Monitoring
Monitoring is a process for the continuous observation and analysis of systems.
Classification
- ComplexityMedium
- Impact areaTechnical
- Decision typeArchitectural
- Organizational maturityAdvanced
Technical context
Principles & goals
Use cases & scenarios
Compromises
- Insufficient monitoring can lead to outages.
- Dependence on tools can be risky.
- Incorrect data can be misleading.
- Conduct regular reviews.
- Provide training for team members.
- Optimize based on data analyses.
I/O & resources
- Access to system resources.
- Install monitoring software.
- Provide configuration data.
- Real-time performance reports.
- Alerts for anomalous data.
- Analyses for system optimization.
Description
Monitoring allows organizations to observe the status of their systems in real-time. Early detection of issues and analysis of performance data are crucial for optimizing processes and systems. Effective monitoring supports improvements in efficiency and reliability.
✔Benefits
- Increased system availability.
- Improved response times to issues.
- Better decision-making through data.
✖Limitations
- High costs for implementation and maintenance.
- Requires specialized knowledge.
- Can lead to information overload.
Trade-offs
Metrics
- Response Time
The time taken to respond to requests.
- System Availability
The percentage of time the system is available.
- Error Rate
The proportion of requests that are erroneous.
Examples & implementations
Monitoring an Online Store
An online store implemented a monitoring system to observe availability and performance in real-time.
IT Infrastructure Monitoring
A company improved its IT infrastructure by implementing a monitoring system for issue detection.
Cloud Service Monitoring
A cloud service provider utilized monitoring to optimize the performance of its services.
Implementation steps
Identify needs and set objectives.
Select and install monitoring software.
Configure monitoring parameters.
⚠️ Technical debt & bottlenecks
Technical debt
- Outdated monitoring tools.
- Integrated systems with different standards.
- Lack of documentation for processes.
Known bottlenecks
Misuse examples
- Monitoring without clear objectives.
- Ignoring data that does not meet expectations.
- Incorrect interpretations of alerts.
Typical traps
- Overload with irrelevant data.
- Ignoring the user's perspective.
- Neglecting training.
Required skills
Architectural drivers
Constraints
- • Regulatory requirements must be observed.
- • Technology stack must be compatible.
- • Resource capacities are limited.