Yvonne  Hickle

Yvonne Hickle

1670657100

How to Set Up Logging in Kubernetes

In this Kubernetes tutorial, we will learn about How to Set Up Logging in Kubernetes. Learn how to setup Elasticsearch, Fluentd and Kibana in your Kubernetes cluster.

In my previous article I showed how to use the Kops tool to create a production ready Kubernetes cluster on the Amazon Web Services (AWS) cloud hosting platform. This time I will guide you in installing into this cluster the free and open source Elasticsearch search engine and its graphical counterpart Kibana, as a visual log database. This will provide you with a powerful system for storing logs from containers running in Kubernetes and navigating and searching them in an appealing graphical interface.

We will also install Fluentd as this component is responsible for transmitting the standard Kubernetes logs to Elasticsearch. These three components are together colloquially known as the EFK stack, a self explanatory acronym (an older variation on this stack is known as ELK, which is the same except that it uses Logstash instead of Fluentd).

Before going the route of maintaining your own Elasticsearch cluster, however, you might want to instead consider using the managed service from Elastic themselves, Elastic Cloud. The reason being that administrating Elasticsearch can be a lot of work, as many people experienced with the system will tell you it can be tricky to keep running smoothly and that it’s a task better outsourced to an external service (i.e. Elastic Cloud).

Official Kubernetes Add-On

Before going any further, it should be mentioned that there is a standard add-on for installing EFK in Kubernetes clusters, as part of the official Kubernetes repository. The current version of the add-on (corresponding to Elasticearch 5.6.2) is based on a contribution by yours truly to bring it up to date (5.5.1 at the time). The guide presented in this article is based on said add-on.

I will go through each part of the stack in succession, and provide the corresponding Kubernetes manifest files, and explain shortly how it functions. In order to install the logging stack in your Kubernetes cluster, apply the manifests via kubectl:

kubectl apply -f *.yaml

Elasticsearch

These manifests install Elasticsearch itself as a StatefulSet of two pods that will allocate a persistent volume of 20 GB per pod (make sure to pick a size that make sense for your workload). A Service is created in front of the StatefulSet pods to load balance them.

Elasticsearch is also configured to run under the service account elasticsearch-logging, which gets bound to the role of the same name in order for it to have the right permissions.

es-statefulset.yaml:

# RBAC authn and authz
apiVersion: v1
kind: ServiceAccount
metadata:
  name: elasticsearch-logging
  namespace: kube-system
  labels:
    k8s-app: elasticsearch-logging
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
---
kind: ClusterRole
apiVersion: rbac.authorization.k8s.io/v1beta1
metadata:
  name: elasticsearch-logging
  labels:
    k8s-app: elasticsearch-logging
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
rules:
- apiGroups:
  - ""
  resources:
  - "services"
  - "namespaces"
  - "endpoints"
  verbs:
  - "get"
---
kind: ClusterRoleBinding
apiVersion: rbac.authorization.k8s.io/v1beta1
metadata:
  namespace: kube-system
  name: elasticsearch-logging
  labels:
    k8s-app: elasticsearch-logging
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
subjects:
- kind: ServiceAccount
  name: elasticsearch-logging
  namespace: kube-system
  apiGroup: ""
roleRef:
  kind: ClusterRole
  name: elasticsearch-logging
  apiGroup: ""
---
# Elasticsearch deployment itself
apiVersion: apps/v1beta1
kind: StatefulSet
metadata:
  name: elasticsearch-logging
  namespace: kube-system
  labels:
    k8s-app: elasticsearch-logging
    version: v5.6.2
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
spec:
  serviceName: elasticsearch-logging
  replicas: 2
  selector:
    matchLabels:
      k8s-app: elasticsearch-logging
      version: v5.6.2
  template:
    metadata:
      labels:
        k8s-app: elasticsearch-logging
        version: v5.6.2
        kubernetes.io/cluster-service: "true"
    spec:
      serviceAccountName: elasticsearch-logging
      containers:
      - image: gcr.io/google-containers/elasticsearch:v5.6.2
        name: elasticsearch-logging
        resources:
          # need more cpu upon initialization, therefore burstable class
          limits:
            cpu: 1000m
          requests:
            cpu: 100m
        ports:
        - containerPort: 9200
          name: db
          protocol: TCP
        - containerPort: 9300
          name: transport
          protocol: TCP
        volumeMounts:
        - name: elasticsearch-logging
          mountPath: /data
        env:
        - name: "NAMESPACE"
          valueFrom:
            fieldRef:
              fieldPath: metadata.namespace
      initContainers:
      - image: alpine:3.6
        command: ["/sbin/sysctl", "-w", "vm.max_map_count=262144"]
        name: elasticsearch-logging-init
        securityContext:
          privileged: true
  volumeClaimTemplates:
  - metadata:
      name: elasticsearch-logging
    spec:
      accessModes: ["ReadWriteOnce"]
      resources:
        requests:
          storage: 20Gi

es-service.yaml:

apiVersion: v1
kind: Service
metadata:
  name: elasticsearch-logging
  namespace: kube-system
  labels:
    k8s-app: elasticsearch-logging
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
    kubernetes.io/name: "Elasticsearch"
spec:
  ports:
  - port: 9200
    protocol: TCP
    targetPort: db
  selector:
    k8s-app: elasticsearch-logging

Elasticsearch Curator

Alongside Elasticsearch itself we deploy a service called Elasticsearch Curator, which does automatic maintenance of your Elasticsearch cluster. In our case we make it delete indices older than three days. If you want to tweak this configuration, Base64 decode the values for action_file.yaml and/or config.yaml in es-curator-secret.yaml (Kubernetes requires secret values to be Base64 encoded), make your changes and re-insert the Base64 encoded contents of respective files.

es-curator.yaml:

apiVersion: apps/v1beta1
kind: Deployment
metadata:
  name: es-curator
  namespace: kube-system
  labels:
    k8s-app: es-curator
spec:
  replicas: 1
  selector:
    matchLabels:
      k8s-app: es-curator
  template:
    metadata:
      labels:
        k8s-app: es-curator
    spec:
      containers:
      - name: es-curator
        image: aknudsen/es-curator-service:5.3.0-1
        imagePullPolicy: IfNotPresent
        args: ["--config", "/etc/config/config.yml", "/etc/config/action_file.yml"]
        volumeMounts:
          - name: config-volume
            mountPath: /etc/config
      volumes:
        - name: config-volume
          secret:
            secretName: curator-config

es-curator-secret.yaml:

apiVersion: v1
kind: Secret
metadata:
  name: curator-config
  namespace: kube-system
type: Opaque
data:
  action_file.yml: 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
  config.yml: Y2xpZW50OgogIGhvc3RzOgogICAgLSBlbGFzdGljc2VhcmNoLWxvZ2dpbmcKICBwb3J0OiA5MjAwCiAgdXJsX3ByZWZpeDoKICB1c2Vfc3NsOiBGYWxzZQogIGNlcnRpZmljYXRlOgogIGNsaWVudF9jZXJ0OgogIGNsaWVudF9rZXk6CiAgc3NsX25vX3ZhbGlkYXRlOiBGYWxzZQogIGh0dHBfYXV0aDogZWxhc3RpYzpjaGFuZ2VtZQogIHRpbWVvdXQ6IDMwCiAgbWFzdGVyX29ubHk6IEZhbHNlCmxvZ2dpbmc6CiAgbG9nbGV2ZWw6IElORk8KICBsb2dmaWxlOgogIGxvZ2Zvcm1hdDogZGVmYXVsdAogIGJsYWNrbGlzdDogWydlbGFzdGljc2VhcmNoJywgJ3VybGxpYjMnXQo=

Fluentd

Fluentd is installed as a DaemonSet, which means that a corresponding pod will run on every Kubernetes worker node in order to collect its logs (and send them to Elasticsearch). Furthermore, the pods run as the service account fluentd-es which is bound to the cluster role with the same name in order to have the necessary permissions.

fluentd-es-configmap.yaml:

kind: ConfigMap
apiVersion: v1
data:
  containers.input.conf: |-
    # This configuration file for Fluentd / td-agent is used
    # to watch changes to Docker log files. The kubelet creates symlinks that
    # capture the pod name, namespace, container name & Docker container ID
    # to the docker logs for pods in the /var/log/containers directory on the host.
    # If running this fluentd configuration in a Docker container, the /var/log
    # directory should be mounted in the container.
    #
    # These logs are then submitted to Elasticsearch which assumes the
    # installation of the fluent-plugin-elasticsearch & the
    # fluent-plugin-kubernetes_metadata_filter plugins.
    # See https://github.com/uken/fluent-plugin-elasticsearch &
    # https://github.com/fabric8io/fluent-plugin-kubernetes_metadata_filter for
    # more information about the plugins.
    #
    # Example
    # =======
    # A line in the Docker log file might look like this JSON:
    #
    # {"log":"2014/09/25 21:15:03 Got request with path wombat\n",
    #  "stream":"stderr",
    #   "time":"2014-09-25T21:15:03.499185026Z"}
    #
    # The time_format specification below makes sure we properly
    # parse the time format produced by Docker. This will be
    # submitted to Elasticsearch and should appear like:
    # $ curl 'http://elasticsearch-logging:9200/_search?pretty'
    # ...
    # {
    #      "_index" : "logstash-2014.09.25",
    #      "_type" : "fluentd",
    #      "_id" : "VBrbor2QTuGpsQyTCdfzqA",
    #      "_score" : 1.0,
    #      "_source":{"log":"2014/09/25 22:45:50 Got request with path wombat\n",
    #                 "stream":"stderr","tag":"docker.container.all",
    #                 "@timestamp":"2014-09-25T22:45:50+00:00"}
    #    },
    # ...
    #
    # The Kubernetes fluentd plugin is used to write the Kubernetes metadata to the log
    # record & add labels to the log record if properly configured. This enables users
    # to filter & search logs on any metadata.
    # For example a Docker container's logs might be in the directory:
    #
    #  /var/lib/docker/containers/997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b
    #
    # and in the file:
    #
    #  997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b-json.log
    #
    # where 997599971ee6... is the Docker ID of the running container.
    # The Kubernetes kubelet makes a symbolic link to this file on the host machine
    # in the /var/log/containers directory which includes the pod name and the Kubernetes
    # container name:
    #
    #    synthetic-logger-0.25lps-pod_default_synth-lgr-997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b.log
    #    ->
    #    /var/lib/docker/containers/997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b/997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b-json.log
    #
    # The /var/log directory on the host is mapped to the /var/log directory in the container
    # running this instance of Fluentd and we end up collecting the file:
    #
    #   /var/log/containers/synthetic-logger-0.25lps-pod_default_synth-lgr-997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b.log
    #
    # This results in the tag:
    #
    #  var.log.containers.synthetic-logger-0.25lps-pod_default_synth-lgr-997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b.log
    #
    # The Kubernetes fluentd plugin is used to extract the namespace, pod name & container name
    # which are added to the log message as a kubernetes field object & the Docker container ID
    # is also added under the docker field object.
    # The final tag is:
    #
    #   kubernetes.var.log.containers.synthetic-logger-0.25lps-pod_default_synth-lgr-997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b.log
    #
    # And the final log record look like:
    #
    # {
    #   "log":"2014/09/25 21:15:03 Got request with path wombat\n",
    #   "stream":"stderr",
    #   "time":"2014-09-25T21:15:03.499185026Z",
    #   "kubernetes": {
    #     "namespace": "default",
    #     "pod_name": "synthetic-logger-0.25lps-pod",
    #     "container_name": "synth-lgr"
    #   },
    #   "docker": {
    #     "container_id": "997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b"
    #   }
    # }
    #
    # This makes it easier for users to search for logs by pod name or by
    # the name of the Kubernetes container regardless of how many times the
    # Kubernetes pod has been restarted (resulting in a several Docker container IDs).

    # Example:
    # {"log":"[info:2016-02-16T16:04:05.930-08:00] Some log text here\n","stream":"stdout","time":"2016-02-17T00:04:05.931087621Z"}
    <source>
      type tail
      path /var/log/containers/*.log
      pos_file /var/log/es-containers.log.pos
      time_format %Y-%m-%dT%H:%M:%S.%NZ
      tag kubernetes.*
      format json
      read_from_head true
    </source>
  system.input.conf: |-
    # Example:
    # 2015-12-21 23:17:22,066 [salt.state       ][INFO    ] Completed state [net.ipv4.ip_forward] at time 23:17:22.066081
    <source>
      type tail
      format /^(?<time>[^ ]* [^ ,]*)[^\[]*\[[^\]]*\]\[(?<severity>[^ \]]*) *\] (?<message>.*)$/
      time_format %Y-%m-%d %H:%M:%S
      path /var/log/salt/minion
      pos_file /var/log/es-salt.pos
      tag salt
    </source>

    # Example:
    # Dec 21 23:17:22 gke-foo-1-1-4b5cbd14-node-4eoj startupscript: Finished running startup script /var/run/google.startup.script
    <source>
      type tail
      format syslog
      path /var/log/startupscript.log
      pos_file /var/log/es-startupscript.log.pos
      tag startupscript
    </source>

    # Examples:
    # time="2016-02-04T06:51:03.053580605Z" level=info msg="GET /containers/json"
    # time="2016-02-04T07:53:57.505612354Z" level=error msg="HTTP Error" err="No such image: -f" statusCode=404
    <source>
      type tail
      format /^time="(?<time>[^)]*)" level=(?<severity>[^ ]*) msg="(?<message>[^"]*)"( err="(?<error>[^"]*)")?( statusCode=($<status_code>\d+))?/
      path /var/log/docker.log
      pos_file /var/log/es-docker.log.pos
      tag docker
    </source>

    # Example:
    # 2016/02/04 06:52:38 filePurge: successfully removed file /var/etcd/data/member/wal/00000000000006d0-00000000010a23d1.wal
    <source>
      type tail
      # Not parsing this, because it doesn't have anything particularly useful to
      # parse out of it (like severities).
      format none
      path /var/log/etcd.log
      pos_file /var/log/es-etcd.log.pos
      tag etcd
    </source>

    # Multi-line parsing is required for all the kube logs because very large log
    # statements, such as those that include entire object bodies, get split into
    # multiple lines by glog.

    # Example:
    # I0204 07:32:30.020537    3368 server.go:1048] POST /stats/container/: (13.972191ms) 200 [[Go-http-client/1.1] 10.244.1.3:40537]
    <source>
      type tail
      format multiline
      multiline_flush_interval 5s
      format_firstline /^\w\d{4}/
      format1 /^(?<severity>\w)(?<time>\d{4} [^\s]*)\s+(?<pid>\d+)\s+(?<source>[^ \]]+)\] (?<message>.*)/
      time_format %m%d %H:%M:%S.%N
      path /var/log/kubelet.log
      pos_file /var/log/es-kubelet.log.pos
      tag kubelet
    </source>

    # Example:
    # I1118 21:26:53.975789       6 proxier.go:1096] Port "nodePort for kube-system/default-http-backend:http" (:31429/tcp) was open before and is still needed
    <source>
      type tail
      format multiline
      multiline_flush_interval 5s
      format_firstline /^\w\d{4}/
      format1 /^(?<severity>\w)(?<time>\d{4} [^\s]*)\s+(?<pid>\d+)\s+(?<source>[^ \]]+)\] (?<message>.*)/
      time_format %m%d %H:%M:%S.%N
      path /var/log/kube-proxy.log
      pos_file /var/log/es-kube-proxy.log.pos
      tag kube-proxy
    </source>

    # Example:
    # I0204 07:00:19.604280       5 handlers.go:131] GET /api/v1/nodes: (1.624207ms) 200 [[kube-controller-manager/v1.1.3 (linux/amd64) kubernetes/6a81b50] 127.0.0.1:38266]
    <source>
      type tail
      format multiline
      multiline_flush_interval 5s
      format_firstline /^\w\d{4}/
      format1 /^(?<severity>\w)(?<time>\d{4} [^\s]*)\s+(?<pid>\d+)\s+(?<source>[^ \]]+)\] (?<message>.*)/
      time_format %m%d %H:%M:%S.%N
      path /var/log/kube-apiserver.log
      pos_file /var/log/es-kube-apiserver.log.pos
      tag kube-apiserver
    </source>

    # Example:
    # I0204 06:55:31.872680       5 servicecontroller.go:277] LB already exists and doesn't need update for service kube-system/kube-ui
    <source>
      type tail
      format multiline
      multiline_flush_interval 5s
      format_firstline /^\w\d{4}/
      format1 /^(?<severity>\w)(?<time>\d{4} [^\s]*)\s+(?<pid>\d+)\s+(?<source>[^ \]]+)\] (?<message>.*)/
      time_format %m%d %H:%M:%S.%N
      path /var/log/kube-controller-manager.log
      pos_file /var/log/es-kube-controller-manager.log.pos
      tag kube-controller-manager
    </source>

    # Example:
    # W0204 06:49:18.239674       7 reflector.go:245] pkg/scheduler/factory/factory.go:193: watch of *api.Service ended with: 401: The event in requested index is outdated and cleared (the requested history has been cleared [2578313/2577886]) [2579312]
    <source>
      type tail
      format multiline
      multiline_flush_interval 5s
      format_firstline /^\w\d{4}/
      format1 /^(?<severity>\w)(?<time>\d{4} [^\s]*)\s+(?<pid>\d+)\s+(?<source>[^ \]]+)\] (?<message>.*)/
      time_format %m%d %H:%M:%S.%N
      path /var/log/kube-scheduler.log
      pos_file /var/log/es-kube-scheduler.log.pos
      tag kube-scheduler
    </source>

    # Example:
    # I1104 10:36:20.242766       5 rescheduler.go:73] Running Rescheduler
    <source>
      type tail
      format multiline
      multiline_flush_interval 5s
      format_firstline /^\w\d{4}/
      format1 /^(?<severity>\w)(?<time>\d{4} [^\s]*)\s+(?<pid>\d+)\s+(?<source>[^ \]]+)\] (?<message>.*)/
      time_format %m%d %H:%M:%S.%N
      path /var/log/rescheduler.log
      pos_file /var/log/es-rescheduler.log.pos
      tag rescheduler
    </source>

    # Example:
    # I0603 15:31:05.793605       6 cluster_manager.go:230] Reading config from path /etc/gce.conf
    <source>
      type tail
      format multiline
      multiline_flush_interval 5s
      format_firstline /^\w\d{4}/
      format1 /^(?<severity>\w)(?<time>\d{4} [^\s]*)\s+(?<pid>\d+)\s+(?<source>[^ \]]+)\] (?<message>.*)/
      time_format %m%d %H:%M:%S.%N
      path /var/log/glbc.log
      pos_file /var/log/es-glbc.log.pos
      tag glbc
    </source>

    # Example:
    # I0603 15:31:05.793605       6 cluster_manager.go:230] Reading config from path /etc/gce.conf
    <source>
      type tail
      format multiline
      multiline_flush_interval 5s
      format_firstline /^\w\d{4}/
      format1 /^(?<severity>\w)(?<time>\d{4} [^\s]*)\s+(?<pid>\d+)\s+(?<source>[^ \]]+)\] (?<message>.*)/
      time_format %m%d %H:%M:%S.%N
      path /var/log/cluster-autoscaler.log
      pos_file /var/log/es-cluster-autoscaler.log.pos
      tag cluster-autoscaler
    </source>

    # Logs from systemd-journal for interesting services.
    <source>
      type systemd
      filters [{ "_SYSTEMD_UNIT": "docker.service" }]
      pos_file /var/log/gcp-journald-docker.pos
      read_from_head true
      tag docker
    </source>

    <source>
      type systemd
      filters [{ "_SYSTEMD_UNIT": "kubelet.service" }]
      pos_file /var/log/gcp-journald-kubelet.pos
      read_from_head true
      tag kubelet
    </source>

    <source>
      type systemd
      filters [{ "_SYSTEMD_UNIT": "node-problem-detector.service" }]
      pos_file /var/log/gcp-journald-node-problem-detector.pos
      read_from_head true
      tag node-problem-detector
    </source>
  forward.input.conf: |-
    # Takes the messages sent over TCP
    <source>
      type forward
    </source>
  monitoring.conf: |-
    # Prometheus Exporter Plugin
    # input plugin that exports metrics
    <source>
      @type prometheus
    </source>

    <source>
      @type monitor_agent
    </source>

    # input plugin that collects metrics from MonitorAgent
    <source>
      @type prometheus_monitor
      <labels>
        host ${hostname}
      </labels>
    </source>

    # input plugin that collects metrics for output plugin
    <source>
      @type prometheus_output_monitor
      <labels>
        host ${hostname}
      </labels>
    </source>

    # input plugin that collects metrics for in_tail plugin
    <source>
      @type prometheus_tail_monitor
      <labels>
        host ${hostname}
      </labels>
    </source>
  output.conf: |-
    # Enriches records with Kubernetes metadata
    <filter kubernetes.**>
      type kubernetes_metadata
    </filter>

    <match **>
       type elasticsearch
       log_level info
       include_tag_key true
       host elasticsearch-logging
       port 9200
       logstash_format true
       # Set the chunk limits.
       buffer_chunk_limit 2M
       buffer_queue_limit 8
       flush_interval 5s
       # Never wait longer than 5 minutes between retries.
       max_retry_wait 30
       # Disable the limit on the number of retries (retry forever).
       disable_retry_limit
       # Use multiple threads for processing.
       num_threads 2
    </match>
metadata:
  name: fluentd-es-config-v0.1.0
  namespace: kube-system
  labels:
    addonmanager.kubernetes.io/mode: Reconcile

fluentd-es-ds.yaml:

apiVersion: v1
kind: ServiceAccount
metadata:
  name: fluentd-es
  namespace: kube-system
  labels:
    k8s-app: fluentd-es
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
---
kind: ClusterRole
apiVersion: rbac.authorization.k8s.io/v1beta1
metadata:
  name: fluentd-es
  labels:
    k8s-app: fluentd-es
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
rules:
- apiGroups:
  - ""
  resources:
  - "namespaces"
  - "pods"
  verbs:
  - "get"
  - "watch"
  - "list"
---
kind: ClusterRoleBinding
apiVersion: rbac.authorization.k8s.io/v1beta1
metadata:
  name: fluentd-es
  labels:
    k8s-app: fluentd-es
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
subjects:
- kind: ServiceAccount
  name: fluentd-es
  namespace: kube-system
  apiGroup: ""
roleRef:
  kind: ClusterRole
  name: fluentd-es
  apiGroup: ""
---
apiVersion: apps/v1beta1
kind: DaemonSet
metadata:
  name: fluentd-es-v2.0.2
  namespace: kube-system
  labels:
    k8s-app: fluentd-es
    version: v2.0.2
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
spec:
  template:
    metadata:
      labels:
        k8s-app: fluentd-es
        kubernetes.io/cluster-service: "true"
        version: v2.0.2
      # This annotation ensures that fluentd does not get evicted if the node
      # supports critical pod annotation based priority scheme.
      # Note that this does not guarantee admission on the nodes (#40573).
      annotations:
        scheduler.alpha.kubernetes.io/critical-pod: ''
    spec:
      serviceAccountName: fluentd-es
      containers:
      - name: fluentd-es
        image: gcr.io/google-containers/fluentd-elasticsearch:v2.0.2
        env:
        - name: FLUENTD_ARGS
          value: --no-supervisor -q
        resources:
          limits:
            memory: 500Mi
          requests:
            cpu: 100m
            memory: 200Mi
        volumeMounts:
        - name: varlog
          mountPath: /var/log
        - name: varlibdockercontainers
          mountPath: /var/lib/docker/containers
          readOnly: true
        - name: libsystemddir
          mountPath: /host/lib
          readOnly: true
        - name: config-volume
          mountPath: /etc/fluent/config.d
      nodeSelector:
        beta.kubernetes.io/fluentd-ds-ready: "true"
      terminationGracePeriodSeconds: 30
      volumes:
      - name: varlog
        hostPath:
          path: /var/log
      - name: varlibdockercontainers
        hostPath:
          path: /var/lib/docker/containers
      # It is needed to copy systemd library to decompress journals
      - name: libsystemddir
        hostPath:
          path: /usr/lib64
      - name: config-volume
        configMap:
          name: fluentd-es-config-v0.1.0

Kibana

There’s not much to say about the Kibana manifests; we install a Deployment, which ensures that one pod is always running, and a Service in front of it (which is capable of load balancing in case there should be several pods in parallel).

Kibana dashboard

Kibana dashboard

kibana-deployment.yaml:

apiVersion: apps/v1beta1
kind: Deployment
metadata:
  name: kibana-logging
  namespace: kube-system
  labels:
    k8s-app: kibana-logging
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
spec:
  replicas: 1
  selector:
    matchLabels:
      k8s-app: kibana-logging
  template:
    metadata:
      labels:
        k8s-app: kibana-logging
    spec:
      containers:
      - name: kibana-logging
        image: docker.elastic.co/kibana/kibana:5.6.2
        resources:
          # need more cpu upon initialization, therefore burstable class
          limits:
            cpu: 1000m
          requests:
            cpu: 100m
        env:
          - name: ELASTICSEARCH_URL
            value: [http://elasticsearch-logging:9200](http://elasticsearch-logging:9200)
          - name: SERVER_BASEPATH
            value: /api/v1/proxy/namespaces/kube-system/services/kibana-logging
          - name: XPACK_MONITORING_ENABLED
            value: "false"
          - name: XPACK_SECURITY_ENABLED
            value: "false"
        ports:
        - containerPort: 5601
          name: ui
          protocol: TCP

kibana-service.yaml

apiVersion: v1
kind: Service
metadata:
  name: kibana-logging
  namespace: kube-system
  labels:
    k8s-app: kibana-logging
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
    kubernetes.io/name: "Kibana"
spec:
  ports:
  - port: 5601
    protocol: TCP
    targetPort: ui
  selector:
    k8s-app: kibana-logging

Scripted Setup

As described in the previous article in this series, we have made a Python script to create a Kubernetes cluster on AWS with the help of the kops tool. This script also installs the EFK stack within the cluster (in addition to Prometheus Operator for monitoring), so you might give it a spin if you are creating your Kubernetes clusters from scratch on AWS or you could simply use its EFK manifests to integrate with your own cluster(s).


Original article sourced at: https://codersociety.com

#kubernetes 

What is GEEK

Buddha Community

How to Set Up Logging in Kubernetes
Hermann  Frami

Hermann Frami

1651383480

A Simple Wrapper Around Amplify AppSync Simulator

This serverless plugin is a wrapper for amplify-appsync-simulator made for testing AppSync APIs built with serverless-appsync-plugin.

Install

npm install serverless-appsync-simulator
# or
yarn add serverless-appsync-simulator

Usage

This plugin relies on your serverless yml file and on the serverless-offline plugin.

plugins:
  - serverless-dynamodb-local # only if you need dynamodb resolvers and you don't have an external dynamodb
  - serverless-appsync-simulator
  - serverless-offline

Note: Order is important serverless-appsync-simulator must go before serverless-offline

To start the simulator, run the following command:

sls offline start

You should see in the logs something like:

...
Serverless: AppSync endpoint: http://localhost:20002/graphql
Serverless: GraphiQl: http://localhost:20002
...

Configuration

Put options under custom.appsync-simulator in your serverless.yml file

| option | default | description | | ------------------------ | -------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------- | | apiKey | 0123456789 | When using API_KEY as authentication type, the key to authenticate to the endpoint. | | port | 20002 | AppSync operations port; if using multiple APIs, the value of this option will be used as a starting point, and each other API will have a port of lastPort + 10 (e.g. 20002, 20012, 20022, etc.) | | wsPort | 20003 | AppSync subscriptions port; if using multiple APIs, the value of this option will be used as a starting point, and each other API will have a port of lastPort + 10 (e.g. 20003, 20013, 20023, etc.) | | location | . (base directory) | Location of the lambda functions handlers. | | refMap | {} | A mapping of resource resolutions for the Ref function | | getAttMap | {} | A mapping of resource resolutions for the GetAtt function | | importValueMap | {} | A mapping of resource resolutions for the ImportValue function | | functions | {} | A mapping of external functions for providing invoke url for external fucntions | | dynamoDb.endpoint | http://localhost:8000 | Dynamodb endpoint. Specify it if you're not using serverless-dynamodb-local. Otherwise, port is taken from dynamodb-local conf | | dynamoDb.region | localhost | Dynamodb region. Specify it if you're connecting to a remote Dynamodb intance. | | dynamoDb.accessKeyId | DEFAULT_ACCESS_KEY | AWS Access Key ID to access DynamoDB | | dynamoDb.secretAccessKey | DEFAULT_SECRET | AWS Secret Key to access DynamoDB | | dynamoDb.sessionToken | DEFAULT_ACCESS_TOKEEN | AWS Session Token to access DynamoDB, only if you have temporary security credentials configured on AWS | | dynamoDb.* | | You can add every configuration accepted by DynamoDB SDK | | rds.dbName | | Name of the database | | rds.dbHost | | Database host | | rds.dbDialect | | Database dialect. Possible values (mysql | postgres) | | rds.dbUsername | | Database username | | rds.dbPassword | | Database password | | rds.dbPort | | Database port | | watch | - *.graphql
- *.vtl | Array of glob patterns to watch for hot-reloading. |

Example:

custom:
  appsync-simulator:
    location: '.webpack/service' # use webpack build directory
    dynamoDb:
      endpoint: 'http://my-custom-dynamo:8000'

Hot-reloading

By default, the simulator will hot-relad when changes to *.graphql or *.vtl files are detected. Changes to *.yml files are not supported (yet? - this is a Serverless Framework limitation). You will need to restart the simulator each time you change yml files.

Hot-reloading relies on watchman. Make sure it is installed on your system.

You can change the files being watched with the watch option, which is then passed to watchman as the match expression.

e.g.

custom:
  appsync-simulator:
    watch:
      - ["match", "handlers/**/*.vtl", "wholename"] # => array is interpreted as the literal match expression
      - "*.graphql"                                 # => string like this is equivalent to `["match", "*.graphql"]`

Or you can opt-out by leaving an empty array or set the option to false

Note: Functions should not require hot-reloading, unless you are using a transpiler or a bundler (such as webpack, babel or typescript), un which case you should delegate hot-reloading to that instead.

Resource CloudFormation functions resolution

This plugin supports some resources resolution from the Ref, Fn::GetAtt and Fn::ImportValue functions in your yaml file. It also supports some other Cfn functions such as Fn::Join, Fb::Sub, etc.

Note: Under the hood, this features relies on the cfn-resolver-lib package. For more info on supported cfn functions, refer to the documentation

Basic usage

You can reference resources in your functions' environment variables (that will be accessible from your lambda functions) or datasource definitions. The plugin will automatically resolve them for you.

provider:
  environment:
    BUCKET_NAME:
      Ref: MyBucket # resolves to `my-bucket-name`

resources:
  Resources:
    MyDbTable:
      Type: AWS::DynamoDB::Table
      Properties:
        TableName: myTable
      ...
    MyBucket:
      Type: AWS::S3::Bucket
      Properties:
        BucketName: my-bucket-name
    ...

# in your appsync config
dataSources:
  - type: AMAZON_DYNAMODB
    name: dynamosource
    config:
      tableName:
        Ref: MyDbTable # resolves to `myTable`

Override (or mock) values

Sometimes, some references cannot be resolved, as they come from an Output from Cloudformation; or you might want to use mocked values in your local environment.

In those cases, you can define (or override) those values using the refMap, getAttMap and importValueMap options.

  • refMap takes a mapping of resource name to value pairs
  • getAttMap takes a mapping of resource name to attribute/values pairs
  • importValueMap takes a mapping of import name to values pairs

Example:

custom:
  appsync-simulator:
    refMap:
      # Override `MyDbTable` resolution from the previous example.
      MyDbTable: 'mock-myTable'
    getAttMap:
      # define ElasticSearchInstance DomainName
      ElasticSearchInstance:
        DomainEndpoint: 'localhost:9200'
    importValueMap:
      other-service-api-url: 'https://other.api.url.com/graphql'

# in your appsync config
dataSources:
  - type: AMAZON_ELASTICSEARCH
    name: elasticsource
    config:
      # endpoint resolves as 'http://localhost:9200'
      endpoint:
        Fn::Join:
          - ''
          - - https://
            - Fn::GetAtt:
                - ElasticSearchInstance
                - DomainEndpoint

Key-value mock notation

In some special cases you will need to use key-value mock nottation. Good example can be case when you need to include serverless stage value (${self:provider.stage}) in the import name.

This notation can be used with all mocks - refMap, getAttMap and importValueMap

provider:
  environment:
    FINISH_ACTIVITY_FUNCTION_ARN:
      Fn::ImportValue: other-service-api-${self:provider.stage}-url

custom:
  serverless-appsync-simulator:
    importValueMap:
      - key: other-service-api-${self:provider.stage}-url
        value: 'https://other.api.url.com/graphql'

Limitations

This plugin only tries to resolve the following parts of the yml tree:

  • provider.environment
  • functions[*].environment
  • custom.appSync

If you have the need of resolving others, feel free to open an issue and explain your use case.

For now, the supported resources to be automatically resovled by Ref: are:

  • DynamoDb tables
  • S3 Buckets

Feel free to open a PR or an issue to extend them as well.

External functions

When a function is not defined withing the current serverless file you can still call it by providing an invoke url which should point to a REST method. Make sure you specify "get" or "post" for the method. Default is "get", but you probably want "post".

custom:
  appsync-simulator:
    functions:
      addUser:
        url: http://localhost:3016/2015-03-31/functions/addUser/invocations
        method: post
      addPost:
        url: https://jsonplaceholder.typicode.com/posts
        method: post

Supported Resolver types

This plugin supports resolvers implemented by amplify-appsync-simulator, as well as custom resolvers.

From Aws Amplify:

  • NONE
  • AWS_LAMBDA
  • AMAZON_DYNAMODB
  • PIPELINE

Implemented by this plugin

  • AMAZON_ELASTIC_SEARCH
  • HTTP
  • RELATIONAL_DATABASE

Relational Database

Sample VTL for a create mutation

#set( $cols = [] )
#set( $vals = [] )
#foreach( $entry in $ctx.args.input.keySet() )
  #set( $regex = "([a-z])([A-Z]+)")
  #set( $replacement = "$1_$2")
  #set( $toSnake = $entry.replaceAll($regex, $replacement).toLowerCase() )
  #set( $discard = $cols.add("$toSnake") )
  #if( $util.isBoolean($ctx.args.input[$entry]) )
      #if( $ctx.args.input[$entry] )
        #set( $discard = $vals.add("1") )
      #else
        #set( $discard = $vals.add("0") )
      #end
  #else
      #set( $discard = $vals.add("'$ctx.args.input[$entry]'") )
  #end
#end
#set( $valStr = $vals.toString().replace("[","(").replace("]",")") )
#set( $colStr = $cols.toString().replace("[","(").replace("]",")") )
#if ( $valStr.substring(0, 1) != '(' )
  #set( $valStr = "($valStr)" )
#end
#if ( $colStr.substring(0, 1) != '(' )
  #set( $colStr = "($colStr)" )
#end
{
  "version": "2018-05-29",
  "statements":   ["INSERT INTO <name-of-table> $colStr VALUES $valStr", "SELECT * FROM    <name-of-table> ORDER BY id DESC LIMIT 1"]
}

Sample VTL for an update mutation

#set( $update = "" )
#set( $equals = "=" )
#foreach( $entry in $ctx.args.input.keySet() )
  #set( $cur = $ctx.args.input[$entry] )
  #set( $regex = "([a-z])([A-Z]+)")
  #set( $replacement = "$1_$2")
  #set( $toSnake = $entry.replaceAll($regex, $replacement).toLowerCase() )
  #if( $util.isBoolean($cur) )
      #if( $cur )
        #set ( $cur = "1" )
      #else
        #set ( $cur = "0" )
      #end
  #end
  #if ( $util.isNullOrEmpty($update) )
      #set($update = "$toSnake$equals'$cur'" )
  #else
      #set($update = "$update,$toSnake$equals'$cur'" )
  #end
#end
{
  "version": "2018-05-29",
  "statements":   ["UPDATE <name-of-table> SET $update WHERE id=$ctx.args.input.id", "SELECT * FROM <name-of-table> WHERE id=$ctx.args.input.id"]
}

Sample resolver for delete mutation

{
  "version": "2018-05-29",
  "statements":   ["UPDATE <name-of-table> set deleted_at=NOW() WHERE id=$ctx.args.id", "SELECT * FROM <name-of-table> WHERE id=$ctx.args.id"]
}

Sample mutation response VTL with support for handling AWSDateTime

#set ( $index = -1)
#set ( $result = $util.parseJson($ctx.result) )
#set ( $meta = $result.sqlStatementResults[1].columnMetadata)
#foreach ($column in $meta)
    #set ($index = $index + 1)
    #if ( $column["typeName"] == "timestamptz" )
        #set ($time = $result["sqlStatementResults"][1]["records"][0][$index]["stringValue"] )
        #set ( $nowEpochMillis = $util.time.parseFormattedToEpochMilliSeconds("$time.substring(0,19)+0000", "yyyy-MM-dd HH:mm:ssZ") )
        #set ( $isoDateTime = $util.time.epochMilliSecondsToISO8601($nowEpochMillis) )
        $util.qr( $result["sqlStatementResults"][1]["records"][0][$index].put("stringValue", "$isoDateTime") )
    #end
#end
#set ( $res = $util.parseJson($util.rds.toJsonString($util.toJson($result)))[1][0] )
#set ( $response = {} )
#foreach($mapKey in $res.keySet())
    #set ( $s = $mapKey.split("_") )
    #set ( $camelCase="" )
    #set ( $isFirst=true )
    #foreach($entry in $s)
        #if ( $isFirst )
          #set ( $first = $entry.substring(0,1) )
        #else
          #set ( $first = $entry.substring(0,1).toUpperCase() )
        #end
        #set ( $isFirst=false )
        #set ( $stringLength = $entry.length() )
        #set ( $remaining = $entry.substring(1, $stringLength) )
        #set ( $camelCase = "$camelCase$first$remaining" )
    #end
    $util.qr( $response.put("$camelCase", $res[$mapKey]) )
#end
$utils.toJson($response)

Using Variable Map

Variable map support is limited and does not differentiate numbers and strings data types, please inject them directly if needed.

Will be escaped properly: null, true, and false values.

{
  "version": "2018-05-29",
  "statements":   [
    "UPDATE <name-of-table> set deleted_at=NOW() WHERE id=:ID",
    "SELECT * FROM <name-of-table> WHERE id=:ID and unix_timestamp > $ctx.args.newerThan"
  ],
  variableMap: {
    ":ID": $ctx.args.id,
##    ":TIMESTAMP": $ctx.args.newerThan -- This will be handled as a string!!!
  }
}

Requires

Author: Serverless-appsync
Source Code: https://github.com/serverless-appsync/serverless-appsync-simulator 
License: MIT License

#serverless #sync #graphql 

Christa  Stehr

Christa Stehr

1602964260

50+ Useful Kubernetes Tools for 2020 - Part 2

Introduction

Last year, we provided a list of Kubernetes tools that proved so popular we have decided to curate another list of some useful additions for working with the platform—among which are many tools that we personally use here at Caylent. Check out the original tools list here in case you missed it.

According to a recent survey done by Stackrox, the dominance Kubernetes enjoys in the market continues to be reinforced, with 86% of respondents using it for container orchestration.

(State of Kubernetes and Container Security, 2020)

And as you can see below, more and more companies are jumping into containerization for their apps. If you’re among them, here are some tools to aid you going forward as Kubernetes continues its rapid growth.

(State of Kubernetes and Container Security, 2020)

#blog #tools #amazon elastic kubernetes service #application security #aws kms #botkube #caylent #cli #container monitoring #container orchestration tools #container security #containers #continuous delivery #continuous deployment #continuous integration #contour #developers #development #developments #draft #eksctl #firewall #gcp #github #harbor #helm #helm charts #helm-2to3 #helm-aws-secret-plugin #helm-docs #helm-operator-get-started #helm-secrets #iam #json #k-rail #k3s #k3sup #k8s #keel.sh #keycloak #kiali #kiam #klum #knative #krew #ksniff #kube #kube-prod-runtime #kube-ps1 #kube-scan #kube-state-metrics #kube2iam #kubeapps #kubebuilder #kubeconfig #kubectl #kubectl-aws-secrets #kubefwd #kubernetes #kubernetes command line tool #kubernetes configuration #kubernetes deployment #kubernetes in development #kubernetes in production #kubernetes ingress #kubernetes interfaces #kubernetes monitoring #kubernetes networking #kubernetes observability #kubernetes plugins #kubernetes secrets #kubernetes security #kubernetes security best practices #kubernetes security vendors #kubernetes service discovery #kubernetic #kubesec #kubeterminal #kubeval #kudo #kuma #microsoft azure key vault #mozilla sops #octant #octarine #open source #palo alto kubernetes security #permission-manager #pgp #rafay #rakess #rancher #rook #secrets operations #serverless function #service mesh #shell-operator #snyk #snyk container #sonobuoy #strongdm #tcpdump #tenkai #testing #tigera #tilt #vert.x #wireshark #yaml

Hermann  Frami

Hermann Frami

1651319520

Serverless APIGateway Service Proxy

Serverless APIGateway Service Proxy

This Serverless Framework plugin supports the AWS service proxy integration feature of API Gateway. You can directly connect API Gateway to AWS services without Lambda.

Install

Run serverless plugin install in your Serverless project.

serverless plugin install -n serverless-apigateway-service-proxy

Supported AWS services

Here is a services list which this plugin supports for now. But will expand to other services in the feature. Please pull request if you are intersted in it.

  • Kinesis Streams
  • SQS
  • S3
  • SNS
  • DynamoDB
  • EventBridge

How to use

Define settings of the AWS services you want to integrate under custom > apiGatewayServiceProxies and run serverless deploy.

Kinesis

Sample syntax for Kinesis proxy in serverless.yml.

custom:
  apiGatewayServiceProxies:
    - kinesis: # partitionkey is set apigateway requestid by default
        path: /kinesis
        method: post
        streamName: { Ref: 'YourStream' }
        cors: true
    - kinesis:
        path: /kinesis
        method: post
        partitionKey: 'hardcordedkey' # use static partitionkey
        streamName: { Ref: 'YourStream' }
        cors: true
    - kinesis:
        path: /kinesis/{myKey} # use path parameter
        method: post
        partitionKey:
          pathParam: myKey
        streamName: { Ref: 'YourStream' }
        cors: true
    - kinesis:
        path: /kinesis
        method: post
        partitionKey:
          bodyParam: data.myKey # use body parameter
        streamName: { Ref: 'YourStream' }
        cors: true
    - kinesis:
        path: /kinesis
        method: post
        partitionKey:
          queryStringParam: myKey # use query string param
        streamName: { Ref: 'YourStream' }
        cors: true
    - kinesis: # PutRecords
        path: /kinesis
        method: post
        action: PutRecords
        streamName: { Ref: 'YourStream' }
        cors: true

resources:
  Resources:
    YourStream:
      Type: AWS::Kinesis::Stream
      Properties:
        ShardCount: 1

Sample request after deploying.

curl https://xxxxxxx.execute-api.us-east-1.amazonaws.com/dev/kinesis -d '{"message": "some data"}'  -H 'Content-Type:application/json'

SQS

Sample syntax for SQS proxy in serverless.yml.

custom:
  apiGatewayServiceProxies:
    - sqs:
        path: /sqs
        method: post
        queueName: { 'Fn::GetAtt': ['SQSQueue', 'QueueName'] }
        cors: true

resources:
  Resources:
    SQSQueue:
      Type: 'AWS::SQS::Queue'

Sample request after deploying.

curl https://xxxxxx.execute-api.us-east-1.amazonaws.com/dev/sqs -d '{"message": "testtest"}' -H 'Content-Type:application/json'

Customizing request parameters

If you'd like to pass additional data to the integration request, you can do so by including your custom API Gateway request parameters in serverless.yml like so:

custom:
  apiGatewayServiceProxies:
    - sqs:
        path: /queue
        method: post
        queueName: !GetAtt MyQueue.QueueName
        cors: true

        requestParameters:
          'integration.request.querystring.MessageAttribute.1.Name': "'cognitoIdentityId'"
          'integration.request.querystring.MessageAttribute.1.Value.StringValue': 'context.identity.cognitoIdentityId'
          'integration.request.querystring.MessageAttribute.1.Value.DataType': "'String'"
          'integration.request.querystring.MessageAttribute.2.Name': "'cognitoAuthenticationProvider'"
          'integration.request.querystring.MessageAttribute.2.Value.StringValue': 'context.identity.cognitoAuthenticationProvider'
          'integration.request.querystring.MessageAttribute.2.Value.DataType': "'String'"

The alternative way to pass MessageAttribute parameters is via a request body mapping template.

Customizing request body mapping templates

See the SQS section under Customizing request body mapping templates

Customizing responses

Simplified response template customization

You can get a simple customization of the responses by providing a template for the possible responses. The template is assumed to be application/json.

custom:
  apiGatewayServiceProxies:
    - sqs:
        path: /queue
        method: post
        queueName: !GetAtt MyQueue.QueueName
        cors: true
        response:
          template:
            # `success` is used when the integration response is 200
            success: |-
              { "message: "accepted" }
            # `clientError` is used when the integration response is 400
            clientError: |-
              { "message": "there is an error in your request" }
            # `serverError` is used when the integration response is 500
            serverError: |-
              { "message": "there was an error handling your request" }

Full response customization

If you want more control over the integration response, you can provide an array of objects for the response value:

custom:
  apiGatewayServiceProxies:
    - sqs:
        path: /queue
        method: post
        queueName: !GetAtt MyQueue.QueueName
        cors: true
        response:
          - statusCode: 200
            selectionPattern: '2\\d{2}'
            responseParameters: {}
            responseTemplates:
              application/json: |-
                { "message": "accepted" }

The object keys correspond to the API Gateway integration response object.

S3

Sample syntax for S3 proxy in serverless.yml.

custom:
  apiGatewayServiceProxies:
    - s3:
        path: /s3
        method: post
        action: PutObject
        bucket:
          Ref: S3Bucket
        key: static-key.json # use static key
        cors: true

    - s3:
        path: /s3/{myKey} # use path param
        method: get
        action: GetObject
        bucket:
          Ref: S3Bucket
        key:
          pathParam: myKey
        cors: true

    - s3:
        path: /s3
        method: delete
        action: DeleteObject
        bucket:
          Ref: S3Bucket
        key:
          queryStringParam: key # use query string param
        cors: true

resources:
  Resources:
    S3Bucket:
      Type: 'AWS::S3::Bucket'

Sample request after deploying.

curl https://xxxxxx.execute-api.us-east-1.amazonaws.com/dev/s3 -d '{"message": "testtest"}' -H 'Content-Type:application/json'

Customizing request parameters

Similar to the SQS support, you can customize the default request parameters serverless.yml like so:

custom:
  apiGatewayServiceProxies:
    - s3:
        path: /s3
        method: post
        action: PutObject
        bucket:
          Ref: S3Bucket
        cors: true

        requestParameters:
          # if requestParameters has a 'integration.request.path.object' property you should remove the key setting
          'integration.request.path.object': 'context.requestId'
          'integration.request.header.cache-control': "'public, max-age=31536000, immutable'"

Customizing request templates

If you'd like use custom API Gateway request templates, you can do so like so:

custom:
  apiGatewayServiceProxies:
    - s3:
        path: /s3
        method: get
        action: GetObject
        bucket:
          Ref: S3Bucket
        request:
          template:
            application/json: |
              #set ($specialStuff = $context.request.header.x-special)
              #set ($context.requestOverride.path.object = $specialStuff.replaceAll('_', '-'))
              {}

Note that if the client does not provide a Content-Type header in the request, ApiGateway defaults to application/json.

Customize the Path Override in API Gateway

Added the new customization parameter that lets the user set a custom Path Override in API Gateway other than the {bucket}/{object} This parameter is optional and if not set, will fall back to {bucket}/{object} The Path Override will add {bucket}/ automatically in front

Please keep in mind, that key or path.object still needs to be set at the moment (maybe this will be made optional later on with this)

Usage (With 2 Path Parameters (folder and file and a fixed file extension)):

custom:
  apiGatewayServiceProxies:
    - s3:
        path: /s3/{folder}/{file}
        method: get
        action: GetObject
        pathOverride: '{folder}/{file}.xml'
        bucket:
          Ref: S3Bucket
        cors: true

        requestParameters:
          # if requestParameters has a 'integration.request.path.object' property you should remove the key setting
          'integration.request.path.folder': 'method.request.path.folder'
          'integration.request.path.file': 'method.request.path.file'
          'integration.request.path.object': 'context.requestId'
          'integration.request.header.cache-control': "'public, max-age=31536000, immutable'"

This will result in API Gateway setting the Path Override attribute to {bucket}/{folder}/{file}.xml So for example if you navigate to the API Gatway endpoint /language/en it will fetch the file in S3 from {bucket}/language/en.xml

Can use greedy, for deeper Folders

The forementioned example can also be shortened by a greedy approach. Thanks to @taylorreece for mentioning this.

custom:
  apiGatewayServiceProxies:
    - s3:
        path: /s3/{myPath+}
        method: get
        action: GetObject
        pathOverride: '{myPath}.xml'
        bucket:
          Ref: S3Bucket
        cors: true

        requestParameters:
          # if requestParameters has a 'integration.request.path.object' property you should remove the key setting
          'integration.request.path.myPath': 'method.request.path.myPath'
          'integration.request.path.object': 'context.requestId'
          'integration.request.header.cache-control': "'public, max-age=31536000, immutable'"

This will translate for example /s3/a/b/c to a/b/c.xml

Customizing responses

You can get a simple customization of the responses by providing a template for the possible responses. The template is assumed to be application/json.

custom:
  apiGatewayServiceProxies:
    - s3:
        path: /s3
        method: post
        action: PutObject
        bucket:
          Ref: S3Bucket
        key: static-key.json
        response:
          template:
            # `success` is used when the integration response is 200
            success: |-
              { "message: "accepted" }
            # `clientError` is used when the integration response is 400
            clientError: |-
              { "message": "there is an error in your request" }
            # `serverError` is used when the integration response is 500
            serverError: |-
              { "message": "there was an error handling your request" }

SNS

Sample syntax for SNS proxy in serverless.yml.

custom:
  apiGatewayServiceProxies:
    - sns:
        path: /sns
        method: post
        topicName: { 'Fn::GetAtt': ['SNSTopic', 'TopicName'] }
        cors: true

resources:
  Resources:
    SNSTopic:
      Type: AWS::SNS::Topic

Sample request after deploying.

curl https://xxxxxx.execute-api.us-east-1.amazonaws.com/dev/sns -d '{"message": "testtest"}' -H 'Content-Type:application/json'

Customizing responses

Simplified response template customization

You can get a simple customization of the responses by providing a template for the possible responses. The template is assumed to be application/json.

custom:
  apiGatewayServiceProxies:
    - sns:
        path: /sns
        method: post
        topicName: { 'Fn::GetAtt': ['SNSTopic', 'TopicName'] }
        cors: true
        response:
          template:
            # `success` is used when the integration response is 200
            success: |-
              { "message: "accepted" }
            # `clientError` is used when the integration response is 400
            clientError: |-
              { "message": "there is an error in your request" }
            # `serverError` is used when the integration response is 500
            serverError: |-
              { "message": "there was an error handling your request" }

Full response customization

If you want more control over the integration response, you can provide an array of objects for the response value:

custom:
  apiGatewayServiceProxies:
    - sns:
        path: /sns
        method: post
        topicName: { 'Fn::GetAtt': ['SNSTopic', 'TopicName'] }
        cors: true
        response:
          - statusCode: 200
            selectionPattern: '2\d{2}'
            responseParameters: {}
            responseTemplates:
              application/json: |-
                { "message": "accepted" }

The object keys correspond to the API Gateway integration response object.

Content Handling and Pass Through Behaviour customization

If you want to work with binary fata, you can not specify contentHandling and PassThrough inside the request object.

custom:
  apiGatewayServiceProxies:
    - sns:
        path: /sns
        method: post
        topicName: { 'Fn::GetAtt': ['SNSTopic', 'TopicName'] }
        request:
          contentHandling: CONVERT_TO_TEXT
          passThrough: WHEN_NO_TEMPLATES

The allowed values correspond with the API Gateway Method integration for ContentHandling and PassthroughBehavior

DynamoDB

Sample syntax for DynamoDB proxy in serverless.yml. Currently, the supported DynamoDB Operations are PutItem, GetItem and DeleteItem.

custom:
  apiGatewayServiceProxies:
    - dynamodb:
        path: /dynamodb/{id}/{sort}
        method: put
        tableName: { Ref: 'YourTable' }
        hashKey: # set pathParam or queryStringParam as a partitionkey.
          pathParam: id
          attributeType: S
        rangeKey: # required if also using sort key. set pathParam or queryStringParam.
          pathParam: sort
          attributeType: S
        action: PutItem # specify action to the table what you want
        condition: attribute_not_exists(Id) # optional Condition Expressions parameter for the table
        cors: true
    - dynamodb:
        path: /dynamodb
        method: get
        tableName: { Ref: 'YourTable' }
        hashKey:
          queryStringParam: id # use query string parameter
          attributeType: S
        rangeKey:
          queryStringParam: sort
          attributeType: S
        action: GetItem
        cors: true
    - dynamodb:
        path: /dynamodb/{id}
        method: delete
        tableName: { Ref: 'YourTable' }
        hashKey:
          pathParam: id
          attributeType: S
        action: DeleteItem
        cors: true

resources:
  Resources:
    YourTable:
      Type: AWS::DynamoDB::Table
      Properties:
        TableName: YourTable
        AttributeDefinitions:
          - AttributeName: id
            AttributeType: S
          - AttributeName: sort
            AttributeType: S
        KeySchema:
          - AttributeName: id
            KeyType: HASH
          - AttributeName: sort
            KeyType: RANGE
        ProvisionedThroughput:
          ReadCapacityUnits: 1
          WriteCapacityUnits: 1

Sample request after deploying.

curl -XPUT https://xxxxxxx.execute-api.us-east-1.amazonaws.com/dev/dynamodb/<hashKey>/<sortkey> \
 -d '{"name":{"S":"john"},"address":{"S":"xxxxx"}}' \
 -H 'Content-Type:application/json'

EventBridge

Sample syntax for EventBridge proxy in serverless.yml.

custom:
  apiGatewayServiceProxies:
    - eventbridge:  # source and detailType are hardcoded; detail defaults to POST body
        path: /eventbridge
        method: post
        source: 'hardcoded_source'
        detailType: 'hardcoded_detailType'
        eventBusName: { Ref: 'YourBusName' }
        cors: true
    - eventbridge:  # source and detailType as path parameters
        path: /eventbridge/{detailTypeKey}/{sourceKey}
        method: post
        detailType:
          pathParam: detailTypeKey
        source:
          pathParam: sourceKey
        eventBusName: { Ref: 'YourBusName' }
        cors: true
    - eventbridge:  # source, detail, and detailType as body parameters
        path: /eventbridge/{detailTypeKey}/{sourceKey}
        method: post
        detailType:
          bodyParam: data.detailType
        source:
          bodyParam: data.source
        detail:
          bodyParam: data.detail
        eventBusName: { Ref: 'YourBusName' }
        cors: true

resources:
  Resources:
    YourBus:
      Type: AWS::Events::EventBus
      Properties:
        Name: YourEventBus

Sample request after deploying.

curl https://xxxxxxx.execute-api.us-east-1.amazonaws.com/dev/eventbridge -d '{"message": "some data"}'  -H 'Content-Type:application/json'

Common API Gateway features

Enabling CORS

To set CORS configurations for your HTTP endpoints, simply modify your event configurations as follows:

custom:
  apiGatewayServiceProxies:
    - kinesis:
        path: /kinesis
        method: post
        streamName: { Ref: 'YourStream' }
        cors: true

Setting cors to true assumes a default configuration which is equivalent to:

custom:
  apiGatewayServiceProxies:
    - kinesis:
        path: /kinesis
        method: post
        streamName: { Ref: 'YourStream' }
        cors:
          origin: '*'
          headers:
            - Content-Type
            - X-Amz-Date
            - Authorization
            - X-Api-Key
            - X-Amz-Security-Token
            - X-Amz-User-Agent
          allowCredentials: false

Configuring the cors property sets Access-Control-Allow-Origin, Access-Control-Allow-Headers, Access-Control-Allow-Methods,Access-Control-Allow-Credentials headers in the CORS preflight response. To enable the Access-Control-Max-Age preflight response header, set the maxAge property in the cors object:

custom:
  apiGatewayServiceProxies:
    - kinesis:
        path: /kinesis
        method: post
        streamName: { Ref: 'YourStream' }
        cors:
          origin: '*'
          maxAge: 86400

If you are using CloudFront or another CDN for your API Gateway, you may want to setup a Cache-Control header to allow for OPTIONS request to be cached to avoid the additional hop.

To enable the Cache-Control header on preflight response, set the cacheControl property in the cors object:

custom:
  apiGatewayServiceProxies:
    - kinesis:
        path: /kinesis
        method: post
        streamName: { Ref: 'YourStream' }
        cors:
          origin: '*'
          headers:
            - Content-Type
            - X-Amz-Date
            - Authorization
            - X-Api-Key
            - X-Amz-Security-Token
            - X-Amz-User-Agent
          allowCredentials: false
          cacheControl: 'max-age=600, s-maxage=600, proxy-revalidate' # Caches on browser and proxy for 10 minutes and doesnt allow proxy to serve out of date content

Adding Authorization

You can pass in any supported authorization type:

custom:
  apiGatewayServiceProxies:
    - sqs:
        path: /sqs
        method: post
        queueName: { 'Fn::GetAtt': ['SQSQueue', 'QueueName'] }
        cors: true

        # optional - defaults to 'NONE'
        authorizationType: 'AWS_IAM' # can be one of ['NONE', 'AWS_IAM', 'CUSTOM', 'COGNITO_USER_POOLS']

        # when using 'CUSTOM' authorization type, one should specify authorizerId
        # authorizerId: { Ref: 'AuthorizerLogicalId' }
        # when using 'COGNITO_USER_POOLS' authorization type, one can specify a list of authorization scopes
        # authorizationScopes: ['scope1','scope2']

resources:
  Resources:
    SQSQueue:
      Type: 'AWS::SQS::Queue'

Source: AWS::ApiGateway::Method docs

Enabling API Token Authentication

You can indicate whether the method requires clients to submit a valid API key using private flag:

custom:
  apiGatewayServiceProxies:
    - sqs:
        path: /sqs
        method: post
        queueName: { 'Fn::GetAtt': ['SQSQueue', 'QueueName'] }
        cors: true
        private: true

resources:
  Resources:
    SQSQueue:
      Type: 'AWS::SQS::Queue'

which is the same syntax used in Serverless framework.

Source: Serverless: Setting API keys for your Rest API

Source: AWS::ApiGateway::Method docs

Using a Custom IAM Role

By default, the plugin will generate a role with the required permissions for each service type that is configured.

You can configure your own role by setting the roleArn attribute:

custom:
  apiGatewayServiceProxies:
    - sqs:
        path: /sqs
        method: post
        queueName: { 'Fn::GetAtt': ['SQSQueue', 'QueueName'] }
        cors: true
        roleArn: # Optional. A default role is created when not configured
          Fn::GetAtt: [CustomS3Role, Arn]

resources:
  Resources:
    SQSQueue:
      Type: 'AWS::SQS::Queue'
    CustomS3Role:
      # Custom Role definition
      Type: 'AWS::IAM::Role'

Customizing API Gateway parameters

The plugin allows one to specify which parameters the API Gateway method accepts.

A common use case is to pass custom data to the integration request:

custom:
  apiGatewayServiceProxies:
    - sqs:
        path: /sqs
        method: post
        queueName: { 'Fn::GetAtt': ['SqsQueue', 'QueueName'] }
        cors: true
        acceptParameters:
          'method.request.header.Custom-Header': true
        requestParameters:
          'integration.request.querystring.MessageAttribute.1.Name': "'custom-Header'"
          'integration.request.querystring.MessageAttribute.1.Value.StringValue': 'method.request.header.Custom-Header'
          'integration.request.querystring.MessageAttribute.1.Value.DataType': "'String'"
resources:
  Resources:
    SqsQueue:
      Type: 'AWS::SQS::Queue'

Any published SQS message will have the Custom-Header value added as a message attribute.

Customizing request body mapping templates

Kinesis

If you'd like to add content types or customize the default templates, you can do so by including your custom API Gateway request mapping template in serverless.yml like so:

# Required for using Fn::Sub
plugins:
  - serverless-cloudformation-sub-variables

custom:
  apiGatewayServiceProxies:
    - kinesis:
        path: /kinesis
        method: post
        streamName: { Ref: 'MyStream' }
        request:
          template:
            text/plain:
              Fn::Sub:
                - |
                  #set($msgBody = $util.parseJson($input.body))
                  #set($msgId = $msgBody.MessageId)
                  {
                      "Data": "$util.base64Encode($input.body)",
                      "PartitionKey": "$msgId",
                      "StreamName": "#{MyStreamArn}"
                  }
                - MyStreamArn:
                    Fn::GetAtt: [MyStream, Arn]

It is important that the mapping template will return a valid application/json string

Source: How to connect SNS to Kinesis for cross-account delivery via API Gateway

SQS

Customizing SQS request templates requires us to force all requests to use an application/x-www-form-urlencoded style body. The plugin sets the Content-Type header to application/x-www-form-urlencoded for you, but API Gateway will still look for the template under the application/json request template type, so that is where you need to configure you request body in serverless.yml:

custom:
  apiGatewayServiceProxies:
    - sqs:
        path: /{version}/event/receiver
        method: post
        queueName: { 'Fn::GetAtt': ['SqsQueue', 'QueueName'] }
        request:
          template:
            application/json: |-
              #set ($body = $util.parseJson($input.body))
              Action=SendMessage##
              &MessageGroupId=$util.urlEncode($body.event_type)##
              &MessageDeduplicationId=$util.urlEncode($body.event_id)##
              &MessageAttribute.1.Name=$util.urlEncode("X-Custom-Signature")##
              &MessageAttribute.1.Value.DataType=String##
              &MessageAttribute.1.Value.StringValue=$util.urlEncode($input.params("X-Custom-Signature"))##
              &MessageBody=$util.urlEncode($input.body)

Note that the ## at the end of each line is an empty comment. In VTL this has the effect of stripping the newline from the end of the line (as it is commented out), which makes API Gateway read all the lines in the template as one line.

Be careful when mixing additional requestParameters into your SQS endpoint as you may overwrite the integration.request.header.Content-Type and stop the request template from being parsed correctly. You may also unintentionally create conflicts between parameters passed using requestParameters and those in your request template. Typically you should only use the request template if you need to manipulate the incoming request body in some way.

Your custom template must also set the Action and MessageBody parameters, as these will not be added for you by the plugin.

When using a custom request body, headers sent by a client will no longer be passed through to the SQS queue (PassthroughBehavior is automatically set to NEVER). You will need to pass through headers sent by the client explicitly in the request body. Also, any custom querystring parameters in the requestParameters array will be ignored. These also need to be added via the custom request body.

SNS

Similar to the Kinesis support, you can customize the default request mapping templates in serverless.yml like so:

# Required for using Fn::Sub
plugins:
  - serverless-cloudformation-sub-variables

custom:
  apiGatewayServiceProxies:
    - kinesis:
        path: /sns
        method: post
        topicName: { 'Fn::GetAtt': ['SNSTopic', 'TopicName'] }
        request:
          template:
            application/json:
              Fn::Sub:
                - "Action=Publish&Message=$util.urlEncode('This is a fixed message')&TopicArn=$util.urlEncode('#{MyTopicArn}')"
                - MyTopicArn: { Ref: MyTopic }

It is important that the mapping template will return a valid application/x-www-form-urlencoded string

Source: Connect AWS API Gateway directly to SNS using a service integration

Custom response body mapping templates

You can customize the response body by providing mapping templates for success, server errors (5xx) and client errors (4xx).

Templates must be in JSON format. If a template isn't provided, the integration response will be returned as-is to the client.

Kinesis Example

custom:
  apiGatewayServiceProxies:
    - kinesis:
        path: /kinesis
        method: post
        streamName: { Ref: 'MyStream' }
        response:
          template:
            success: |
              {
                "success": true
              }
            serverError: |
              {
                "success": false,
                "errorMessage": "Server Error"
              }
            clientError: |
              {
                "success": false,
                "errorMessage": "Client Error"
              }

Author: Serverless-operations
Source Code: https://github.com/serverless-operations/serverless-apigateway-service-proxy 
License: 

#serverless #api #aws 

Maud  Rosenbaum

Maud Rosenbaum

1601051854

Kubernetes in the Cloud: Strategies for Effective Multi Cloud Implementations

Kubernetes is a highly popular container orchestration platform. Multi cloud is a strategy that leverages cloud resources from multiple vendors. Multi cloud strategies have become popular because they help prevent vendor lock-in and enable you to leverage a wide variety of cloud resources. However, multi cloud ecosystems are notoriously difficult to configure and maintain.

This article explains how you can leverage Kubernetes to reduce multi cloud complexities and improve stability, scalability, and velocity.

Kubernetes: Your Multi Cloud Strategy

Maintaining standardized application deployments becomes more challenging as your number of applications and the technologies they are based on increase. As environments, operating systems, and dependencies differ, management and operations require more effort and extensive documentation.

In the past, teams tried to get around these difficulties by creating isolated projects in the data center. Each project, including its configurations and requirements were managed independently. This required accurately predicting performance and the number of users before deployment and taking down applications to update operating systems or applications. There were many chances for error.

Kubernetes can provide an alternative to the old method, enabling teams to deploy applications independent of the environment in containers. This eliminates the need to create resource partitions and enables teams to operate infrastructure as a unified whole.

In particular, Kubernetes makes it easier to deploy a multi cloud strategy since it enables you to abstract away service differences. With Kubernetes deployments you can work from a consistent platform and optimize services and applications according to your business needs.

The Compelling Attributes of Multi Cloud Kubernetes

Multi cloud Kubernetes can provide multiple benefits beyond a single cloud deployment. Below are some of the most notable advantages.

Stability

In addition to the built-in scalability, fault tolerance, and auto-healing features of Kubernetes, multi cloud deployments can provide service redundancy. For example, you can mirror applications or split microservices across vendors. This reduces the risk of a vendor-related outage and enables you to create failovers.

#kubernetes #multicloud-strategy #kubernetes-cluster #kubernetes-top-story #kubernetes-cluster-install #kubernetes-explained #kubernetes-infrastructure #cloud

Lawson  Wehner

Lawson Wehner

1672833558

How to Use Bash Set Command

Bash has many environment variables for various purposes. The set command of Bash is used to modify or display the different attributes and parameters of the shell environment. This command has many options to perform the different types of tasks. The uses of set command for various purposes are described in this tutorial.

Syntax

set [options] [arguments]

This command can be used with different types of options and arguments for different purposes. If no option or argument is used with this command, the shell variables are printed. The minus sign (-) is used with the command’s option to enable that option and the plus sign (+) is used with the command’s option to disable that option.

Exit Values of Set Command

Three exit values can be returned by this command which are mentioned in the following:

  1. Zero (0) is returned to complete the task successfully.
  2. One (1) is returned if a failure occurs for any invalid argument.
  3. One (1) is returned if a failure occurs for a missing argument.

Different Options of Set Command

The purposes of the most commonly used options of the set command are described in this part of the tutorial.

OptionPurpose
-aIt defines those variables or functions which are created or modified or exported.
-bIt informs the job termination.
-BTo do the task of the brace expansion.
-CIt disables the overwriting feature of the existing file.
-eIt exits for non-zero exit status value.
-fIt disables the filename generation task.
-hIt saves the location of the command where it has been used.
-mIt enables job control.
-nIt reads the commands.
-tIt exits from the command after executing a single command.
-uIt traces the unset variables.
-vIt prints the shell input lines.
-xIt displays the commands and their attributes sequentially. It is mainly used to debug the script.

Different Examples of the Set Command

The uses of set command with different options are shown in this part of this tutorial.

Example 1: Using the Set Command with -a Option

Create a Bash file with the following script that enables the “set –a” command and initialize three variables named $v1, $v2, and $v3. These variables can be accessed after executing the script.

#!/bin/bash
#Enable -a option to read the values of the variables
set -a
#Initialize three variables
v1=78
v2=50
v3=35

Run the script using the following command:

$ bash set1.bash

Read the values of the variable using the “echo” command:

$ echo $v1 $v2 $v3

The following output appears after executing the previous commands:

Example 2: Using the Set Command with -C Option

Run the “cat” command to create a text file named testfile.txt. Next, run the “set –C” command to disable the overwriting feature. Next, run the “cat” command again to overwrite the file to check whether the overwriting feature is disabled or not.

$ cat > testfile.txt
$ set -C
$ cat > testfile.txt

The following output appears after executing the previous commands:

Example 3: Using the Set Command with -x Option

Create a Bash file with the following script that declares a numeric array of 6 elements. The values of the array are printed using for loop.

#!/bin/bash
#Declare an array
arr=(67 3 90 56 2 80)
#iterate the array values
for value in ${arr[@]}
do
   echo $value
done

Execute the previous script by the following command:

$ bash set3.bash

Enable the debugging option using the following command:

$ set -x

The following output appears after executing the provided commands:

Example 4: Using the Set Command with -e Option

Create a Bash file with the following script that reads a file using the “cat” command before and after using the “set –e” command.

#!/bin/bash
#Read a non-existing file without setting set -e
cat myfile.txt
echo "Reading a file..."
#Set the set command with -e option
set -e
#Read a non-existing file after setting set -e
cat myfile.txt
echo "Reading a file..."

The following output appears after executing the provided commands. The first error message is shown because the file does not exist in the current location. The next message is then printed. But after executing the “set –e” command, the execution stops after displaying the error message.

Example 5: Using the Set Command with -u Option

Create a Bash file with the following script that initializes a variable but prints the initialized and uninitialized variable before and after using the “set –u” command.

#!/bin/bash
#Assign value to a variable
strvar="Bash Programming"
printf "$strvar $intvar\n"
#Set the set command with -u option
set -u
#Assign value to a variable
strvar="Bash Programming"
printf "\n$strvar $intvar\n"

The following output appears after executing the previous script. Here, the error is printed for the uninitialized variable:

Example 6: Using the Set Command with -f Option

Run the following command to print the list of all text files of the current location:

$ ls *.txt

Run the following command to disable the globbing:

$ set –f

Run the following command again to print the list of all text files of the current location:

$ ls *.txt

The following output appears after executing the previous script. Based on the output, the “ls *.txt” command did not work after setting “set –f” command:

Example 7: Split the String Using the Set Command with Variable

Create a Bash file with the following script that splits the string value based on the space using the “set – variable” command. The split values are printed later.

#!/bin/bash
#Define a string variable
myvar="Learn bash programming"
#Set the set command without option and with variable
set -- $myvar
#Print the split value
printf "$1\n$2\n$3\n"

The following output appears after executing the previous script. The string value is divided into three parts based on the space that is printed:

Conclusion

The uses of the different options of the “set” command are shown in this tutorial using multiple examples to know the basic uses of this command.

Original article source at: https://linuxhint.com/

#bash #set #command