run Amazon Redshift Serverless was 32 RPUs. With the new lower base capacity minimum of 8 RPUs, you now have even more flexibility to support a diverse set of workloads of small to large complexity based on your price performance requirements. You can increment or decrement the RPU in units of 8 RPUs. Amazon Redshift Serverless allows you to run and scale analytics without having to provision and manage data warehouse clusters. With Amazon Redshift Serverless, all users, including data analysts, developers, and data scientists, can use Amazon Redshift to get insights from data in seconds. With the new lower capacity configuration, you can use Amazon Redshift Serverless for production environments, test and development environments at an optimal price point when a workload needs a small amount of compute. To get started, see the Amazon Redshift Serverless https://aws.amazon.com/redshift/redshift-serverless/, https://docs.aws.amazon.com/redshift/latest/mgmt/working-with-serverless.html, and https://docs.aws.amazon.com/redshift-serverless/latest/APIReference/Welcome.html.

https://aws.amazon.com/redshift/redshift-serverless/, which allows you to run and scale analytics without having to provision and manage data warehouse clusters, is now generally available in the AWS Asia Pacific (Osaka) and Asia Pacific (Malaysia) regions. With Amazon Redshift Serverless, all users, including data analysts, developers, and data scientists, can use Amazon Redshift to get insights from data in seconds. Amazon Redshift Serverless automatically provisions and intelligently scales data warehouse capacity to deliver high performance for all your analytics. You only pay for the compute used for the duration of the workloads on a per-second basis. You can benefit from this simplicity without making any changes to your existing analytics and business intelligence applications. With a few clicks in the AWS Management Console, you can get started with querying data using the Query Editor V2 or your tool of choice with Amazon Redshift Serverless. There is no need to choose node types, node count, workload management, scaling, and other manual configurations. You can create databases, schemas, and tables, and load your own data from Amazon S3, access data using Amazon Redshift data shares, or restore an existing Amazon Redshift provisioned cluster snapshot. With Amazon Redshift Serverless, you can directly query data in open formats, such as Apache Parquet, in Amazon S3 data lakes. Amazon Redshift Serverless provides unified billing for queries on any of these data sources, helping you efficiently monitor and manage costs. To get started, see the Amazon Redshift Serverless https://aws.amazon.com/redshift/redshift-serverless/, https://docs.aws.amazon.com/redshift/latest/mgmt/working-with-serverless.html, and https://docs.aws.amazon.com/redshift-serverless/latest/APIReference/Welcome.html.

In this post, we demonstrate how Amazon Redshift Serverless AI-driven scaling and optimization impacts performance and cost across different optimization profiles.

Amazon Redshift Serverless, which allows you to run and scale analytics without having to provision and manage data warehouse clusters, is now generally available in the AWS Asia Pacific(Taipei) region. With Amazon Redshift Serverless, all users, including data analysts, developers, and data scientists, can use Amazon Redshift to get insights from data in seconds. Amazon Redshift Serverless automatically provisions and intelligently scales data warehouse capacity to deliver high performance for all your analytics. You only pay for the compute used for the duration of the workloads on a per-second basis. You can benefit from this simplicity without making any changes to your existing analytics and business intelligence applications. With a few clicks in the AWS Management Console, you can get started with querying data using the Query Editor V2 or your tool of choice with Amazon Redshift Serverless. There is no need to choose node types, node count, workload management, scaling, and other manual configurations. You can create databases, schemas, and tables, and load your own data from Amazon S3, access data using Amazon Redshift data shares, or restore an existing Amazon Redshift provisioned cluster snapshot. With Amazon Redshift Serverless, you can directly query data in open formats, such as Apache Parquet, in Amazon S3 data lakes. Amazon Redshift Serverless provides unified billing for queries on any of these data sources, helping you efficiently monitor and manage costs. To get started, see the Amazon Redshift Serverless feature page, user documentation, and API Reference.

Amazon Redshift Serverless, which allows you to run and scale analytics without having to provision and manage data warehouse clusters, is now generally available in the AWS Mexico (Central) and Asia Pacific (Thailand) regions. With Amazon Redshift Serverless, all users, including data analysts, developers, and data scientists, can use Amazon Redshift to get insights from data in seconds. Amazon Redshift Serverless automatically provisions and intelligently scales data warehouse capacity to deliver high performance for all your analytics. You only pay for the compute used for the duration of the workloads on a per-second basis. You can benefit from this simplicity without making any changes to your existing analytics and business intelligence applications. With a few clicks in the AWS Management Console, you can get started with querying data using the Query Editor V2 or your tool of choice with Amazon Redshift Serverless. There is no need to choose node types, node count, workload management, scaling, and other manual configurations. You can create databases, schemas, and tables, and load your own data from Amazon S3, access data using Amazon Redshift data shares, or restore an existing Amazon Redshift provisioned cluster snapshot. With Amazon Redshift Serverless, you can directly query data in open formats, such as Apache Parquet, in Amazon S3 data lakes. Amazon Redshift Serverless provides unified billing for queries on any of these data sources, helping you efficiently monitor and manage costs. To get started, see the Amazon Redshift Serverless https://aws.amazon.com/redshift/redshift-serverless/, https://docs.aws.amazon.com/redshift/latest/mgmt/working-with-serverless.html, and https://docs.aws.amazon.com/redshift-serverless/latest/APIReference/Welcome.html.

AWS continues its global expansion with Redshift Serverless now available in Osaka and Malaysia, offering simplified data analytics solutions for businesses across the region. What Makes Redshift Serverless Different Amazon Redshift Serverless represents a significant evolution in data analytics technology, fundamentally transforming how organizations approach large-scale data processing and analysis. By eliminating the complexities of […]

Amazon Redshift introduces Serverless Reservations, a new pricing option that allows customers to save up to 24% on compute costs by committing to specific RPU levels for one year.