Learning Fullstack Observability: Metrics

(Originally published on Medium) Introduction According to RedHat: Observability refers to the ability to monitor, measure, and understand the state of a system or application by examining its outp...

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Learning Fullstack Observability: Metrics

Source: DEV Community

(Originally published on Medium) Introduction According to RedHat: Observability refers to the ability to monitor, measure, and understand the state of a system or application by examining its outputs, logs, and performance metrics. OpenTelemetry is a vendor-neutral framework for observability, and is made of 3* main pillars: Metrics Traces Logs (* Profiles are an upcoming 4th pillar, but still in development) In the “Expense Tracker” series, this article will be the first of 3 where I apply OpenTelemetry to my app, primarily with the Grafana stack: In order to find out which REST API requests are the slowest, what services are hogging the most memory, and how saturated my web server's thread pool is, I need to track the numbers behind them, and the tool fit for that is the first in this observability series: Prometheus. For Expense Tracker, the exporters I’m interested in include: Node exporter: for my Linux VMs Windows exporter: for my host machine MySQL exporter: for my database NGi

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