Category: Expert (400)

As data becomes increasingly valuable, robust security measures are critical. This post reviews how Protegrity’s tokenization integration with Amazon Redshift Dynamic Data Masking enables organizations to effectively protect sensitive data. It provides an overview of key concepts like Protegrity Vaultless Tokenization and Redshift Dynamic Data Masking, including code examples to better safeguard sensitive information within their Redshift data warehouse both at rest and in use.

Amazon EC2 Mac instances provide Apple hardware to develop for iOS and macOS at scale. Dependencies for building apps require privileged access, normally needing manual user approval. By enrolling EC2 Macs into Mobile Device Management (MDM) with Jamf Pro, administrators can automate remote configuration and software deployment without per-instance interaction. After launching an instance and installing required profiles with Jamf, users should create an AMI to retain the instance state.

Leveraging AWS Lambda response streaming functionality enables progressive data delivery from large datasets, enhancing web application performance. This post compares a traditional API implementation to a Lambda streaming API, demonstrating reduced time-to-first-byte latency and quicker, more dynamic client-side rendering. By incrementally sending data, response streaming eliminates lag from waiting on entire dataset transfers, vastly improving user experience for data-intensive applications.

Generating high-quality synthetic data protects privacy and augments scarce real-world data for training machine learning models. This post shows how to integrate the Gretel synthetic data platform with Amazon SageMaker Pipelines for a full ML workflow. Gretel’s integration with SageMaker Pipelines in a hybrid or fully managed cloud environment enables responsible and robust adoption of AI while optimizing model accuracy. With Gretel, data scientists can overcome data scarcity without compromising individuals’ privacy.

Intelligent document processing (IDP) automates data extraction from diverse document formats, accelerating information retrieval. Manually labeling is expensive and difficult, and Cognizant’s IDP solution on AWS automates document labeling at scale to overcome this challenge. Its customized user interface in Amazon SageMaker Ground Truth lets subject matter experts efficiently label documents.

Verana Health leverages an exclusive real-world data network and AI-enhanced data engine to transform healthcare data into curated, disease-specific data modules called Qdata. This powers Verana’s analytics solutions for real-world evidence generation, clinical trials, quality reporting, and registry data management to enhance patient care and quality of life. Through AWS Data Exchange and Amazon Redshift, Verana offers life sciences customers easy, convenient access to high-quality clinical real-world data for research.

TensorIoT leverages AWS services and the Guidance for Carbon Accounting framework to build carbon accounting solutions. It provides a technical walkthrough for calculating a facility’s Scope 2 emissions using EPA data on building energy use and electricity emissions factors. The solution allows input of building details like type, area, and zip code to estimate or calculate emissions, and AWS services provide adaptability, transparency, efficiency, and security.

AWS customers can run Kubernetes on managed services like Amazon EKS or self-managed options. To secure these environments, Red Hat Advanced Cluster Security for Kubernetes (RHACS) detects vulnerabilities and policy violations. Its findings can be sent to AWS Security Hub which aggregates security issues across AWS services. This post walks through installing RHACS on Red Hat OpenShift Service on AWS, creating policies in RHACS, and integrating with Security Hub to view findings.

Industrial IoT adoption is increasing the connectivity of operational technology to IT systems, necessitating better visibility into assets. Claroty Edge on AWS Snowcone enables asset discovery to build an accurate inventory and identify vulnerabilities. Combined with Claroty xDome, this provides comprehensive IT/OT asset management and vulnerability insights. xDome integrates with AWS Security Hub to simplify deploying asset visibility and enable organizations to defend and secure their connected environments.

Darwinbox wanted to reduce the time to infer resumes against job descriptions using PyTorch models. AWS Premier Partner Minfy helped them leverage Amazon SageMaker and AWS Inferentia to compile models with Neuron SDK and deploy them, achieving 87% faster inference without retraining. Key steps were compiling models with the Neuron SDK, extending SageMaker containers, using Inference Recommender to optimize configurations, and sending requests in mini-batches.