What problems have you encountered during product deployment and how did you mitigate them?

• Environment mismatch (dev, staging, production): Differences in library versions, OS settings, or environment variables led to incorrect behavior. Solution – using containerization (Docker) and orchestration systems (Kubernetes) to create a uniform environment, as well as automated deployment scripts.
• Dependencies: Internal and external dependencies might be unavailable or have incorrect versions during deployment. Mitigation – using dependency management systems (Go Modules), private repositories for internal dependencies, and strict versioning.
• Configuration errors: Incorrect values in configuration files or environment variables caused startup failures. Solution – centralized configuration management (HashiCorp Vault, Kubernetes Secrets/ConfigMaps), configuration validation before launch, using dotenv files for local development.
• Network or access issues: Port blocking, incorrect firewall settings, or access restrictions to necessary resources (databases, APIs). Mitigation – careful planning of network infrastructure, using VPNs or secure connections, automated network accessibility tests during deployment.
• Insufficient resources: Lack of CPU, memory, or disk space on servers led to crashes or unstable operation. Solution – resource monitoring, load planning, using auto-scaling and horizontal scaling.
• Lack of automation: Manual deployment increased the risk of errors and was time-consuming. Mitigation – implementing CI/CD pipelines (GitLab CI, GitHub Actions, Jenkins) for automation of build, testing, and deployment.
• Rollback issues: Failed deployments without a proper rollback mechanism led to prolonged downtime. Solution – implementing automated rollback to the previous stable version within CI/CD pipelines, using orchestration tools supporting rolling updates and rollbacks.
• Monitoring and logging: Lack or insufficiency of monitoring and logging complicated problem diagnosis after deployment. Mitigation – setting up centralized logging systems (ELK stack, Grafana Loki) and monitoring (Prometheus, Grafana) with dashboards and alerts.

Example code for automated deployment (simplified, within a CI/CD script):

#!/bin/bash

# Build Docker image
docker build -t my-app:${CI_COMMIT_SHORT_SHA} .

# Login to Docker Registry
docker login -u ${DOCKER_USER} -p ${DOCKER_PASSWORD} ${DOCKER_REGISTRY}

# Push image to Registry
docker push ${DOCKER_REGISTRY}/my-app:${CI_COMMIT_SHORT_SHA}

# Update deployed application in Kubernetes
kubectl set image deployment/my-app my-app=${DOCKER_REGISTRY}/my-app:${CI_COMMIT_SHORT_SHA} --namespace production