minor modification to prereqs and reordering pages based on RI agenda (…

…#174)

* adding monitoring using prometheus & grafana chapter

* changing draft: false

* minor change to grafana dashboards

* adding challenge question & offering solution

* formatting changes - removed  for re-emphasizing

* minor change with relative links

* fixing typo in health checks chapter

* minor improvements in health check chapter

* minor changes to healthcheck chapter

* added challenge question to network policy

* minor modification to add shortcut to ssh key link

* reordering pages based on RI agenda

* minor modification to /content/prerequisities/aws_event/portal.md

content/batch/_index.md

@@ -1,7 +1,7 @@
 ---
 title: "Batch Processing with Argo"
 date: 2018-11-18T00:00:00-05:00
-weight: 69
+weight: 44
 draft: false
 ---
 

content/calico/_index.md

@@ -1,7 +1,7 @@
 ---
 title: "Create Network Policies Using Calico"
 chapter: true
-weight: 61
+weight: 50
 ---
 
 # Create Network Policies Using Calico
@@ -15,4 +15,4 @@ For example, you can only allow traffic from frontend to backend in your applica
 Network policies also help in isolating traffic within namespaces. For instance, if you have separate namespaces for development and production, you can prevent traffic flow between them by restrict pod to pod communication within the same namespace.
 
 
-![calico](/images/Project-Calico-logo-1000px.png)
+![calico](/images/Project-Calico-logo-1000px.png)

content/cloudformation/_index.md

@@ -1,7 +1,7 @@
 ---
 title: "Launch using CloudFormation"
 chapter: true
-weight: 40
+weight: 26
 draft: true
 ---
 

content/codepipeline/_index.md

@@ -1,7 +1,7 @@
 ---
 title: "CI/CD with CodePipeline"
 chapter: true
-weight: 64
+weight: 42
 draft: false
 ---
 
@@ -13,4 +13,3 @@ without disruption.
 
 In this module, we will build a CI/CD pipeline using [AWS CodePipeline](https://aws.amazon.com/codepipeline/). The CI/CD pipeline will deploy a sample Kubernetes service,
 we will make a change to the GitHub repository and observe the automated delivery of this change to the cluster.
-

content/dashboard/_index.md

@@ -1,7 +1,7 @@
 ---
 title: "Deploy the Kubernetes Dashboard"
 chapter: true
-weight: 50
+weight: 30
 ---
 
 # Deploy the Kubernetes Dashboard

content/deploy/_index.md

@@ -1,7 +1,7 @@
 ---
 title: "Deploy the Example Microservices"
 chapter: true
-weight: 60
+weight: 31
 ---
 
 # Deploy the Example Microservices

content/healthchecks/_index.md

@@ -1,7 +1,7 @@
 ---
 title: "Health Checks"
 chapter: true
-weight: 61
+weight: 40
 ---
 
 # Health Checks

content/helm_root/_index.md

@@ -1,7 +1,7 @@
 ---
 title: "Helm"
 chapter: true
-weight: 62
+weight: 32
 ---
 
 # Kubernetes Helm

content/logging/_index.md

@@ -1,10 +1,10 @@
 ---
 title: "Logging with Elasticsearch, Fluentd, and Kibana (EFK)"
 chapter: true
-weight: 64
+weight: 51
 ---
 
-# Implement Logging with EFK 
+# Implement Logging with EFK
 
 In this Chapter, we will deploy a common Kubernetes logging pattern which consists of the following:
 

content/monitoring/_index.md

@@ -1,7 +1,7 @@
 ---
 title: "Monitoring using Prometheus and Grafana"
 date: 2018-10-14T09:27:46-04:00
-weight: 66
+weight: 52
 chapter: true
 draft: false
 ---

content/prerequisites/_index.md

@@ -11,4 +11,4 @@ To start the workshop, follow one of the following depending on whether you are.
 * ...[attending an AWS hosted event](aws_event/), or
 * ...[running the workshop on your own](self_paced/)
 
-Once you have completed with either setup, continue with [creating a SSH key](/prerequisites/sshkey/).
+Once you have completed with either setup, continue with [**Create a SSH key section**](/prerequisites/sshkey/)

content/prerequisites/aws_event/portal.md

@@ -28,3 +28,5 @@ Once you have been logged in, please first log into the AWS console by clicking
 {{% notice note %}}
 The workshop added an IAM role for performing all the steps of the workshop in the Cloud9 Environment. You do not need to add a role to the instance powering the Cloud9 Environment.
 {{% /notice %}}
+
+Once you have completed the step above, you can head straight to [**Create a SSH key section**](/prerequisites/sshkey/)

content/scaling/_index.md

@@ -1,7 +1,7 @@
 ---
 title: "Autoscaling our Applications and Clusters"
 chapter: true
-weight: 65
+weight: 41
 ---
 
 # Implement AutoScaling with HPA and CA
@@ -11,4 +11,3 @@ In this Chapter, we will show patterns for scaling your worker nodes and applica
 * **Horizontal Pod Autoscaler (HPA)** scales the pods in a deployment or replica set. It is implemented as a K8s API resource and a controller. The controller manager queries the resource utilization against the metrics specified in each HorizontalPodAutoscaler definition. It obtains the metrics from either the resource metrics API (for per-pod resource metrics), or the custom metrics API (for all other metrics).
 
 * **Cluster Autoscaler (CA)** is the default K8s component that can be used to perform pod scaling as well as scaling nodes in a cluster. It automatically increases the size of an Auto Scaling group so that pods have a place to run. And it attempts to remove idle nodes, that is, nodes with no running pods.
-

content/servicemesh/_index.md

@@ -1,7 +1,7 @@
 ---
 title: "Service Mesh with Istio"
 date: 2018-11-13T16:32:30+09:00
-weight: 68
+weight: 53
 draft: false
 ---
 

content/statefulset/_index.md

@@ -1,7 +1,7 @@
 ---
 title: "Stateful containers using StatefulSets"
 chapter: true
-weight: 63
+weight: 54
 ---
 
 # Stateful containers using StatefulSets

content/terraform/_index.md

@@ -1,7 +1,7 @@
 ---
 title: "Launch using Terraform"
 chapter: false
-weight: 30
+weight: 25
 draft: true
 ---
 

content/x-ray/_index.md

@@ -1,7 +1,7 @@
 ---
 title: "Tracing with X-Ray"
 chapter: true
-weight: 64
+weight: 43
 draft: false
 ---
 
@@ -12,4 +12,3 @@ As [distributed systems](https://en.wikipedia.org/wiki/Distributed_computing) ev
 In this module, we are going to deploy the [X-Ray agent](https://docs.aws.amazon.com/xray/latest/devguide/xray-daemon.html) as a [DaemonSet](https://kubernetes.io/docs/concepts/workloads/controllers/daemonset/), deploy sample front-end and back-end services that are instrumented with the [X-Ray SDK](https://docs.aws.amazon.com/xray/index.html#lang/en_us), make some sample requests and then examine the traces and service maps in the AWS Management Console.
 
 ![GitHub Edit](/images/x-ray/overview.png)
-