ERP

ERP Performance Monitoring and Alerting Setup

Proactive ERP performance monitoring transforms the support model from reactive firefighting to predictive prevention. Instead of learning about performance problems from frustrated users, a well-instrumented monitoring system detects degradation trends, alerts on threshold violations, and provides the diagnostic data needed for rapid root cause analysis. Comprehensive ERP monitoring spans four layers: infrastructure (CPU, memory, disk, network), database (wait statistics, query performance, blocking), application (response times, error rates, session counts), and business process (transaction throughput, batch job durations, integration queue depths).

Monitoring Stack Architecture for ERP

The modern ERP monitoring stack combines time-series metrics collection, log aggregation, and visualization. Prometheus collects metrics from exporters deployed on ERP infrastructure, Grafana provides dashboards and alerting, and Loki or Elasticsearch aggregates log data. For SQL Server-based ERP systems, the SQL Server exporter for Prometheus collects DMV metrics (wait statistics, query performance, buffer cache hit ratio) at configurable intervals. Windows Server metrics come from the Windows Exporter (cpu, memory, disk, network). Application-level metrics require custom instrumentation or APM tools (Datadog, New Relic, Application Insights).

  • Deploy Prometheus with SQL Server exporter to collect DMV metrics every 15-30 seconds from ERP database servers
  • Install Windows Exporter on ERP application and database servers for CPU, memory, disk I/O, and network metrics
  • Configure Grafana dashboards with ERP-specific panels: database waits, query durations, connection pool status, and user sessions
  • Implement Loki or Elasticsearch for centralized ERP application log aggregation with structured log parsing
  • Deploy APM agents (Datadog, New Relic, Application Insights) on ERP application servers for transaction-level tracing

Key Metrics and Dashboard Design for ERP

ERP monitoring dashboards should answer three questions at a glance: Is the ERP system healthy right now? Is performance trending in the right direction? Where should I investigate if something is wrong? The top-level dashboard shows traffic light indicators for each tier (green/yellow/red), with drill-down dashboards for database performance, application server health, and business process monitoring. Key metrics include ERP login response time (user experience proxy), database buffer cache hit ratio (memory adequacy), top wait types (bottleneck indicator), and active session count (demand level).

  • Track ERP login page response time as the primary user experience metric: alert when p95 exceeds 3 seconds
  • Monitor SQL Server buffer cache hit ratio: sustained values below 95% indicate insufficient memory for the ERP database workload
  • Dashboard the top 5 SQL Server wait types with 5-minute rolling averages to detect bottleneck shifts in real time
  • Track ERP concurrent session count with historical overlay to identify abnormal usage patterns or license compliance issues
  • Monitor ERP batch job durations (MRP, posting, EDI) with trend lines: gradual increases indicate growing data volumes requiring attention

Alerting Strategy and Escalation Procedures

Effective ERP alerting requires carefully calibrated thresholds that minimize false positives while catching real problems early. Alert fatigue from noisy thresholds causes teams to ignore alerts, defeating the purpose of monitoring. Use tiered alerting: warning thresholds that log to dashboards for awareness, and critical thresholds that page on-call staff for immediate action. Each alert must include context: what metric violated what threshold, the current value, the recent trend, and a link to the relevant diagnostic dashboard. Define runbooks for each critical alert that guide responders through initial triage steps.

  • Define two-tier thresholds: warning (dashboard notification) at 70% of critical, and critical (page on-call) at absolute limits
  • Configure alert deduplication and cooldown periods (5-10 minutes) to prevent alert storms during cascading ERP failures
  • Include diagnostic context in every alert: metric name, current value, threshold, 1-hour trend graph, and dashboard deep link
  • Create runbooks for each critical alert documenting triage steps, common root causes, and escalation contacts with response SLAs
  • Review alert history monthly: tune or remove alerts with >10% false positive rate and add alerts for incidents that were user-reported

Want proactive visibility into your ERP system health? Netray sets up comprehensive monitoring with Grafana dashboards and intelligent alerting--schedule an implementation.