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-Your answers to the questions go here.
+# Solutions-Engineer exercise - Nahuel Porzio
+
+0. [Setting up environments](https://github.com/nporzio/hiring-engineers/blob/master/answers.md#0-setting-up-environments)
+1. [Adding host tags](https://github.com/nporzio/hiring-engineers/blob/master/answers.md#1-adding-host-tags)
+2. [Installing database](https://github.com/nporzio/hiring-engineers/blob/master/answers.md#2-installing-database)
+3. [Custom agent check](https://github.com/nporzio/hiring-engineers/blob/master/answers.md#3-custom-agent-check)
+4. [Creating Timeboard via API](https://github.com/nporzio/hiring-engineers/blob/master/answers.md#4-creating-timeboard-via-api)
+5. [Sharing a graph](https://github.com/nporzio/hiring-engineers/blob/master/answers.md#5-sharing-snapshot)
+6. [Creating a monitor](https://github.com/nporzio/hiring-engineers/blob/master/answers.md#6-creating-alert-monitor)
+7. [Collecting APM data](https://github.com/nporzio/hiring-engineers/blob/master/answers.md#7-collecting-apm-data)
+
+
+
+## 0) Setting up environments
+
+
+I've opted for the vagrant-option and initiated a standard Ubuntu 18.04 distribution. In my case I'm using a MacBook Pro, which is easily deployed via Brew:
+
+
+```
+# Install
+brew install vagrant
+
+# Create directory
+mkdir ~/vagrant
+cd ~/vagrant
+
+# Build image
+vagrant init hashicorp/bionic64
+
+# Add project-conf to ~/vagrant/VagrantFile
+
+Vagrant.configure("2") do |config|
+ config.vm.box = "hashicorp/bionic64"
+end
+
+# Start vm
+vagrant up
+
+# Connect to box
+vagrant ssh
+```
+
+
+
+
+_____
+
+
+
+## 1) Adding host tags
+
+
+After successfully installing and running the datadog-agent as per https://app.datadoghq.eu/account/settings#agent/ubuntu
+
+
+
+and making sure that there's activity in the web-dashboard, I proceeded to configure some tags as per https://docs.datadoghq.com/getting_started/tagging.
+
+```
+# Add tags
+sudo nano /etc/datadog-agent/datadog.yaml
+
+# Content added
+
+tags:
+ - ":"
+ - ":"
+ - ":"
+```
+
+which after some propagation-time they showed in the Host Map section for my account:
+
+
+
+____
+
+
+## 2) Installing database
+
+Here I've installed a standard mysql-service and created a test-database to make sure it works (steps followed very similar to the ones described in this external article https://www.digitalocean.com/community/tutorials/how-to-install-mysql-on-ubuntu-20-04).
+
+
+
+
+Then I've configured the integration and deployed the datadog mysql-user along its pertinent permissions as per https://docs.datadoghq.com/integrations/mysql.
+
+
+
+
+Which enabled the agent to report some metrics visible in the dashboard almost immediately
+
+
+
+____
+
+
+## 3) Custom agent check
+
+I referred to https://docs.datadoghq.com/developers/custom_checks/write_agent_check/ and configured a custom-check:
+
+````
+# Add file for the check
+sudo nano /etc/datadog-agent/conf.d/custom_metric.yaml
+
+# Add correspondent script
+sudo nano /etc/datadog-agent/checks.d/custom_metric.py
+
+# Verify that the check works
+sudo -u dd-agent -- datadog-agent check custom_metric
+
+# Restart service
+sudo service datadog-agent restart
+````
+
+
+
+
+**custom_metric.yaml**
+```
+init_config:
+
+instances:
+ [{}]
+ ````
+**custom_metric.py**
+````
+from checks import AgentCheck
+import random
+
+class custom_metric(AgentCheck):
+
+ def check(self, instance):
+ self.gauge('custom.metric', self.generate_random_number())
+
+ def generate_random_number(self):
+ random_int = random.randint(1,1000)
+ return random_int
+````
+
+
+**Changing interval for the check** --the answer to the bonus question is yes, (as per https://docs.datadoghq.com/developers/custom_checks/write_agent_check/#updating-the-collection-interval) although it may be possible, there's no need to do do this via the python-script itself, since it can admittedly be modified directly on the .yaml.
+
+```
+# Update interval
+sudo nano /etc/datadog-agent/conf.d/custom_metric.yaml
+````
+
+**new custom_metric.yaml**
+````
+init_config:
+
+instances:
+ - min_collection_interval: 45
+````
+
+
+snapshot of the metric itself on the dashboard
+
+
+___
+
+
+## 4) Creating Timeboard via API
+
+After reading the pertinent articles
+ https://docs.datadoghq.com/api/latest
+ https://docs.datadoghq.com/api/latest/authentication/
+ https://docs.datadoghq.com/api/latest/dashboards/
+ https://docs.datadoghq.com/dashboards/querying/
+
+--I've made sure that I'm able to connect to the system by querying ```https://api.datadoghq.eu/api/v1/validate``` (200) via Postman.
+
+
+
+____
+
+
+Then I started testing and interacting with the /dashboards API to get a sense of the mechanics --I must say that since there's many depth levels of information and stated ways of creating dashboards/widgets, I was a little confused over which json-structure is the simplest and ideal model to be used for this instance. For which I went through some trial-and-error cycles with cURL and Postman until figuring out what works for this assignment.
+
+
+
+Ultimately what helped me defining the right format for the requests was combining the DD Postman Collection available in the docs (https://docs.datadoghq.com/getting_started/api/#import-the-datadog-collection-into-postman) together with the JSON-definition available in the UX for the widgets that I created manually, and some basic grasp of functions (https://docs.datadoghq.com/dashboards/functions).
+
+
Once these elements were as clear as possible, I proceeded to write a simple python-script which creates the desired timeboard with the pertinent widgets:
+
+```
+import os
+import json
+import requests
+
+# Auth keys (stored in local variables)
+api_key = os.environ['API_KEY']
+app_key = os.environ['APP_KEY']
+
+# URL
+url = 'https://api.datadoghq.eu/api/v1/dashboard'
+
+# Headers
+headers = {
+ 'DD-API-KEY': api_key,
+ 'DD-APPLICATION-KEY': app_key
+ }
+
+# JSON body
+data = {
+ "layout_type": "ordered",
+ "title": "Timeboard created via API",
+ "widgets": [{
+ "definition": {
+ "type": "timeseries",
+ "title": "custom_metric_api",
+ "requests": [{
+ "q": "custom.metric{host:vagrant}"
+ }]
+ }
+ }, {
+ "definition": {
+ "type": "timeseries",
+ "title": "mysql_cpu_api",
+ "requests": [{
+ "q": "anomalies(mysql.performance.cpu_time{host:vagrant}, 'basic', 3)"
+ }]
+ }
+ },
+ {
+ "definition": {
+ "type": "timeseries",
+ "title": "mysql_cpu_last_hour",
+ "requests": [{
+ "q": "custom.metric{host:vagrant}.rollup(sum,3600)"
+ }]
+ }
+ }
+ ]
+}
+
+# Execute call
+response = requests.post(url, headers=headers, data=json.dumps(data))
+
+# Print result
+print(response.json())
+```
+
+
+
+URL to the dashboard - https://app.datadoghq.eu/dashboard/qgd-6r3-seb/timeboard-created-via-api?from_ts=1644583120454&to_ts=1644586720454&live=true
+
+
+
+
+
+## 5) Sharing snapshot
+
+Here based on the wording of the exercise I wasn't sure that it was possible to share a snapshot of the whole timeboard, or only a specific graph.
+
+After reading trough https://docs.datadoghq.com/metrics/explorer/#snapshot I deduced that it needs to be a graph, and shared it with myself:
+
+
+
+* NOTE - @ notation didn't work here for me, could it be that some setting is off? or perhaps it just doesn't work like that any longer?
+
+
+
+* > Bonus Question: What is the Anomaly graph displaying?
+* Bonus Answer: It overlaps the metric with the expected trayectory (I assume based on previous behaviour) in gray, together with the unexpected spikes in red (as in, anything deviating off the gray normal-behaviour reference).
+
+
+
+## 6) Creating alert-monitor
+
+Based on the given specs, I created the following monitor https://app.datadoghq.eu/monitors/4399442 with the configuration shown below.
+
+
+
+
+
+-Email screenshot
+
+
+
+
+
+* Scheduling downtime
+
+I added the following downtime items:
+
+
+-https://app.datadoghq.eu/monitors/downtimes?id=94331716
+
+
+-https://app.datadoghq.eu/monitors/downtimes?id=94333243
+
+
+-Email screenshot
+
+
+
+_____
+
+
+
+## 7) Collecting APM data
+
+
+
+As per https://docs.datadoghq.com/tracing/setup_overview/setup/python I enabled APM-tracing in the vagrant vm
+```
+# Edit config
+sudo nano /etc/datadog-agent/datadog.yaml
+
+# Content
+set apm_config: true
+
+# Restart service
+sudo service datadog-agent restart
+```
+
+
+
+After resolving some dependencies with python/pip I was able to install ddtrace.
+
+Then I stored the flask-app under ```/etc/flask/flask_app.py``` and ran it as advised in the docs.
+
+```DD_SERVICE="flask_app" DD_ENV="test" DD_LOGS_INJECTION=true ddtrace-run python flask_app.py```
+
+
+
+In order to create some visible activity in the service I executed this simple unix-script a couple of times to generate some _visits_:
+```
+#!/bin/bash
+
+for i in {1..500}
+do
+ curl -X get http://0.0.0.0:5050/
+done
+```
+
+and proceeded as requested to create the following dashboard with some specific APM stats and standard cpu-metrics https://app.datadoghq.eu/dashboard/gx9-nzj-3zr/apm-metrics
+
+
+
+
+
+* > Bonus Question: What is the difference between a Service and Resource?
+* Bonus Answer: Based on my reading through the documentation, in my own words, a service is a process, or a bundle of processes with a specific function in your architecture --while resources are normally the different domains which can be consumed and monitored within or in relation to the service itself.
+
+
+
+ ________
+
+ ## What's something creative I would do with Datadog?
+
+Given my environmentalist nature, provided the resources I would use it to trace and map the actual fuel consumption-metrics from every vehicle in a country (or any larger scale for that matter) running on petrol in order to have tangible data to later properly argument regulations and measures accordingly.
+
+
+
+The idea's premise is that we currently don't have an accurate way of knowing exactly how much a car actually pollutes in a live nor accumulative fashion except for what car-producers claim or governments sample-test.
+
+Having _true_ metrics on this would in my view help in realising footprint and take another step forward towards a more sustainable system.
+
+_______
+
+
+End
+
+
+Thanks for taking your time to read my assignment!
+
+
+
+Nahuel Porzio
+