Monitoring and logging are complementary practices providing visibility into system behaviour. Monitoring tracks metrics (CPU, memory, requests) enabling detection of issues. Logging records events enabling understanding of what happened during problems. Together, monitoring and logging enable rapid issue detection and diagnosis, guided improvements, and compliance validation.
Monitoring Fundamentals
Monitoring tracks system health:
Metrics - Quantitative measurements (CPU, memory, response time, error rate).
Thresholds - Alerting when metrics exceed acceptable ranges.
Collection - Agents on systems report metrics to central repository.
Aggregation - Combining metrics from multiple sources.
Visualisation - Dashboards showing system health.
Alerting - Notifying teams when issues are detected.
Effective monitoring enables proactive issue detection before customers are impacted.
Key Metrics
Essential metrics to monitor:
System metrics - CPU, memory, disk utilisation.
Application metrics - Request rate, response time, error rate.
Business metrics - Orders, revenue, user count.
Infrastructure metrics - Network throughput, database connections.
User experience metrics - Page load time, application availability.
Choosing appropriate metrics guides system optimisation.
Logging Fundamentals
Logging records events:
Log levels - DEBUG, INFO, WARN, ERROR, FATAL indicate severity.
Structured logging - Logging as structured data (JSON) enabling parsing and analysis.
Log collection - Logs forwarded to central repository.
Log aggregation - Combining logs from multiple sources.
Search and analysis - Querying logs to understand issues.
Retention - Storing logs for compliance and troubleshooting.
Comprehensive logging enables understanding what happened during problems.
Log Aggregation Tools
Tools centralise logging:
ELK Stack - Elasticsearch, Logstash, Kibana for log aggregation and analysis.
Splunk - Comprehensive log analysis and monitoring.
CloudWatch (AWS) - AWS-integrated logging and monitoring.
Datadog - Cloud-hosted monitoring and logging.
New Relic - Application performance monitoring and logging.
Centralised logging enables searching and correlating logs across systems.
Monitoring Tools
Tools enable monitoring:
Prometheus - Open-source metrics collection and alerting.
Grafana - Visualisation and dashboarding for metrics.
CloudWatch (AWS) - AWS monitoring service.
Datadog - Cloud-hosted monitoring platform.
New Relic - Application performance monitoring.
Elastic - Metrics and monitoring with Elasticsearch backend.
Tool choice depends on existing infrastructure and scale.
Application Performance Monitoring (APM)
APM tools understand application behaviour:
Request tracing - Following individual requests through systems.
Distributed tracing - Understanding requests across microservices.
Dependency mapping - Understanding service dependencies.
Performance analysis - Understanding where time is spent.
Error tracking - Identifying and understanding errors.
APM enables understanding complex, distributed systems.
Alerting Strategy
Effective alerting requires careful configuration:
Alert thresholds - Triggering on meaningful conditions, avoiding false positives.
Escalation - Increasing response priority as situation worsens.
On-call rotations - Ensuring coverage for various types of issues.
Runbooks - Documentation guiding response to specific alerts.
Alert fatigue - Too many alerts cause ignoring valid ones. Keep alert count reasonable.
Effective alerting enables rapid response without overwhelming teams.
Distributed Tracing
Tracing requests across systems:
Trace IDs - Unique IDs following requests through systems.
Span creation - Recording work in each service.
Context propagation - Passing trace context between services.
Latency analysis - Understanding where time is spent.
Error tracking - Identifying which service caused errors.
Distributed tracing is essential for understanding microservice systems.
Metrics vs. Logs vs. Traces
Understanding the differences:
Metrics - Aggregated data over time (CPU at 75 per cent).
Logs - Individual events (User login at 10:23:45).
Traces - Request flows through systems.
All three are necessary for comprehensive visibility.
Monitoring and Logging at PixelForce
PixelForce implements comprehensive monitoring and logging for all production systems. CloudWatch provides AWS metrics and logs; APM tools provide application performance visibility; custom dashboards show system health. This visibility enables rapid issue detection and diagnosis, critical for maintaining the 98.2 per cent client satisfaction we achieve.
SLOs and SLIs
Measuring reliability:
Service Level Objectives (SLOs) - Target reliability (99.9 per cent uptime).
Service Level Indicators (SLIs) - Measurements of reliability (actual uptime).
Error budgets - Allowed downtime before missing SLOs. Guides deployment decisions.
Monitoring SLOs - Tracking actual performance against targets.
SLOs and SLIs align teams on reliability expectations.
Cost of Monitoring
Monitoring and logging have costs:
Storage - Logs and metrics require storage.
Ingestion - Processing and storing data costs.
Retention - Balancing retention requirements with cost.
Sampling - For high-volume systems, sampling reduces costs.
Aggregation - Pre-aggregating data reduces storage.
Optimising monitoring cost whilst maintaining visibility is important.
Security and Privacy
Protecting sensitive data:
Data masking - Removing sensitive data from logs and metrics.
Access control - Limiting who can view logs and metrics.
Encryption - Protecting data in transit and at rest.
Compliance - Meeting regulatory requirements (GDPR, HIPAA).
Audit trails - Recording who accessed sensitive data.
Security is essential when handling production data.
Conclusion
Monitoring and logging provide essential visibility into system behaviour. By collecting appropriate metrics, aggregating logs, analysing data, and alerting effectively, organisations detect issues rapidly, understand root causes, and continuously improve systems. Comprehensive monitoring and logging are fundamental to reliability and operational excellence.