Tag: Amazon Kinesis Data Firehose

As a SaaS provider, it’s essential to have a clear picture of how tenants are exercising your system. Being able to model the functional and operational profile of tenants and tenant tiers is critical to evolving the business and technical strategies of a SaaS organization. Learn about the role metrics play within a SaaS-based application, and dive deep into a solution that provides all of the infrastructure that will support the ingestion, aggregation, and analysis of SaaS metric data.

Scaling doctors’ expertise through artificial intelligence (AI) and machine learning (ML) provides an affordable and accurate solution, giving millions of infants equal access to eye screening. Learn how Pr3vent, a medical AI company founded by ophthalmologists, teamed up with AWS Machine Learning Competency Partner Provectus to develop an advanced disease screening solution powered by deep learning that detects pathology and signs of possible abnormalities in the retinas of newborns.

Itron Idea Labs has been leveraging IoT devices for decades and using technology in innovative ways, but they faced two major problems in developing solutions for public sector organizations: project delays, and large up-front costs. To overcome these challenges, Itron teamed up with TensorIoT and created a new route to integration in the form of the Itron Manhattan SDK, which gives IoT device manufacturers the ability to integrate their devices into the Itron Idea Labs Cloud and AWS.

It can be complicated to maintain a robust, scalable, and reliable monitoring system that inputs terabytes of data under heavy traffic. Learn how Thundra has delivered 99.9 percent availability to customers since incorporating AWS services into its product. Thundra’s platform can handle scalability and availability challenges, recover both from partial failures and major outages, and support point-in-time recovery in case of disaster.

Customers are always looking for new ways to improve operational efficiency and the security posture of applications running in their virtual private clouds (VPCs). Amazon Route 53 recently launched a Resolver Query Logs capability which lets customers log the DNS queries originating in their Amazon VPC. Follow along with our step-by-step instructions for logging VPC DNS queries in Amazon Route 53, ingesting them into Splunk, and then analyzing them with Splunk.

AWS introduced Amazon EventBridge partner event source integrations to showcase reference architectures and end-to-end use cases that help you get started quickly with integrating SaaS partners in your own applications. Fully open source, these solutions include code and AWS Serverless Application Model (SAM) templates that can be customized and extended to fit your application’s needs. The reference architectures include AWS Quick Starts and GitHub code to ease integration.

Work is becoming more complex, collaborative, and fast-paced in the time of COVID-19. With the role of crisis communications increasing in visibility, the capability of SaaS applications to facilitate actionable communications is paramount. Whispir’s integration of Amazon EventBridge means the Whispir platform can power communication workflows between your apps, systems, and databases without the need to write any connection code.

Fragmented supply-chain management systems can impair an enterprise’s ability to make informed, timely decisions. Accenture’s Intelligent Revenue and Supply Chain (IRAS) platform integrates insights generated by machine learning models into an enterprise’s technical and business ecosystems. This post explains how Accenture’s IRAS solution is architected, how it can coexist with other ML forecasting models or statistical packages, and how you can consume its insights in an integrated way.

Explore several common AWS services and architectural patterns used by SaaS vendors to interact with their customers’ cloud accounts. Examples of SaaS products requiring some level of account interaction often fall into the categories of logging and monitoring, security, compliance, data analytics, DevOps, workflow management, and resource optimization. SaaS products, such as the ones in these categories, regularly interact with resources in the subscribing customer’s AWS account.

In spite of the rich set of machine learning tools AWS provides, coordinating and monitoring workflows across an ML pipeline remains a complex task. Control-M by BMC Software that simplifies complex application, data, and file transfer workflows, whether on-premises, on the AWS Cloud, or across a hybrid cloud model. Walk through the architecture of a predictive maintenance system we developed to simplify the complex orchestration steps in a machine learning pipeline used to reduce downtime and costs for a trucking company.