Tag: Amazon EventBridge

Large enterprise customers depend heavily on commercial off the shelf (COTS) products for scheduling jobs or running batch jobs, but these COTS products are often not cloud-native which prevents them from taking advantage of the various cloud services. Learn how Resolution Life US collaborated with Cognizant and AWS to modernize its on-premises third-party enterprise job scheduler with an event-driven custom scheduler solution using Amazon FSx, AWS Step Functions, Amazon EventBridge, and AWS Lambda.

Since the release of Amazon EC2 Mac instances, AWS customers have been able to access on-demand Apple Mac devices in the AWS Cloud. In collaboration with Jamf, an AWS Partner and leader in Apple device management, AWS has developed integration between the Amazon EC2 Mac instances and Jamf Pro to simplify managing, securing, and configuring EC2 Mac instances. Learn how to configure AWS and Jamf accounts to automatically enroll EC2 Mac into Jamf Pro EC2 Mac instances when they are launched.

SAP systems need a capable document management solution. Syntax, an SAP Gold Partner and AWS Premier Tier Services Partner, has focused on customer needs to develop a cloud-native, SAP-certified solution to meet data and document modernization requirements through its CxLink product portfolio. Explore the Syntax CxLink Documents solution and the process of how to handle a large number of documents from SAP applications and storing them directly on Amazon S3.

AdaptX clinical management software uses electronic medical records (EMRs) to derive insights—enabling providers and clinical leaders to efficiently leverage real-world data to transform patient care. This post explores how AdaptX built a modern data architecture using Amazon Athena, AWS Lambda, and AWS Step Functions to automate the extraction, transformation, and loading (ETL) of clinical data from provider EMR systems. Results included improved accuracy, scalability, and a better end-customer experience.

Both AWS and Deloitte understand that a customer’s cloud journey is different and have their own set of requirements. This is why Deloitte’s Cyber CMS solution provides a wide range of options for businesses to choose from to create the right package for them. Learn how Cyber CMS can help organizations become more trustworthy, resilient, and secure through proactive management of cyber risks.

Cisco Meraki customers commonly question how they can extend their SD-WAN environment into an existing Amazon Web Services (AWS) footprint. They desire high availability and a way to automate reachability from their cloud resources down to their local branches. This post explores how Cisco Meraki customers can use an AWS Quick Start to help automate the highly available deployment of Meraki vMXs in multiple AWS Regions along with route propagation.

Firms spend substantial efforts to identify and collect quality data streams from different sources. However, identifying and interpreting energy, water, or gas usage patterns and consumption types is sometimes insufficient. In this post, you’ll learn how Storm Reply, combining industry knowledge with its expertise in the development of data analytics platforms in AWS, can help customers in the design, development, and maintenance of secure serverless IoT big data platforms with a focus on sustainability.

As data grows at an exponential rate both in volume and velocity, it becomes important for organizations to carve out a strategy to store data in appropriate locations with the correct safeguards to address data access and privacy concerns. Learn how organizations can transform their data landscape into a more controlled, flexible, and secure landscape using LTI’s Canvas Scarlet Data Mesh framework built on AWS to meet the data challenges an organization faces today.

Learn now Provectus looked into how machine learning models were prototyped and evaluated at VTS, and then delivered a template-based solution enabling their data scientists to more easily create Amazon SageMaker jobs, pipelines, endpoints, and other AWS resources. The resulting coherent set of templates, with usage cookbook and extension guidelines, was applied successfully on an ML model that predicted leasing outcomes.

Organizations hosting customer-specific machine learning models on AWS have unique isolation and performance requirements and require a solution that provides a scalable, high-performance, and feature-rich ML platform. Learn how Amazon SageMaker Pipelines helps you to pre-process data, build, train, tune, and register ML models in SaaS applications. We’ll focus on best practices for building tenant-specific ML models with particular focus on tenant isolation and cost attribution.