KCNA Cloud Native Observability Practice Question
A team is designing a Kubernetes observability stack and wants to use Prometheus for metrics. They need to understand how Prometheus collects and stores time series data. Which TWO of the following statements accurately describe Prometheus? (Choose two.)
⚠ Common exam trap
The trap here is assuming that Prometheus is a distributed system with automatic cluster-wide discovery, when it is actually a single-node scraper that requires explicit configuration and stores data locally.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Prometheus pulls metrics from targets by scraping HTTP endpoints at regular intervals.
Prometheus is a pull-based monitoring system that scrapes HTTP endpoints and stores samples in a local append-only time-series database. It does not depend on distributed consensus, does not require proprietary SDKs, and does not automatically scrape all pods without configuration. The two accurate statements describe its core collection and storage mechanisms, which are essential to understand when designing a Kubernetes observability stack.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Prometheus requires a distributed consensus protocol to ensure data consistency across all nodes.
Why it's wrong here
Prometheus is not a distributed consensus-based system; it is typically run as independent single-node servers that scrape and store data locally. It does not use a consensus protocol like Raft to coordinate writes across nodes. While remote write and federation can aggregate data, the core Prometheus server does not rely on distributed consensus for consistency, so this statement is incorrect.
- ✓
Prometheus pulls metrics from targets by scraping HTTP endpoints at regular intervals.
Why this is correct
Prometheus uses a pull-based model, actively scraping configured targets over HTTP at defined intervals. This is a core design characteristic and is how it collects metrics from exporters, kubelets, and instrumented applications. The statement accurately reflects the scraping mechanism, so it is one of the correct descriptions of how Prometheus operates in a Kubernetes observability stack.
- ✗
Prometheus automatically discovers and scrapes all pods in a cluster without any configuration.
Why it's wrong here
Prometheus does not automatically discover and scrape all pods by default. It relies on configuration, often through Kubernetes service discovery roles, and requires scrape configs or ServiceMonitor/PodMonitor custom resources when using the Prometheus Operator. Without explicit configuration, Prometheus will not know which endpoints to scrape, so this statement overstates its out-of-the-box behavior.
- ✗
Prometheus can only collect metrics that are pushed to it by applications using a proprietary SDK.
Why it's wrong here
Prometheus primarily uses a pull model and supports open standards like the Prometheus exposition format; it does not require a proprietary SDK. Applications can expose metrics via client libraries, exporters, or the Pushgateway for batch jobs. The claim that it can only collect pushed metrics with a proprietary SDK misrepresents Prometheus's design and supported collection methods.
- ✓
Prometheus stores data in a local time-series database optimized for append-only writes.
Why this is correct
Prometheus includes its own time-series database (TSDB) that stores samples locally and is optimized for append-only ingestion. It compresses and indexes data for efficient queries. This is a fundamental architectural fact, and the statement correctly describes the storage layer, making it a valid description of how Prometheus handles metrics data in this scenario.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official CNCF exam blueprint
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