Skip to main content

Kentik Synthetic Monitoring Launched

Kentik announced the launch of Kentik Synthetic Monitoring, proactive network monitoring that simulates an end-user’s experience with infrastructure, applications or services.

The Kentik Network Intelligence Platform is now the only fully integrated network traffic and synthetic monitoring analytics solution on the market, and the only solution to enable autonomous testing ― for both cloud and hybrid networks.

With Kentik Synthetic Monitoring, network teams have a fully integrated solution that can autonomously configure their tests, present the full network context, and make the resulting insights actionable immediately.

Synthetic testing integrated with actual network traffic and device data gives Kentik trillions of even better eyes on the network.

“Lack of understanding of network usage and state has led to the massive failure of synthetic monitoring,” said Avi Freedman, co-founder and CEO of Kentik. “Kentik already has real-time visibility into over 1 trillion traffic measurements per day across billions of users and sees every network connected to the internet. Synthetic testing integrated with actual network traffic and device data gives Kentik trillions of even better eyes on the network. We are changing the game with synthetic monitoring that’s exponentially more valuable.”

Kentik Synthetic Monitoring uses private agents that deploy quickly and easily and a network of global agents that are strategically positioned in internet cities around the world and in every cloud region within AWS, Google Cloud, Microsoft Azure and IBM Cloud. The service feeds into the Kentik Data Engine (KDE), a patented hybrid columnar and streaming data engine for distributed ingest, enrichment, learning and analytics, which uses machine learning to analyze, predict and respond in real time, at internet scale.

“Data from Kentik Synthetic Monitoring allows us to continue to extend our already insurmountable lead in volume, velocity and quality of network measurement, leveraging the telemetry to build even better models of network, application, and user behavior,” added Freedman.

Kentik Synthetic Monitoring frequently and autonomously measures performance and availability metrics of essential infrastructure, applications and services including:

- SaaS solutions

- Applications hosted in the public cloud

- Internal applications

- Transit and peer networks

- Content delivery networks

- Streaming video, social, gaming and other content providers

- Site-to-site performance across traditional WAN and SD-WANs

- Service provider connectivity and customer SLAs

“Our customers have been vocal for some time that the existing approaches to synthetic network testing are falling short because they are too manual, too static and too expensive,” said Christoph Pfister, CPO of Kentik. “We designed Kentik Synthetics to test autonomously, taking into account the dynamic nature of modern networks and the internet. In addition, we believe the industry has been held back for too long by a lack of affordability, forcing customers to trade off testing needs with cost constraints. Kentik is doing away with all this today by introducing a price point that allows customers to monitor frequently, monitor autonomously, and monitor everything that matters.”

Kentik Synthetic Monitoring is available now in preview, with GA planned for this quarter.

The Latest

While 87% of manufacturing leaders and technical specialists report that ROI from their AIOps initiatives has met or exceeded expectations, only 37% say they are fully prepared to operationalize AI at scale, according to The Future of IT Operations in the AI Era, a report from Riverbed ...

Many organizations rely on cloud-first architectures to aggregate, analyze, and act on their operational data ... However, not all environments are conducive to cloud-first architectures ... There are limitations to cloud-first architectures that render them ineffective in mission-critical situations where responsiveness, cost control, and data sovereignty are non-negotiable; these limitations include ...

For years, cybersecurity was built around a simple assumption: protect the physical network and trust everything inside it. That model made sense when employees worked in offices, applications lived in data centers, and devices rarely left the building. Today's reality is fluid: people work from everywhere, applications run across multiple clouds, and AI-driven agents are beginning to act on behalf of users. But while the old perimeter dissolved, a new one quietly emerged ...

For years, infrastructure teams have treated compute as a relatively stable input. Capacity was provisioned, costs were forecasted, and performance expectations were set based on the assumption that identical resources behaved identically. That mental model is starting to break down. AI infrastructure is no longer behaving like static cloud capacity. It is increasingly behaving like a market ...

Resilience can no longer be defined by how quickly an organization recovers from an incident or disruption. The effectiveness of any resilience strategy is dependent on its ability to anticipate change, operate under continuous stress, and adapt confidently amid uncertainty ...

Mobile users are less tolerant of app instability than ever before. According to a new report from Luciq, No Margin for Error: What Mobile Users Expect and What Mobile Leaders Must Deliver in 2026, even minor performance issues now result in immediate abandonment, lost purchases, and long-term brand impact ...

Artificial intelligence (AI) has become the dominant force shaping enterprise data strategies. Boards expect progress. Executives expect returns. And data leaders are under pressure to prove that their organizations are "AI-ready" ...

Agentic AI is a major buzzword for 2026. Many tech companies are making bold promises about this technology, but many aren't grounded in reality, at least not yet. This coming year will likely be shaped by reality checks for IT teams, and progress will only come from a focus on strong foundations and disciplined execution ...

AI systems are still prone to hallucinations and misjudgments ... To build the trust needed for adoption, AI must be paired with human-in-the-loop (HITL) oversight, or checkpoints where humans verify, guide, and decide what actions are taken. The balance between autonomy and accountability is what will allow AI to deliver on its promise without sacrificing human trust ...

More data center leaders are reducing their reliance on utility grids by investing in onsite power for rapidly scaling data centers, according to the Data Center Power Report from Bloom Energy ...

Kentik Synthetic Monitoring Launched

Kentik announced the launch of Kentik Synthetic Monitoring, proactive network monitoring that simulates an end-user’s experience with infrastructure, applications or services.

The Kentik Network Intelligence Platform is now the only fully integrated network traffic and synthetic monitoring analytics solution on the market, and the only solution to enable autonomous testing ― for both cloud and hybrid networks.

With Kentik Synthetic Monitoring, network teams have a fully integrated solution that can autonomously configure their tests, present the full network context, and make the resulting insights actionable immediately.

Synthetic testing integrated with actual network traffic and device data gives Kentik trillions of even better eyes on the network.

“Lack of understanding of network usage and state has led to the massive failure of synthetic monitoring,” said Avi Freedman, co-founder and CEO of Kentik. “Kentik already has real-time visibility into over 1 trillion traffic measurements per day across billions of users and sees every network connected to the internet. Synthetic testing integrated with actual network traffic and device data gives Kentik trillions of even better eyes on the network. We are changing the game with synthetic monitoring that’s exponentially more valuable.”

Kentik Synthetic Monitoring uses private agents that deploy quickly and easily and a network of global agents that are strategically positioned in internet cities around the world and in every cloud region within AWS, Google Cloud, Microsoft Azure and IBM Cloud. The service feeds into the Kentik Data Engine (KDE), a patented hybrid columnar and streaming data engine for distributed ingest, enrichment, learning and analytics, which uses machine learning to analyze, predict and respond in real time, at internet scale.

“Data from Kentik Synthetic Monitoring allows us to continue to extend our already insurmountable lead in volume, velocity and quality of network measurement, leveraging the telemetry to build even better models of network, application, and user behavior,” added Freedman.

Kentik Synthetic Monitoring frequently and autonomously measures performance and availability metrics of essential infrastructure, applications and services including:

- SaaS solutions

- Applications hosted in the public cloud

- Internal applications

- Transit and peer networks

- Content delivery networks

- Streaming video, social, gaming and other content providers

- Site-to-site performance across traditional WAN and SD-WANs

- Service provider connectivity and customer SLAs

“Our customers have been vocal for some time that the existing approaches to synthetic network testing are falling short because they are too manual, too static and too expensive,” said Christoph Pfister, CPO of Kentik. “We designed Kentik Synthetics to test autonomously, taking into account the dynamic nature of modern networks and the internet. In addition, we believe the industry has been held back for too long by a lack of affordability, forcing customers to trade off testing needs with cost constraints. Kentik is doing away with all this today by introducing a price point that allows customers to monitor frequently, monitor autonomously, and monitor everything that matters.”

Kentik Synthetic Monitoring is available now in preview, with GA planned for this quarter.

The Latest

While 87% of manufacturing leaders and technical specialists report that ROI from their AIOps initiatives has met or exceeded expectations, only 37% say they are fully prepared to operationalize AI at scale, according to The Future of IT Operations in the AI Era, a report from Riverbed ...

Many organizations rely on cloud-first architectures to aggregate, analyze, and act on their operational data ... However, not all environments are conducive to cloud-first architectures ... There are limitations to cloud-first architectures that render them ineffective in mission-critical situations where responsiveness, cost control, and data sovereignty are non-negotiable; these limitations include ...

For years, cybersecurity was built around a simple assumption: protect the physical network and trust everything inside it. That model made sense when employees worked in offices, applications lived in data centers, and devices rarely left the building. Today's reality is fluid: people work from everywhere, applications run across multiple clouds, and AI-driven agents are beginning to act on behalf of users. But while the old perimeter dissolved, a new one quietly emerged ...

For years, infrastructure teams have treated compute as a relatively stable input. Capacity was provisioned, costs were forecasted, and performance expectations were set based on the assumption that identical resources behaved identically. That mental model is starting to break down. AI infrastructure is no longer behaving like static cloud capacity. It is increasingly behaving like a market ...

Resilience can no longer be defined by how quickly an organization recovers from an incident or disruption. The effectiveness of any resilience strategy is dependent on its ability to anticipate change, operate under continuous stress, and adapt confidently amid uncertainty ...

Mobile users are less tolerant of app instability than ever before. According to a new report from Luciq, No Margin for Error: What Mobile Users Expect and What Mobile Leaders Must Deliver in 2026, even minor performance issues now result in immediate abandonment, lost purchases, and long-term brand impact ...

Artificial intelligence (AI) has become the dominant force shaping enterprise data strategies. Boards expect progress. Executives expect returns. And data leaders are under pressure to prove that their organizations are "AI-ready" ...

Agentic AI is a major buzzword for 2026. Many tech companies are making bold promises about this technology, but many aren't grounded in reality, at least not yet. This coming year will likely be shaped by reality checks for IT teams, and progress will only come from a focus on strong foundations and disciplined execution ...

AI systems are still prone to hallucinations and misjudgments ... To build the trust needed for adoption, AI must be paired with human-in-the-loop (HITL) oversight, or checkpoints where humans verify, guide, and decide what actions are taken. The balance between autonomy and accountability is what will allow AI to deliver on its promise without sacrificing human trust ...

More data center leaders are reducing their reliance on utility grids by investing in onsite power for rapidly scaling data centers, according to the Data Center Power Report from Bloom Energy ...