Paessler PRTG gives your IT team deep visibility into network devices, servers, and infrastructure sensors. Atatus gives your engineering team request-level traces, real user sessions, and AI-powered anomaly detection across your entire application stack.
PRTG is built around sensors — every metric you monitor is a sensor, and the platform excels at collecting and graphing thousands of them across network devices, servers, and cloud resources. But when a sensor goes red, your engineers still need to find out which application component, which transaction, and which user is affected. PRTG cannot answer those questions. Atatus is built to answer exactly those questions.
Atatus instruments your application code directly, capturing every request from the user's browser through your API layer, microservices, and database calls with full span-level timing at every hop. PRTG collects sensor data from network devices and servers but has no mechanism to trace a request through application code or link a sensor alert to a specific user-facing transaction.
PRTG alerts fire when a sensor value crosses a configured warning or error threshold. Atatus uses machine learning to baseline the normal performance of every transaction and endpoint, detecting behavioral drift — a p95 rising steadily, an error rate increasing on a specific endpoint, a query slowing after a deployment — before any sensor metric reports an issue at the infrastructure level.
PRTG monitors the infrastructure delivering your application. It has no browser agent and no ability to measure what real users experience when they interact with your product. Atatus captures Core Web Vitals, session-level timing, and JavaScript errors from real browsers in production, giving engineering teams the user perspective that sensor-based monitoring was never designed to provide.
Here is where Atatus delivers application observability that PRTG was not built to provide, for engineering teams who need visibility at the request, code, and user level.
PRTG reports sensor health across your infrastructure. A specific API endpoint returning 500s with all server and network sensors within range produces no PRTG alert. Atatus captures every exception, groups it by fingerprint, links it to the failing endpoint, and shows exactly how many user sessions are affected in real time.
PRTG sensor thresholds fire on discrete metric values. A checkout endpoint whose p95 has risen from 250ms to 950ms over two hours, with all server CPU and memory sensors within range, produces no alert. Atatus AI detects the performance drift per transaction and fires before users notice a problem, without requiring a manually configured threshold per endpoint.
PRTG has no browser agent and no client-side visibility. A JavaScript exception that breaks your signup or payment flow in a specific browser version is entirely invisible to PRTG sensors. Atatus captures it from real user browsers, groups it by error fingerprint, and surfaces the affected page URLs and user session count immediately.
PRTG can check database connectivity and basic response but has no visibility into individual query performance. Atatus captures every database call with normalized SQL, execution time, call frequency, and the application transaction responsible for each call, showing exactly which code paths are generating the most expensive queries and how that maps to user-facing latency.
Atatus tracks deployments and immediately correlates each release with changes in error rates, response time distributions, and query behavior per endpoint. When a new version introduces a regression, Atatus surfaces it within minutes alongside the affected transactions and full stack traces. PRTG has no deployment context and no code-level regression detection capability.
PRTG pricing is based on the number of active sensors. Every metric you monitor counts against your license, and sensor counts grow quickly as infrastructure expands. Atatus uses predictable per-seat pricing where APM, RUM, error tracking, logs, and synthetics are all included in one plan with no per-sensor or per-metric billing.
A technical breakdown of where each platform focuses and what the gaps mean for engineering teams managing modern application stacks.
Full-stack APM with distributed tracing from browser to database across Node.js, Python, Ruby, Java, .NET, PHP, Go
Real User Monitoring capturing Core Web Vitals, session detail, and JS error correlation from real browsers in production
AI anomaly detection that baselines every transaction and endpoint, alerting on behavioral drift before sensor-level metrics report an issue
Error tracking with auto-grouped server and browser exceptions linked to affected transactions, user sessions, and release versions
Log management with structured log ingestion unified with traces and metrics in one platform without switching tools
Synthetic monitoring with HTTP and browser checks from 20+ global locations at per-minute intervals
Infrastructure monitoring for host metrics, containers, and Kubernetes alongside APM and RUM data in one unified view
Predictable per-seat pricing with all capabilities in every plan and no per-sensor or per-metric billing
No APM — PRTG collects infrastructure sensor data but does not instrument application code or produce distributed request traces at any layer
No Real User Monitoring — browser performance, user session data, and Core Web Vitals are entirely outside the PRTG sensor model
Threshold-based sensor alerting — alerts fire when sensor values cross configured warning and error thresholds; no ML-based anomaly detection at the application transaction level
No application error tracking — PRTG monitors sensor health across infrastructure but has no visibility into code-level exceptions or application stack traces
No log management — structured application log ingestion, search, and trace correlation are not part of the PRTG platform
HTTP and web checks available — PRTG HTTP sensors check endpoint availability and response time but with no browser rendering or real user experience measurement
Deep infrastructure and network monitoring — strong SNMP, WMI, NetFlow, and agentless sensor coverage for network devices, servers, VMs, and cloud resources
Sensor-based license model — pricing scales with the number of active sensors; costs grow quickly as infrastructure expands and sensor counts increase
“We had PRTG covering our infrastructure and it did that job well. But the moment an incident touched the application layer, our developers had nothing. No traces, no query data, nothing. The network team and the engineering team were essentially running separate investigations on the same problem. That gap cost us a lot of time. Atatus closed it.”
What teams running Paessler PRTG most commonly want to know before evaluating Atatus.
They address different layers of the monitoring stack. PRTG is a strong infrastructure and network monitoring platform with broad sensor coverage for network devices, servers, VMs, IoT, and cloud resources particularly valuable for IT operations teams managing complex physical and hybrid infrastructure. Atatus covers the application and user experience layer: distributed tracing, RUM, error tracking, log management, and AI-based anomaly detection at the transaction level. Atatus also includes host, container, and Kubernetes infrastructure monitoring, so engineering teams whose primary need is application observability can cover both layers with Atatus. Teams with significant PRTG network monitoring investments typically run both, using PRTG for infrastructure and network sensor data and Atatus for application-level observability.
PRTG alerting fires when a sensor value crosses a configured warning or error threshold. This is reliable for discrete metric changes but requires you to know in advance what to alert on and at what value, and it misses gradual performance drift. Atatus ML-based anomaly detection learns the normal performance pattern for each application transaction and endpoint automatically, alerting when behavior deviates from the learned baseline without requiring per-transaction threshold configuration. Regressions that develop slowly over hours are caught significantly earlier with behavioral baselining than with fixed sensor thresholds.
Atatus monitors application hosts, containers, and Kubernetes but does not provide SNMP-based network device monitoring, NetFlow bandwidth analysis, IoT sensor monitoring, or the broad infrastructure sensor coverage that PRTG is built for. If your team manages network hardware, industrial devices, or requires thousands of infrastructure sensor metrics, PRTG is the right tool for that layer. Atatus covers everything happening inside the application and user experience layer running above that infrastructure.
PRTG pricing is based on sensor count tiers such as 500, 1000, 2500, 5000, and XL licenses. Every metric you monitor consumes a sensor, and teams must actively manage sensor counts to avoid hitting license limits. Atatus uses a per-seat model where APM, RUM, error tracking, log management, and synthetics are all included in one plan. Costs are publicly listed, scale with team size rather than metric count, and are straightforward to forecast as your application and infrastructure grow.
PRTG has a relatively fast setup for infrastructure monitoring, a single installer and auto-discovery scan gets network sensors running quickly. For application observability, Atatus is faster still: agents install with a single command per language runtime and most teams see their first application traces within 5 minutes. Adding RUM is one script tag on your frontend. There are no sensor configurations, probe setups, or device definitions required to start seeing transaction-level application data.
Yes. Atatus holds SOC 2 Type II certification and is GDPR compliant. All data is encrypted in transit and at rest. Data residency options are available on Enterprise plans and full security documentation including penetration test results is available on request for compliance and procurement review processes.
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