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New Full-Stack Capabilities and Insight-Driven Enhancements from Selector AI

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“Your industry-leading AIOps platform for real-time operational intelligence.”

A strong start from network-aware AIOps (i.e. artificial intelligence for IT operations, a term Gartner coined in 2017) provider, Selector AI.

In tow with its AIOps, Selector provides multi-domain analytics and smart observability solutions, and this week the company announced the addition of new capabilities to its platform, set to (according to Selector) “empower today’s growth-hungry organizations with unparalleled insights, from the network up to the application.” The new full-stack capabilities enable organizations to delve deeper into their network infrastructure, as well as their cloud environments, containers and applications, providing a holistic view of their entire respective application ecosystem.

Selector is positioned well to offer these fresh capabilities (part of its Selector Summer rollout), as its team of experts consistently brings together industry-steeped experts in networking, AI and data science that are committed to creating next-gen solutions for customers.

For IT operations personnel looking to improve their proactive issue identification and resolution workflows (i.e. while optimizing resource allocation and preventing service interruptions), this new capabilities bump from Selector might be just fit that bill.

More in-depth highlights of this release include:

  • Integrations: Selector now supports more than 500 integrations across a variety of categories. From BGP/BMP and SNMP, to CloudWatch and Stackdriver, to Postgres and NGINX, Selector seamlessly integrates with a wide range of data sources to provide comprehensive insights.
  • Outlier Detection: Selector's outlier detection capabilities help connect the dots within an organization’s infrastructure, enabling rapid identification and ranking of abnormal conditions. IT teams can then quickly identify misbehaving devices and ideally prevent outages before they occur.
  • Forecasting: Leveraging advanced machine learning (ML), Selector's forecasting tool predicts the evolution of metrics over time. Users can configure alerts based on said predictions, allowing for easier resource management to prevent service interruptions.
  • PingMesh: Selector's PingMesh feature provides, per Selector, “comprehensive latency measurement and analysis for sophisticated networks.” Essentially, this allows network developers, engineers, and application and service developers to rapidly validate network impact on application performance. PingMesh supports complex topologies and measures latency, jitter, packet loss and path changes.
  • Deployment Model Improvements: “Selector focuses on improved availability and fault tolerance,” the company said, “with multi-node deployment and geo-redundancy capabilities.” Multi-node deployment supports Kubernetes clusters (enhancing performance and scalability), and geo-redundancy ensures the data replication and service availability across multiple geographic regions, thus mitigating the risk of service disruptions.

 “We are thrilled to introduce these powerful capabilities to our network observability and AIOps platform,” said Kevin Kamel, Selector’s Vice President of Product Management. “With these enhancements, organizations gain visibility into their entire network stack, from devices and interfaces to applications. This empowers them to make data-driven decisions, optimize performance, and ensure a truly seamless user experience.”




Edited by Greg Tavarez
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