add gsp 313 315 321 330 344 388

labs/gsp313_create-and-manage-cloud-resources/readme.md

@@ -0,0 +1,22 @@
+# [Create and Manage Cloud Resources: Challenge Lab ](https://www.qwiklabs.com/focuses/10258?parent=catalog)
+
+## Overview
+
+This lab is recommended for students who have enrolled in the labs in the [Create and Manage Cloud Resources](https://google.qwiklabs.com/quests/120) quest. Be sure to review those labs before starting this lab. Are you ready for the challenge?
+
+Topics tested:
+* Create an instance
+* Create a 3-node Kubernetes cluster and run a simple service
+* Create an HTTP(s) load balancer in front of two web servers
+
+## Challenge Scenario
+
+You have started a new role as a Junior Cloud Engineer for Jooli, Inc. You are expected to help manage the infrastructure at Jooli. Common tasks include provisioning resources for projects.
+
+You are expected to have the skills and knowledge for these tasks, so step-by-step guides are not provided.
+
+Some Jooli, Inc. standards you should follow:
+
+* Create all resources in the default region or zone, unless otherwise directed.
+* Naming normally uses the format team-resource; for example, an instance could be named nucleus-webserver1.
+* Allocate cost-effective resource sizes. Projects are monitored, and excessive resource use will result in the containing project's termination (and possibly yours), so plan carefully. This is the guidance the monitoring team is willing to share: unless directed, use f1-micro for small Linux VMs, and use n1-standard-1 for Windows or other applications, such as Kubernetes nodes.

labs/gsp313_create-and-manage-cloud-resources/script.sh

@@ -0,0 +1,72 @@
+# Create and Manage Cloud Resources: Challenge Lab
+# https://www.qwiklabs.com/focuses/10258
+
+# 1. Create a project jumphost instance (zone: us-east1-b)
+gcloud compute instances create nucleus-jumphost \
+        --zone="us-east1-b" \
+        --machine-type="f1-micro" \
+        --boot-disk-size=10GB
+# if failed to check, go create it manually
+
+# 2. Create a Kubernetes service cluster
+gcloud config set compute/zone us-east1-b
+gcloud container clusters create nucleus-jumphost-webserver1
+gcloud container clusters get-credentials nucleus-jumphost-webserver1
+kubectl create deployment hello-app --image=gcr.io/google-samples/hello-app:2.0
+kubectl expose deployment hello-app --type=LoadBalancer --port 8080
+kubectl get service
+
+# 3. Create the web server frontend 
+## 3.1 Create Instance Template
+cat << EOF > startup.sh
+#! /bin/bash
+apt-get update
+apt-get install -y nginx
+service nginx start
+sed -i -- 's/nginx/Google Cloud Platform - '"\$HOSTNAME"'/' /var/www/html/index.nginx-debian.html
+EOF
+gcloud compute instance-templates create nginx-template \
+--metadata-from-file startup-script=startup.sh
+
+## 3.2 Create Target Pool
+gcloud compute target-pools create nginx-pool
+# NOTE: Create it us-east1 region
+
+## 3.3 Create managed instance group
+gcloud compute instance-groups managed create nginx-group \
+    --base-instance-name nginx \
+    --size 2 \
+    --template nginx-template \
+    --target-pool nginx-pool
+
+## 3.4 Create firewall rule
+gcloud compute firewall-rules create www-firewall --allow tcp:80
+gcloud compute forwarding-rules create nginx-lb \
+    --region us-east1 \
+    --ports=80 \
+    --target-pool nginx-pool
+
+## 3.5 Create health check
+gcloud compute http-health-checks create http-basic-check
+gcloud compute instance-groups managed set-named-ports nginx-group \
+    --named-ports http:80
+
+## 3.6 Create backend service
+gcloud compute backend-services create nginx-backend \
+    --protocol HTTP --http-health-checks http-basic-check --global
+gcloud compute backend-services add-backend nginx-backend \
+    --instance-group nginx-group \
+    --instance-group-zone us-east1-b \
+    --global
+
+## 3.7 Create url map
+gcloud compute url-maps create web-map \
+    --default-service nginx-backend
+gcloud compute target-http-proxies create http-lb-proxy \
+    --url-map web-map
+
+## 3.8 Create forwarding rule
+gcloud compute forwarding-rules create http-content-rule \
+    --global \
+    --target-http-proxy http-lb-proxy \
+    --ports 80

labs/gsp315_perform-foundational-infrastructure-tasks-in-google-cloud/readme.md

@@ -0,0 +1,17 @@
+# [Perform Foundational Infrastructure Tasks in Google Cloud: Challenge Lab ](https://www.qwiklabs.com/focuses/10379?parent=catalog)
+
+## Your challenge
+
+You are now asked to help a newly formed development team with some of their initial work on a new project around storing and organizing photographs, called memories. You have been asked to assist the memories team with initial configuration for their application development environment; you receive the following request to complete the following tasks:
+
+* Create a bucket for storing the photographs.
+* Create a Pub/Sub topic that will be used by a Cloud Function you create.
+* Create a Cloud Function.
+* Remove the previous cloud engineer’s access from the memories project.
+
+Some Jooli Inc. standards you should follow:
+
+* Create all resources in the **us-east1** region and **us-east1-b** zone, unless otherwise directed.
+* Use the project VPCs.
+* Naming is normally team-resource, e.g. an instance could be named **kraken-webserver1**
+* Allocate cost effective resource sizes. Projects are monitored and excessive resource use will result in the containing project's termination (and possibly yours), so beware. This is the guidance the monitoring team is willing to share; unless directed, use **f1-micro** for small Linux VMs and **n1-standard-1** for Windows or other applications such as Kubernetes nodes.

labs/gsp315_perform-foundational-infrastructure-tasks-in-google-cloud/script.sh

@@ -0,0 +1,20 @@
+export PROJECT_ID=$DEVSHELL_PROJECT_ID
+
+# 1. Create a bucket
+gsutil mb gs://$PROJECT_ID
+
+# 2. Create a Pub/Sub topic
+gcloud pubsub topics create $PROJECT_ID
+
+# 3. Create the Cloud Function
+# Go to Cloud Functions > Create Function
+# Trigger: Cloud Storage
+# Event type: Finalize/Create
+# Entry Point: thumbnail
+# Runtime: Node.js
+# fill index.js and package.json with given scripts
+# replace line 15 in index.js, in this case, fill with your project id
+# upload one JPG or PNG image into the bucket
+
+# 4. Remove the previous cloud engineer 
+# Go to IAM > find your second username > Click Pencil Icon > Delete

labs/gsp321_set-up-and-configure-a-cloud-environment-in-google-cloud-challenge-lab/guide.txt

@@ -1,7 +1,7 @@
 # Set up and Configure a Cloud Environment in Google Cloud: Challenge Lab 
 # https://www.qwiklabs.com/focuses/10603?parent=catalog
 
-# NOTE: ALL RESOURCES MUST BE CREATED IN REGION us-east1-b
+# NOTE: Create all resources in the us-east1 region and us-east1-b zone, unless otherwise directed.
 
 # Task 1: Create development VPC manually
     - Go to Navigation menu > VPC Network > Create VPC Network

labs/gsp321_set-up-and-configure-a-cloud-environment-in-google-cloud-challenge-lab/readme.md

@@ -16,12 +16,12 @@ You are expected to have the skills and knowledge for these tasks so don’t exp
 
 You need to complete the following tasks:
 
-    * Create a development VPC with three subnets manually
-    * Create a production VPC with three subnets using a provided Deployment Manager configuration
-    * Create a bastion that is connected to both VPCs
-    * Create a development Cloud SQL Instance and connect and prepare the WordPress environment
-    * Create a Kubernetes cluster in the development VPC for WordPress
-    * Prepare the Kubernetes cluster for the WordPress environment
-    * Create a WordPress deployment using the supplied configuration
-    * Enable monitoring of the cluster via stackdriver
-    * Provide access for an additional engineer
+* Create a development VPC with three subnets manually
+* Create a production VPC with three subnets using a provided Deployment Manager configuration
+* Create a bastion that is connected to both VPCs
+* Create a development Cloud SQL Instance and connect and prepare the WordPress environment
+* Create a Kubernetes cluster in the development VPC for WordPress
+* Prepare the Kubernetes cluster for the WordPress environment
+* Create a WordPress deployment using the supplied configuration
+* Enable monitoring of the cluster via stackdriver
+* Provide access for an additional engineer

labs/gsp330_implement-devops-in-google-cloud-challenge-lab/guide.txt → labs/gsp330_implement-devops-in-google-cloud-challenge-lab/script.sh

@@ -1,9 +1,7 @@
 # Implement DevOps in Google Cloud: Challenge Lab 
 # https://www.qwiklabs.com/focuses/13287?parent=catalog
 
-# NOTE: im confusing with this lab, if you still failed (in task 2 and/or 4) try look at other people reference
-
-- Open Cloud shell, run: 
+# Open Cloud shell, run: 
 gcloud config set compute/zone us-east1-b
 git clone https://source.developers.google.com/p/$DEVSHELL_PROJECT_ID/r/sample-app
 gcloud container clusters get-credentials jenkins-cd
@@ -19,7 +17,7 @@ printf $(kubectl get secret cd-jenkins -o jsonpath="{.data.jenkins-admin-passwor
     - username: admin
     - password: see at your cloud shell output
 
-- Back to Cloud shell, run:
+# Back to Cloud shell, run:
 cd sample-app
 kubectl create ns production
 kubectl apply -f k8s/production -n production
@@ -36,66 +34,64 @@ git add .
 git commit -m "initial commit"
 git push origin master
 
-- Back to Jenkins Dashboard > Manage Jenkins (left pane) > manage Credentials
-    - Look at Stores scoped to Jenkins, click Jenkins
-    - Click Global credentials (unrestricted)
-    - Click Add Credentials
-        - Kind: Google Service Account from metadata
-        - Project Name: <your_project_id>
-        - Click OK
-
-- Back to Jenkins Dashboard > New Item (left pane)
-    - Enter an item name: sample-app
-    - Click Multibranch Pipeline
-    - OK
-    - *in sample-app config*
-        - Branch Sources: Git
-            - Project Repository: https://source.developers.google.com/p/[PROJECT_ID]/r/sample-app
-            - Credentials: qwiklabs service account
-        - Scan Multibranch Pipeline Triggers, check Periodically if not otherwise run
-            - Interval: 1 minute
-        - SAVE # building will take long time
-        # Note: Repeat if you see error msg while scanning Multibranch Pipeline Log
-        - CHECK YOUR FIRST CHECKPOINT
+# Back to Jenkins Dashboard > Manage Jenkins (left pane) > manage Credentials
+#     - Look at "Stores scoped", click Jenkins
+#     - Click Global credentials (unrestricted)
+#     - Click Add Credentials
+#         - Kind: Google Service Account from metadata
+#         - Project Name: <your_project_id>
+#         - Click OK
+#
+# Back to Jenkins Dashboard > New Item (left pane)
+#    Enter an item name: sample-app
+#    Click Multibranch Pipeline
+#    OK
+#    *in sample-app config*
+#        - Branch Sources: Git
+#            - Project Repository: https://source.developers.google.com/p/[PROJECT_ID]/r/sample-app
+#            - Credentials: qwiklabs service account
+#        - Scan Multibranch Pipeline Triggers, check "Periodically if not otherwise run"
+#            - Interval: 1 minute
+#        - SAVE # building will take long time
+#        # Note: Repeat if you see error msg while scanning Multibranch Pipeline Log
+#        - CHECK YOUR FIRST CHECKPOINT
+#
 
-- Back to Cloud shell
+# Back to Cloud Shell
 git checkout -b new-feature
-nano main.go
+edit main.go
 # change the version number to "2.0.0". 
 # example: version string = "2.0.0" (in line 46)
-
-run: nano html.go
+edit html.go
 # change both lines that contains the word blue to orange
 # example: <div class="card orange"> (in line 37 and 81)
 
-back to cloud shell, run: 
+# Back to Cloud Shell
 git add Jenkinsfile html.go main.go
 git commit -m "Version 2.0.0"
 git push origin new-feature
-# Check your Jenkins Dashboard
+# Check your sample-app branches from jenkins dashboard (new-feature branch)
 
-back to cloud shell, run: 
+# Back to Cloud Shell 
 curl http://localhost:8001/api/v1/namespaces/new-feature/services/gceme-frontend:80/proxy/version
 kubectl get service gceme-frontend -n production  
 git checkout -b canary
 git push origin canary
-export FRONTEND_SERVICE_IP=$(kubectl get -o \
-jsonpath="{.status.loadBalancer.ingress[0].ip}" --namespace=production services gceme-frontend)
 git checkout master
 git push origin master
-# Check your Jenkins Dashboard
+# Check your sample-app branches from jenkins dashboard (canary branch)
 
-back to cloud shell, run: 
+# Back to Cloud Shell 
 export FRONTEND_SERVICE_IP=$(kubectl get -o \
 jsonpath="{.status.loadBalancer.ingress[0].ip}" --namespace=production services gceme-frontend)
 while true; do curl http://$FRONTEND_SERVICE_IP/version; sleep 1; done
-# NOTE: after the you see output 2.0.0 CHECK YOUR #2 PROGRESS (CHECK MAY FAIL OR/AND NEED DELAY, DUNNO WHY)
+# after the you see output 2.0.0, run:
 kubectl get service gceme-frontend -n production
-# CHECK YOUR #3 CHECKPOINT
-# CHECK YOUR #4 CHECKPOINT (CHECK MAY FAIL OR/AND NEED LONG DELAY)
+# CHECK YOUR #2 #3 AND #4 CHECKPOINT (may be a delay)
+
+###############################################################################################
 
-# Note if task 4 not yet marked, try run (may take a long delay):
+# Note if task 4 not yet marked, try run:
 git merge canary
 git push origin master
-export FRONTEND_SERVICE_IP=$(kubectl get -o \
-jsonpath="{.status.loadBalancer.ingress[0].ip}" --namespace=production services gceme-frontend)
+# may take a long delay before check progress

labs/gsp344_serverless-firebase-development-challenge-lab/readme.md

@@ -0,0 +1,13 @@
+# [Serverless Firebase Development: Challenge Lab](https://www.qwiklabs.com/focuses/14677?parent=catalog)
+
+## Prerequisites
+
+In this challenge lab you will be assessed on your knowledge of the following areas:
+* Firestore
+* Cloud Run
+* Cloud Build
+* Container Registry
+
+## Challenge scenario
+
+In this lab you will create a frontend solution using a Rest API and Firestore database. Cloud Firestore is a NoSQL document database that is part of the Firebase platform where you can store, sync, and query data for your mobile and web apps at scale. Lab content is based on resolving a real world scenario through the use of Google Cloud serverless infrastructure.

labs/gsp344_serverless-firebase-development-challenge-lab/script.sh

@@ -0,0 +1,40 @@
+gcloud config set project $(gcloud projects list --format='value(PROJECT_ID)' --filter='qwiklabs-gcp')
+git clone https://github.com/rosera/pet-theory.git
+
+# 1. Firestore Database Create
+Go to Firestore > Select Naive Mode > Location: nam5 > Create Database
+
+# 2. Firestore Database Populate
+cd pet-theory/lab06/firebase-import-csv/solution
+npm install
+node index.js netflix_titles_original.csv
+
+# 3. Cloud Build Rest API Staging
+cd ~/pet-theory/lab06/firebase-rest-api/solution-01
+npm install
+gcloud builds submit --tag gcr.io/$GOOGLE_CLOUD_PROJECT/rest-api:0.1
+gcloud beta run deploy netflix-dataset-service --image gcr.io/$GOOGLE_CLOUD_PROJECT/rest-api:0.1 --allow-unauthenticated
+# Choose 1 and us-central1
+
+# 4. Cloud Build Rest API Production
+cd ~/pet-theory/lab06/firebase-rest-api/solution-02
+npm install
+gcloud builds submit --tag gcr.io/$GOOGLE_CLOUD_PROJECT/rest-api:0.2
+gcloud beta run deploy netflix-dataset-service --image gcr.io/$GOOGLE_CLOUD_PROJECT/rest-api:0.2 --allow-unauthenticated
+# go to cloud run and click netflix-dataset-service then copy the url
+SERVICE_URL=<copy url from your netflix-dataset-service>
+curl -x GET $SERVICE_URL/2019
+
+# 5. Cloud Build Frontend Staging
+cd ~/pet-theory/lab06/firebase-frontend/public
+nano app.js # comment line 3 and uncomment line 4, insert your netflix-dataset-service url
+npm install
+cd ~/pet-theory/lab06/firebase-frontend
+gcloud builds submit --tag gcr.io/$GOOGLE_CLOUD_PROJECT/frontend-staging:0.1
+gcloud beta run deploy frontend-staging-service --image gcr.io/$GOOGLE_CLOUD_PROJECT/frontend-staging:0.1
+# Choose 1 and us-central1
+
+# 6. Cloud Build Frontend Production
+gcloud builds submit --tag gcr.io/$GOOGLE_CLOUD_PROJECT/frontend-production:0.1
+gcloud beta run deploy frontend-production-service --image gcr.io/$GOOGLE_CLOUD_PROJECT/frontend-production:0.1
+# Choose 1 and us-central1

labs/gsp388_monitor-and-log-with-google-cloud-operations-suite-challenge-lab/guide.txt

@@ -0,0 +1,40 @@
+# 1. Check that Cloud Monitoring has been enabled
+Open Monitoring from console
+
+# 2. Check that the video queue length custom metric has been created
+Check Monitoring > Dashboard > Media_Dashboard
+Open VM Instances
+- Stop video-queue-monitor instances
+- Edit video-queue-monitor instace:
+  - Go to Custom metadata
+    - startup-script: 
+      - replace MY_PROJECT_ID value with your PROJECT ID
+      - replace MY_GCE_INSTANCE_ID value with your your video-queue-monitor Instance id (find it in top)
+      - replace MY_GCE_INSTANCE_ZONE value with us-east1-b
+    - SAVE
+- Start video-queue-monitor instance
+
+# 3. Check that a custom log based metric for large video upload rate has been created
+Go to log explorer
+- fill textPayload=~"file_format\: ([4,8]K).*" in query box and run it
+- Click Action > Create Metric with name "large_video_upload_rate", Click Create Metric
+
+# 4. Check that custom metrics for the video service have been added to the media dashboard
+Go to Monitoring > Dashboard
+  - Click Media_Dashboard
+  - Add Chart
+    - Resource Type: VM Instance
+    - Metrics: OpenCensus/my.videoservice.org/measure/input_queue_size (uncheck Only show active)
+    - Filter: instance_id, click your video-queue-monitor instance id (from step 2) then Apply
+    - SAVE
+  - Add Chart
+    - Resource: VM Instance
+    - Metric: logging/user/large_video_upload_rate
+
+# 5. Check that an alert has been created for large video uploads 
+Go to Monitoring > Alert
+  - Create Policy
+  	- Metric: logging/user/large_video_upload_rate 
+  	- Treshold: 3
+  	- For: 1 minute
+  - Name your alert with "large video uploads" then Save