customer Archives

Tech Optimizer

February 22, 2025

How Mindbody improved query latency and optimized costs using Amazon Aurora PostgreSQL Optimized Reads

Mindbody utilizes a cloud-based platform for the fitness and wellness industry, offering services such as client booking, scheduling, payments, marketing, and analytics. Their email marketing platform is built on an Aurora PostgreSQL cluster, currently at version 13.8, with a size of approximately 17 TB and a workload distribution of 80% reads and 20% writes. Mindbody faced scaling and performance challenges due to architectural limitations and increasing data demands, leading to all workloads being directed to the writer node. The average BufferCacheHitRatio was below 80%, indicating frequent disk access rather than cache hits, contributing to higher query latencies and I/O costs. To address these issues, Mindbody adopted Aurora Optimized Reads, which enhances caching capacity and improves latency and throughput for I/O-intensive workloads. Transitioning required upgrading the database cluster to version 14.9 or higher, and extensive testing was conducted in a proof-of-concept environment. The upgrade process involved a blue/green deployment strategy to minimize production disruption. After implementing Aurora Optimized Reads, Mindbody experienced significant performance improvements, including a 50% reduction in average daily CPU utilization and a 90% reduction in ReadIOPS. The AuroraOptimizedReadsCacheHitRatio indicated that 85% of read requests were served from the optimized cache. Cost analysis revealed a 23% reduction in monthly Aurora costs post-transition, with potential for further savings by downsizing instances.

Tech Optimizer

February 21, 2025

Self-managed multi-tenant vector search with Amazon Aurora PostgreSQL

Organizations are using generative AI and machine learning tools to extract value from unstructured data, employing specialized machine learning models to convert data into vectors for efficient searching and retrieval. Amazon Aurora PostgreSQL-Compatible Edition, with the pgvector extension, allows developers to create a vector store for generative AI applications. Multi-tenant architectures in software-as-a-service (SaaS) applications ensure tenant data isolation to maintain security and privacy. In a multi-tenant scenario, home survey requests are processed, and survey reports are stored in Amazon S3. Embedding models convert these documents into vector embeddings, which are stored in a vector store. There are two approaches to building a vector-based application: a self-managed approach, where developers handle data processing and queries, and a fully-managed option using Amazon Bedrock Knowledge Bases. The self-managed approach involves coding to process data, generate vector embeddings, and store them in Aurora. The architecture includes data ingestion via AWS Lambda, embedding conversion, SQL queries for data retrieval, and response enhancement using a large language model (LLM). Key terminologies include vector embeddings, embedding models, chunking, pgvector, HNSW index, and IVFFlat index. The process of creating a vector store involves configuring the Aurora PostgreSQL database, enabling the pgvector extension, and establishing a schema for the vector store. The vector table includes fields for UUID, vector embeddings, text chunks, metadata, and tenant identification. Data ingestion requires coding to convert data into embeddings and insert them into the database. Retrieval of vector data is crucial for enhancing prompts sent to LLMs, with various distance functions supported for identifying similar vectors. Multi-tenancy is enforced using row-level security in PostgreSQL, ensuring tenant data isolation. The process includes updating query functions to support tenant isolation and setting the current tenant ID for queries.

Winsage

February 21, 2025

Unblockable ads now litter Microsoft’s Windows Surface app

Microsoft's Surface app has transformed into a marketplace filled with advertisements, overshadowing its original purpose of device management. Users encounter promotional offers, including a 30% discount on an Xbox controller, prominently displayed at the bottom of the interface. Ads are integrated into the app, raising concerns about user consent, and persist even with ad blockers in Microsoft Edge. The app now resembles a shopping platform, which may dishearten users who expected a streamlined experience. This shift reflects a broader trend in Microsoft's ecosystem of frequent marketing pushes across platforms, potentially affecting customer satisfaction and loyalty.

Tech Optimizer

February 21, 2025

Multi-tenant vector search with Amazon Aurora PostgreSQL and Amazon Bedrock Knowledge Bases

The article discusses the implementation of a multi-tenant vector store using Amazon Aurora PostgreSQL-Compatible Edition and Amazon Bedrock Knowledge Bases. It outlines a scenario where users request home surveys, and surveyors update findings stored in an Amazon S3 bucket. The process involves converting documents into vector embeddings for enhanced natural language queries through the Retrieval Augmented Generation (RAG) technique. Key steps include: 1. Ingesting data from S3 into Amazon Bedrock Knowledge Bases. 2. Using an embeddings model to convert documents into vector embeddings. 3. Storing vector embeddings, data chunks, and metadata in Aurora with pgvector. 4. Submitting natural language queries that are transformed into embeddings for retrieval from the vector store. 5. Forwarding relevant documents to a large language model for response generation. To set up the vector store, prerequisites include access to an Amazon Aurora PostgreSQL-compatible database, Amazon S3 for document storage, and Amazon Bedrock for managing knowledge bases. The article provides SQL commands for creating the necessary schema, vector table, and index in Aurora, as well as instructions for ingesting data and ensuring multi-tenant data isolation through metadata filtering. Best practices for deploying a multi-tenant vector store include optimizing chunk size, evaluating embedding models, and monitoring query performance. The article emphasizes the benefits of fully managed solutions to reduce operational complexity.

AppWizard

February 21, 2025

Amazon to Discontinue Amazon Coins and Amazon Appstore on Android

Amazon will cease the availability of Amazon Coins on February 20, 2025, and the Amazon Appstore on Android devices will be discontinued on August 20, 2025. Customers must use any remaining Amazon Coins by that date, as unspent balances will be refunded afterward. The Appstore will still be available on Fire TV and Fire Tablet devices. Additionally, the Appstore will not be downloadable from the Microsoft store on Windows 11 devices starting March 6, 2024. Amazon Web Services will stop accepting new customers for Amazon Chime on February 19, 2025, with full support until February 20, 2026. The social commerce feature, Inspire, integrated into the Amazon shopping app in 2022, will also be discontinued.

AppWizard

February 20, 2025

Amazon Appstore will no longer be available on Android

Amazon will discontinue its Appstore for Android devices effective August 20, 2025, and will also terminate its Coins digital currency program. Users will lose access to the Appstore on Android devices, but any coins held in accounts by that date will be eligible for a refund. The Appstore will continue to operate on Amazon's proprietary devices, including Fire TV and Fire Tablets. Additionally, Amazon will end support for its app store on Windows, which had allowed Android applications since March 5, 2025.

AppWizard

February 20, 2025

Amazon to retire its Android app store

Amazon will close its app store for Android devices on August 20, 2025, and will also discontinue the Amazon Coins program on the same date. Users will no longer be able to download or use apps from the Amazon Appstore on Android devices after this date, but the app store will continue to operate on Amazon's Fire TV and Fire Tablet products. Unredeemed Amazon Coins will be refunded before the shutdown. The decision is aimed at focusing efforts on the Appstore experience on Amazon devices, where most customer engagement occurs.

AppWizard

February 20, 2025

Amazon will suspend support for its Appstore on Android

Amazon will close its Appstore for Android devices effective August 20. New app submissions will not be accepted, but developers can update existing apps until the deadline. The Appstore, operational in 200 countries, primarily serves Amazon devices. After the closure, previously downloaded apps may not function on Android devices. Amazon will also discontinue its virtual currency, Amazon Coins, with refunds for unused coins after the deadline. The Appstore will continue to operate on Amazon's proprietary devices, such as Fire TV and Fire Tablet.

Winsage

February 20, 2025

Can’t quit Windows 10? You can pay Microsoft for updates after October, or try these alternatives

An ESU subscription allows customers to receive updates automatically through Windows Update, with updates also available for individual download via the Microsoft Update Catalog. Customers can set reminders to check for updates after their release, typically on the second Tuesday of each month. For a more streamlined approach, the third-party service 0patch offers critical security patches for Windows 10 for at least five years after the end-of-support date, costing between and per PC annually. 0patch provides "micropatches" for vulnerabilities discovered after October 14, 2025, which are small and applied to running processes without altering Microsoft's original files. Unauthorized alternatives, like PowerShell activation scripts from the Massgrave hacking collective, allow users to bypass Microsoft's licensing agreements for a free three-year ESU subscription, but using these scripts is illegal and poses significant risks to businesses.

AppWizard

February 20, 2025

Amazon remembers it has an Android app store, kills it

Google may be required to allow third-party app stores access to the Google Play app catalog following a legal setback. This change could benefit companies like Epic Games and Microsoft. Amazon, despite potentially benefiting from this shift, has decided to discontinue phone support for its Appstore due to low user engagement. Amazon's Fire devices, which run on a customized version of Android called Fire OS, will continue to support the Appstore, although the company does not explicitly acknowledge the Android connection. Amazon's statement suggests that its apps may not operate on Android devices after the Appstore's shutdown, potentially excluding Fire tablets and Fire TVs from this definition. Developers who have optimized their apps for the Amazon store may be negatively affected by the transition, but the financial impact is expected to be minimal due to low user engagement.