Category: Application Services

Organizations have a requirement to implement data governance due to the presence of personally identifiable information. The process of sharing and operationalizing data movement becomes an involved task, as it must encompass data governance, data security, and include audit capabilities. Learn about a modern process LTIMindtree has introduced for data transfer using AWS Step Functions and for sharing transformed data to another account regardless of regional location.

The modern API lifecycle does not end once your CI/CD pipeline pushes a deployment to production and the API becomes available to clients. They still have to access documentation, try out different parts of the API, or get notifications about changes. API developer portals have become standard for businesses offering APIs to their partners and end users. Learn how to integrate ReadMe.com with Amazon API Gateway to make sure your documentation is up to date and gets changed every time you change the API.

Most applications require a form of identity service to manage, authenticate, and authorize users. In SaaS applications, multi-tenancy adds specific challenges to this task. To meet these needs, SaaS builders must consider integrating with an identity service provider. AWS services such as Amazon Cognito or AWS Partner services like Auth0 provide deep expertise in the field and allow you to focus on your SaaS application’s value proposition while relying on a secure, feature-rich identity provider.

Multi-region architectures improve latency for applications with global user bases and optimize RTO across the broadest set of potential failure events. However, creating and maintaining these architectures can add significant cost and complexity. Learn how to build and deploy a multi-region serverless application while minimizing cost and complexity using AWS Step Functions and Fauna, an AWS Partner and distributed document-relational database delivered as a cloud API.

Every SaaS architecture must introduce mechanisms and policies that prevent noisy neighbor conditions. Getting these policies right is essential to building a robust SaaS solution that delivers a consistent experience to customers. This post looks at the different strategies that can be used to introduce the throttles (transaction rate) and quotas (transaction volume) that manage each tenant’s activity, exploring the various AWS services that can be used to bring these concepts to life.

Explore a solution Contino built for a client to automate security scanning on software packages. This allowed developers to continue building, without added friction, and helped security teams be confident that vulnerabilities are discovered early and didn’t make their way to production. Learn about the context Contino was working with and the approach it took, and the technical challenges faced. After reading this post, you’ll understand how to develop a similar solution for your organization and some pitfalls to avoid.

There is a growing need for automotive dealers to adopt innovative technology to transition into the digital era smoothly, as customers are leaning towards secure, cloud-native solutions with modern features that are backed by superior support. Learn how Tech Mahindra transformed a monolithic application into a resilient and reliable solution to support expanding dealer networks. To build this cloud-native transformation approach, Tech Mahindra used AWS and a microservices-based API-first architecture.

The Pega Digital Messaging Service allows customer service applications to receive and send messages in a simplified, consistent format over digital channels such as Apple Messages for Business, Facebook, SMS, WhatsApp, Twitter, and web chat. This post explores how Pegasystems built a solution to enable the Pega Digital Messaging service to manage inbound multi-tenant WebSocket connection and message rates using Amazon API Gateway, AWS Lambda, SQS, and Amazon DynamoDB.

Learn about a multi-regional first-line of support solution Chaos Gears put together using a serverless application running AWS Lambda under the baton of AWS Step Functions to relieve a customer’s engineers from some of their operational burdens. The approach described in this post can be adapted to serve other needs or cover different cases, as AWS Step Functions’ visual workflows allow for a quick translation of business requirements to technical ones.

As multi-tenant SaaS providers look to leverage machine learning services, they must consider how they’ll protect the data that flows in and out of these services from different tenants. Learn how tenant isolation of machine learning services can be achieved using AWS IAM, and how the integration between IAM, Amazon SageMaker, and many other AWS services provide developers with a rich set of mechanisms that can be applied to realize tenant isolation goals.