Evaluating Prometheus Knowledge in Interviews (PromCon 2018)
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The document discusses Brian Brazil's experience and contributions to Prometheus, including insights on hiring Prometheus developers and evaluating their skills using a simplified programming task like FizzBuzz. It suggests practical methods to filter candidates based on their experience and knowledge of PromQL, emphasizing a reasonable approach rather than looking for overly experienced individuals. Additionally, it outlines the FizzBuzz challenge for evaluating basic understanding and provides steps for a solution using Prometheus recording rules.
Evaluating Prometheus Knowledge in Interviews (PromCon 2018)
- 1. Brian Brazil Founder Evaluating Prometheus Knowledge in Interviews
- 2. Who am I? ● One of the developers of Prometheus ● Author of Prometheus: Up&Running ● Primary author of Reliable Insights blog You may have heard of me :)
- 3. Looking Back.. Two years I gave a lightning talk on "An Exploration of the Formal Properties of PromQL" demonstrating that PromQL was Turing Complete via Conway's Life. Last year I gave a talk on "Rule 110 for Prometheus", a simpler demonstration of the above.
- 4. Filtering With the growth of the ecosystem you may looking to hire an employee with existing experience to assist you on your Prometheus journey. How can you filter the wheat from the chaff?
- 5. CV You could look at someone's experience with Prometheus ● Are they a Prometheus developer? ● Have they written a book? ● Do they have a well known blog? ● Have they demonstrated esoteric PromQL knowledge? But the technology is fairly new, and this is a high bar. No one has 10+ years of experience with Prometheus after all!
- 6. Low Pass Filter Rather than looking for a unicorn, how about instead throwing away applicants that are pretty obviously faking it until they make it. From there you can more deeply consider the remaining applicants. Enter FizzBuzz.
- 7. FizzBuzz Write a program that prints the numbers from 1 to 100. But for multiples of three print “Fizz” instead of the number and for the multiples of five print “Buzz”. For numbers which are multiples of both three and five print “FizzBuzz”. Source: http://wiki.c2.com/?FizzBuzzTest
- 8. FizzBuzz for Prometheus FizzBuzz is a trivial programming task, that an experienced programmer should have no problem coding up. We could use this to evaluate PromQL knowledge, and thus get an idea if someone has at least a very basic understanding of Prometheus.
- 9. Let's do it then! FizzBuzz is a trivial problem, but let me share my solution.
- 10. Input Data We'll need some input data for the for loop. We can build it up with a recording rule.
- 11. Input Recording Rule record: input expr: > ( input or count_values("number", (input + 1) <= 100) * on() group_left max(input) + 1 or vector(0) )
- 12. Output From there we need to filter based on the values. PromQL has a modulus operator, and label_replace can do strings, so this isn't hard.
- 13. Output Recording Rule record: output expr: > ( label_replace(input % 15 == 0, "output", "FizzBuzz", "", "") or on (number) label_replace(input % 5 == 0, "output", "Buzz", "", "") or on (number) label_replace(input % 3 == 0, "output", "Fizz", "", "") or on (number) label_replace(input, "output", "$1", "number", "(.*)") )
- 14. Output Result The answer is right, but out of order. That can be fixed.
- 15. Output Recording Rule - v2 record: output expr: > ( label_replace(input % 15 == 0, "output", "FizzBuzz", "", "") or on (number) label_replace(input % 5 == 0, "output", "Buzz", "", "") or on (number) label_replace(input % 3 == 0, "output", "Fizz", "", "") or on (number) label_replace(input, "output", "$1", "number", "(.*)") ) * 0 + on(number) group_left input > 0
- 16. Output Result v2 and Sorted The values now match in input number, so we can do sort(output)!
- 17. Resources Book: http://shop.oreilly.com/product/0636920147343.do Robust Perception Blog: www.robustperception.io/blog Queries: prometheus@robustperception.io