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Monitoring and Logging

Centralized Logging

  1. Log Aggregation:
  2. Implement centralized log aggregation using tools like ELK Stack (Elasticsearch, Logstash, Kibana) or managed services like AWS CloudWatch Logs, GCP Logging, or Azure Monitor.
  3. Configure applications and infrastructure components to send logs to the centralized logging system.

  4. Ensure logs are structured and include important metadata such as timestamps, severity levels, and request IDs.

  5. Log Retention and Management:

  6. Set log retention policies based on regulatory requirements and business needs.
  7. Implement log rotation and archiving to manage storage costs and ensure log availability.
  8. Use tools like AWS S3 Lifecycle Policies, GCP Object Lifecycle Management, or Azure Blob Storage lifecycle policies to automate log retention and deletion.

Comprehensive Monitoring

  1. Metrics Collection:
  2. Collect system metrics (CPU, memory, disk, network) and application metrics (response time, error rates) using tools like Prometheus, Datadog, or cloud provider native tools.

  3. Implement custom metrics for specific application performance indicators.

  4. Dashboards:

  5. Create dashboards to visualize key metrics and provide an at-a-glance view of system health.

  6. Use tools like Grafana, Datadog, or cloud provider dashboards to create interactive and customizable dashboards.

  7. Service Monitoring:

  8. Monitor critical services like databases, caches, and message queues to ensure they are functioning correctly.
  9. Use tools like AWS RDS Performance Insights, GCP Cloud Monitoring, or Azure Monitor for specialized service monitoring.

Alerting

  1. Alert Policies:
  2. Define alert policies for critical metrics and events, such as high CPU usage, low disk space, or increased error rates.

  3. Set up thresholds and conditions for triggering alerts.

  4. Alert Routing:

  5. Use alerting tools like PagerDuty, OpsGenie, or cloud provider native tools to route alerts to the appropriate on-call team members.

  6. Configure escalation policies to ensure critical alerts are addressed promptly.

  7. Alert Noise Reduction:

  8. Implement strategies to reduce alert noise, such as setting appropriate thresholds, using deduplication, and implementing alert suppression during maintenance windows.
  9. Regularly review and refine alerting rules to minimize false positives.

Example Implementation

  1. Set Up Centralized Logging with ELK Stack:
  2. Deploy Elasticsearch, Logstash, and Kibana on AWS EC2 instances.
  3. Configure Logstash to collect logs from various sources, such as application servers, database servers, and network devices.

  4. Set up Kibana dashboards to visualize logs and create alerts for specific log patterns.

  5. Implement Comprehensive Monitoring with Prometheus and Grafana:

  6. Deploy Prometheus to collect metrics from application servers, databases, and other infrastructure components.
  7. Create Grafana dashboards to visualize Prometheus metrics and set up alerts for critical conditions.

  8. Configure Prometheus Alertmanager to route alerts to PagerDuty.

  9. Set Up CloudWatch Alarms and Dashboards in AWS:

  10. Configure CloudWatch to collect metrics from AWS services like EC2, RDS, and Lambda.
  11. Create CloudWatch dashboards to visualize metrics and monitor system health.
  12. Set up CloudWatch Alarms to trigger notifications for critical metrics and integrate with SNS to route alerts to on-call engineers.