A dashboard is a visual interface that presents selected observability data so people can monitor system health, trends, objectives, and business-relevant outcomes. section 5.1.4 section 5.1
Dashboards reduce the cost of understanding a system when they unify metrics, logs, traces, and other data sources. Fragmented views force developers, SREs, business owners, and other stakeholders to assemble the overall picture themselves. section 5.1.4 section 5.2.1
Effective dashboard ownership separates product-specific insight from shared observability infrastructure:
- Development teams create dashboards for their services and define alerts around operational context such as response times and error rates. section 5.2.3
- Platform teams manage metrics scraping, trace ingestion, storage, dashboard hosting, and the tools that make dashboards available. section 5.2.3
- Baseline dashboards, alerts, and monitors should be maintained in code so starter kits and CI/CD pipelines can manage them consistently. section 5.2.1 section 5.3.1
SLO dashboard
An SLO dashboard can show the target SLO, current error-budget consumption, remaining monthly budget, warning and critical statuses, performance trends, and burn-rate charts. These views let platform teams assess objective attainment and distinguish platform faults from problems elsewhere. section 5.4.1
Table 5.1 Tools used by Epetech across the eight different axes of observability
| Axis |
Tool Used |
| Infrastructure |
Prometheus (metrics collection) + Grafana (Dashboarding) |
| Application |
DataDog |
| Service Health |
Pingdom |
| Incident Response |
PagerDuty |
| Portfolio |
JIRA |
| Platform |
DataDog |
| Cloud Costs |
IBM Kubecost |
| Business |
Tableau |
Compare the observability tools used across infrastructure, application, service health, incident response, portfolio, platform, cloud-cost, and business views. section 5.1.4
