Skip to main content

Paessler Adds Support for Docker Container Monitoring

Paessler AG announced a new sensor type for its core product, PRTG Network Monitor, that enables users to monitor Docker containers, giving them key insights into performance, availability and other metrics.

PRTG Network Monitor is a comprehensive monitoring solution with more than 200 out-of-the-box sensor types, capable of monitoring everything from routers and switches to virtual machines and, now, Docker containers. Docker has become an increasingly popular technology with both DevOps teams and network administrators since its launch in 2013. Network administrators in particular have used containers to efficiently roll out and manage applications. With this progress in mind, Paessler created a dedicated Docker Container Sensor to give users the ability to monitor containers without the need to acquire a specific application performance monitoring solution. PRTG users can now monitor container status, uptime/downtime, CPU usage, memory, packets and traffic in/out, and exit code.

"IT should be able to monitor its entire infrastructure from one solution, and Docker is quickly becoming a part of that infrastructure," said Andrew Cutting, Director of Channel Sales, North America, Paessler. "It has always been our belief that IT is best served by a single pane of glass view of its infrastructure, and to make that a reality for PRTG Network Monitor, we have incorporated the Docker Container Sensor. This new sensor affirms are longstanding commitment to our customers to provide a fully-featured, flexible and vendor-neutral monitoring solution."

The Docker Container Sensor displays values for each metric within channels in PRTG Network Monitor. Users can define threshholds in each specific channel that will affect the sensor's status and trigger notifications and alerts.

The Latest

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 ...

Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...

Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

Paessler Adds Support for Docker Container Monitoring

Paessler AG announced a new sensor type for its core product, PRTG Network Monitor, that enables users to monitor Docker containers, giving them key insights into performance, availability and other metrics.

PRTG Network Monitor is a comprehensive monitoring solution with more than 200 out-of-the-box sensor types, capable of monitoring everything from routers and switches to virtual machines and, now, Docker containers. Docker has become an increasingly popular technology with both DevOps teams and network administrators since its launch in 2013. Network administrators in particular have used containers to efficiently roll out and manage applications. With this progress in mind, Paessler created a dedicated Docker Container Sensor to give users the ability to monitor containers without the need to acquire a specific application performance monitoring solution. PRTG users can now monitor container status, uptime/downtime, CPU usage, memory, packets and traffic in/out, and exit code.

"IT should be able to monitor its entire infrastructure from one solution, and Docker is quickly becoming a part of that infrastructure," said Andrew Cutting, Director of Channel Sales, North America, Paessler. "It has always been our belief that IT is best served by a single pane of glass view of its infrastructure, and to make that a reality for PRTG Network Monitor, we have incorporated the Docker Container Sensor. This new sensor affirms are longstanding commitment to our customers to provide a fully-featured, flexible and vendor-neutral monitoring solution."

The Docker Container Sensor displays values for each metric within channels in PRTG Network Monitor. Users can define threshholds in each specific channel that will affect the sensor's status and trigger notifications and alerts.

The Latest

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 ...

Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...

Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...