Tag: AWS Marketplace

What does it take to build and run a successful SaaS business on AWS? This is a question the AWS SaaS Factory team gets often during our conversations with AWS Partners and customers who are moving to SaaS. While there is no single formula, we have been observing some common patterns and strategies that help organizations maximize SaaS success. In a recent webinar series, AWS SaaS Factory demystified some of the common patterns and strategies with AWS Partners Druva, NetWise, Stripe, Crowdstike, and Snowflake.

Financial services customers face new industry regulations that require additional compute capacity up to 10 times to meet their regulatory demands. Learn about new service integrations and functionality that make TIBCO DataSynapse GridServer on AWS a great match to run grid computing workloads. These integrations help customers scale their grid workloads to take advantage of the compute elasticity and flexibility of AWS and GridServer without up-front capital expenditure.

A serverless architecture strategy reduces complexity and provides more flexibility in adopting the features and non-functional requirements needed to support market agility. In this post, walk through an example of an IoT use case and build a serverless scalable platform using Amazon Kinesis Data Firehose, Amazon Managed Service for Apache Flink, and MongoDB Realm. You’ll learn how easy it is to develop mobile and desktop applications on top of the data platform for different personas.

As a multi-cloud network security platform, Valtix enables teams to meet the most stringent security requirements in a cloud-first and simple way. Learn about the transformation of network security use case leveraging Valtix for segmentation of workloads and to help meet compliance requirements. We’ll also walk through an example of how to enforce consistent security across tens and hundreds of VPCs spanning multiple regions and AWS accounts.

With the proliferation of different, constantly changing applications, it’s become a challenge to innovate quickly while having a strategy in place to prevent ballooning storage costs. Legacy archival and analytic tools often restrict developers and diminish the benefits of NoSQL’s handling of modern, rich data sources. Learn how MongoDB is committed to making it easier for customers to scale and transform their data management solutions to make developers’ lives easier.

Dataiku orchestrates the entire machine learning lifecycle and makes it accessible to data scientists and analysts alike. With deep integration with AWS AI tools, Dataiku enables users to augment their analytics workflow with pretrained NLP and computer vision models. Learn how you can use Amazon Comprehend and Amazon Rekognition plugins on Dataiku Data Science Studio (DSS) to build a simple workflow of NLP and computer vision use cases, respectively.

To reap the benefits of cloud computing, organizations cannot simply take their existing applications and architectures in their legacy on-premises environment and move them as-is to the cloud. True cloud modernization with MongoDB Atlas on AWS enables you to move data and simultaneously apply the latest innovations in development methodologies, architectural patterns, and technologies to refresh your portfolio of existing applications.

By avoiding inspections, insurers lose the opportunity to adequately consider all factors during underwriting and take on more risk. TCS has built a virtual inspection solution on AWS that is customizable to various inspection use cases, such as home insurance inspections and claims, auto claims damage assessment and estimation, and mortgage inspection. This post provides an overview of the TCS virtual inspection solution, describes the high-level architecture, and explores the potential business benefits for insurers.

Security is the highest priority for AWS, which works closely with industry-leading partners such as CloudHealth by VMware to build security solutions for customers like CloudHealth Secure State (CHSS). Learn how you can set up CHSS projects, suppress rules and alerts, find misconfigurations through CHSS Explore, and set up remediation jobs all built on CloudHealth’s unified security monitoring approach for AWS.

Operationalizing machine learning models can be a challenge due to lack of established ML architecture and its integration with the existing landscape. DataRobot integrates with AWS and provides the flexibility for a model trained in DataRobot to be deployed on AWS services with centralized model governance, management, and monitoring. Learn how the DataRobot AutoML platform orchestrates the complete model development and training lifecycle.