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Amazon Relational Database Service (Amazon RDS) for PostgreSQL, MySQL, and MariaDB now supports AWS Graviton2-based M6gd database instances in Asia Pacific (Hyderabad), Europe (Spain, Zurich), and Middle East (UAE) regions. View the full article

Amazon Relational Database Service (RDS) for Oracle now supports version 23.2 of Oracle Application Express (APEX) for 19c and 21c versions of Oracle Database. Using APEX, developers can build applications entirely within their web browser. View the full article

Amazon Relational Database Service (Amazon RDS) for Oracle now offers Oracle Database Standard Edition 2 (SE2) with the License-Included (LI) purchase option in additional AWS Regions and for additional instance classes. R6i instances are now available in Asia Pacific (Mumbai), Europe (Zurich), and Israel (Tel Aviv). T3 instances are now supported in Europe (Zurich) and Israel (Tel Aviv). View the full article

AWS Summit season is starting! I’m happy I will meet our customers, partners, and the press next week at the AWS Summit Paris and the week after at the AWS Summit Amsterdam. I’ll show you how mobile application developers can use generative artificial intelligence (AI) to boost their productivity. Be sure to stop by and say hi if you’re around. Now that my talks for the Summit are ready, I took the time to look back at the AWS launches from last week and write this summary for you. Last week’s launches Here are some launches that got my attention: AWS License Manager allows you to track IBM Db2 licenses on Amazon Relational Database Service (Amazon RDS) – I wrote about Amazon RDS when we launched IBM Db2 back in December 2023 and I told you that you must bring your own Db2 license. Starting today, you can track your Amazon RDS for Db2 usage with AWS License Manager. License Manager provides you with better control and visibility of your licenses to help you limit licensing overages and reduce the risk of non-compliance and misreporting. AWS CodeBuild now supports custom images for AWS Lambda – You can now use compute container images stored in an Amazon Elastic Container Registry (Amazon ECR) repository for projects configured to run on Lambda compute. Previously, you had to use one of the managed container images provided by AWS CodeBuild. AWS managed container images include support for AWS Command Line Interface (AWS CLI), Serverless Application Model, and various programming language runtimes. AWS CodeArtifact package group configuration – Administrators of package repositories can now manage the configuration of multiple packages in one single place. A package group allows you to define how packages are updated by internal developers or from upstream repositories. You can now allow or block internal developers to publish packages or allow or block upstream updates for a group of packages. Read my blog post for all the details. Return your Savings Plans – We have announced the ability to return Savings Plans within 7 days of purchase. Savings Plans is a flexible pricing model that can help you reduce your bill by up to 72 percent compared to On-Demand prices, in exchange for a one- or three-year hourly spend commitment. If you realize that the Savings Plan you recently purchased isn’t optimal for your needs, you can return it and if needed, repurchase another Savings Plan that better matches your needs. Amazon EC2 Mac Dedicated Hosts now provide visibility into supported macOS versions – You can now view the latest macOS versions supported on your EC2 Mac Dedicated Host, which enables you to proactively validate if your Dedicated Host can support instances with your preferred macOS versions. Amazon Corretto 22 is now generally available – Corretto 22, an OpenJDK feature release, introduces a range of new capabilities and enhancements for developers. New features like stream gatherers and unnamed variables help you write code that’s clearer and easier to maintain. Additionally, optimizations in garbage collection algorithms boost performance. Existing libraries for concurrency, class files, and foreign functions have also been updated, giving you a more powerful toolkit to build robust and efficient Java applications. Amazon DynamoDB now supports resource-based policies and AWS PrivateLink – With AWS PrivateLink, you can simplify private network connectivity between Amazon Virtual Private Cloud (Amazon VPC), Amazon DynamoDB, and your on-premises data centers using interface VPC endpoints and private IP addresses. On the other side, resource-based policies to help you simplify access control for your DynamoDB resources. With resource-based policies, you can specify the AWS Identity and Access Management (IAM) principals that have access to a resource and what actions they can perform on it. You can attach a resource-based policy to a DynamoDB table or a stream. Resource-based policies also simplify cross-account access control for sharing resources with IAM principals of different AWS accounts. For a full list of AWS announcements, be sure to keep an eye on the What's New at AWS page. Other AWS news Here are some additional news items, open source projects, and Twitch shows that you might find interesting: British Broadcasting Corporation (BBC) migrated 25PB of archives to Amazon S3 Glacier – The BBC Archives Technology and Services team needed a modern solution to centralize, digitize, and migrate its 100-year-old flagship archives. It began using Amazon Simple Storage Service (Amazon S3) Glacier Instant Retrieval, which is an archive storage class that delivers the lowest-cost storage for long-lived data that is rarely accessed and requires retrieval in milliseconds. I did the math, you need 2,788,555 DVD discs to store 25PB of data. Imagine a pile of DVDs reaching 41.8 kilometers (or 25.9 miles) tall! Read the full story. Build On Generative AI – Season 3 of your favorite weekly Twitch show about all things generative AI is in full swing! Streaming every Monday, 9:00 AM US PT, my colleagues Tiffany and Darko discuss different aspects of generative AI and invite guest speakers to demo their work. AWS open source news and updates – My colleague Ricardo writes this weekly open source newsletter in which he highlights new open source projects, tools, and demos from the AWS Community. Upcoming AWS events Check your calendars and sign up for these AWS events: AWS Summits – As I wrote in the introduction, it’s AWS Summit season again! The first one happens next week in Paris (April 3), followed by Amsterdam (April 9), Sydney (April 10–11), London (April 24), Berlin (May 15–16), and Seoul (May 16–17). AWS Summits are a series of free online and in-person events that bring the cloud computing community together to connect, collaborate, and learn about AWS. AWS re:Inforce – Join us for AWS re:Inforce (June 10–12) in Philadelphia, Pennsylvania. AWS re:Inforce is a learning conference focused on AWS security solutions, cloud security, compliance, and identity. Connect with the AWS teams that build the security tools and meet AWS customers to learn about their security journeys. You can browse all upcoming in-person and virtual events. That’s all for this week. Check back next Monday for another Weekly Roundup! -- seb This post is part of our Weekly Roundup series. Check back each week for a quick roundup of interesting news and announcements from AWS! View the full article

Amazon Relational Database Service (Amazon RDS) for MySQL zero-ETL integration with Amazon Redshift was announced in preview at AWS re:Invent 2023 for Amazon RDS for MySQL version 8.0.28 or higher. In this post, we provide step-by-step guidance on how to get started with near real-time operational analytics using this feature. This post is a continuation of the zero-ETL series that started with Getting started guide for near-real time operational analytics using Amazon Aurora zero-ETL integration with Amazon Redshift. Challenges Customers across industries today are looking to use data to their competitive advantage and increase revenue and customer engagement by implementing near real time analytics use cases like personalization strategies, fraud detection, inventory monitoring, and many more. There are two broad approaches to analyzing operational data for these use cases: Analyze the data in-place in the operational database (such as read replicas, federated query, and analytics accelerators) Move the data to a data store optimized for running use case-specific queries such as a data warehouse The zero-ETL integration is focused on simplifying the latter approach. The extract, transform, and load (ETL) process has been a common pattern for moving data from an operational database to an analytics data warehouse. ELT is where the extracted data is loaded as is into the target first and then transformed. ETL and ELT pipelines can be expensive to build and complex to manage. With multiple touchpoints, intermittent errors in ETL and ELT pipelines can lead to long delays, leaving data warehouse applications with stale or missing data, further leading to missed business opportunities. Alternatively, solutions that analyze data in-place may work great for accelerating queries on a single database, but such solutions aren’t able to aggregate data from multiple operational databases for customers that need to run unified analytics. Zero-ETL Unlike the traditional systems where data is siloed in one database and the user has to make a trade-off between unified analysis and performance, data engineers can now replicate data from multiple RDS for MySQL databases into a single Redshift data warehouse to derive holistic insights across many applications or partitions. Updates in transactional databases are automatically and continuously propagated to Amazon Redshift so data engineers have the most recent information in near real time. There is no infrastructure to manage and the integration can automatically scale up and down based on the data volume. At AWS, we have been making steady progress towards bringing our zero-ETL vision to life. The following sources are currently supported for zero-ETL integrations: Amazon Aurora MySQL-Compatible Edition (generally available) Amazon Aurora PostgreSQL-Compatible Edition (preview) Amazon RDS for MySQL (preview) Amazon DynamoDB (limited preview) When you create a zero-ETL integration for Amazon Redshift, you continue to pay for underlying source database and target Redshift database usage. Refer to Zero-ETL integration costs (Preview) for further details. With zero-ETL integration with Amazon Redshift, the integration replicates data from the source database into the target data warehouse. The data becomes available in Amazon Redshift within seconds, allowing you to use the analytics features of Amazon Redshift and capabilities like data sharing, workload optimization autonomics, concurrency scaling, machine learning, and many more. You can continue with your transaction processing on Amazon RDS or Amazon Aurora while simultaneously using Amazon Redshift for analytics workloads such as reporting and dashboards. The following diagram illustrates this architecture. Solution overview Let’s consider TICKIT, a fictional website where users buy and sell tickets online for sporting events, shows, and concerts. The transactional data from this website is loaded into an Amazon RDS for MySQL 8.0.28 (or higher version) database. The company’s business analysts want to generate metrics to identify ticket movement over time, success rates for sellers, and the best-selling events, venues, and seasons. They would like to get these metrics in near real time using a zero-ETL integration. The integration is set up between Amazon RDS for MySQL (source) and Amazon Redshift (destination). The transactional data from the source gets refreshed in near real time on the destination, which processes analytical queries. You can use either the serverless option or an encrypted RA3 cluster for Amazon Redshift. For this post, we use a provisioned RDS database and a Redshift provisioned data warehouse. The following diagram illustrates the high-level architecture. The following are the steps needed to set up zero-ETL integration. These steps can be done automatically by the zero-ETL wizard, but you will require a restart if the wizard changes the setting for Amazon RDS or Amazon Redshift. You could do these steps manually, if not already configured, and perform the restarts at your convenience. For the complete getting started guides, refer to Working with Amazon RDS zero-ETL integrations with Amazon Redshift (preview) and Working with zero-ETL integrations. Configure the RDS for MySQL source with a custom DB parameter group. Configure the Redshift cluster to enable case-sensitive identifiers. Configure the required permissions. Create the zero-ETL integration. Create a database from the integration in Amazon Redshift. Configure the RDS for MySQL source with a customized DB parameter group To create an RDS for MySQL database, complete the following steps: On the Amazon RDS console, create a DB parameter group called zero-etl-custom-pg. Zero-ETL integration works by using binary logs (binlogs) generated by MySQL database. To enable binlogs on Amazon RDS for MySQL, a specific set of parameters must be enabled. Set the following binlog cluster parameter settings: binlog_format = ROW binlog_row_image = FULL binlog_checksum = NONE In addition, make sure that the binlog_row_value_options parameter is not set to PARTIAL_JSON. By default, this parameter is not set. Choose Databases in the navigation pane, then choose Create database. For Engine Version, choose MySQL 8.0.28 (or higher). For Templates, select Production. For Availability and durability, select either Multi-AZ DB instance or Single DB instance (Multi-AZ DB clusters are not supported, as of this writing). For DB instance identifier, enter zero-etl-source-rms. Under Instance configuration, select Memory optimized classes and choose the instance db.r6g.large, which should be sufficient for TICKIT use case. Under Additional configuration, for DB cluster parameter group, choose the parameter group you created earlier (zero-etl-custom-pg). Choose Create database. In a couple of minutes, it should spin up an RDS for MySQL database as the source for zero-ETL integration. Configure the Redshift destination After you create your source DB cluster, you must create and configure a target data warehouse in Amazon Redshift. The data warehouse must meet the following requirements: Using an RA3 node type (ra3.16xlarge, ra3.4xlarge, or ra3.xlplus) or Amazon Redshift Serverless Encrypted (if using a provisioned cluster) For our use case, create a Redshift cluster by completing the following steps: On the Amazon Redshift console, choose Configurations and then choose Workload management. In the parameter group section, choose Create. Create a new parameter group named zero-etl-rms. Choose Edit parameters and change the value of enable_case_sensitive_identifier to True. Choose Save. You can also use the AWS Command Line Interface (AWS CLI) command update-workgroup for Redshift Serverless: aws redshift-serverless update-workgroup --workgroup-name <your-workgroup-name> --config-parameters parameterKey=enable_case_sensitive_identifier,parameterValue=true Choose Provisioned clusters dashboard. At the top of you console window, you will see a Try new Amazon Redshift features in preview banner. Choose Create preview cluster. For Preview track, chose preview_2023. For Node type, choose one of the supported node types (for this post, we use ra3.xlplus). Under Additional configurations, expand Database configurations. For Parameter groups, choose zero-etl-rms. For Encryption, select Use AWS Key Management Service. Choose Create cluster. The cluster should become Available in a few minutes. Navigate to the namespace zero-etl-target-rs-ns and choose the Resource policy tab. Choose Add authorized principals. Enter either the Amazon Resource Name (ARN) of the AWS user or role, or the AWS account ID (IAM principals) that are allowed to create integrations. An account ID is stored as an ARN with root user. In the Authorized integration sources section, choose Add authorized integration source to add the ARN of the RDS for MySQL DB instance that’s the data source for the zero-ETL integration. You can find this value by going to the Amazon RDS console and navigating to the Configuration tab of the zero-etl-source-rms DB instance. Your resource policy should resemble the following screenshot. Configure required permissions To create a zero-ETL integration, your user or role must have an attached identity-based policy with the appropriate AWS Identity and Access Management (IAM) permissions. An AWS account owner can configure required permissions for users or roles who may create zero-ETL integrations. The sample policy allows the associated principal to perform the following actions: Create zero-ETL integrations for the source RDS for MySQL DB instance. View and delete all zero-ETL integrations. Create inbound integrations into the target data warehouse. This permission is not required if the same account owns the Redshift data warehouse and this account is an authorized principal for that data warehouse. Also note that Amazon Redshift has a different ARN format for provisioned and serverless clusters: Provisioned – arn:aws:redshift:{region}:{account-id}:namespace:namespace-uuid Serverless – arn:aws:redshift-serverless:{region}:{account-id}:namespace/namespace-uuid Complete the following steps to configure the permissions: On the IAM console, choose Policies in the navigation pane. Choose Create policy. Create a new policy called rds-integrations using the following JSON (replace region and account-id with your actual values): { "Version": "2012-10-17", "Statement": [{ "Effect": "Allow", "Action": [ "rds:CreateIntegration" ], "Resource": [ "arn:aws:rds:{region}:{account-id}:db:source-instancename", "arn:aws:rds:{region}:{account-id}:integration:*" ] }, { "Effect": "Allow", "Action": [ "rds:DescribeIntegration" ], "Resource": ["*"] }, { "Effect": "Allow", "Action": [ "rds:DeleteIntegration" ], "Resource": [ "arn:aws:rds:{region}:{account-id}:integration:*" ] }, { "Effect": "Allow", "Action": [ "redshift:CreateInboundIntegration" ], "Resource": [ "arn:aws:redshift:{region}:{account-id}:cluster:namespace-uuid" ] }] } Attach the policy you created to your IAM user or role permissions. Create the zero-ETL integration To create the zero-ETL integration, complete the following steps: On the Amazon RDS console, choose Zero-ETL integrations in the navigation pane. Choose Create zero-ETL integration. For Integration identifier, enter a name, for example zero-etl-demo. For Source database, choose Browse RDS databases and choose the source cluster zero-etl-source-rms. Choose Next. Under Target, for Amazon Redshift data warehouse, choose Browse Redshift data warehouses and choose the Redshift data warehouse (zero-etl-target-rs). Choose Next. Add tags and encryption, if applicable. Choose Next. Verify the integration name, source, target, and other settings. Choose Create zero-ETL integration. You can choose the integration to view the details and monitor its progress. It took about 30 minutes for the status to change from Creating to Active. The time will vary depending on the size of your dataset in the source. Create a database from the integration in Amazon Redshift To create your database from the zero-ETL integration, complete the following steps: On the Amazon Redshift console, choose Clusters in the navigation pane. Open the zero-etl-target-rs cluster. Choose Query data to open the query editor v2. Connect to the Redshift data warehouse by choosing Save. Obtain the integration_id from the svv_integration system table: select integration_id from svv_integration; -- copy this result, use in the next sql Use the integration_id from the previous step to create a new database from the integration: CREATE DATABASE zetl_source FROM INTEGRATION '<result from above>'; The integration is now complete, and an entire snapshot of the source will reflect as is in the destination. Ongoing changes will be synced in near real time. Analyze the near real time transactional data Now we can run analytics on TICKIT’s operational data. Populate the source TICKIT data To populate the source data, complete the following steps: Copy the CSV input data files into a local directory. The following is an example command: aws s3 cp 's3://redshift-blogs/zero-etl-integration/data/tickit' . --recursive Connect to your RDS for MySQL cluster and create a database or schema for the TICKIT data model, verify that the tables in that schema have a primary key, and initiate the load process: mysql -h <rds_db_instance_endpoint> -u admin -p password --local-infile=1 Use the following CREATE TABLE commands. Load the data from local files using the LOAD DATA command. The following is an example. Note that the input CSV file is broken into several files. This command must be run for every file if you would like to load all data. For demo purposes, a partial data load should work as well. Analyze the source TICKIT data in the destination On the Amazon Redshift console, open the query editor v2 using the database you created as part of the integration setup. Use the following code to validate the seed or CDC activity: SELECT * FROM SYS_INTEGRATION_ACTIVITY ORDER BY last_commit_timestamp DESC; You can now apply your business logic for transformations directly on the data that has been replicated to the data warehouse. You can also use performance optimization techniques like creating a Redshift materialized view that joins the replicated tables and other local tables to improve query performance for your analytical queries. Monitoring You can query the following system views and tables in Amazon Redshift to get information about your zero-ETL integrations with Amazon Redshift: SVV_INTEGRATION – Provides configuration details for your integrations SYS_INTEGRATION_ACTIVITY– Provides information about completed integration runs SVV_INTEGRATION_TABLE_STATE – Describes the table-level integration information To view the integration-related metrics published to Amazon CloudWatch, open the Amazon Redshift console. Choose Zero-ETL integrations in the navigation pane and choose the integration to display activity metrics. Available metrics on the Amazon Redshift console are integration metrics and table statistics, with table statistics providing details of each table replicated from Amazon RDS for MySQL to Amazon Redshift. Integration metrics contain table replication success and failure counts and lag details. Manual resyncs The zero-ETL integration will automatically initiate a resync if a table sync state shows as failed or resync required. But in case the auto resync fails, you can initiate a resync at table-level granularity: ALTER DATABASE zetl_source INTEGRATION REFRESH TABLES tbl1, tbl2; A table can enter a failed state for multiple reasons: The primary key was removed from the table. In such cases, you need to re-add the primary key and perform the previously mentioned ALTER command. An invalid value is encountered during replication or a new column is added to the table with an unsupported data type. In such cases, you need to remove the column with the unsupported data type and perform the previously mentioned ALTER command. An internal error, in rare cases, can cause table failure. The ALTER command should fix it. Clean up When you delete a zero-ETL integration, your transactional data isn’t deleted from the source RDS or the target Redshift databases, but Amazon RDS doesn’t send any new changes to Amazon Redshift. To delete a zero-ETL integration, complete the following steps: On the Amazon RDS console, choose Zero-ETL integrations in the navigation pane. Select the zero-ETL integration that you want to delete and choose Delete. To confirm the deletion, choose Delete. Conclusion In this post, we showed you how to set up a zero-ETL integration from Amazon RDS for MySQL to Amazon Redshift. This minimizes the need to maintain complex data pipelines and enables near real time analytics on transactional and operational data. To learn more about Amazon RDS zero-ETL integration with Amazon Redshift, refer to Working with Amazon RDS zero-ETL integrations with Amazon Redshift (preview). About the Authors Milind Oke is a senior Redshift specialist solutions architect who has worked at Amazon Web Services for three years. He is an AWS-certified SA Associate, Security Specialty and Analytics Specialty certification holder, based out of Queens, New York. Aditya Samant is a relational database industry veteran with over 2 decades of experience working with commercial and open-source databases. He currently works at Amazon Web Services as a Principal Database Specialist Solutions Architect. In his role, he spends time working with customers designing scalable, secure and robust cloud native architectures. Aditya works closely with the service teams and collaborates on designing and delivery of the new features for Amazon’s managed databases. View the full article

Starting today, Amazon RDS Custom for SQL Server supports memory-optimized X2iedn instance types and EBS-optimized R5b instance types. Amazon RDS Custom for SQL Server is a managed database service that allows customization of the underlying operating system and includes the ability to bring your own licensed SQL Server media or use SQL Server Developer Edition. View the full article

Today, we are announcing that your MySQL 5.7 and PostgreSQL 11 database instances running on Amazon Aurora and Amazon Relational Database Service (Amazon RDS) will be automatically enrolled into Amazon RDS Extended Support starting on February 29, 2024. This will help avoid unplanned downtime and compatibility issues that can arise with automatically upgrading to a new major version. This provides you with more control over when you want to upgrade the major version of your database. This automatic enrollment may mean that you will experience higher charges when RDS Extended Support begins. You can avoid these charges by upgrading your database to a newer DB version before the start of RDS Extended Support. What is Amazon RDS Extended Support? In September 2023, we announced Amazon RDS Extended Support, which allows you to continue running your database on a major engine version past its RDS end of standard support date on Amazon Aurora or Amazon RDS at an additional cost. Until community end of life (EoL), the MySQL and PostgreSQL open source communities manage common vulnerabilities and exposures (CVE) identification, patch generation, and bug fixes for the respective engines. The communities release a new minor version every quarter containing these security patches and bug fixes until the database major version reaches community end of life. After the community end of life date, CVE patches or bug fixes are no longer available and the community considers those engines unsupported. For example, MySQL 5.7 and PostgreSQL 11 are no longer supported by the communities as of October and November 2023 respectively. We are grateful to the communities for their continued support of these major versions and a transparent process and timeline for transitioning to the newest major version. With RDS Extended Support, Amazon Aurora and RDS takes on engineering the critical CVE patches and bug fixes for up to three years beyond a major version’s community EoL. For those 3 years, Amazon Aurora and RDS will work to identify CVEs and bugs in the engine, generate patches and release them to you as quickly as possible. Under RDS Extended Support, we will continue to offer support, such that the open source community’s end of support for an engine’s major version does not leave your applications exposed to critical security vulnerabilities or unresolved bugs. You might wonder why we are charging for RDS Extended Support rather than providing it as part of the RDS service. It’s because the engineering work for maintaining security and functionality of community EoL engines requires AWS to invest developer resources for critical CVE patches and bug fixes. This is why RDS Extended Support is only charging customers who need the additional flexibility to stay on a version past community EoL. RDS Extended Support may be useful to help you meet your business requirements for your applications if you have particular dependencies on a specific MySQL or PostgreSQL major version, such as compatibility with certain plugins or custom features. If you are currently running on-premises database servers or self-managed Amazon Elastic Compute Cloud (Amazon EC2) instances, you can migrate to Amazon Aurora MySQL-Compatible Edition, Amazon Aurora PostgreSQL-Compatible Edition, Amazon RDS for MySQL, Amazon RDS for PostgreSQL beyond the community EoL date, and continue to use these versions these versions with RDS Extended Support while benefiting from a managed service. If you need to migrate many databases, you can also utilize RDS Extended Support to split your migration into phases, ensuring a smooth transition without overwhelming IT resources. In 2024, RDS Extended Support will be available for RDS for MySQL major versions 5.7 and higher, RDS for PostgreSQL major versions 11 and higher, Aurora MySQL-compatible version 2 and higher, and Aurora PostgreSQL-compatible version 11 and higher. For a list of all future supported versions, see Supported MySQL major versions on Amazon RDS and Amazon Aurora major versions in the AWS documentation. Community major version RDS/Aurora version Community end of life date End of RDS standard support date Start of RDS Extended Support pricing End of RDS Extended Support MySQL 5.7 RDS for MySQL 5.7 October 2023 February 29, 2024 March 1, 2024 February 28, 2027 Aurora MySQL 2 October 31, 2024 December 1, 2024 PostgreSQL 11 RDS for PostgreSQL 11 November 2023 March 31, 2024 April 1, 2024 March 31, 2027 Aurora PostgreSQL 11 February 29, 2024 RDS Extended Support is priced per vCPU per hour. Learn more about pricing details and timelines for RDS Extended Support at Amazon Aurora pricing, RDS for MySQL pricing, and RDS for PostgreSQL pricing. For more information, see the blog posts about Amazon RDS Extended Support for MySQL and PostgreSQL databases in the AWS Database Blog. Why are we automatically enrolling all databases to Amazon RDS Extended Support? We had originally informed you that RDS Extended Support would provide the opt-in APIs and console features in December 2023. In that announcement, we said that if you decided not to opt your database in to RDS Extended Support, it would automatically upgrade to a newer engine version starting on March 1, 2024. For example, you would be upgraded from Aurora MySQL 2 or RDS for MySQL 5.7 to Aurora MySQL 3 or RDS for MySQL 8.0 and from Aurora PostgreSQL 11 or RDS for PostgreSQL 11 to Aurora PostgreSQL 15 and RDS for PostgreSQL 15, respectively. However, we heard lots of feedback from customers that these automatic upgrades may cause their applications to experience breaking changes and other unpredictable behavior between major versions of community DB engines. For example, an unplanned major version upgrade could introduce compatibility issues or downtime if applications are not ready for MySQL 8.0 or PostgreSQL 15. Automatic enrollment in RDS Extended Support gives you additional time and more control to organize, plan, and test your database upgrades on your own timeline, providing you flexibility on when to transition to new major versions while continuing to receive critical security and bug fixes from AWS. If you’re worried about increased costs due to automatic enrollment in RDS Extended Support, you can avoid RDS Extended Support and associated charges by upgrading before the end of RDS standard support. How to upgrade your database to avoid RDS Extended Support charges Although RDS Extended Support helps you schedule your upgrade on your own timeline, sticking with older versions indefinitely means missing out on the best price-performance for your database workload and incurring additional costs from RDS Extended Support. MySQL 8.0 on Aurora MySQL, also known as Aurora MySQL 3, unlocks support for popular Aurora features, such as Global Database, Amazon RDS Proxy, Performance Insights, Parallel Query, and Serverless v2 deployments. Upgrading to RDS for MySQL 8.0 provides features including up to three times higher performance versus MySQL 5.7, such as Multi-AZ cluster deployments, Optimized Reads, Optimized Writes, and support for AWS Graviton2 and Graviton3-based instances. PostgreSQL 15 on Aurora PostgreSQL supports the Aurora I/O Optimized configuration, Aurora Serverless v2, Babelfish for Aurora PostgreSQL, pgvector extension, Trusted Language Extensions for PostgreSQL (TLE), and AWS Graviton3-based instances as well as community enhancements. Upgrading to RDS for PostgreSQL 15 provides features such as Multi-AZ DB cluster deployments, RDS Optimized Reads, HypoPG extension, pgvector extension, TLEs for PostgreSQL, and AWS Graviton3-based instances. Major version upgrades may make database changes that are not backward-compatible with existing applications. You should manually modify your database instance to upgrade to the major version. It is strongly recommended that you thoroughly test any major version upgrade on non-production instances before applying it to production to ensure compatibility with your applications. For more information about an in-place upgrade from MySQL 5.7 to 8.0, see the incompatibilities between the two versions, Aurora MySQL in-place major version upgrade, and RDS for MySQL upgrades in the AWS documentation. For the in-place upgrade from PostgreSQL 11 to 15, you can use the pg_upgrade method. To minimize downtime during upgrades, we recommend using Fully Managed Blue/Green Deployments in Amazon Aurora and Amazon RDS. With just a few steps, you can use Amazon RDS Blue/Green Deployments to create a separate, synchronized, fully managed staging environment that mirrors the production environment. This involves launching a parallel green environment with upper version replicas of your production databases lower version. After validating the green environment, you can shift traffic over to it. Then, the blue environment can be decommissioned. To learn more, see Blue/Green Deployments for Aurora MySQL and Aurora PostgreSQL or Blue/Green Deployments for RDS for MySQL and RDS for PostgreSQL in the AWS documentation. In most cases, Blue/Green Deployments are the best option to reduce downtime, except for limited cases in Amazon Aurora or Amazon RDS. For more information on performing a major version upgrade in each DB engine, see the following guides in the AWS documentation. Upgrading the MySQL DB engine for Amazon RDS Upgrading the PostgreSQL DB engine for Amazon RDS Upgrading the Amazon Aurora MySQL DB cluster Upgrading Amazon Aurora PostgreSQL DB clusters Now available Amazon RDS Extended Support is now available for all customers running Amazon Aurora and Amazon RDS instances using MySQL 5.7, PostgreSQL 11, and higher major versions in AWS Regions, including the AWS GovCloud (US) Regions beyond the end of the standard support date in 2024. You don’t need to opt in to RDS Extended Support, and you get the flexibility to upgrade your databases and continued support for up to 3 years. Learn more about RDS Extended Support in the Amazon Aurora User Guide and the Amazon RDS User Guide. For pricing details and timelines for RDS Extended Support, see Amazon Aurora pricing, RDS for MySQL pricing, and RDS for PostgreSQL pricing. Please send feedback to AWS re:Post for Amazon RDS and Amazon Aurora or through your usual AWS Support contacts. — Channy View the full article

Amazon Relational Database Service (Amazon RDS) for Oracle now supports the October 2023 Release Update (RU) for Oracle Database versions 19c and 21c. View the full article

Amazon Relational Database Service (Amazon RDS) for SQL Server now supports db.t3.micro instances in all commercial regions and the AWS GovCloud (US) Regions. This provides you with more options in addition to the db.t2.micro instance in the current AWS Free Tier for new AWS customers. View the full article

Starting today Amazon Relational Database Service (RDS) for Oracle supports publishing Oracle Management Agent (OMA) logs from your DB instances to Amazon CloudWatch Logs. View the full article