Traffic Routing Failover with Active Hot Standby Clusters
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Solution Overview
Problem
Conventional network provisioning systems reactively address service degradations, leading to untimely traffic routing and prolonged service disruptions during data center failures, failing to maintain continuous uptime and customer service integrity.
Innovation Solution
Implementing an active hot standby (AHS) setup with a network provisioning engine (NPE) that proactively monitors and synchronizes clusters across primary and standby data centers, enabling real-time failover to resume transactions at the standby site when component failures occur.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional network provisioning systems are used, then system complexity is reduced, but service continuity and reliability deteriorate during data center failures
Solution Approach 1:
The system performs preliminary actions by proactively monitoring component health status and pre-synchronizing transaction data to standby data centers before failures occur. The NPE detects component failures in real-time and triggers automated failover to standby sites, ensuring service continuity without manual intervention. This resolves the contradiction by establishing complex monitoring and redundancy infrastructure that maintains reliability while managing system complexity through automation.
Solution Approach 2:
The system changes operational parameters by dynamically switching between active and standby data center configurations based on detected component health. When failures are detected, the system transitions traffic routing parameters from primary to standby sites, maintaining service continuity. This parameter-based approach resolves the contradiction by using automated state transitions rather than static architecture, improving reliability while keeping the system adaptable to failure conditions.
2Loss of time
If reactive traffic routing is used, then system simplicity is maintained, but service disruption time increases during failures
Solution Approach 1:
The system implements continuous feedback loops where the NPE monitors component health status in real-time and automatically triggers failover actions when thresholds are exceeded. This feedback mechanism reduces service disruption time by detecting failures immediately and initiating recovery procedures without manual intervention. The automation complexity is justified by the significant reduction in service disruption time achieved through real-time monitoring and automated response.
Solution Approach 2:
The system performs preliminary actions by pre-configuring standby data centers with synchronized transaction data and pre-established failover routing paths. When failures occur, the system can immediately activate pre-prepared recovery configurations, minimizing service disruption time. This approach resolves the contradiction by investing in automated preliminary setup that eliminates manual recovery procedures, reducing time loss despite increased automation complexity.
3Productivity
If manual failover procedures are used, then system complexity is reduced, but transaction resumption time increases
Solution Approach 1:
The system implements self-service automation where the NPE autonomously detects component failures, selects appropriate standby data centers, and executes failover procedures without human intervention. Transaction data is automatically synchronized to standby sites, and routing is dynamically updated to maintain processing continuity. This self-automating approach resolves the contradiction by using complex automated systems to eliminate manual procedures, significantly improving transaction continuity despite increased system complexity.
Data Source
AI summary
Embodiments of the present disclosure are directed to systems and methods for routing traffic to back-up clusters within a wireless communication system. A network provisioning engine (NPE) resumes an in-progress transaction at a standby site in an active hot standby (AHS) setup. As such, the present disclosure is directed to a proactive method of traffic routing in which an AHS setup is used in conjunction with an NPE. The present disclosure also detects and identifies system issues to trigger failover in real-time or near real-time. Every NPE includes a set of clusters. Every cluster being processed at a first data center is paired up with the same set of clusters (e.g., back-up clusters) at a second data center to ensure that geographic redundancy is maintained. When the first data center experiences a disruption, the second data center picks up with processing the transaction where the first data center left off.