June 2020 Summaries

The Redis project marks an important milestone with Salvatore Sanfilippo stepping back from his role as the primary maintainer after 11 years. The transition will be led by a new core team of contributors, including Yossi Gottlieb and Oran Agra, who have been instrumental in advancing the project's evolution. Despite this change, Salvatore will continue to play a vital role in the community, serving as a technical advisory board member. The Redis project is poised for growth and innovation under its new governance structure, which prioritizes collaboration, transparency, and community involvement. With the core team sharing their plans for the future, the community is invited to contribute, provide feedback, and help shape the direction of the project. Thanks are extended to Salvatore for his dedication to Redis, which has enabled it to become a widely adopted and respected database solution.

The Redis project has a new governing structure with a community-driven approach after its maintainer, antirez (Salvatore Sanfilippo), stepped back from the role. This change is significant as it shifts away from the BDFL (Single Person in Charge of Everything) style that antirez had maintained for 11 years. The new model aims to promote teamwork and structure while preserving Redis's unique DNA, which emphasizes simplicity, solving problems better, and doing the right thing by default. A small core team of developers will be formed based on their familiarity with Redis, contributions, and commitment, with the goal of making Redis more approachable and community-driven.

The Redis Beyond Cache Hackathon saw over 320 participants submit 48 entries, with five applications moving on to the final round. Three prizes were awarded: Grand Prize, Judge's Choice, and People's Choice. intelliSchool won the Grand Prize for its web application that generates quizzes, notes, and flashcards using Redis modules. FaceMark won the People's Choice award with a real-time video solution for student attendance using contactless face recognition. Other finalists included Redisafe, Voluntree, and SpecKart. The hackathon aimed to showcase how Redis can be used beyond caching and attracted interest from developers worldwide.

The Redis Enterprise Kubernetes Operator provides a way to create, manage, and deploy databases in a Kubernetes cluster using custom resources. This allows developers to package database configurations alongside their application workloads in a familiar YAML format, enabling continuous integration/continuous deployment (CI/CD) processes like GitOps for Infrastructure as Code (IaC) deployments. The operator can create databases within a namespace by applying a custom resource, and it will discover and update the database based on changes to the configuration. The Redis Enterprise operator also provides a live demo of this process, showcasing how developers can use the operator in conjunction with GitOps and continuous deployment.

Kineviz is a software developer and consultancy focused on visual analytics, providing a unified visual environment for working with big, connected data. Its GraphXR platform integrates with RedisGraph, enabling users to read and write graphs. Kineviz has prepared a video demonstration of GraphXR's capabilities, showcasing its ability to work with ontologies in the OBO Foundry format. Knowledge graphs are used in various applications, including law enforcement, medical research, and business intelligence, accelerating time to insight and discovery.

RedisRaft is an experimental module for open source Redis that enables the operation of multiple Redis servers as a single fault-tolerant and strongly consistent cluster. It uses the Raft consensus algorithm and is designed to provide strong consistency with strict serialization deployment option, making it suitable for scenarios requiring high reliability and consistency. The new module can be used along with existing Redis clients, libraries, and data types in beyond-cache scenarios. Setting up a three-node RedisRaft cluster is straightforward, involving starting three Redis servers and joining them to the cluster. Once set up, clients can write data to the cluster, which will be replicated to at least a majority of the nodes. RedisRaft can also handle automatic forwarding of requests from follower nodes to the leader node, simplifying the process for applications that don't want to modify their existing code. The cluster configuration is dynamic and allows adding or removing nodes after setup, with proper care taken to avoid leaving the cluster in a degraded state during transitions. Most of RedisRaft's basic functionality is currently in place, with a first preview version expected to be released in a couple of months.

A knowledge graph is a data structure that represents what we know about part of the real world, enabling search algorithms to provide better responses by understanding relationships between terms and instances of facts and concepts. It can be used in computing for various applications, including machine learning, natural language processing, and search. Redis Enterprise's RedisGraph module can help load and use ontologies when building knowledge graph infrastructures, allowing users to query the ontology structure via Cypher queries and visualize it with RediSearch. Knowledge graphs have been used in various domains, such as retail and medicine, to extend the hand-curated aspects of an ontology into instances of data that relate to items within the ontology. They can be used to provide recommendations, summarize information, and support professionals in clinical settings or for drug development by carefully constructing the knowledge graph. Additionally, knowledge graphs do not have to be completely realized as graphs and can be combined with other data structures, such as tabular data stores, to store instance data and enable model inference and full-text searches. The possibilities for implementing and using knowledge graphs within Redis are widespread, and users can try out ontologies and knowledge graphs on various platforms, including Docker, Redis Enterprise, and the Redis Cloud Pro service.

The text discusses deploying an autoscaling group into AWS using Terraform, specifically for a stateless service with simple configuration that can be easily configured using cloud-init. The goal is to configure everything with Terraform and update the configuration whenever needed, without updating instances in place. To achieve this, the authors create a launch template that defines the critical elements of the instance and loads the service configuration from a user data file. They then create an autoscaling group using the launch template and modify it to dynamically update the desired capacity based on the existence of current autoscaling groups, ensuring clean instances when making configuration changes. The process involves using Terraform's `data` and `resource` blocks to query for the latest AMI, launch template, and autoscaling group information, and then updating the autoscaling group resource with the new desired capacity value.

The post discusses how Redis Enterprise uses syslog for logging events and alerts in a production system. It explains how to configure syslog to capture cluster events and alerts from Redis Enterprise, including creating a custom configuration file, configuring the `omfile` action to send logs to a file, and using an `omfwd` action to forward logs over the network to a centralized logging server. The post also provides examples of how to aggregate all log entries into a single location for processing and how to use syslog with tools like Splunk or Datadog to parse and integrate these messages.

The Redis `Beyond Cache` Hackathon has concluded, and now it's time to vote for the People's Choice award. The four finalists are competing for a spot in this final round based on their projects that utilize various Redis modules such as RedisGears, RedisAI, RediSearch, RedisGraph, RedisTimeSeries, RedisJSON, and RedisBloom, among others. The voting process is open to the community, with 50% of points coming from community votes and the remaining 50% from a panel of judges. The final round will run from June 11-18, and the winners will be announced on June 19. During this period, participants can review the projects by watching demo videos and project pages and vote for their favorite using LinkedIn.

Real-time inventory management is crucial for retailers to make a sale and gain an appreciative customer, as it enables them to manage stock across multiple physical and digital channels and locations in real-time, avoiding lost sales and frustrating customers. Without real-time inventory, retailers risk losing money on the table, inflating costs, and reducing the accuracy of their forecasts and planning. It also optimizes order fulfillment and shipping costs by having items delivered from a closer store or warehouse, and enables retailers to optimize inventory, yield management, and supply-chain management. Additionally, it provides a unified national order-fulfillment strategy, letting retailers pool geographically clustered store locations and warehouses to contribute to a single inventory.

The text discusses the importance of monitoring Redis Enterprise in production and provides an overview of its built-in monitoring capabilities, including the cluster management UI and alert mechanism. It also introduces Prometheus Metrics Exporter as a popular choice for many organizations, offering real-time monitoring and integration with Grafana. Additionally, the REST API is mentioned as a flexible way to integrate Redis Enterprise with third-party monitoring systems, providing a high degree of customization and flexibility. The author emphasizes that Redis Enterprise offers a range of monitoring options, giving customers a choice of which solution to use depending on their specific needs.

Stack Overflow's Annual Developer Survey has named Redis as the Most Loved Database four years in a row. The survey reached over 65,000 developers, with an effort to include a more diverse population. While Redis received 66% of the Most-Loved votes this year, down from 71% last year, it maintained its position as the sixth Most Popular Database overall among developers. Redis is recognized for being easy to learn, use, and manage regardless of background or skill level. The company's recent success with RedisConf 2020 Takeaway conference attracted nearly 4,000 attendees from 103 countries, demonstrating the growing interest in Redis beyond caching.