Category: Technical How-to

With an increased pace of innovation and demand for faster development and testing cycles, customers with mainframes want to adopt DevOps practices for their z/OS environments. To facilitate these practices, IBM offers the IBM Z Development and Test (ZD&T), a hardware emulation solution that allows regular z/OS software to run on the x86 platform by emulating the IBM Z instruction set, IO, and other devices. Learn how to create your own IBM ZD&T and z/OS environment on AWS.

MongoDB Atlas is the global cloud database service for modern applications, and in this post learn how to configure MongoDB Atlas to authenticate using AWS Single Sign-On (AWS SSO). Instead of having to sign in separately to MongoDB Atlas Control Plane, with this configuration enabled users can access the MongoDB Atlas user interface with their corporate credentials using AWS SSO. This delivers a better user experience without the need for managing separate sets of credentials.

Developing and maintaining an on-premises data lake is a complex undertaking. To maximize the value of data and use it as the basis for critical decisions, the data platform must be flexible and cost-effective. Learn how to build a hybrid data lake with Alluxio to leverage analytics and AI on AWS alongside a multi-petabyte on-premises data lake. Alluxio’s solution is called “zero-copy” hybrid cloud, indicating a cloud migration approach without first copying data to Amazon S3.

With Amazon Keyspaces, AWS has enabled SaaS providers to run their Apache Cassandra workloads using a fully managed, serverless offering. This option allows you to leverage the strengths of Cassandra while getting all of the scale, cost, reliability, and operational efficiency that comes with a managed model. Learn how Amazon Keyspaces can be used to store data in a multi-tenant architecture and review common models for partitioning each tenant’s data.

Virtusa recently received a requirement to make an application programming interface (API) accessible across another AWS account. The API was an internal-only API hosted in a private subnet, and could be accessed only from within the network. The requirement also stipulated Virtusa make only a few read-only (Get) methods accessible, and not all the methods from the API. Learn how Virtusa addressed the customer’s challenge by designing a solution that uses Amazon API Gateway with IAM authentication.

Many companies are using Amazon Redshift to analyze and transform their data. As data continues to grow and become even more important, they are looking for more ways to extract valuable insights. One use case we’re especially excited to support is that of data tokenization and masking. Amazon Redshift has collaborated with Protegrity, an AWS Advanced Technology Partner, to enable organizations with strict security requirements to protect their data while being able to obtain the powerful insights.

Baffle Data Protection Services (DPS) provides a data-centric protection layer allowing customers to tokenize, encrypt, and mask data in Amazon RDS at the column or row level, without any application code modifications while supporting a BYOK or HYOK model. Review the architecture for Baffle DPS, and walk through how to launch and test Baffle DPS from an AWS CloudFormation template with Amazon RDS databases to encrypt data at the column level.

As COVID-19 cases continue to surge, institutions are working tirelessly to ensure they are prepared. Contact tracing is a complex problem to solve, and CareBand’s SafeTrack is a solution. This post covers how to get started partnering with CareBand’s technology and building a solution using AWS that collects data from SafeTrack wearables and integrates that with AWS IoT. The solution will generate a report of all the individuals who have been exposed to a detected case of COVID-19.

Customers often need to rely on third-party solutions to extract and transform data from sources such as Slack and Zendesk. Some vendors, however, do not support all of the sources and rely on multiple products to perform ETL and persist data into Snowflake. This post details how Amazon AppFlow simplifies the data transfer process, and how customers can use AWS PrivateLink for transmitting data over AWS rather than via the public internet.

Organizations often need business analysts and citizen data scientists to work with data scientists to create machine learning (ML) models, but they struggle to provide a common ground for collaboration. Newly enriched Dataiku Data Science Studio (DSS) and Amazon SageMaker capabilities answer this need, empowering a broader set of users by leveraging the managed infrastructure of Amazon SageMaker and combining it with Dataiku’s visual interface to develop models at scale.