Aurora PostgreSQL

Tech Optimizer
August 15, 2025
Wiz has transitioned its Amazon Aurora PostgreSQL database from version 14 to version 16 with near-zero downtime using Aurora Blue/Green Deployments. The upgrade process is facilitated by the DB Upgrade Pilot, which features an automated eight-step flow, including automated validation steps, enhanced synchronization monitoring, and end-to-end orchestration. This has reduced the downtime for database upgrades from one hour to 30 seconds.
Tech Optimizer
July 24, 2025
The Amazon Aurora PostgreSQL Limitless Database has launched in various regions, including the US West (Northern California), Africa (Cape Town), Asia Pacific (Hyderabad, Jakarta, Melbourne), Canada (Central and West), Europe (London, Milan, Paris, Spain, Zurich), Israel (Tel Aviv), Mexico (Central), the Middle East (Bahrain, UAE), and South America (Sao Paulo). It features a serverless endpoint that distributes data and queries across multiple Amazon Aurora Serverless instances, ensuring transactional consistency and enhancing performance. The database includes distributed query planning and transaction management, dynamically allocates compute resources based on workload fluctuations, and supports PostgreSQL versions 16.6 and 16.8. Users can create an Aurora PostgreSQL Limitless Database via the Amazon RDS console.
Tech Optimizer
July 9, 2025
Amazon Bedrock Knowledge Bases has introduced a fully managed Retrieval Augmented Generation (RAG) feature that connects large language models (LLMs) with internal data sources, enhancing the relevance and accuracy of responses by integrating contextual information from private datasets. During AWS re:Invent 2024, it was announced that this feature now supports natural language querying for structured data retrieval from Amazon Redshift and Amazon SageMaker Lakehouse, allowing generative AI applications to access both structured and unstructured data sources. The system converts user queries into SQL queries using natural language processing, enabling data retrieval without requiring users to know SQL syntax. Amazon Bedrock Knowledge Bases currently supports structured data retrieval from Amazon Redshift and SageMaker Lakehouse. Although direct support for Aurora PostgreSQL-Compatible is not available, users can utilize zero-ETL integration between Aurora PostgreSQL-Compatible and Amazon Redshift to make their data accessible. This integration replicates Aurora PostgreSQL tables to Amazon Redshift in near real-time, simplifying data management. To enable natural language querying of structured application data stored in Aurora, organizations can set up an Aurora PostgreSQL database, create a schema with interconnected tables (products, customers, and orders), and populate these tables with sample data while maintaining referential integrity. Subsequently, they can establish zero-ETL integration with Amazon Redshift, which involves creating a Redshift Serverless workgroup and mapping the database for synchronization. Once the zero-ETL integration is verified, organizations can create an Amazon Bedrock knowledge base for natural language querying. This requires granting appropriate permissions to the Amazon Bedrock Knowledge Bases AWS Identity and Access Management (IAM) role and ensuring the knowledge base is synchronized with Amazon Redshift. After setting up the knowledge base, users can execute natural language queries, which are translated into SQL and processed to generate human-readable responses. Examples of queries include counting unique customers and identifying customers who have purchased the most products. Finally, it is recommended to clean up resources after use to avoid ongoing charges.
Tech Optimizer
July 7, 2025
Atlassian has migrated its database infrastructure to Amazon Web Services’ Aurora, transferring four million Postgres databases that support Jira implementations. The migration involved approximately 3,000 PostgreSQL servers across 13 AWS regions. The move aims to reduce costs, enhance reliability, and improve performance, upgrading the service level agreement from 99.95% uptime on RDS to 99.99% on Aurora. Samsung has postponed the completion of its chip manufacturing plant in Texas due to difficulties in securing customers. Infosys has advised its employees against exceeding nine hours and 15 minutes of work daily to combat burnout. Qantas has acknowledged a cyberattack affecting six million customers and will provide details on the incident's impact. Xerox has acquired Lexmark from Ninestar Corporation for .5 billion. India and Australia are collaborating on a research initiative to improve tracking of submarines and underwater vehicles. JPMorgan Chase has requested to terminate its custom top-level domains, ".CHASE" and ".JPMORGAN." China’s National Space Administration has released images of Earth and the Moon taken by its Tianwen 2 probe.
Tech Optimizer
July 6, 2025
Amazon Aurora PostgreSQL-Compatible Edition now supports a maximum storage limit of 256 TiB, doubling the previous limit of 128 TiB. Customers are charged only for the storage they use, and to utilize the increased limit, users must upgrade their clusters to supported database versions. The new storage capacity is available across all AWS regions where Aurora PostgreSQL is offered.
Tech Optimizer
June 21, 2025
The Amazon Aurora PostgreSQL-Compatible Edition supports managed blue/green deployments to minimize downtime and risks during updates. This deployment strategy involves creating a staging environment (green) that mirrors the production database (blue) through logical replication. The blue environment represents the current production database, while the green environment incorporates updates without changing the application endpoint. After validating changes, the green environment can be promoted to production. In case of issues post-upgrade, a rollback plan is essential, as the managed blue/green deployment feature does not provide built-in rollback functionality. A manual rollback cluster can be established using self-managed logical replication to maintain synchronization with the new version after a switchover. Before the switchover, two clusters exist: the blue cluster (production) and the green cluster (staging). After the switchover, three clusters are present: the old blue cluster (original production), the new blue cluster (updated production), and the blue prime (rollback) cluster (a clone of the old blue cluster). To implement the solution, prerequisites include a cluster parameter group for the new version database with logical replication enabled and familiarity with the Aurora cloning feature. The process involves creating a blue/green deployment, stopping traffic on the blue cluster, performing the switchover, deleting the blue/green deployment, cloning the old blue cluster to create the blue prime cluster, and establishing logical replication from the new blue cluster to the blue prime cluster. Limitations of the managed blue/green deployment include the inability to replicate certain DDL operations and the need to handle endpoint changes manually if a rollback is required. Setting up the rollback cluster incurs additional downtime. To roll back to the blue prime cluster, application traffic must be ceased, the application or DNS records updated, the subscription on the blue prime cluster dropped, and sequence values manually updated if necessary. This process is not automatic and requires careful planning and testing. In production, it is advisable to retain the new blue prime cluster until all applications have transitioned successfully, and the old blue cluster can be backed up for compliance before deletion. For testing purposes, all clusters should be deleted to avoid additional charges.
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