Category: Advanced (300)

Business intelligence (BI) teams aim to automate Amazon QuickSight asset deployment across environments. CyberCX developed a solution using AWS Step Functions to orchestrate exporting QuickSight analyses from one environment and importing them to another, simplifying migration. This reusable module integrates with CyberCX’s broader serverless data platform but can standalone. The entire solution is designed with security in mind and follows the principles of least privilege access.

TextRay is an information extraction solution that automatically extracts data from scanned documents using deep learning models. It leverages AWS services to provide a scalable and cost-effective way to process documents while reducing errors and turnaround time. An AWS CloudFormation template simplifies deployment, while a pre-trained base model demonstrates TextRay’s precision in extracting tabular and form data into structured CSV outputs.

The Amazon Athena Teradata Connector enables Athena to query data in Teradata Vantage using SQL, and comprises two AWS Lambda functions for metadata and record reading. This post describes deploying the connector, creating a Lambda layer for the Teradata JDBC driver, and running queries on Teradata from Athena, including a federated query joining Teradata and S3 data. This provides a scalable, serverless way to analyze data across different data stores without data duplication.

Using the AWS console to manage cloud infrastructure can be convenient and user-friendly, especially for beginners or small projects. Yet, it also carries inherent challenges when used at scale. In this post, we will dive deep into how ControlMonkey can assist you with transitioning manually-created environments to an Infrastructure as Code approach, integrating seamlessly with GitOps and Hashicorp Terraform.

Learn how to connect the ThoughtSpot analytics platform to an Amazon Aurora MySQL database for real-time operational analytics. This post outlines the steps to create an Aurora MySQL instance, populate it with sample data, create a connection from ThoughtSpot, and build generative AI-powered analytics using natural language search. By integrating ThoughtSpot and Aurora MySQL, businesses can get instant insights from their transactional database.

Containers are a leading method for packaging applications, with Kubernetes emerging as the top orchestration solution. You can enable secure and efficient self-service cluster provisioning on Amazon EKS using open-source tools like AWS Controllers for Kubernetes (ACK), Kyverno, and ArgoCD. This post demonstrates how enterprises can leverage these tools along with Nirmata’s Policy Manager to streamline EKS cluster management, apply security policies, and ensure compliance in a Kubernetes environment.

Cornerstone Consulting Group developed a plugin to simplify migrating on-premises or Amazon EC2 self-managed Apache Kafka clusters to Amazon MSK. The plugin automates MirrorMaker 2 replication, scales connectors, and integrates monitoring and notifications. It supports requirements like zero data loss, minimal code changes, auto-scaling, and performance/security parity. The plugin eases complex setup steps, working seamlessly for a smooth cutover to Amazon MSK after replication completes.

Amazon Athena allows analyzing petabytes of data directly with SQL queries or via analytics tools like ThoughtSpot. This post covers creating an IAM access key, two Amazon S3 buckets (one for data storage, one for query results), creating an Amazon Athena table from sample data using an AWS Glue crawler, and establishing a connection between Athena and ThoughtSpot. With the connection, ThoughtSpot can search and visualize the Athena data using AI capabilities.

AWS HealthImaging is a new HIPAA-eligible service for storing, analyzing, and sharing medical imaging data securely in the cloud. CitiusTech developed a solution leveraging AWS services like HealthImaging to automate ingesting DICOM data. It scans for malware, validates DICOM files, copies clean images to HealthImaging for storage, and notifies users. Healthcare providers can easily migrate imaging workloads to realize improved accessibility and cost-efficiency.

The Synopsys.ai electronic design automation (EDA) suite on AWS harnesses AI to optimize chip design. A key component is Synopsys DSO.ai, using reinforcement learning to enhance power, performance, and area. Benefits include faster optimization, better engineer productivity, design reuse, and faster process node migration. Deploying on AWS ParallelCluster provides auto-scaling, elasticity, and fast setup for massive EDA workloads. Testing showed 20% lower power, timing closure improvements, and significant cost savings.