Building a Closed‑Loop ‘Monitor‑Manage‑Control’ System for Bank IT Operations

Background

Rapid digital transformation in a commercial bank introduced big‑data and AI services, which increased the requirements for reliable, real‑time monitoring of IT infrastructure and business applications. Existing monitoring tools were fragmented, provided expert‑only dashboards, and offered limited automation, creating a need for a unified, standardized monitoring framework.

Key Issues

Monitoring data were scattered across multiple platforms, resulting in inconsistent alert policies and duplicated data collection.

Visualization focused on technical staff; frontline operators lacked concise, actionable views.

Automation covered only a few scenarios and there was no systematic workflow for developing, testing, and deploying remediation scripts.

Closed‑Loop "Monitor‑Manage‑Control" Architecture

1. Monitor – Data Collection and Event Processing

Adopt ITM and Zabbix as the core agents. Use standard protocols (syslog, SNMP) to ingest events from storage, network, and security devices.

Normalize alerts through an Omnibus layer and forward them to SMS gateways and ITIL ticketing systems, establishing a consistent incident‑handling workflow.

Instrument application servers to emit formatted transaction logs. Forward these logs to a big‑data analytics platform (e.g., Hadoop/Kafka‑based) for centralized collection, archiving, and visual analytics.

Introduce heartbeat logs that record periodic health checks, enabling real‑time availability monitoring of each service.

Deploy AIOps modules that perform statistical anomaly detection on alerts and business logs, automatically generating fault‑diagnosis suggestions.

2. Manage – Integrated Operations Management Platform

Automate registration of monitoring objects (hosts, services, components) and the deployment of corresponding monitoring policies. The platform calls the underlying Zabbix/ITM APIs to push configurations in real time.

Define a hierarchical model: Asset → KPI → Monitoring Policy → Monitoring Coverage. Encode each policy as a structured record, enabling version control and audit trails.

Integrate with the CMDB to import authoritative asset information. The CMDB data feed supplies the platform with up‑to‑date topology, which is also exposed to disaster‑recovery (DR) systems.

3. Control – Automated Inspection and Remediation

Develop 16 predefined inspection‑and‑remediation workflows covering major alarm categories (e.g., prolonged online‑banking transaction latency). Example workflow: detect latency → trace middleware bottleneck → disable front‑end transaction flag → restart affected process → re‑enable flag.

Standardize disaster‑recovery procedures with coordinated multi‑system failover schedules. The platform generates orchestration scripts that respect dependency order and timing constraints.

Expose a unified API that links alarm events to their corresponding remediation playbooks, allowing operators to trigger or schedule tasks from a single console.

Benefits

Visualization of the full service map (applications ↔ infrastructure ↔ business services) enables rapid impact assessment and priority ranking.

Automated synchronization of monitoring policies guarantees data consistency between CMDB, monitoring agents, and DR systems.

The centralized data‑mid‑platform supplies clean, timestamped events for AIOps pipelines (clustering, root‑cause analysis, predictive alerting).

Future Directions

Maintain online synchronization of monitoring objects (CMDB‑driven) and policies (monitoring‑system‑driven) while instituting periodic manual verification to ensure data quality.

Expand the knowledge base of scenario‑based remediation scripts, reducing manual intervention and improving mean‑time‑to‑repair (MTTR).

Leverage the unified data lake as a reliable source for advanced AI/ML models, enabling proactive fault prediction and capacity planning.

Conclusion

The "monitor‑manage‑control" closed‑loop framework provides a systematic, automated, and AI‑enhanced approach to banking IT operations. By consolidating data collection, policy management, and automated remediation, the solution improves operational efficiency, lowers risk, and creates a virtuous cycle of continuous improvement.