Category: Technical How-to

Sisense Fusion Embed and Amazon Redshift Serverless provide customers with an integrated and seamless AI-powered data analytics experiences combined with predictive intelligence, natural language querying, and more. Together, these solutions enable data-driven decisions and deliver business insights at the point of decision making. Explore the benefits and synergy of these two powerful data solutions and how they can help organizations turn data into actionable insights.

Precisely’s geo addressing solution is coupled with data enrichment to enable organizations to accelerate the use of address data and quickly associate rich, relevant contextual information to power faster and more confident decision-making. The Precisely Geo Addressing SDK allows organizations to develop and deploy geocoding desktop, mobile, or web applications capable of delivering location information for over 250 countries and territories.

Kubernetes provides several autoscaling features that enable organizations to dynamically adjust their application resources in response to varying demands, but optimizing Kubernetes costs can be challenging. Learn how optimization tools like Karpenter and StormForge Optimize Live help organizations automate resource allocation, optimize performance, and reduce costs, thus making the process of cost optimization more accessible and efficient for anyone.

Gremlin is an AWS Partner that gives users a solution for safely and securely improving the reliability of their technology stack. Teams can use Gremlin to find hidden reliability risks, standardize reliability testing and measurement, and simulate real-world outages with an ever-growing library of tests. Learn how to test and measure the reliability of AWS systems using Gremlin Reliability Management and Amazon CloudWatch.

Maintaining multiple machine learning models across different teams can be challenging. Having a centralized platform to monitor and manage them can significantly reduce operational overhead and improve efficiency. Learn how the models trained and deployed in Amazon SageMaker can be monitored by DataRobot in a highly scalable fashion. In this way, customers can monitor both DataRobot-originated models and SageMaker-originated models under a single pane of glass.

Customers want an easier way to gather operational insights across their environments, including monitoring who has made changes to resources and when. Tata Consulting Services (TCS) developed a cloud management and orchestration platform called TCS Cloud Exponence that provides resource maintenance, patching, perimeter monitoring, vulnerability protection, observability, and compliance auditing. TCS leveraged AWS CloudTrail Lake to support the monitoring and compliance auditing capabilities.

Modern enterprise customers use AWS Marketplace datasets along with their business and operational data to create meaningful and deeper insights to improve their customer experience. Learn how to consume datasets from AWS Data Exchange to transform and store data in Databricks Lakehouse Platform using Delta Live Tables (DLT) and visualize it in Amazon QuickSight. DLT is a framework for building reliable, maintainable, and testable data processing pipelines.

With the advent of high-speed 5G networks, enterprises have sought to deliver low-latency experiences across industrial Internet of Things IoT (IIoT), media and entertainment, automotive, and beyond. At the core of these low latency experiences is data. This post builds on an earlier demonstration of MongoDB Realm on AWS Wavelength by amplifying the existing architecture with new features, and shows how to use the AWS Load Balancer Controller to deploy an Application Load Balancer in front of the database.

Managing and securing account access can feel like navigating a complex landmine of risk. Learn how to take a risk score calculated by Transmit Security and use it as an input to an authorization decision made by Amazon Verified Permissions, which delivers a pre-built system that simplifies policy-based access control and is flexible enough to address the most advanced authorization requirements for custom applications. With granular policies, it’s highly effective for determining who has access to what.

SaaS applications and services secure access to their resources by adding logic to make decisions when handling a user request. These decisions can be based on user roles and attributes, request context, and more. In this post, learn how CyberArk Identity works seamlessly as the identity provider with Amazon Verified Permissions. A managed authorization service, Amazon Verified Permissions provides a scalable, fine-grained permissions management and authorization service for custom apps.