Code-Memo

Monitoring and Logging

1. Understanding Monitoring and Logging

a. What is Monitoring?

• Definition: Monitoring involves continuously observing the system’s performance, health, and operational metrics to ensure that it operates efficiently and remains available. It helps in detecting anomalies, identifying trends, and responding to incidents in real-time.
• Purpose:
  • Detect and alert on system failures or performance issues.
  • Provide visibility into system behavior and resource usage.
  • Enable proactive management and optimization of system performance.

b. What is Logging?

• Definition: Logging is the process of recording events, transactions, and system activities in log files or databases. Logs provide a detailed account of system operations and interactions, which is crucial for debugging, auditing, and compliance.
• Purpose:
  • Record system events for analysis and troubleshooting.
  • Maintain an audit trail for security and compliance.
  • Provide detailed information for post-incident analysis.

2. Monitoring Methods

a. Infrastructure Monitoring:

• Components Monitored:
  • Servers: CPU usage, memory utilization, disk I/O, network bandwidth.
  • Databases: Query performance, connection counts, transaction rates.
  • Network: Latency, packet loss, throughput.
• Tools: Nagios, Zabbix, Datadog, Prometheus, Grafana.

b. Application Monitoring:

• Components Monitored:
  • Application Performance: Response times, error rates, throughput.
  • User Interactions: Session durations, page load times, transaction success rates.
• Tools: New Relic, AppDynamics, Dynatrace.

c. Real-Time Monitoring:

• Purpose: Provides immediate visibility into system performance and operational status.
• Components: Real-time dashboards, alerts, and notifications.
• Tools: Datadog, Grafana, Prometheus.

d. Synthetic Monitoring:

• Purpose: Simulates user interactions to test the availability and performance of applications from various locations.
• Tools: Pingdom, Uptrends, Catchpoint.

e. APM (Application Performance Monitoring):

• Purpose: Monitors the performance of applications, including transaction tracing, database performance, and application dependencies.
• Tools: New Relic, Dynatrace, AppDynamics.

3. Logging Methods

a. Log Collection:

• Types of Logs:
  • Application Logs: Events, errors, transactions, and debug information.
  • System Logs: OS-level events, hardware status, and system services.
  • Access Logs: User interactions, API requests, and security events.
• Tools: Logstash, Fluentd, Filebeat.

b. Log Storage:

• Options:
  • File-Based Storage: Local or networked log files.
  • Database Storage: Relational or NoSQL databases.
  • Cloud-Based Storage: Managed log storage services.
• Tools: Elasticsearch, AWS CloudWatch Logs, Google Cloud Logging.

c. Log Analysis:

• Purpose: Analyzes logs to identify patterns, detect anomalies, and derive insights.
• Tools: Kibana, Grafana, Splunk.

d. Log Management:

• Purpose: Manages log lifecycle, including retention policies, archival, and deletion.
• Tools: Logrotate, ELK Stack (Elasticsearch, Logstash, Kibana), Graylog.