August 2020 Summaries

In this webinar, Brian Mortimore from DataStax discussed the process of migrating enterprise applications from relational databases to Apache Cassandra using CDC (Change Data Capture) and ETL (Extract, Transform, Load). He explained that the first step is to identify a business function and define its API object. Then, the data model in Cassandra is built based on this definition, and DDL (Data Definition Language) is provided for implementation. The CDC pipeline is established to keep the replica updated in real-time, while the query-based pipeline helps with migration by transforming legacy data. The methodology involves accelerating the CDC pipeline, connection, and query-based pipeline, as well as enabling the operational data layer and delivering a spring framework-based microservice architecture for CRUD operations. This approach allows customers to take incremental bites of their transformation journey, starting with the most painful process and moving on to bigger transformations over time. Some key points from the Q&A session include: 1. Handling multiple applications using the same reference data during migration - The existing systems can be migrated over time to the new microservice architecture, allowing for a live migration without cutting off access to the source data. 2. Creating Cassandra data models before starting CDC - It is necessary to create the Cassandra data model before starting CDC because it serves as the destination for the captured data. 3. Repair node impact on high throughput clusters with sub 10 ms response times - DataStax has developed Node Sync, which significantly improves repair efficiency and performance in newer versions of Cassandra. 4. Best modeling tool for creating NoSQL models - Brian Mortimore prefers using text modeling tools like Notepad and focuses on the query-based approach to data modeling. 5. Consistency issues with multiple spring base API microservices connecting to the same database - Cassandra is an eventual consistency system, and it's essential to follow proper consistency rules when designing applications that interact with Cassandra. 6. Migrating from MongoDB to Cassandra using CDC - It is possible to migrate data from MongoDB to Cassandra using CDC. 7. Managing/planning for growth/cost in a NoSQL environment - Focus on identifying and eliminating extraneous data, ensuring that the data model can scale appropriately, and aligning growth with business objectives to justify costs. 8. Resolving data conflicts in CDC inquiry-based pipelines - Avoid pipeline collisions by designing the data model to prevent multiple pipelines from updating the same data objects. Use lightweight transactions or error checking if necessary. 9. Sample applications for learning DDDD (Domain-Driven Design) and other concepts - DataStax offers introductory classes and training materials through their DataStax Academy, which can help newcomers to the NoSQL world grasp these concepts.

In this episode of Inspired Execution, Home Depot SVP of Information Technology, Fahim Siddiqui, discusses the importance of agile working methods while maintaining a strong foundation in people, processes, and technologies. He emphasizes the significance of velocity in decision-making during times when Home Depot experiences 'Black Friday' volumes daily. Siddiqui also highlights how startups' grit and determination can be transferred to larger corporations by encouraging team members to believe in "the art of the possible." Furthermore, he discusses how Home Depot is transforming customer engagement by viewing their mobile application and the internet as the front door to their stores. The podcast series is available on InspiredExecution.com, Apple Podcasts, Google Podcasts, and Spotify.

The Spring Framework continues to be widely used for developing microservices in Java due to its numerous capabilities. In this issue, the Spring Data Starter project is introduced, which utilizes Spring Data Cassandra to provide a REST API backed by DataStax Astra. This example demonstrates how simple it is to quickly develop and test microservice applications using Cassandra as a data store. The repository's README guides users through setting up a free-forever Astra database, deploying the service with Gitpod in one click, and connecting the running service to their Astra database. Once the service is initialized, users can interact with the REST API via Swagger or fork the repository for customization. For more information on using Spring and Cassandra, consider attending the "Staying Ahead of the Curve with Spring and Cassandra 4" talk at SpringOne on September 2, 2020, featuring Alexandre Dutra of DataStax and Mark Paluch of VMware.

The Spring Framework continues to be widely used for developing microservices in Java, and the Spring Data Starter project is an example of this. This project uses Spring Data Cassandra to serve a REST API backed by DataStax Astra, demonstrating how easily developers can create and test microservice applications with Cassandra as a datastore. The process involves setting up a free-forever Astra database, deploying the service using Gitpod, and connecting it to the database. Once set up, users can interact with the REST API through Swagger or customize the code by forking the repository. For more information on Spring and Cassandra, check out the talk "Staying Ahead of the Curve with Spring and Cassandra 4" at SpringOne on September 2, 2020.

The Astra sample application gallery has been launched, allowing developers to quickly deploy Cassandra-backed applications using their preferred programming languages and frameworks. This resource aims to connect every developer with the power of Apache Cassandra™ for scalability and performance benefits. The gallery includes samples for various technologies such as React.js, JAMstack, Gatsby.js, GraphQL, Spark, Next.js, and more. Users can access the gallery directly or create a DataStax Astra cluster to get started with one of the samples. New sample apps are being added regularly, with bi-weekly updates provided.

"Inspired Execution" is a podcast series hosted by DataStax Chairman and CEO Chet Kapoor, featuring interviews with technology leaders from global enterprises. In the first episode, FedEx CIO Rob Carter shares his experiences from a 27-year career at the company, discussing the importance of technology as the "digital nervous system" of a business, balancing present responsibilities while driving innovation, and emphasizing the value of diversity in creating success. The podcast delves into how companies like FedEx have transformed through modern technologies and innovations, offering valuable insights for leading data-driven enterprises. Upcoming guests include tech leaders from various industries, with episodes available on InspiredExecution.com, Apple Podcasts, Google Podcasts, and Spotify.

The text discusses the growing interest in accessing Apache Cassandra from JavaScript applications, particularly with the launch of Astra and the increasing popularity of JAM Stack (JavaScript, APIs, and Markup) web applications. It presents a sample "Todo List" app using ReactJS and Astra's free tier that can be deployed to Netlify or Gitpod in just a few clicks. The application requires a DataStax Astra account and a free-tier Cassandra database, with the option to run it locally on your desktop. Deployment options include running on Gitpod, deploying to Netlify, or running on your local machine. The example can be applied to personal application development, aiming to speed up the development lifecycle and showcase Astra's utility in daily work. Feedback is welcome at [email protected] or @DataStaxDevs.

This article discusses the growing interest in accessing Apache Cassandra from JavaScript applications, particularly with the launch of Astra and the increasing popularity of JAM Stack (JavaScript, APIs, and Markup) web applications. It presents a sample "Todo List" app using ReactJS and Astra's free tier that can be deployed to Netlify or Gitpod in just a few clicks. The article provides instructions for setting up the application with DataStax Astra account and free-tier Cassandra database, as well as three deployment options: running on Gitpod, deploying to Netlify, or running locally. It aims to speed up development lifecycles and showcase how to leverage Astra in daily work.

The text discusses the release of DataStax's bulk loading utility and Apache Kafka® connector as open-source tools under Apache license, available on GitHub for users to explore, contribute or report issues. It also introduces DSBulk version 1.6.0 with improved throughput and fixes, and the availability of its libraries from Maven Central. Additionally, it mentions changes in Kafka Sink Connector 1.4.0 and how to ignore errors during processing. Users can download these tools from DataStax's download server or Confluent Hub.