Offers a real-time view of microservices' health and performance using Grafana, enabling quick access to metrics for streamlined operations and troubleshooting.
Role
Personal project
Timeline
2023
Grafana dashboards
Real-time
// architecture
Sources
AWS Services
CPU, network, billing
Database
Storage + latency
Lambda
Logs
GitHub
Repo activity
Collect
CloudWatch
Metrics + logs
GitHub API
Project activity
Host
EC2 + Docker
Grafana runtime
Ansible
Provisioning
Expose
ALB + Reverse Proxy
Routed access
Route 53
DNS
Visualize
Grafana
Health dashboards
Context
To understand observability hands-on, I built a monitoring stack that surfaces the health and performance of a set of microservices in real time, so issues are visible at a glance instead of buried in logs.
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Challenges
Avoided overcomplicating the deployment while keeping the monitoring stack manageable.
Needed to consolidate metrics from multiple cloud services into one readable operational view.
Had to expose Grafana securely behind AWS networking, DNS, and routing components.
Approach
Hosted Grafana on an AWS EC2 Linux instance with supporting monitoring packages.
Connected Grafana to AWS CloudWatch and other service data sources for metrics and logs.
Used Docker and Ansible to make deployment and configuration more repeatable.
Outcomes
Built a centralized dashboard for CPU, billing, network, database, Lambda, and GitHub activity.
Improved visibility into the health and behavior of cloud microservices.
Gained a clearer sense of where automation adds value versus where it creates unnecessary complexity.