Your routers, switches, and firewalls have been monitored by a tool that knows nothing about your applications or your security — and your application observability has been blind to the network underneath it. 24Observe ends that split. Poll your devices over SNMP, take in their event streams, alert on interface and link health, and let one analyst reason across the network and the services that ride on it.
Ask most teams how they watch the network and you will hear the name of a tool that does exactly one thing, lives on its own server, and has never once heard of the applications running across the links it polls.
That separation made sense in 1998. It makes no sense now. When checkout slows to a crawl, the cause might be a saturated uplink, a flapping interface, a routing change a network engineer made an hour ago, or a failover that quietly cut capacity in half — and none of that is visible from the application side, because the application tools cannot see the network and the network tool cannot see the application. So two teams open two sets of dashboards, argue about whose problem it is, and burn an hour proving it was the network all along.
The cost of the silo is not just duplicate tooling. It is the gap in the middle, where an incident lives that neither side can see whole. The network team sees a device event with no business context. The application team sees latency with no idea what changed underneath them. The truth — that a two-line routing change took down a dozen services — sits in the seam between the two products, invisible to both.
24Observe closes the seam by putting the network on the same platform as everything else. The same place that holds your logs, your metrics, your uptime checks, and your security detections holds your device health and device events too. One console, one alerting pipeline, and one analyst that can look at the device event and the service impact together and tell you, in plain language, which caused which.
The outage was rarely just the app or just the network. It was the network and the app — and the answer was hiding in the gap between two tools that never spoke.
Network gear cannot run software agents, so 24Observe does not ask it to. A lightweight collector runs on a host inside your network and reaches the devices the way they expect to be reached.
One small collector per network segment is enough; a handful covers a large estate. It runs on an ordinary Linux host and reaches outward to the devices — nothing touches the routers and firewalls themselves.
Enable SNMP with a read community or credential and add the device addresses. The collector polls interface throughput, error and discard counters, link state, and device CPU and memory on a steady cycle — the vital signs of every port and box.
Point each device’s logging at the collector and its syslog flows in: configuration changes, interface up/down, routing-adjacency changes, authentication events, and high-availability failovers — normalised so they search and alert consistently.
Device metrics feed threshold alerts; device events feed the infrastructure and security detections; and every incident is investigated by the analyst against the live map of what depends on that device. The network is now a first-class citizen of your operations and security workflow.
Throughput, utilisation, errors, and discards per port — so a saturating uplink or a flapping interface is a threshold alert, not a customer complaint.
CPU and memory on the device itself — control-plane exhaustion and creeping resource pressure caught before the box falls over.
Interface up/down and routing-adjacency changes from the device’s own events — the upstream cause of most multi-service outages.
Every running-config write surfaced with who and when, so the change that broke the network is the first thing the analyst checks.
Failover and role-change events flagged immediately, so a silent loss of redundancy does not become an outage in waiting.
Brute-force against management planes, scanning, and known-bad sources, watched on the network alongside your other detections.
Because the device telemetry lands on the same platform as everything else, the analyst can reason across the boundary that used to hide the truth.
When a routing change on an edge router takes down a wave of services, the analyst sees both halves: the device event and the service impact. It names the device as the common upstream cause, points at the change that triggered it, and tells you the fix — instead of leaving two teams to argue over a boundary neither can see across. This is the single capability a standalone network tool can never offer, because it does not know your applications exist.
Your devices and the services that depend on them appear together in a live topology map with a health overlay. A node turns red when it stops reporting or an incident implicates it, so the blast radius of a failed device is visible at a glance — what is down, and everything downstream of it. See the context graph.
An interface saturating and an application erroring open the same kind of incident, route through the same channels, and obey the same on-call schedule. No second alerting tool for the network, no separate escalation policy, no reconciling two pagers. The network simply joins the queue your team already works — and benefits from the same alerting and storm-grouping as the rest.
One collector fronts a whole segment, so scaling to hundreds of devices is a matter of collectors, not licences-per-port gymnastics. For a managed-service provider, every customer is an isolated tenant: run a collector in each network, keep the data cleanly separated, and operate them all from one console with the same analyst working every one.
Most network incidents do not announce themselves. They build quietly for hours, invisible to a tool that only flips between up and down, until the symptoms reach a customer and the ticket lands on the NOC. Here are the everyday failures the platform surfaces while they are still cheap to fix.
The slowly saturating uplink. A link does not fail at eighty percent utilisation — it just gets slower, retransmits more, and quietly degrades every service that crosses it. A simple up/down monitor sees nothing wrong because the link is, technically, up. A threshold on interface utilisation sees the curve climbing and opens an incident while you still have time to shift traffic or add capacity, instead of after checkout has been mysteriously slow for an afternoon.
The flapping interface. An interface that bounces up and down every few minutes is one of the most disruptive faults in networking and one of the easiest to miss — each individual flap looks like a blip. Watching the link-state events together turns a scatter of blips into a clear pattern and a single incident, so a failing transceiver or a marginal cable is replaced before it takes a segment with it.
The silent failover. A high-availability pair fails over, the standby takes the load, and everything keeps working — so nobody notices. Except now you are running on one device with no redundancy, one fault away from a real outage, and you will not find out until the second device also fails at the worst possible moment. The failover event is flagged the instant it happens, so a silent loss of redundancy becomes a same-day fix, not a future catastrophe.
The change that broke routing. Someone makes a well-intentioned edit to a routing policy, a neighbour relationship drops, and traffic quietly reroutes the long way around — or stops reaching part of the network entirely. Because the configuration change and the adjacency-down event both arrive on the same platform, the analyst can put them side by side and tell you the change at 14:02 caused the reachability problem at 14:03, instead of leaving you to suspect a change you cannot see.
The creeping error counter. Interface error and discard counters climbing slowly are the early warning of duplex mismatches, bad optics, and congestion — the kind of fault that shaves a few percent off performance for weeks before anyone connects the dots. Surfaced as a trend with a threshold, it becomes a ticket you open on your terms, not a degradation users learn to live with.
The exhausted control plane. A device whose CPU or memory is creeping toward its limit will, eventually, stop forwarding or stop responding to management — and it rarely gives much warning at the moment it tips over. Watching device CPU and memory the same way you watch a server’s catches the slow climb, so an overloaded box is rebalanced or upgraded before it becomes an outage.
Every one of these is invisible to a tool that only knows reachable-or-not, and every one of them is a quiet tax on reliability that the network team pays in firefighting. Watching the real signals — utilisation, errors, link state, config changes, failovers, device health — turns reactive 3 a.m. surprises into proactive, business-hours maintenance. And because it all lands on one platform with the analyst, the rare time a failure does cascade, you get the cause and the blast radius in seconds rather than a war room.
Stand up a collector, point your devices at it, and watch interface health, device events, and config changes land on the same platform — and the same investigation — as your applications.