If you want to apply as a support engineer at Datadog you are in the right spot. Read on, it's fun, I promise.

Don't forget to read the References.

• Sign up for Datadog, get the agent reporting metrics from your local machine.
• Bonus question: what is the agent?
• Submit an event via the API.
• Get an event to appear in your email inbox (the email address you signed up for the account with)

• Take a simple web app (in any of our supported languages) that you've already built and instrument your code with dogstatsd. This will create metrics.
• While running a load test (see References) for a few minutes, visualize page views per second. Send us the link to this graph!
• Create a histogram to see the latency; also give us the link to the graph
• Bonus points for putting together more creative dashboards.

Using the same web app from level 2:

• tag your metrics with support (one tag for all metrics)
• tag your metrics per page (e.g. metrics generated on / can be tagged with page:home, /page1 with page:page1)
• visualize the latency by page on a graph (using stacked areas, with one color per page)

Same web app:

• count the overall number of page views using dogstatsd counters.
• count the number of page views, split by page (hint: use tags)
• visualize the results on a graph
• Bonus question: do you know why the graphs are very spiky?

Let's switch to the agent.

• Write an agent check that samples a random value. Call this new metric: test.support.random

Here is a snippet that prints a random value in python:

import random
print(random.random())

If you have a question, create an issue in this repository.

To submit your answers:

1. Fork this repo.
2. Answer the questions in answers.md
3. Commit your code for question #4.
4. Submit a pull request.
5. Don't forget to include links to your dashboard(s)

• Datadog overview
• Guide to graphing in Datadog

• API docs
• Guide to the Agent
• Libraries
• Guide to Metrics

• Writing an agent check

Load testing

• ab
• tsung