Abstract
- Basically collecting info from different components of the system to help us to better manage the system. We can use tools like Datadog for this task
- Improving the system’s Reliability (可靠性)
Metric
- A time-bound information related to a system captured at a certain point in time like per second/min
- Collecting different types of metrics help us to gain business insights and understand the health status of the system
Aggregated Level Metric
- Metric that indicates the top-level health of system by measuring its useful output
- Examples are success rate & error rate
Host Level Metric
- Metric that indicates timely information of physical resources like CPU & Main Memory
- Examples are utilisation
Key business metrics:
- Daily active users, retention, revenue
Log
- A detailed list of Events that happen within the system/application
- Examples can be web server log which contains the IP, data & time of HTTP Request
- Monitoring error logs is important because it helps to identify errors and problems in the system
- We can use Datadog to aggregate them for easy search and viewing
Log Router
- A tool or service that collects log data from various sources and forwards or routes it to one or more destinations
- Play a crucial role in centralized logging architectures, especially in environments with multiple applications, services, or systems that generate logs
- Examples are Fluentd, Fluent Bit(If you need a lightweight, high-performance log shipper, especially for containerized or edge environments, Fluent Bit is the way to go), Logstash (part of the ELK Stack), and AWS FireLens (for Amazon ECS and EKS)