The Prometheus text-based exposition format and data model are built around four core metric types. These are:

1. Counter: A cumulative metric that represents a single monotonically increasing counter whose value can only increase or be reset to zero on restart. It is ideal for tracking request counts, tasks completed, or errors.

2. Gauge: A metric that represents a single numerical value that can arbitrarily go up and down. Gauges are typically used for measured values like temperatures, memory usage, or the number of concurrent requests.

3. Histogram: Samples observations (e.g., request durations or response sizes) and counts them in configurable buckets. It also provides a sum of all observed values.

4. Summary: Similar to a histogram, a summary samples observations but calculates configurable φ-quantiles over a sliding time window.

A. 40: This number is incorrect and does not align with the defined metric types in the official Prometheus data model.

C. 8: This is an incorrect count. The Prometheus specification explicitly defines four primary metric types.

D. 10: This is an incorrect count and does not reflect the number of metric types supported by Prometheus.

1. Prometheus Authors. (n.d.). Metric types. Prometheus Documentation. Retrieved from https://prometheus.io/docs/concepts/metrictypes/. The entire page is dedicated to describing the four core metric types: "The Prometheus client libraries offer four core metric types. These are currently only differentiated in the client libraries (to enable APIs tailored to the usage of the specific types) and in the wire protocol." The document then lists and details Counter, Gauge, Histogram, and Summary.

2. Schwarzkopf, M. (2020). Lecture 15: Cluster Monitoring. In CS 149: Parallel Computing. Stanford University. Retrieved from http://cs149.stanford.edu/fall20/lecture/15/notes.pdf. On slide 28, the notes explicitly list the "Four types of Prometheus metrics" as Counter, Gauge, Histogram, and Summary.