Infrastructure Monitoring and Business Analytics
What you must know
Infrastructure Monitoring extends visibility beyond the app tier to servers, databases, and network via Machine Agents, Server Agents, and Database Agents. Candidates should understand hardware/OS metrics (CPU, memory, disk, network), database monitoring for engines like MySQL, Oracle, and SQL Server, and how infrastructure health rules and tiers/nodes relate. Business Analytics (now Analytics) collects transaction and log data into a searchable store, enabling funnel analysis, segment/cohort analysis, ADQL queries, and custom dashboards. Know the difference between metric data (time series) and analytics event data (searchable records) and how data collectors feed analytics.
Traps
A common trap is confusing Machine Agent (infrastructure/hardware) with APM agent (application). Another is assuming all transaction data lands in Analytics by default - analytics collection must be enabled/configured. Watch for questions that treat ADQL like SQL; it queries the analytics event store, not a relational database. Also distinguish health rules on infrastructure from application health rules, and remember database agent metrics are separate from APM backend metrics.
Worked example / rule of thumb
A funnel shows drop-off between cart and checkout. Rule of thumb: use Analytics for behavior, Infrastructure for cause. Query analytics events with ADQL to find the drop-off segment, then check infrastructure and APM metrics for that timeframe to see whether a resource bottleneck (CPU, DB) explains it. If the data is missing, verify analytics collection is enabled for those BTs.
Key concepts checklist
- Machine/Server/Database agents
- Hardware and OS metrics
- Analytics event store and ADQL
- Funnel and segment analysis
- Data collectors feeding analytics