PACS and DICOM observability
The PACS and DICOM network are the backbone of medical imaging workflow. When something goes down or slows, studies are lost, radiologists can't read and the hospital's clinical operation jams. But observability of these systems is usually limited to generic IT metrics, not to the clinical logic of DICOM.
The PACS doesn't only fail when it's down — it fails much earlier
A PACS rarely goes fully down. What happens often is degradation: rising latency, C-STORE or C-MOVE timeouts, intermittent errors in the acquisition queue, DICOM integrations with modalities that disconnect without anyone noticing. The study eventually uploads, but the technician has lost time and confidence in the system erodes.
In most hospitals, PACS monitoring depends on the vendor or on the generic IT team. The first sees what affects their contractual SLAs. The second sees uptime and CPU. What's missing is the in-between layer: the DICOM/HL7 logic of the clinical workflow itself.
That intermediate layer is what tells "the PACS is down" apart from "the PACS is losing 3% of MR studies during peak hours and no one has noticed in six weeks".
Operational metrics no uptime check captures
Beyond the classic "alive or dead", useful PACS/DICOM observability covers five dimensions that affect real clinical experience.
End-to-end DICOM latency
Time from the modality sending a study to it being available to the radiologist. The mean hides outliers; the distribution and high percentiles tell the truth.
DICOM timeouts and errors
Failed C-STORE, C-MOVE, C-FIND. Patterns by modality and by time of day reveal network or capacity issues before a uptime dashboard does.
Study integrity
Incomplete studies, series with missing instances, inconsistent metadata. Data-quality issues are invisible to most IT monitoring.
Modality integration health
Each modality has its own AET, its own configuration and its own failure point. A view per modality catches when one has disconnected from the PACS.
System load under real clinical flow
Used capacity vs total, IO, queues — not as plain server metrics but contextualised: how does the PACS behave during morning peak? On a Friday at 6 p.m.?
Argus complements the PACS, it does not replace it
Argus focuses on the technical observability of the physical imaging equipment and the telemetry layer around the clinical workflow. PACS/DICOM-specific observability is a natural use case — we approach it in discoveries with the hospital's IT team and the PACS vendor, not as a replacement but as an additional visibility layer.
Explore ArgusWhat teams ask us about PACS and DICOM
How is PACS observability different from generic IT monitoring?
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The protocol layer and the clinical logic. Generic IT monitoring tells you whether the server is alive and how much CPU it uses. PACS observability tells you whether studies are arriving, whether latency is acceptable for clinical workflow and whether the integrations with each modality are healthy.
Do you need access to the PACS to monitor it?
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Depends on the depth. For network and protocol metrics, visibility on DICOM traffic is enough. For study integrity and internal metrics, it usually requires collaboration with the PACS vendor or the hospital IT team.
Does it cover RIS in addition to PACS?
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The RIS provides workflow context (order, patient, resource). The integration between RIS, modality and PACS is a frequent silent-failure point. Covering that integration end-to-end is a natural progression of any clinical observability project.
Does it replace the hospital's IT team?
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No. The IT team remains the operational owner. Argus provides an additional clinical-visibility layer that generic IT tools don't, and operates in collaboration.
Silent issues with your PACS?
If your hospital or clinical group operates PACS and RIS and you suspect signals are being lost on the DICOM network, let's talk. We'll run a technical discovery with you.