System Health Monitoring

Overview#

Reactive incident response is expensive. By the time a user reports a problem, the root cause may have been building for hours. The System Health Monitoring module shifts operations from reactive to predictive by detecting degradation trends in performance metrics before they cross the threshold that produces user-visible symptoms. When issues do occur, alert correlation reduces hundreds of individual signals to a small number of actionable incidents.

Key Features#

Multi-Tier Health Checks: Continuous validation across infrastructure, application, and business layers. Monitor server and container resources, database connectivity and query performance, cache availability, queue throughput, storage capacity, and API responsiveness with configurable check frequencies.
Predictive Alerting: Statistical analysis detects degradation trends before failures occur. The system identifies anomalous patterns in performance metrics and predicts potential issues minutes before they impact users, enabling preemptive action rather than reactive response.
Alert Correlation and Deduplication: Automatically correlate related alerts into unified incidents. Intelligent deduplication groups similar alerts, identifies root causes, and presents actionable incident summaries rather than individual alert noise that overwhelms on-call teams.
Automated Remediation: Configure automated responses to common failure patterns including service restarts, resource scaling, traffic rerouting, and cache clearing. All automated actions are logged and can require approval for sensitive environments.
Service Dependency Mapping: Visualise service dependencies and understand how component failures cascade through your infrastructure. Dependency-aware health scoring identifies the true blast radius of issues and prioritises remediation accordingly.
Custom Health Checks: Define application-specific validation including business logic verification, integration connectivity, data pipeline health, and custom metric thresholds. Extend monitoring beyond infrastructure to cover your complete operational landscape.
Multi-Channel Alerting: Route alerts through email, Slack, Microsoft Teams, PagerDuty, OpsGenie, and custom webhooks with configurable severity levels, escalation paths, on-call schedules, and quiet hours.
Historical Analysis and Trending: Retain health metrics for trend analysis, capacity planning, and post-incident review. Compare performance across time periods and deployments, and track how system changes affect long-term health.

Monitoring Domains#

Compute: CPU utilisation, memory consumption, container health, process counts, and resource saturation
Storage: Disk capacity, I/O throughput, latency, replication status, and growth projections
Network: Bandwidth utilisation, latency, packet loss, DNS resolution, and connectivity checks
Database: Connection pool health, query performance (platform record store primary), replication lag, and lock contention
Application: Response times, error rates, throughput, queue depths, and business transaction health
External Services: Third-party API availability, response times, and integration health

Use Cases#

Critical infrastructure operators monitoring systems where degradation has safety implications, using predictive alerting to act before operational thresholds are breached.
Government departments maintaining SLA commitments on citizen-facing services with automated escalation when metrics approach contractual boundaries.
Financial institutions tracking database performance and queue health for transaction processing systems where latency directly affects business outcomes.
Healthcare providers monitoring clinical system availability with dependency mapping that shows which downstream services are affected by any given component failure.

Open Standards#

Prometheus Exposition Format (OpenMetrics): Health and performance metrics (HTTP request counters, latency histograms, platform record store pool gauges, rate-limit counters) are exposed at a /metrics scrape endpoint in the Prometheus text exposition format, compatible with Prometheus and any OpenMetrics-compliant collector.
OpenTelemetry (OTLP): Distributed traces are produced via the OpenTelemetry developer toolkit and exported over OTLP/HTTP to any compatible backend (Tempo, Jaeger, or cloud-native collectors), enabling end-to-end latency and error analysis across service dependencies.
W3C Trace Context (Level 1): Every inbound and outbound HTTP request carries traceparent and tracestate headers per the W3C Trace Context specification, ensuring correlated traces propagate correctly across system boundaries without vendor lock-in.
HTTP Liveness and Readiness Probes: Dedicated /health (liveness) and /ready (readiness) endpoints return HTTP 200 or 503 following the Kubernetes probe convention, allowing container orchestrators and load balancers to gate traffic on real dependency availability.
JSON Web Token (RFC 7519): Administrative and metrics endpoints are access-controlled using JWT Bearer tokens; the organisation scope claim embedded in each token enforces tenant isolation on all health data returned via the API.
ISO 8601 Timestamps: All health event records, alert timestamps, incident open/close times, and metric data points are serialised as ISO 8601 UTC strings, ensuring unambiguous interoperability with external monitoring tools and SIEM systems.
OAuth 2.0 and JWT Bearer Token: Token-based authentication protects typed, auditable read and write workflows across the platform.

Getting Started#

Configure Health Checks: Enable monitoring for your infrastructure components and set appropriate check frequencies.
Set Alert Thresholds: Define warning and critical thresholds based on your operational requirements and SLA commitments.
Configure Alert Routing: Set up notification channels, on-call schedules, and escalation paths for your operations team.
Define Remediation Rules: Configure automated responses for common failure patterns to reduce manual intervention.
Establish Baselines: Allow the system to learn normal performance patterns before activating anomaly detection.

Integration#

Monitoring Tools: Prometheus, Grafana, Datadog, New Relic, and cloud-native monitoring services
Alerting Channels: PagerDuty, OpsGenie, Slack, Microsoft Teams, email, and custom webhooks
Cloud Providers: AWS CloudWatch, Azure Monitor, and GCP Operations Suite

Last Reviewed: 2026-02-05 Last Updated: 2026-04-14