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Case study

One Monitoring View Across 14 Device Types for a National Healthcare Network

How SquareShift unified monitoring across 14 network and security devices for a national healthcare authority, correlating about 10 million events a minute through one platform.

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Line drawing of a hospital building with a gold cross on its front
35role-based dashboards, so each team sees only its own data
10million events correlated every minute across the fleet

Client

A public-sector healthcare authority that runs a nationwide network of hospitals and primary care clinics.

Industry

Healthcare

Services

ObObservability & Reliability

Stack

Elasticsearch · SNMP · Syslog · Index Lifecycle Management (ILM)

How SquareShift delivered it.

01

The challenge

The client is a public-sector healthcare authority running a nationwide network of hospitals and primary care clinics. Its facilities ran on a mixed fleet of legacy and modern devices, and monitoring data arrived through inconsistent protocols and formats, with no shared layer to correlate it across teams.

02

What we delivered

SquareShift built custom SNMP and syslog adapters that normalize data from the client's mixed device fleet into one common format, then routed it through Elastic ingest pipelines with lifecycle policies to keep long-term storage costs down.

The team built 35 role-based dashboards, so each group sees only the data relevant to its own operations instead of piecing it together from disconnected tools.

03

The outcome

Observability now covers 14 network and security devices through one correlated pipeline instead of disconnected tools, processing roughly 10 million events a minute. The healthcare authority has one shared, role-based view across its whole device fleet for the first time. To see how we run monitoring on Elastic, read about our Elastic search and observability services.

“
A hospital network's device fleet is rarely uniform, and it doesn't need to be. Normalizing everything into one schema at ingest is what lets 35 different dashboards trust the same underlying data.

Observability & Reliability Practice Lead, SquareShift

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