Category: AWS Step Functions

Business intelligence (BI) teams aim to automate Amazon QuickSight asset deployment across environments. CyberCX developed a solution using AWS Step Functions to orchestrate exporting QuickSight analyses from one environment and importing them to another, simplifying migration. This reusable module integrates with CyberCX’s broader serverless data platform but can standalone. The entire solution is designed with security in mind and follows the principles of least privilege access.

CyberCX built an AWS serverless data lake and data masking solution to enable using production data securely in non-production environments. The modular, AWS-native solution combines AWS services to mask sensitive data in near real-time while retaining data utility. This allows thorough testing and confidence before deployment to production, improving data security and accelerating time to market.

Geospatial ETL pipelines prepare data for business analysis and insights, enabling leaders to make informed decisions. Learn how to migrate a geospatial pipeline to AWS Step Functions and AWS Batch to simplify pipeline management while improving performance and costs. Migrating to AWS Batch and AWS Step Functions has transformed the way WSP Digital handles data processing and orchestration, enabling streamlined and automated workflows.

Advanced Care Cloud is a SaaS solution running on AWS that provides care organizations of different sizes with the power to effectively manage their entire business from anywhere, at any time. Learn how Advanced used AWS Step Functions to orchestrate the solution’s onboarding process and data migration activities. We’ll also discuss the benefits Advanced achieved by leveraging Step Functions rather than building custom orchestration capability.

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.

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.

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.

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.

Moving data between multiple data stores requires an extract, transform, load (ETL) process using various data analysis approaches. ETL operations form the backbone of any modern enterprise data and analytics platform. AWS provides a broad range of services to deploy enterprise-grade applications in the cloud. This post explores a strategic collaboration between Tech Mahindra and a customer to build and deploy an enterprise data repository on AWS and create ETL workflows using a serverless architecture.

Many enterprises have .NET Framework legacy applications they need modernize and convert to cloud-native. One of the largest product feed automation and optimization platforms, GoDataFeed has a back-end platform that ingests millions of items of catalog data from multiple sources. Learn how Kloia addressed GoDataFeed’s challenges by transforming their legacy .NET Framework monolithic application into a .NET Core-based decoupled architecture.