If you're new to Prometheus and want to understand what terms like target, job, instance, scrape, and alertmanager really mean, this guide will walk you through each concept in simple terms. Whether you're a developer setting up monitoring for your app or just exploring observability tools, this post will give you a solid foundation in Prometheus terminology.
1. Scrape: In Prometheus, scraping refers to the process of collecting metrics data from configured targets at regular intervals.
Unlike some other monitoring systems where the application pushes data to the monitoring tool, Prometheus pulls (scrapes) the data from endpoints that expose metrics, usually at a special URL like /metrics.
For example, Your application (e.g., a Spring Boot service) exposes metrics at an endpoint like:
http://localhost:8080/actuator/prometheus
In the Prometheus configuration file (prometheus.yml), you specify the job and its targets:
scrape_configs: - job_name: 'my-app' metrics_path: '/actuator/prometheus' static_configs: - targets: ['localhost:8080']
Prometheus will make a GET request to http://localhost:8080/actuator/prometheus every 15 seconds (by default). It reads all the metrics exposed and stores them in its time-series database.
2. Monitoring: It is the continuous process of systematically collecting, recording, and analyzing data from an application or system to track its performance, availability, and overall health. It involves observing various metrics such as response times, error rates, resource usage, and system logs to gain insights into how the system is functioning both in real-time and over extended periods.
Effective monitoring helps teams to identify issues, ensure that the system is operating within expected parameters, and verify whether it is meeting its intended objectives and service-level agreements (SLAs). This proactive approach is essential for maintaining system reliability, optimizing performance, and supporting troubleshooting and root cause analysis when problems arise.
3. Alerting: Alerting in Prometheus refers to the process of setting up predefined rules that continuously evaluate certain conditions or thresholds based on collected metrics. These rules help to detect when something abnormal or potentially harmful is happening in the system.
For example, a sudden spike in error rates, high memory usage, or service downtime. When a specified condition is met, Prometheus generates an alert and marks it as "firing," indicating that the issue is currently active. These alerts are then forwarded to Alertmanager, a companion tool that handles the routing, grouping, silencing, and notification of alerts. Alertmanager can send alerts through various communication channels like email, Slack, PagerDuty, or SMS, ensuring the right people are notified promptly to take action.
4. Alertmanager: Alertmanager is a critical component in the Prometheus monitoring ecosystem, responsible for handling and managing the alerts that Prometheus generates. Once Prometheus detects a condition that triggers an alert, it forwards that alert to Alertmanager, which then takes care of organizing and delivering it effectively.
Alertmanager performs several key functions to reduce alert fatigue and ensure relevant notifications reach the appropriate recipients. Alert fatigue occurs when system administrators, developers, or on-call engineers are bombarded with excessive alerts from monitoring systems. This often leads to stress, burnout, or even ignoring alerts altogether. Over time, critical alerts can be overlooked or delayed in response, increasing the risk of downtime or unresolved issues.
Alertmanager perform following activites.
· Grouping: It intelligently groups related alerts together to avoid overwhelming users with a flood of individual notifications.
· Deduplication: It eliminates duplicate alerts that may be triggered by the same underlying issue.
· Silencing: It allows users to temporarily mute alerts for known issues that are already being addressed, preventing unnecessary noise.
· Throttling: It controls the frequency of notifications to avoid sending too many alerts in a short period.
· Notification Routing: It sends alerts to various configured destinations such as email, Slack, PagerDuty, or XMatters, based on rules and receiver preferences.
Overall, Alertmanager plays a key role in ensuring that alerts are actionable, relevant, and delivered in a timely and manageable way.
5. Target: In the context of Prometheus, a target is any endpoint or system that Prometheus is configured to scrape (collect) metrics from. Essentially, a target is a source that exposes monitoring data in a format Prometheus understands. Targets typically provide metrics via an HTTP endpoint—usually at /metrics that Prometheus polls at regular intervals.
These targets can be various types of systems or applications, such as:
· A Spring Boot application with an actuator endpoint exposing Prometheus-formatted metrics.
· A Linux server, monitored using exporters like the Node Exporter.
· A Windows machine, using a compatible Windows exporter.
· Even Prometheus itself, since it can expose its own internal metrics.
In simple terms, if Prometheus scrapes metrics from something, that “something” is called a target.
6. Instance: In Prometheus, an instance refers to the specific network endpoint, typically a combination of a host (IP address or hostname) and a port, where Prometheus scrapes metrics. It represents a single running copy of a target service or application.
For example,
192.168.1.100:8080
This is an instance, it points to one particular service running on IP 192.168.1.100 and listening on port 8080.
If your application is running on three different servers (or the same server with different ports), each one is a separate instance of that application.
7. Job: In Prometheus, a job is a logical grouping of instances that perform the same or similar roles within a system. It's a way to organize multiple targets under a common label, making it easier to manage and analyze them together.
Think of a job as a label or category for a set of services that share the same purpose.
Example:
Job: "web_app"
Instances:
- 10.0.0.1:8080
- 10.0.0.2:8080
In this example, both instances are part of the "web_app" job, meaning they are likely running the same application and serving the same type of traffic. Prometheus uses this job name when labeling the metrics it scrapes from these instances.
8. Sample: A sample is a single numeric value representing a metric at a specific point in time. It’s what gets stored in the Prometheus time series database.
http_requests_total{method="get"} = 56
Here, 56 is the sample value recorded when Prometheus scraped this metric from a target.
Target vs Instance vs Job in Prometheus with a Practical Example
Imagine you're running a web application called "MyWebApp", deployed across three different servers to support scalability and high availability. Each server exposes Prometheus metrics on port 8080.
Additionally, you're monitoring the underlying Linux operating systems using the Node Exporter, which exposes system-level metrics on port 9100.
1. Job: my_webapp
A Job is a logical grouping of related targets that serve the same purpose. It helps you organize services in Prometheus.
Example jobs:
· my_webapp for the application metrics.
· node_exporter for the system metrics.
In your Prometheus configuration (prometheus.yml):
scrape_configs: - job_name: 'my_webapp' static_configs: - targets: - 'app-server-01.example.com:8080' - '10.0.1.15:8080' - 'app-server-03.example.com:8080' - job_name: 'node_exporter' static_configs: - targets: - 'app-server-01.example.com:9100' - '10.0.1.15:9100' - 'app-server-03.example.com:9100'
2. Targets: A target is an address (host:port) that Prometheus scrapes for metrics. Each target belongs to a job and can be an app endpoint (8080) or Node Exporter endpoint (9100).
For my_webapp job:
Targets: - app-server-01.example.com:8080 - 10.0.1.15:8080 - app-server-03.example.com:8080
For node_exporter job:
Targets: - app-server-01.example.com:9100 - 10.0.1.15:9100 - app-server-03.example.com:9100
3. Instances: An instance is a specific host:port combination that Prometheus actually scrapes. These are typically what show up in Prometheus metrics under the instance label.
Example Instances
|
Job |
Target |
Resolved IP |
Instance Label |
|
my_webapp |
app-server-01:8080 |
192.168.1.10 |
192.168.1.10:8080
|
|
my_webapp |
10.0.1.15:8080 |
10.0.1.15 |
10.0.1.15:8080 |
|
node_exporter |
app-server-01:9100 |
192.168.1.10 |
192.168.1.10:9100
|
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