What is your experience in troubleshooting in microservice architecture and what skills do you use for this?

To troubleshoot issues in a microservices architecture, I use a range of approaches and tools:

• Centralized logging: Collecting logs from all services into a single system (e.g., Elasticsearch, Fluentd, Kibana - EFK stack or Grafana Loki). This allows for quick correlation of events across services.
• Distributed tracing: Tracking the lifecycle of a request across different services (e.g., Jaeger, Zipkin). Helps identify bottlenecks and errors in the call chain.
• Monitoring and alerting systems: Setting up performance metrics (CPU, RAM, network activity, request count, delays) for each service and the overall infrastructure (Prometheus, Grafana, Zabbix). Alerts for anomalies.
• Profiling: Analyzing resource consumption and execution time in individual services to identify "heavy" operations.
• Post-mortem culture: Analyzing incidents to identify root causes and prevent recurrence.

Key skills:

• Understanding network protocols (TCP/IP, HTTP).
• Ability to work with logging, monitoring, and tracing tools.
• Knowledge of scripting languages (Bash, Python) for automation of analysis.
• Understanding of microservices operation principles, containerization (Docker), and orchestration (Kubernetes).
• Skills in reading and analyzing code, including identifying potential issues in asynchronous interactions.
• System thinking and problem decomposition skills.

Example of a command for request tracing using curl and debug headers:

# Sending a request with a tracing header (e.g., X-Request-Id)
curl -H "X-Request-Id: $(uuidgen)" http://my-service/api/v1/data

Example of log analysis with grep:

# Searching for errors within a specific time frame in centralized logs
grep "ERROR" /var/log/services/* | grep "2023-10-27T10"