In this guide to the Prometheus Certified Associate (PCA) certification, we will explore the resources needed to prepare for the exam, along with tips for passing the PCA certification.
The PCA, a certification from the Linux Foundation, primarily tests candidates on their knowledge of observability and Prometheus skills. In the DevOps certification landscape, PCA falls under the Observability category.
This guide covers everything you need to know about the Prometheus Certified Associate certification.
Prometheus Certified Associate Registration
The first step in the PCA certification exam is registration.
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Here is what you need to know about the exam.
- The PCA exam is to be taken online and it is proctored remotely. It is a closed book exam.
- After registration, you get 12 months to schedule the exam.
- You get one free retake if you fail on the first attempt. If you miss a scheduled exam for any reason – your second attempt gets nullified.
- Within 24 hours of completing the exam, you will get the exam results via email.
PCA Exam Details
I have organized all the PCA exam details in the following table.
Exam Duration | 90 minutes. |
Total Questions | 60 |
Exam Type | Multiple Choice Exam |
Pass Percentage | 75% (45 out of 60 questions) |
PCA Certification Validity | 2 Years |
Exam Cost | $250 USD |
Free Retake | One Retake |
Exam Language | Only English |
You can find other details from the following official Linux Foundation documentations.
- PCA Exam Instructions: Information about system requirements (PSI Secure Browser), location and ID card requirements.
- PCA FAQ’s: Commonly asked quested related to PCA exam.
Domains & Competencies
Now that you have a complete understanding of the exam, let’s look at the PCA exam syllabus with domains and competencies.
Domain | Concepts | Weightage |
---|---|---|
Observability Concepts | 1. Metrics 2. Understand logs and events 3. Tracing and Spans 4. Push vs Pull 5. Service Discovery 6. Basics of SLOs, SLAs, and SLIs | 18% |
Prometheus Fundamentals | 1. System Architecture 2. Configuration and Scraping 3. Understanding Prometheus 4. Limitations Data Model and 5. Labels Exposition Format | 20% |
PromQL | 1. Selecting Data 2. Rates and Derivatives 3. Aggregating over time 4. Aggregating over dimensions 5. dimensions 6. Binary operators 7. Histograms 8. Timestamp Metrics | 28% |
Instrumentation and Exporters | 1. Client Libraries 2. Instrumentation 3. Exporters 4. Structuring and naming metrics | 16% |
Alerting & Dashboarding | 1. Dashboarding basics 2. Configuring Alerting rules 3. Understand and Use 4. Alertmanager 5. Alerting basics (when, what, and why) | 18% |
PCA Lab
Even though the PCA is a multiple-choice exam, you need to have a running Prometheus setup to learn the concepts in detail.
You can start with a simple VM-based Prometheus setup and then move on to a Kubernetes-based setup based on the concepts you learn.
The following are the detailed guides that will help you setup a PCA exam lab.
- Setup Prometheus on Linux
- Setup prometheus stack using Docker Compose
- Setup Prometheus on Kubernetes
Note: I highly suggest you set up your own lab locally or on the cloud to learn all the Prometheus concepts better
PCA Preparation Guide
I have added all the Prometheus official documentation references and other useful authoritative resources for each concept that comes under the exam syllabus.
Observability Concepts
This section primarily deals with Observability concepts in general.
Resource | Concepts Covered |
---|---|
What is Observability | Metrics Understand logs and events Tracing and Spans |
Push vs pull in metrics collecting systems | Push vs Pull |
What is Service Discovery? | Service Discovery |
SRE Fundamentals | Basics of SLOs, SLAs, and SLIs |
Prometheus Fundamentals
This section deals with prometheus architecture, its components, storage, metric data format, metric labels and prometheus limitations.
Resource | Concepts Covered |
---|---|
What is Prometheus? | System Architecture |
Prometheus Configuration | Configuration and Scraping |
Prometheus Architecture Scalability | Prometheus Limitations |
Data Model | Data model and labels |
Exposition formats | Prometheus metric data format |
PromQL
PromQL (Prometheus Query Language) is the native query language for Prometheus. It lets you select and aggregate prometheus time series data in real time. It helps in analyzing and understanding the metrics scrapped by Prometheus.
Resource | Concepts Covered |
---|---|
Complete PromQL Guide | Selecting Data Rates and Derivatives Aggregating over time Aggregating over dimensions Binary operators Histograms Timestamp Metrics |
Instrumentation and Exporters
Instrumentation is a term typically used in application monitoring. In terms of prometheus, it is the process of configuring the application parameters to expose metrics in a format that Prometheus can scrape and store.
Exporters are like agents that capture application metrics and translate them into a data format that Prometheus can understand. For example, Node Exporter translates OS-level metrics like CPU, memory, disk, and network statistics to prometheus specific metric format.
Resource | Concepts Covered |
---|---|
List of client Libraries | Client Libraries |
How to Instrument | Instrumentation |
Exporters and Integrations | Exporters |
Practical Guide to Prometheus Metrics | Structuring and naming metrics |
Alerting & Dashboarding
Prometheus comes with a native alerting tool called Alert Manager. It can be configured with prometheus to trigger alerts based on Prometheus alert rules.
You can create Dashboards based on prometheus metrics using tools like Grafana. It support PromQL queries to create dashboards.
Resource | Concepts Covered |
---|---|
Alerting Rules | Configuring Alerting rules |
Alert Manager | Understand and Use Alertmanager |
Alerting Overview | Alerting basics (when, what, and why) |
Conclusion
Preparing for Prometheus Certified Associate required detailed learning of all prometheus related components and monitoring & alerting concepts.
PCA as a whole, not only enhances you knowledge on prometheus, but also on Observability, monitoring and alerting concepts. It will help you in your day-to-day DevOps/SRE job.
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