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SELECTOR ENHANCES NETWORK OBSERVABILITY AND AIOPS PLATFORM WITH FULL-STACK CAPABILITIES
Wednesday, July 19, 2023
Summer release offers insights into network health from devices and interfaces to infrastructure, cloud, and containers.
SANTA CLARA, Calif., July 11, 2023 /PRNewswire/ -- Selector AI, the leading provider of network-aware AIOps, observability, and multi-domain analytics, today announced the addition of new capabilities to its platform, empowering organizations with unparalleled insights from the network up to the application. The enhancements move Selector forward as the first true full-stack observability and AIOPs platform on the market.
The Summer release enables organizations to delve deeper into their network infrastructure, cloud environments, containers, and applications, providing a holistic view of their entire application ecosystem. This empowers IT operations teams to proactively identify and resolve issues, optimize resource allocation, and prevent service interruptions.
Key highlights of the new release include:
1. Integrations: Selector now supports over 500 integrations across various
categories, including network, infrastructure, cloud, and applications.
From BGP/BMP and SNMP, CloudWatch and Stackdriver, to Postgres and
NGINX, Selector seamlessly integrates with a wide range of data sources
to provide comprehensive insights.
2. Outlier Detection: Selector's outlier detection capabilities help connect
the dots within your infrastructure, enabling rapid identification and
ranking of abnormal conditions. Operations teams can proactively identify
misbehaving devices and prevent outages before they occur.
3. Forecasting: Leveraging advanced machine learning, Selector's forecasting
capability predicts the evolution of metrics over time. Users can
configure alerts based on these predictions, allowing them to proactively
manage resources and prevent service interruptions.
4. PingMesh: Selector's PingMesh feature provides comprehensive latency
measurement and analysis for sophisticated networks. This allows network
developers, engineers, and application/service developers to rapidly
validate network impact on application performance. PingMesh supports
complex topologies and measures latency, jitter, packet loss, and path
changes.
5. Deployment Model Improvements: Selector focuses on improved availability
and fault tolerance with multi-node deployment and geo-redundancy
capabilities. Multi-node deployment supports Kubernetes clusters,
enhancing performance and scalability. Geo-redundancy ensures data
replication and service availability across multiple geographic regions,
mitigating the risk of service disruptions.
"We are thrilled to introduce these powerful capabilities to our network observability and AIOps platform," said Kevin Kamel, VP of Product Management at Selector. "With these enhancements, organizations can gain unparalleled 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 seamless user experience."
For more information about Selector's full-stack observability and AIOps platform and to request a demo, please visit www.selector.ai.
About Selector AI
Selector AI empowers network, cloud, and application operators with data-centric multi-domain analytics, driving the transition to AI and ML-based operations intelligence. As the industry's first network-aware operations intelligence platform, Selector Analytics converges network, applications, and IT system observability across heterogeneous data sources and provides actionable insights. Selector's customer base includes Internet Service Providers (ISP), Media, Financial Institutions, Cloud Service Providers (CSP), and Retail. Founded in 2019, Selector is backed by Two Bear Capital, Atlantic Bridge, Sinewave Ventures, Comcast Ventures, and many key angel investors. Learn more at www.selector.ai.
FOR IMMEDIATE RELEASE
Media Contact
Sherri Walkenhorst
Connect Marketing
sherriw@connectmarketing.com
(801) 373-7888
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SOURCE Selector
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