Skip to main content

Itential Partners with Selector on Network Automation

Itential and Selector announced a strategic partnership to deliver real-time, closed-loop automation for enterprise and service provider infrastructure teams.

The integration between the Itential Platform and the Selector AIOps Platform bridges a critical operational gap — turning insights into instant action. By combining real-time event detection and root cause identification from Selector with policy-driven orchestration and automated remediation from Itential, teams can now detect, diagnose, and resolve issues across hybrid environments automatically — with no manual intervention required.

"The combination of AI-powered observability and intelligent orchestration is a game changer for modern infrastructure teams," said Peter Sprygada, Chief Architect, Itential. "Selector provides deep, real-time insights into what's happening in the environment, and Itential enables those insights to drive immediate, automated action. Together, we're helping organizations unlock the true promise of AI-driven infrastructure — seamless, secure, closed-loop operations that are faster, smarter, and fully automated."

With Itential + Selector, that manual chain is broken. Selector applies machine learning to correlate anomalies across telemetry, logs, and events to identify the root cause of incidents. Itential receives these triggers in real-time and executes automated workflows to resolve issues, update inventory, and close tickets — all while maintaining full auditability and policy alignment.

The Itential + Selector integration empowers infrastructure and operations teams to move faster and respond smarter. From routine maintenance to urgent incident response, the joint solution enables AI-driven, fully automated, closed-loop workflows across a range of everyday use cases:

  • Automated Port Resets: Detect degraded port performance and trigger policy-driven fixes without opening a ticket.
  • Compliance Remediation: Identify non-compliant configurations and automatically correct them in real time.
  • Service Degradation Resolution: Surface root cause from noisy alerts and orchestrate resolution across systems.

"This partnership is a big step forward for infrastructure teams," said Kannan Kothandaraman, CEO and Co-Founder of Selector. "By integrating our observability and AIOps platform with Itential's orchestration platform, we're enabling organizations to go beyond detection. Together, we're helping teams move faster, cut through the noise, and finally close the loop between detection and resolution. This partnership brings us one step closer to fully autonomous, self-healing networks."

By combining Selector's AI-driven insight with Itential's intelligent orchestration, organizations can reduce mean time to resolution (MTTR), eliminate manual escalations, and operate with greater confidence — whether responding to anomalies, performing routine tasks, or automating across cloud and network domains.

The Latest

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...

Itential Partners with Selector on Network Automation

Itential and Selector announced a strategic partnership to deliver real-time, closed-loop automation for enterprise and service provider infrastructure teams.

The integration between the Itential Platform and the Selector AIOps Platform bridges a critical operational gap — turning insights into instant action. By combining real-time event detection and root cause identification from Selector with policy-driven orchestration and automated remediation from Itential, teams can now detect, diagnose, and resolve issues across hybrid environments automatically — with no manual intervention required.

"The combination of AI-powered observability and intelligent orchestration is a game changer for modern infrastructure teams," said Peter Sprygada, Chief Architect, Itential. "Selector provides deep, real-time insights into what's happening in the environment, and Itential enables those insights to drive immediate, automated action. Together, we're helping organizations unlock the true promise of AI-driven infrastructure — seamless, secure, closed-loop operations that are faster, smarter, and fully automated."

With Itential + Selector, that manual chain is broken. Selector applies machine learning to correlate anomalies across telemetry, logs, and events to identify the root cause of incidents. Itential receives these triggers in real-time and executes automated workflows to resolve issues, update inventory, and close tickets — all while maintaining full auditability and policy alignment.

The Itential + Selector integration empowers infrastructure and operations teams to move faster and respond smarter. From routine maintenance to urgent incident response, the joint solution enables AI-driven, fully automated, closed-loop workflows across a range of everyday use cases:

  • Automated Port Resets: Detect degraded port performance and trigger policy-driven fixes without opening a ticket.
  • Compliance Remediation: Identify non-compliant configurations and automatically correct them in real time.
  • Service Degradation Resolution: Surface root cause from noisy alerts and orchestrate resolution across systems.

"This partnership is a big step forward for infrastructure teams," said Kannan Kothandaraman, CEO and Co-Founder of Selector. "By integrating our observability and AIOps platform with Itential's orchestration platform, we're enabling organizations to go beyond detection. Together, we're helping teams move faster, cut through the noise, and finally close the loop between detection and resolution. This partnership brings us one step closer to fully autonomous, self-healing networks."

By combining Selector's AI-driven insight with Itential's intelligent orchestration, organizations can reduce mean time to resolution (MTTR), eliminate manual escalations, and operate with greater confidence — whether responding to anomalies, performing routine tasks, or automating across cloud and network domains.

The Latest

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...