this article outlines the monitoring points and alarm practices for high-bandwidth cross-border links. it focuses on three types of indicators: network quality, resource utilization, and service availability. it provides reasonable thresholds, alarm classification, and suppression strategies. it also explains the deployment suggestions for collection points and alarm channels to facilitate the rapid implementation of the operation and maintenance team and reduce false alarms and omissions.
the first thing to pay attention to is the network layer: real-time upstream/downstream bandwidth usage, traffic mutation, packet loss rate, round-trip delay (rtt), and jitter (jitter); secondly, the host resources: cpu, memory, disk io, number of connections, and process abnormalities; on the business side, look at the tcp/http error rate, response time, and number of syn/established connections. for cross-border services, packet loss and delay have the greatest impact on user experience and should be regarded as core monitoring items.
thresholds should be set based on business peaks and historical data. recommended reference values: bandwidth usage continuously >80% (alarm), >90% (severe); packet loss rate >0.5% (warning), >1% (severe); average external network rtt >80–100ms (warning), >150ms (severe); cpu/memory usage >85% (warning), >95% (severe); disk io waiting time and queue length should also be configured with corresponding thresholds. the threshold supports both short-term burst and persistence determination (for example, the alarm will only be triggered if it continues to be triggered within 5 minutes).
adopt hierarchical alarms (information → warning → serious) and multi-condition triggers (such as high bandwidth and increased packet loss to trigger serious network alarms). introduce suppression and recovery strategies: short-term thresholds are used for detection and long-term thresholds are used for confirmation; repeat thresholds and silent windows are set to avoid short-term jitter and frequent alarms. combined with aggregation rules, the anomalies of multiple probes on the same link are cross-validated to reduce local false positives.
the monitoring system adopts multi-layer deployment: agents are installed in the hong kong computer room to collect host resources and link indicators, and external probes are deployed in domestic/other regions for active monitoring (ping/traceroute, tcp/http detection). in addition, it is recommended to observe the operator's intermediate links at the backbone interconnection point or cdn pre-probe to facilitate locating whether the problem is the computer room, cn2 backbone or international export.
although the cn2 link is stable, sudden black holes, route redistribution, or operator throttling may occur. customized alarms can identify abnormal link quality rather than pure bandwidth usage. route awareness (combined with bgp/route detection) can quickly locate whether it is a local computer room problem or an upstream operator change, avoiding misjudgment of upstream faults as vps resource problems, thereby reducing mishandling costs.
multi-channel parallel notification is adopted: sms/phone is used for serious alarms and duty wake-up, email/dingtalk/enterprise wechat is used for daily alarms and work order integration, and webhook/slack is used for automated response and operation and maintenance platform. configure hierarchical subscriptions and duty relays. severe events are automatically upgraded and continuously pushed until confirmed. important alarms are accompanied by diagnostic links and recent sampling charts to speed up response.

establish an alarm tuning closed loop: record the cause of each false alarm and adjust the threshold or collection frequency, and use alarm suppression rules to block known maintenance windows or large-scale confirmed events; combine runbooks and automated scripts (such as traffic speed limit, restart services, switch links) to achieve one-click or automatic processing, while retaining manual review steps to ensure automation is safe and controllable.
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