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02-path-working-with-clusters/204-cluster-logging-with-EFK/readme.adoc

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@@ -32,7 +32,7 @@ This example creates a two instance Amazon Elasticsearch cluster named `kubernet
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--ebs-options EBSEnabled=true,VolumeType=standard,VolumeSize=100 \
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--access-policies '{"Version":"2012-10-17","Statement":[{"Effect":"Allow","Principal":{"AWS":["*"]},"Action":["es:*"],"Resource":"*"}]}'
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It takes a little while for the cluster to be created and arrive at an `active` state. The AWS Console should show the following status when the cluster is ready:
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It takes a little while for the cluster to be created and arrive at an `active` state. The https://console.aws.amazon.com/es/home[AWS Console] should show the following status when the cluster is ready:
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image::logging-cloudwatch-es-cluster.png[]
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aws logs create-log-group --log-group-name kubernetes-logs
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Create the log group in the same region as your cluster.
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== Deploy Fluentd
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=== Log group name and log stream name
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num_threads 8
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</match>
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It uses the log group name of `kubernetes-logs` and the log stream name of `fluentd-cloudwatch`. If a different log group name is used in the previous command or a different log stream name is needed, then that needs to be configured in this configuration file.
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It uses the default log group name of `kubernetes-logs` and the log stream name of `fluentd-cloudwatch`.
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If you've followed the instructions in this chapter as is, then no change is required in this configuration file. However if a different log group name is used in the previous command or a different log stream name is needed, then that needs to be configured in this configuration file.
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=== IAM configuration
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cicd/codesuite/README.adoc

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= Codesuite - Continuous Deployment
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:toc:
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:icons:
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:linkcss:
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:imagesdir: ../images
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= CodeSuite - Continuous Deployment Reference Architecture for Kubernetes
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The CodeSuite Continuous Deployment reference architecture demonstrates how to achieve continuous
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deployment of an application to a Kubernetes cluster using AWS CodePipeline, AWS CodeCommit, AWS CodeBuild and AWS Lambda.
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Launching this AWS CloudFormation stack provisions a continuous deployment process that uses AWS CodePipeline
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to monitor an AWS CodeCommit repository for new commits, AWS CodeBuild to create a new Docker container image and to push
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it into Amazon ECR. Finally an AWS Lambda function with the Kubernetes Python SDK updates a Kubernetes deployment in a live cluster.
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When you deploy the cloudformation stack there will be four parameters that are specific to your Kubernetes cluster. You will need the API endpoint (enter only the subdomain and omit 'api'), Certificate Authority Data, Client Certificate Data and Client Key Data.
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The last of these three are sensitive, the cloudformation parameter is marked with the "NoEcho" property set to true so that the contents are not exposed through cloudformation. In addition those strings are encrypted with the account default
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KMS key and stored in parameter store. The Lambda function that authenticates to your Kubernetes API endpoint is assigned an IAM role that has permission to access those keys. The Lambda function builds a config file in the tmpfs directory of the Lambda which is in memory
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so that when the Lambda function terminates the secrets are gone.
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image::../../images/cicd.png[Architecture]
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Head over the https://github.com/aws-samples/aws-kube-codesuite[repo] to deploy this architecture into your own cluster.

images/cicd.png

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