April 2020 Summaries

Cybercrime and payment fraud pose significant challenges for businesses handling digital transactions. To combat this issue, a successful fraud prevention strategy requires the ability to process large volumes of data quickly and accurately. Many organizations have turned to NoSQL databases like DataStax Enterprise to support their mission-critical systems due to their performance and scalability capabilities. ACI Worldwide, which processes over $14 trillion in payments daily, has implemented a solution using DataStax Enterprise, Apache Kafka, and Hadoop to detect fraud in real-time. This approach combines machine learning and AI to achieve the necessary speed and accuracy for fraud detection.

Cloud computing heavily relies on Linux as a standard operating system, with most providers investing in various distributions of this open-source OS. Amazon Web Services (AWS) has released its next generation of Linux, named Linux 2, promising better performance, long-term support, and integration with popular AWS services. DataStax is now a certified Service Ready Partner for AWS Linux 2, ensuring compatibility and best practices for users deploying their software in the cloud. As cloud adoption grows, there's an increasing need for data portability and flexible cloud options, which can be addressed through hybrid or multi-cloud architectures. DataStax, built on Apache Cassandra™ NoSQL database, offers expertise and enterprise capabilities to help enterprises build scalable cloud applications and meet the demands of real-time distributed workloads and cloud-native applications.

Jeff Carpenter, author of "Cassandra: The Definitive Guide," is working on the third edition of the book to keep up with the evolving Cassandra database system. The new edition will cover updates from version 4.0, including performance improvements, virtual tables for easier monitoring and management, transient replication, and enhanced security features. Additionally, the book will discuss running Cassandra in Docker, using Kubernetes operators, and migrating from legacy relational databases to Cassandra. The third edition is set to release on April 21, 2020, with a free copy available for a limited time through DataStax's sponsorship.

Kong has released a preview build with support for DataStax Astra (beta), a cloud-native database-as-a-service built on Apache Cassandra™, making it accessible to every developer using the world's most popular open-source microservice API gateway. This integration aims to provide developers with full access to Cassandra in the cloud, enabling them to manage all their data on Astra and simplify application development while reducing administrative overhead and costs. Both DataStax and Kong are committed to the open-source community and helping developers build modern, data-rich applications in hybrid and multi-cloud environments.

Kong, an open-source API gateway, has been tested with DataStax Astra, a managed Apache Cassandra service. The integration required additional Lua support for proxy connections and certificates in the lua-cassandra driver. With this enhancement, Kong can now communicate with Cassandra hosted on Astra. This combination allows developers to focus on deploying applications while leaving the management of Cassandra to DataStax professionals. Instructions are provided for installing Kong on a Kubernetes cluster and validating its functionality using an admin API.

In this blog post, the author continues developing an ordering application for Better Botz using Node.js, Express backend server, and DataStax Astra database. They use Glitch to expedite development and create a copy of the project by remixing it. The secure connect bundle is moved to a hidden directory for security purposes. An authorization token is created using cURL commands and the Astra Data API. The orders table is updated with a quantity column, and data is added to the table using update rows endpoint of the DataStax Astra API. Shipping table is created in the database using add table endpoint. Finally, the Express server is started with the included Jade templates, and data retrieval endpoints are tested. In the next post, CRUD operations will be developed for managing data in and out of tables.

DataStax has joined the Cloud Native Computing Foundation (CNCF) to collaborate with its communities and broaden integrations with CNCF projects in a hybrid cloud-driven, cloud-native data world. The company believes that Apache Cassandra will be the standard database for scale-out data moving forward. DataStax recently open-sourced their version of a Kubernetes Operator for Cassandra and plans to work with the Cassandra community on a single, open-source Kubernetes operator. They are also developing DataStax Astra, a cloud-native service powered by Cassandra, to make it easier for users to develop and deploy data-driven applications without traditional database administration hassles.

Distributed systems testing presents unique challenges due to the difficulty in predicting how small failures can lead to large-scale errors across clusters. DataStax has developed Fallout, a large scale distributed testing tool that allows engineers to define and run experiments on running clusters in an automated and repeatable manner. Fallout integrates with NoSQLBench for simulating production workloads and is designed to work with existing testing tools and infrastructure. It uses Kubernetes for managing the Cassandra cluster lifecycle, allowing developers to focus on writing code and experiments. The tool is now available for download under the Apache License.

The text discusses how Instagram initially used Apache Cassandra™ to store its data in a single data center, but as the company expanded and added more data centers globally, it faced challenges with replication strategy. To address these issues, Instagram decided to stop duplicating data everywhere and instead stored data closest to the region where it was generated. This approach allowed for faster and more efficient network performance. The company also utilized a tool called Akkio developed by Facebook to manage local data at scale.