DataStax today announced the private beta of Vector, an AIOps service for Apache Cassandra™. Vector continually assesses the behavior of a Cassandra cluster to provide developers and operators with automated diagnostics and advice, helping them be consistently successful with Cassandra and DataStax Enterprise (DSE) clusters.
Vector provides recommendations with detailed background knowledge and offers multiple ways to fix a problem. With Vector, developers and operators can resolve issues quickly, while gaining a deeper understanding of how clusters are performing.
“Our enterprises requested a service like Vector because, as a community, we know it takes a high level of skill to be consistently successful with Cassandra,” said DataStax Chief Product Officer Ed Anuff. “Our goal is to provide an AIOps service to proactively monitor the health of clusters to help developers and operators be more productive and effective with Cassandra.”
Vector is built upon a decade of expert guidance and learnings. The beta release uses reactive learnings to offer proactive advice. With this embedded knowledge base, Vector is able to analyze individual nodes, compare behavior to other nodes in the cluster, and serve up recommendations, such as: Cassandra and operating system configuration, schema design, and Cassandra performance and query techniques.
“Vector is a very good service, which helps not only identify the issues, but also provides the suggestions and recommendations along with the solutions. This will be a great help to the Developer/Application team,” said Bidhu Das, Sr. Lead Database Domain Architect at Cisco.
“DataStax Enterprise enables us to build highly scalable cloud-native applications as an industrial IoT platform and bring them to any cloud with ease,” says Shinichiro Matsunaga, Manager, iQuattro® at NTT DATA Corporation. “Vector promises to optimize our devOps workflows considerably, enabling our team to build better data-driven applications in less time and with less friction—all while leveraging cutting-edge technologies and open source tools to delight our users.”
- Automated expert advice – Proactively identifies current and potential issues to help developers and operators solve problems quickly. Automated advice provides contextual learning with background knowledge to build skills.
- Continuous updates – Rules and advice are continuously updated, deployed to SaaS and on-premises applications, and automatically applied to clusters.
- Hands-off management – Advanced visualizations of system usage with insightful charting to understand tables, keyspaces, and nodes. Vector helps developers and operators see and understand how the cluster is performing and its configuration without having to log into Cassandra nodes.
- Cassandra skills development – Helps strengthen Cassandra skills and knowledge by providing detailed advice and recommendations. Vector helps to reduce unexpected and unplanned items so experts can spend more time innovating.
“Vector is an industry first for Cassandra with its automated advice, continuous updates, and hands-off management. By working closely with our enterprises in the beta program and acquiring actionable feedback, we will continue to advance Vector’s features to improve Cassandra management and operations,” concluded Anuff.
To learn more, join us for the Vector Deep Dive webinar on June 25, 2020. Register here.
Blog: AI Ops and Cassandra Monitoring for Apache Cassandra – Introducing Vector
Vector Demo: Watch Vector in action
Webinar: A First Look at DataStax Vector – AIOps for Apache Cassandra
Cassandra Workshops: www.datastax.com/company/
DataStax is the company behind the massively scalable, highly available, cloud-native NoSQL data platform built on Apache Cassandra™. DataStax gives users and enterprises the freedom to run data in any cloud at global scale with zero downtime and zero lock-in. More than 450 of the world’s leading enterprises including Capital One, Cisco, Comcast, Delta Airlines, eBay, Macy’s, McDonald’s, Safeway, Sony, and Walmart use DataStax to build transformational data architectures for real-world outcomes. For more, visit DataStax.com and @DataStax.
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