May 2021 Summaries

The Aerospike Standup is a newsletter written by developers for developers, featuring blog posts, community questions, documentation, releases, and events. The team recently held their annual user summit with over 1000 attendees from 40+ countries, where they showcased content including talks on demand. Additionally, the team announced updates to streamline query capabilities on massive datasets, making it more ML-friendly, which will be shared every other week through email subscriptions. Community members have also been sharing questions and new articles on topics such as using Aerospike with AI/ML workloads and Spark 3.0. The team is also participating in upcoming events like DevOpsCon Berlin.

The online gaming industry has experienced significant growth due to the pandemic, with players worldwide increasing their weekly gaming hours by 14%. However, some gamers express dissatisfaction with new games' inability to handle a surge of users or poor-quality graphics. To compete effectively and satisfy users, game developers must address critical factors such as scaling capacity, dependable performance, high availability, cost effectiveness, and real-time data platforms. Aerospike offers solutions for these challenges, enabling gaming companies to improve user experience and maintain customer loyalty in the rapidly expanding market.

This summary provides an overview of the example project that demonstrates the use of Spring Cache with Aerospike database. The project allows for caching user data in memory using an Aerospike database, enabling performance improvements by reducing the load on a main database and providing faster read operations. The cache is configured using annotations such as `@Cacheable`, `@CachePut`, and `@CacheEvict` to manage cache behavior. The example showcases how to create a Spring Boot application with caching capabilities, including configuration of AerospikeClient and AerospikeCacheManager beans. It also demonstrates the use of repositories, services, and controllers to interact with the cache layer. The project can be tested using Postman to simulate client requests, such as adding a user, reading a user, and removing a user from the cache. Overall, this example provides a simple yet effective way to implement caching in a Spring Boot application using Aerospike database.

The pandemic has led to a significant increase in online banking and e-commerce activities, attracting fraudsters who prey on businesses and consumers alike. Fraud costs can extend beyond financial loss, impacting reputation and relationships with credit card companies. However, understanding customer fraud risk profiles can help businesses personalize their offerings, improve customer satisfaction, reduce churn, and grow market share. Advanced AI/ML-based systems are being used to detect fraud more accurately, with some companies moving towards neural network and deep learning solutions for better results. Explainable AI is also gaining importance as it helps understand how the system works, improves tweaks, and ensures compliance with data privacy regulations. Utilizing sophisticated fraud analytics on a modern technology platform can help businesses thwart fraudsters while improving customer understanding, service personalization, revenue growth, and standing out from competitors.

Aerospike Backup (asbackup)` is a tool used to backup and restore namespaces in an Aerospike database. The new feature added allows for compressing and encrypting backup files as they are being made, ensuring data security even if the backup job is aborted before finishing. This is achieved by operating on the data before it is written to the file, preventing unencrypted data from being stored on disk. The compression algorithm used is `zstd`, while encryption is done using `AES 128/AES 256` in Counter Mode, requiring a private key for decryption.

Aerospike Digital Summit 2021, Reimagine Real-time, recently concluded with virtual attendees from over 40 countries participating in keynote sessions, customer presentations, and technical workshops. The event featured speakers such as CEO John Dillon, Guy Kawasaki, and representatives from HPE, Intel, Western Digital, Adobe, The Trade Desk, and Verizon Media discussing the importance of real-time data and Aerospike's role in data-intensive applications. Technical tracks focused on developer-centric sessions and workshops, with the launch announcement of Aerospike Database 5.6 and enhanced Aerospike Connect for Spark. The event also touched upon topics like IoT and featured meetups such as a Star Wars-themed networking session and a Cinco de Mayo cooking session with celebrity chef Fabio Viviani.

The Aerospike Standup Vol. 28 is a newsletter that provides updates on various aspects of Aerospike development. It includes blog posts, community questions, documentation, releases, and events. Recently, the team held a successful summit where they shared their latest updates and learned about clients' success stories with Aerospike. The Standup will be released every other week, and users can subscribe to receive updates via email. Notable recent articles include "Continuous Integration with Aerospike on GitHub" by Eugene Rizhkov and "Let AI/ML workloads take off with Aerospike and Spark 3.0" by Kiran Matty. The release notes for May include updates to the Go Client, REST Client, JDBC Driver, and Skyhook. Upcoming events include a talk about NoSQL databases on May 19 at 3:50 PM CET and another talk about infrastructure for ML applications on May 19 at 6:00 PM CET.

The telecom industry is undergoing a digital transformation driven by market forces, aiming for cost reduction, improved customer experience (CX), increased agility, and overall intelligence. Telecom operators are looking to diversify their revenue streams beyond traditional services, transitioning from communication service providers to digital service providers. They also seek solutions to reduce costs associated with network utilization, such as cloudification and adoption of emerging IT practices like DevOps and CI/CD. 5G technology is seen as a game-changer for the telecom industry, offering revolutionary performance, cloud-native architecture, and distributed topology, which will enable new value chain positions and revenue pools for network builders. However, back-end data platforms supporting new services in areas like IoT and enterprise must be able to keep up with the increased data volume, velocity, and veracity brought by 5G.

The Aerospike Standup is a newsletter written by developers for developers, providing updates on blog posts, community questions, documentation, releases, and events. The newsletter will be published every other week, with the option to subscribe via email. Recent articles include discussions on continuous integration and AI/ML workloads using Aerospike and Spark 3.0. Upcoming events include talks at Codemotion and InTech meetups, covering topics such as the brief history of NoSQL databases and infrastructure for ML applications. The newsletter also includes release notes for various Aerospike components, including the Go client, REST gateway, JDBC driver, and Skyhook.

Aerospike has released version 5.6, a developer-focused update with new features and improvements. The release includes set indexes for improved scanning performance, operation expressions for atomic cross-bin operations, and per-user quotas to manage resource allocation in multi-application scenarios. Additionally, minor updates include support for Boolean bin type, new statistics for index storage usage, and enhanced security configurations for logging data operations.

The text discusses the integration of AI/ML workloads with Aerospike and Spark 3.0, which is particularly relevant in light of increased digitalization due to the COVID-19 pandemic. It highlights that data science teams are dealing with larger datasets than ever before, leading to a need for efficient model training and deployment solutions. The integration of Apache Spark 3.0 and Aerospike can help achieve this goal effectively and cost-efficiently. The text also delves into the benefits of using Spark 3.0, such as its support for Kubernetes, enabling a single low latency and high-throughput pipeline from data ingest to model training on GPU-powered clusters. It mentions that Spark 3.0 can now schedule AI/ML applications on Spark clusters with GPUs, allowing the unification of CPU-based data platforms used for data preparation via ETL and largely GPU-based AI/ML platforms into a single unified data infrastructure. Additionally, the text discusses new query enhancements in Spark 3.0, such as Adaptive Query Execution (AQE), which helps when statistics on the data source do not exist or are not accurate. It also highlights the features added to Aerospike Connect for Spark, including data sampling at scale, support for set indexes and quotas of the Aerospike Database 5.6, pushdown predicates with previously unsupported operators to speed up queries, and support for highly performant Spark Data Source V2 API. The text concludes by providing two case studies where companies have successfully utilized this integration in their AI/ML initiatives. It also mentions future plans to validate the Spark connector with the RAPIDS Accelerator for Apache Spark, allowing direct feeding of Aerospike data into Deep Learning models running on GPUs.