November 2020 Summaries

The text discusses the advantages of using open source software over proprietary alternatives, particularly for business-critical data. Open source offers better security due to a larger community constantly reviewing the code, access to global support from developers, and continuous innovation through cutting-edge features developed by the community. Additionally, open source eliminates licensing fees, allowing businesses to scale up without additional costs or complications. Moreover, it ensures that users retain control of their data and are not locked into a single vendor's technology. The text concludes by recommending managed open source solutions for maximum benefits.

Black Friday is a peak load time for retailers, often highlighting weaknesses in their systems. To handle increased traffic, it's crucial to monitor system status and consider upgrading service plans before the surge occurs. If necessary, take downtime to modify applications or add more disk space, processing power, and database connections. Speeding up queries can also help manage high loads. Additionally, re-evaluating support contracts ensures assistance when needed.

Time series databases (TSDBs) have been growing in popularity, outpacing all other database models over the past two years. They store data as pairs of time(s) and value(s), making it easy to analyze sequences of points recorded in order over time. TSDBs can handle concurrent series, measuring many different variables or metrics in parallel. IoT technology is a major driver for the growth of TSDBs, as they are well-suited for dealing with the large amounts of data produced by sensors and other connected devices. The benefits of using a TSDB include more accurate and meaningful time series measurement, resource-efficient data storage, and lightning-fast data queries. Common use cases for TSDBs include storing and accessing IoT data, monitoring web services, applications, and infrastructure, understanding financial trends, processing self-driving vehicle data, and sales forecasting. As more capable solutions become available and managed services help users focus on the problem space, the use of time series databases is expected to continue expanding.

Alef Education, a leading provider of online learning solutions in the K-12 sector, successfully scaled their blended learning platform from 10 schools to over 400 using Aiven for Apache Kafka. The AI-powered Alef Platform serves over 120,000 students worldwide and is built around microservices, centering on Apache Kafka and related technologies. Alef Education chose to move to a managed Kafka provider to handle the infrastructure side of their platform in its entirety. They now use Aiven for all their data processing with a service chain composed of Kafka, InfluxDB, and Grafana, which has improved the reliability and user experience of their platform.

Aiven now offers Redis 6 as a managed service on its platform, bringing enhancements such as Access Control Lists (ACLs) for improved security and threaded I/O for faster processing. The new version also includes support for client-side caching in experimental stages, which can improve performance by using application server memory to cache some database information. Users of Aiven for Redis can upgrade their service as needed or upon specific changes such as plan alterations or node replacement.