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AIops — the practice of applying AI to automate and improve IT operations — has gained currency during the pandemic. As businesses embrace digital transformation strategies involving “multicloud,” or the use of services from more than one cloud vendor, there’s an increasing need to improve the observability and analytics around networking infrastructure and performance. In a 2022 Nutanix survey, organizations cited interoperability, security and data integration as the top challenges in managing mutlicloud setups.
Spurred by the challenge, Kannan Kothandaraman and Nitin Kumar — both networking industry veterans — in 2019 launched Selector, an AIops platform for network, cloud and app delivery workflows. Selector detects anomalies in cloud environments, automatically notifying IT team members when failures or outages occur.
To lay a runway for growth, Selector closed a $28 million series A, the company announced — bringing its total funding to $33 million. Two Bear Capital, SineWave Ventures and Atlantic Bridge co-led the round.
“We saw that cloud providers can build large and complex cloud infrastructures while enterprises, service providers, financial institutions and retailers are struggling to manage their own infrastructure. The key insight was that cloud builders have built in-house observability tools not available to enterprises and service providers,” Kothandaraman told VentureBeat via email. “We set out with a vision to build the first network and IT operations intelligence platform that combines network and application observability with actionable insights from any data source to eliminate downtime.”
AIops for networking
CEO Kothandaraman was previously a software engineer at Cisco before joining Juniper Networks, where he worked his way up to the role of VP of product line management. Kumar, formerly an engineer at FORE Systems and Procket Networks, also spent time at Juniper — first as an engineer, then as VP and fellow.
With Selector, the two cofounders sought to create a platform that could ingest data from any data source and provide the monitoring necessary for multicloud infrastructures. Selector normalizes, filters, clusters and correlates events from networks, apps and security tools and delivers these insights through a dashboard. Teams can use Slack and other chat tools in tandem with Selector to receive answers to questions about infrastructure by searching through conversations.
“Operations teams can audit configuration changes, correlate configuration changes to anomalies and search for the presence or absence of specific configuration statements,” the company explains on its website. “Selector’s synthetic analytics solution rapidly isolates and identifies any contribution the network makes to application anomalies. Operations teams can rapidly determine network innocence or triage network anomalies.”
Kothandaraman claims that these capabilities enable IT teams to diagnose and remediate potential or existing issues more quickly than they could otherwise.
“Selector uses a data-centric AI approach and focuses on enhancing ingested data with metadata from multiple sources. For example, in addition to ingesting data from multiple heterogeneous domains, Selector ingests enterprise-specific metadata such as inventory and [customer relationship management info] to enrich insights and analysis,” Kothandaraman said. “The added complexity from [siloed monitoring tools] often reduces availability and performance rather than improving it. Selector solves [this challenge] through data aggregation, normalization and enrichment of heterogeneous data, correlation of that data and providing a simple, easy-to-use interface for … teams to access and share analysis.”
AIops solutions aren’t appropriate for every company. Network World’s Shamus McGillicuddy, reporting on an EMA study, notes that successful users of AIops are focused on transforming network engineering and operations rather than addressing challenges with existing network management tools.
“AIops-driven network management can make a business run better. [But companies who report] the most success with applying AIops to network management [are] the most likely to say that their AIops interest isn’t driven by network management tool problems,” McGillicuddy wrote in a July 2021 article
Moreover, Selector competes with products like IBM’s Watson AIops, which uses AI to detect, diagnose and remediate networking equipment anomalies. Startups like Augtera Networks also leverage AI for network planning and predictive infrastructure maintenance, applying algorithms trained on production data from real-world systems.
But Kothandaraman says that there has been growing interest in Selector, fueled in part by pandemic-related technical hurdles. Prior to the platform’s official launch, 25-employee Selector worked with Comcast and Bell Canada as well as NBC Sports, which used the platform to monitor its networks at the Tokyo 2020 and Beijing 2022 Olympics.
“We have over 10 paying customers … with more than 50 customers in the pipeline. Our customer base includes internet service providers, media, financial institutions, cloud service providers and retail,” Kothandaraman said. “Enterprises need flexibility to deploy their applications on any cloud, datacenter or edge computing to meet the myriad of ways their customers and employees are accessing their services … With this funding, we’ll focus on expanding solutions for telco cloud, healthcare and retail. We’re also expanding our product functionality to add use cases for multicloud and internet of things.”
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