In Datadog, monitors are used to keep track of the health and performance of your systems, infrastructure, and applications. A monitor evaluates data from your metrics, logs, or traces to trigger alerts when certain conditions are met. There are several types of monitors, each with specific use cases and configurations.

Metric monitors are used to track the value of metrics over time. These monitors allow you to define thresholds for certain metrics and receive alerts if the metric exceeds or falls below the threshold.

- Types of Metric Monitors:

1. Threshold-based monitors: Alerts are triggered when the metric value crosses a specified threshold.
2. Anomaly detection: Alerts are triggered if a metric deviates from its expected behavior, based on historical data patterns.
3. Outlier detection: Alerts are triggered when a metric exhibits significantly different behavior from the majority of similar entities.

- Example use cases:

1. Monitoring CPU usage or memory usage on servers.
2. Tracking request counts or response times in web applications.

- Configuration:

To create a metric monitor, select the metric you wish to track, define the threshold, and specify the evaluation conditions (e.g., above, below, or within a certain range).

Log monitors are used to monitor logs for specific patterns or conditions. These monitors trigger alerts when certain log events occur, such as error messages or specific keywords.

- Types of Log Monitors:

1. Threshold-based monitors: Alerts are triggered based on the count of log entries within a time frame.
2. Pattern-based monitors: Alerts are triggered when specific text patterns or log entries are detected.
3. Error monitoring: Alerts are triggered when error logs or specific error messages are detected.

- Example use cases:

1. Monitoring for specific error logs (e.g., “500 Internal Server Error”).
2. Tracking log events related to system failures or security breaches.

- Configuration:

When creating a log monitor, you can define the search query (e.g., specific log text or patterns) and set thresholds for the count of logs to trigger an alert.

APM monitors focus on monitoring traces and performance data from your applications. These monitors help you track the performance of your services and quickly identify issues such as slow requests, latency, or errors in your distributed systems.

- Types of APM Monitors:

1. Service-level monitoring: Alerts are triggered based on latency, error rates, or throughput of a service.
2. Resource-level monitoring: Alerts are triggered based on the performance of individual resources (e.g., databases or microservices).
3. Trace-based monitoring: Alerts are triggered based on trace-level metrics such as request duration or error rates.

- Example use cases:

1. Monitoring the response time of an HTTP API endpoint.
2. Tracking database query performance or error rates.

- Configuration:

In APM monitors, you specify the service, endpoint, or resource to monitor, and configure the alert conditions based on the performance metrics such as request latency or error percentage.

Integration monitors are pre-configured monitors based on Datadog's integrations with various third-party services. These monitors track service-specific metrics and can alert you about problems in integrations like databases, cloud services, web servers, and other technologies.

- Example use cases:

1. Monitoring AWS EC2 instances or RDS performance.
2. Tracking Docker container health or Kubernetes cluster metrics.

- Configuration:

Integration monitors can be configured by installing the relevant Datadog integration for the service you want to monitor. Most integrations provide predefined monitors that you can customize based on your needs.

Synthetics monitors are used to simulate user interactions with your application or website and ensure that key user flows (such as logins or form submissions) are functioning properly. These monitors can alert you if the synthetic tests fail.

- Types of Synthetics Monitors:

1. API tests: Simulate HTTP requests to your API endpoints to ensure they are responsive and returning the expected results.
2. Browser tests: Simulate end-to-end user interactions with your website using real browser-based tests to ensure functionality.

- Example use cases:

1. Monitoring the availability and functionality of your public API.
2. Ensuring key user flows on your website are working (e.g., login, checkout).

- Configuration:

You define the tests (either browser or API) you want to run and configure the frequency and alerting conditions (e.g., failure rate or response time).

Network monitors track network-related metrics and events, such as bandwidth usage, packet loss, and network latency, to ensure the health of your network infrastructure.

- Types of Network Monitors:

1. Network performance: Alerts are triggered when network performance metrics fall below acceptable thresholds.
2. Network events: Alerts are triggered based on changes in network behavior, such as sudden traffic spikes or drops.

- Example use cases:

1. Monitoring network bandwidth usage on specific interfaces.
2. Tracking network errors or unusual spikes in traffic.

- Configuration:

Configure network monitors by selecting the relevant network metric (e.g., `system.net.bytes_recv`) and defining the threshold conditions for the alert.

Custom monitors are created by defining your own queries and conditions based on any data available in Datadog, such as custom metrics or logs that are not covered by built-in monitors.

- Example use cases:

1. Monitoring custom application metrics not covered by existing Datadog integrations.
2. Creating alerts based on aggregated data from multiple sources.

- Configuration:

You can define custom monitors using Datadog’s query language, selecting the appropriate data sources and alert conditions.

Datadog provides a wide variety of monitor types to meet the monitoring needs of your systems, infrastructure, and applications. Whether you're monitoring metrics, logs, APM data, or synthetic tests, Datadog's monitors can help you keep track of system health and trigger timely alerts when things go wrong. By selecting the appropriate monitor type, you can ensure the smooth operation of your entire infrastructure.