1 # ============LICENSE_START=======================================================
3 # ================================================================================
4 # Copyright (c) 2018 AT&T Intellectual Property. All rights reserved.
5 # ================================================================================
6 # Licensed under the Apache License, Version 2.0 (the "License");
7 # you may not use this file except in compliance with the License.
8 # You may obtain a copy of the License at
10 # http://www.apache.org/licenses/LICENSE-2.0
12 # Unless required by applicable law or agreed to in writing, software
13 # distributed under the License is distributed on an "AS IS" BASIS,
14 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
15 # See the License for the specific language governing permissions and
16 # limitations under the License.
17 # ============LICENSE_END=========================================================
19 # ECOMP is a trademark and service mark of AT&T Intellectual Property.
24 from kubernetes import config, client, stream
26 # Default values for readiness probe
27 PROBE_DEFAULT_PERIOD = 15
28 PROBE_DEFAULT_TIMEOUT = 1
30 # Regular expression for interval/timeout specification
31 INTERVAL_SPEC = re.compile("^([0-9]+)(s|m|h)?$")
32 # Conversion factors to seconds
33 FACTORS = {None: 1, "s": 1, "m": 60, "h": 3600}
35 # Regular expression for port mapping
36 # group 1: container port
37 # group 2: / + protocol
40 PORTS = re.compile("^([0-9]+)(/(udp|UDP|tcp|TCP))?:([0-9]+)$")
42 def _create_deployment_name(component_name):
43 return "dep-{0}".format(component_name)
45 def _create_service_name(component_name):
46 return "{0}".format(component_name)
48 def _create_exposed_service_name(component_name):
49 return ("x{0}".format(component_name))[:63]
52 # Look for a kubernetes config file in ~/.kube/config
53 kubepath = os.path.join(os.environ["HOME"], '.kube/config')
54 if os.path.exists(kubepath):
55 config.load_kube_config(kubepath)
57 # Maybe we're running in a k8s container and we can use info provided by k8s
58 # We would like to use:
59 # config.load_incluster_config()
60 # but this looks into os.environ for kubernetes host and port, and from
61 # the plugin those aren't visible. So we use the InClusterConfigLoader class,
62 # where we can set the environment to what we like.
63 # This is probably brittle! Maybe there's a better alternative.
65 config.incluster_config.SERVICE_HOST_ENV_NAME : "kubernetes.default.svc.cluster.local",
66 config.incluster_config.SERVICE_PORT_ENV_NAME : "443"
68 config.incluster_config.InClusterConfigLoader(
69 token_filename=config.incluster_config.SERVICE_TOKEN_FILENAME,
70 cert_filename=config.incluster_config.SERVICE_CERT_FILENAME,
74 def _parse_interval(t):
76 Parse an interval specification
78 - a simple integer quantity, interpreted as seconds
79 - a string representation of a decimal integer, interpreted as seconds
80 - a string consisting of a represention of an decimal integer followed by a unit,
81 with "s" representing seconds, "m" representing minutes,
82 and "h" representing hours
83 Used for compatibility with the Docker plugin, where time intervals
84 for health checks were specified as strings with a number and a unit.
85 See 'intervalspec' above for the regular expression that's accepted.
87 m = INTERVAL_SPEC.match(str(t))
89 time = int(m.group(1)) * FACTORS[m.group(2)]
91 raise ValueError("Bad interval specification: {0}".format(t))
94 def _create_probe(hc, port, use_tls=False):
95 ''' Create a Kubernetes probe based on info in the health check dictionary hc '''
96 probe_type = hc['type']
98 period = _parse_interval(hc.get('interval', PROBE_DEFAULT_PERIOD))
99 timeout = _parse_interval(hc.get('timeout', PROBE_DEFAULT_TIMEOUT))
100 if probe_type in ['http', 'https']:
101 probe = client.V1Probe(
102 failure_threshold = 1,
103 initial_delay_seconds = 5,
104 period_seconds = period,
105 timeout_seconds = timeout,
106 http_get = client.V1HTTPGetAction(
107 path = hc['endpoint'],
109 scheme = probe_type.upper()
112 elif probe_type in ['script', 'docker']:
113 probe = client.V1Probe(
114 failure_threshold = 1,
115 initial_delay_seconds = 5,
116 period_seconds = period,
117 timeout_seconds = timeout,
118 _exec = client.V1ExecAction(
119 command = [hc['script']]
124 def _create_container_object(name, image, always_pull, use_tls=False, env={}, container_ports=[], volume_mounts = [], readiness = None):
125 # Set up environment variables
126 # Copy any passed in environment variables
127 env_vars = [client.V1EnvVar(name=k, value=env[k]) for k in env.keys()]
128 # Add POD_IP with the IP address of the pod running the container
129 pod_ip = client.V1EnvVarSource(field_ref = client.V1ObjectFieldSelector(field_path="status.podIP"))
130 env_vars.append(client.V1EnvVar(name="POD_IP",value_from=pod_ip))
132 # If a health check is specified, create a readiness probe
133 # (For an HTTP-based check, we assume it's at the first container port)
138 if len(container_ports) > 0:
139 (hc_port, proto) = container_ports[0]
140 probe = _create_probe(readiness, hc_port, use_tls)
142 # Define container for pod
143 return client.V1Container(
146 image_pull_policy='Always' if always_pull else 'IfNotPresent',
148 ports=[client.V1ContainerPort(container_port=p, protocol=proto) for (p, proto) in container_ports],
149 volume_mounts = volume_mounts,
150 readiness_probe = probe
153 def _create_deployment_object(component_name,
161 deployment_name = _create_deployment_name(component_name)
163 # Label the pod with the deployment name, so we can find it easily
164 labels.update({"k8sdeployment" : deployment_name})
166 # pull_secrets is a list of the names of the k8s secrets containing docker registry credentials
167 # See https://kubernetes.io/docs/concepts/containers/images/#specifying-imagepullsecrets-on-a-pod
169 for secret in pull_secrets:
170 ips.append(client.V1LocalObjectReference(name=secret))
172 # Define pod template
173 template = client.V1PodTemplateSpec(
174 metadata=client.V1ObjectMeta(labels=labels),
175 spec=client.V1PodSpec(hostname=component_name,
176 containers=containers,
177 init_containers=init_containers,
179 image_pull_secrets=ips)
182 # Define deployment spec
183 spec = client.ExtensionsV1beta1DeploymentSpec(
188 # Create deployment object
189 deployment = client.ExtensionsV1beta1Deployment(
191 metadata=client.V1ObjectMeta(name=deployment_name),
197 def _create_service_object(service_name, component_name, service_ports, annotations, labels, service_type):
198 service_spec = client.V1ServiceSpec(
200 selector={"app" : component_name},
204 metadata = client.V1ObjectMeta(name=_create_service_name(service_name), labels=labels, annotations=annotations)
206 metadata = client.V1ObjectMeta(name=_create_service_name(service_name), labels=labels)
208 service = client.V1Service(
216 def _parse_ports(port_list):
218 Parse the port list into a list of container ports (needed to create the container)
219 and to a set of port mappings to set up k8s services.
224 m = PORTS.match(p.strip())
226 cport = int(m.group(1))
227 hport = int (m.group(4))
229 proto = (m.group(3)).upper()
232 container_ports.append((cport, proto))
233 port_map[(cport, proto)] = hport
235 raise ValueError("Bad port specification: {0}".format(p))
237 return container_ports, port_map
239 def _parse_volumes(volume_list):
242 for v in volume_list:
243 vname = str(uuid.uuid4())
244 vhost = v['host']['path']
245 vcontainer = v['container']['bind']
246 vro = (v['container']['mode'] == 'ro')
247 volumes.append(client.V1Volume(name=vname, host_path=client.V1HostPathVolumeSource(path=vhost)))
248 volume_mounts.append(client.V1VolumeMount(name=vname, mount_path=vcontainer, read_only=vro))
250 return volumes, volume_mounts
252 def _service_exists(namespace, component_name):
256 client.CoreV1Api().read_namespaced_service(_create_service_name(component_name), namespace)
258 except client.rest.ApiException:
263 def _patch_deployment(namespace, deployment, modify):
265 Gets the current spec for 'deployment' in 'namespace',
266 uses the 'modify' function to change the spec,
267 then sends the updated spec to k8s.
271 # Get deployment spec
272 spec = client.ExtensionsV1beta1Api().read_namespaced_deployment(deployment, namespace)
274 # Apply changes to spec
277 # Patch the deploy with updated spec
278 client.ExtensionsV1beta1Api().patch_namespaced_deployment(deployment, namespace, spec)
280 def _execute_command_in_pod(namespace, pod_name, command):
282 Execute the command (specified by an argv-style list in the "command" parameter) in
283 the specified pod in the specified namespace. For now at least, we use this only to
284 run a notification script in a pod after a configuration change.
286 The straightforward way to do this is with the V1 Core API function "connect_get_namespaced_pod_exec".
287 Unfortunately due to a bug/limitation in the Python client library, we can't call it directly.
288 We have to make the API call through a Websocket connection using the kubernetes.stream wrapper API.
289 I'm following the example code at https://github.com/kubernetes-client/python/blob/master/examples/exec.py.
290 There are several issues tracking this, in various states. It isn't clear that there will ever
292 - https://github.com/kubernetes-client/python/issues/58
293 - https://github.com/kubernetes-client/python/issues/409
294 - https://github.com/kubernetes-client/python/issues/526
296 The main consequence of the workaround using "stream" is that the caller does not get an indication
297 of the exit code returned by the command when it completes execution. It turns out that the
298 original implementation of notification in the Docker plugin did not use this result, so we can
299 still match the original notification functionality.
301 The "stream" approach returns a string containing any output sent by the command to stdout or stderr.
302 We'll return that so it can logged.
306 output = stream.stream(client.CoreV1Api().connect_get_namespaced_pod_exec,
314 except client.rest.ApiException as e:
315 # If the exception indicates the pod wasn't found, it's not a fatal error.
316 # It existed when we enumerated the pods for the deployment but no longer exists.
317 # Unfortunately, the only way to distinguish a pod not found from any other error
318 # is by looking at the reason text.
319 # (The ApiException's "status" field should contain the HTTP status code, which would
320 # be 404 if the pod isn't found, but empirical testing reveals that "status" is set
322 if "404 not found" in e.reason.lower():
323 output = "Pod not found"
327 return {"pod" : pod_name, "output" : output}
329 def deploy(namespace, component_name, image, replicas, always_pull, k8sconfig, **kwargs):
331 This will create a k8s Deployment and, if needed, one or two k8s Services.
332 (We are being opinionated in our use of k8s... this code decides what k8s abstractions and features to use.
333 We're not exposing k8s to the component developer and the blueprint author.
334 This is a conscious choice. We want to use k8s in a controlled, consistent way, and we want to hide
335 the details from the component developer and the blueprint author.)
337 namespace: the Kubernetes namespace into which the component is deployed
338 component_name: the component name, used to derive names of Kubernetes entities
339 image: the docker image for the component being deployed
340 replica: the number of instances of the component to be deployed
341 always_pull: boolean flag, indicating that Kubernetes should always pull a new copy of
342 the Docker image for the component, even if it is already present on the Kubernetes node.
344 - image_pull_secrets: a list of names of image pull secrets that can be used for retrieving images.
345 (DON'T PANIC: these are just the names of secrets held in the Kubernetes secret store.)
346 - filebeat: a dictionary of filebeat sidecar parameters:
347 "log_path" : mount point for log volume in filebeat container
348 "data_path" : mount point for data volume in filebeat container
349 "config_path" : mount point for config volume in filebeat container
350 "config_subpath" : subpath for config data in filebeat container
351 "config_map" : ConfigMap holding the filebeat configuration
352 "image": Docker image to use for filebeat
353 - tls: a dictionary of TLS init container parameters:
354 "cert_path": mount point for certificate volume in init container
355 "image": Docker image to use for TLS init container
357 - volumes: array of volume objects, where a volume object is:
358 {"host":{"path": "/path/on/host"}, "container":{"bind":"/path/on/container","mode":"rw_or_ro"}
359 - ports: array of strings in the form "container_port:host_port"
360 - env: map of name-value pairs ( {name0: value0, name1: value1...}
361 - msb_list: array of msb objects, where an msb object is as described in msb/msb.py.
362 - log_info: an object with info for setting up ELK logging, with the form:
363 {"log_directory": "/path/to/container/log/directory", "alternate_fb_path" : "/alternate/sidecar/log/path"}
364 - tls_info: an object with info for setting up TLS (HTTPS), with the form:
365 {"use_tls": true, "cert_directory": "/path/to/container/cert/directory" }
366 - labels: dict with label-name/label-value pairs, e.g. {"cfydeployment" : "lsdfkladflksdfsjkl", "cfynode":"mycomponent"}
367 These label will be set on all the pods deployed as a result of this deploy() invocation.
368 - readiness: dict with health check info; if present, used to create a readiness probe for the main container. Includes:
369 - type: check is done by making http(s) request to an endpoint ("http", "https") or by exec'ing a script in the container ("script", "docker")
370 - interval: period (in seconds) between probes
371 - timeout: time (in seconds) to allow a probe to complete
372 - endpoint: the path portion of the URL that points to the readiness endpoint for "http" and "https" types
373 - path: the full path to the script to be executed in the container for "script" and "docker" types
377 deployment_ok = False
378 cip_service_created = False
379 deployment_description = {
380 "namespace": namespace,
389 core = client.CoreV1Api()
390 ext = client.ExtensionsV1beta1Api()
392 # Parse the port mapping
393 container_ports, port_map = _parse_ports(kwargs.get("ports", []))
395 # Parse the volumes list into volumes and volume_mounts for the deployment
396 volumes, volume_mounts = _parse_volumes(kwargs.get("volumes",[]))
398 # Initialize the list of containers that will be part of the pod
402 # Set up the ELK logging sidecar container, if needed
403 log_info = kwargs.get("log_info")
404 if log_info and "log_directory" in log_info:
405 log_dir = log_info["log_directory"]
406 fb = k8sconfig["filebeat"]
407 sidecar_volume_mounts = []
409 # Create the volume for component log files and volume mounts for the component and sidecar containers
410 volumes.append(client.V1Volume(name="component-log", empty_dir=client.V1EmptyDirVolumeSource()))
411 volume_mounts.append(client.V1VolumeMount(name="component-log", mount_path=log_dir))
412 sc_path = log_info["alternate_fb_path"] if "alternate_fb_path" in log_info \
413 else "{0}/{1}".format(fb["log_path"], component_name)
414 sidecar_volume_mounts.append(client.V1VolumeMount(name="component-log", mount_path=sc_path))
416 # Create the volume for sidecar data and the volume mount for it
417 volumes.append(client.V1Volume(name="filebeat-data", empty_dir=client.V1EmptyDirVolumeSource()))
418 sidecar_volume_mounts.append(client.V1VolumeMount(name="filebeat-data", mount_path=fb["data_path"]))
420 # Create the container for the sidecar
421 containers.append(_create_container_object("filebeat", fb["image"], False, False, {}, [], sidecar_volume_mounts))
423 # Create the volume for the sidecar configuration data and the volume mount for it
424 # The configuration data is in a k8s ConfigMap that should be created when DCAE is installed.
426 client.V1Volume(name="filebeat-conf", config_map=client.V1ConfigMapVolumeSource(name=fb["config_map"])))
427 sidecar_volume_mounts.append(
428 client.V1VolumeMount(name="filebeat-conf", mount_path=fb["config_path"], sub_path=fb["config_subpath"]))
430 # Set up the TLS init container, if needed
431 tls_info = kwargs.get("tls_info")
433 if tls_info and "use_tls" in tls_info and tls_info["use_tls"]:
434 if "cert_directory" in tls_info and len(tls_info["cert_directory"]) > 0:
436 tls_config = k8sconfig["tls"]
438 # Create the certificate volume and volume mounts
439 volumes.append(client.V1Volume(name="tls-info", empty_dir=client.V1EmptyDirVolumeSource()))
440 volume_mounts.append(client.V1VolumeMount(name="tls-info", mount_path=tls_info["cert_directory"]))
441 init_volume_mounts = [client.V1VolumeMount(name="tls-info", mount_path=tls_config["cert_path"])]
443 # Create the init container
444 init_containers.append(_create_container_object("init-tls", tls_config["image"], False, False, {}, [], init_volume_mounts))
446 # Create the container for the component
447 # Make it the first container in the pod
448 containers.insert(0, _create_container_object(component_name, image, always_pull, use_tls, kwargs.get("env", {}), container_ports, volume_mounts, kwargs["readiness"]))
450 # Build the k8s Deployment object
451 labels = kwargs.get("labels", {})
452 labels.update({"app": component_name})
453 dep = _create_deployment_object(component_name, containers, init_containers, replicas, volumes, labels, pull_secrets=k8sconfig["image_pull_secrets"])
456 ext.create_namespaced_deployment(namespace, dep)
458 deployment_description["deployment"] = _create_deployment_name(component_name)
460 # Create service(s), if a port mapping is specified
462 service_ports = [] # Ports exposed internally on the k8s network
463 exposed_ports = [] # Ports to be mapped to ports on the k8s nodes via NodePort
464 for (cport, proto), hport in port_map.iteritems():
465 service_ports.append(client.V1ServicePort(port=int(cport),protocol=proto,name="port-{0}-{1}".format(proto[0].lower(), cport)))
467 exposed_ports.append(client.V1ServicePort(port=int(cport),protocol=proto,node_port=int(hport),name="xport-{0}-{1}".format(proto[0].lower(),cport)))
469 # If there are ports to be exposed via MSB, set up the annotation for the service
470 msb_list = kwargs.get("msb_list")
471 annotations = msb.create_msb_annotation(msb_list) if msb_list else ''
473 # Create a ClusterIP service for access via the k8s network
474 service = _create_service_object(_create_service_name(component_name), component_name, service_ports, annotations, labels, "ClusterIP")
475 core.create_namespaced_service(namespace, service)
476 cip_service_created = True
477 deployment_description["services"].append(_create_service_name(component_name))
479 # If there are ports to be exposed on the k8s nodes, create a "NodePort" service
480 if len(exposed_ports) > 0:
482 _create_service_object(_create_exposed_service_name(component_name), component_name, exposed_ports, '', labels, "NodePort")
483 core.create_namespaced_service(namespace, exposed_service)
484 deployment_description["services"].append(_create_exposed_service_name(component_name))
486 except Exception as e:
487 # If the ClusterIP service was created, delete the service:
488 if cip_service_created:
489 core.delete_namespaced_service(_create_service_name(component_name), namespace)
490 # If the deployment was created but not the service, delete the deployment
492 client.ExtensionsV1beta1Api().delete_namespaced_deployment(_create_deployment_name(component_name), namespace, client.V1DeleteOptions())
495 return dep, deployment_description
497 def undeploy(deployment_description):
500 namespace = deployment_description["namespace"]
502 # remove any services associated with the component
503 for service in deployment_description["services"]:
504 client.CoreV1Api().delete_namespaced_service(service, namespace)
506 # Have k8s delete the underlying pods and replicaset when deleting the deployment.
507 options = client.V1DeleteOptions(propagation_policy="Foreground")
508 client.ExtensionsV1beta1Api().delete_namespaced_deployment(deployment_description["deployment"], namespace, options)
510 def is_available(namespace, component_name):
512 dep_status = client.AppsV1beta1Api().read_namespaced_deployment_status(_create_deployment_name(component_name), namespace)
513 # Check if the number of available replicas is equal to the number requested and that the replicas match the current spec
514 # This check can be used to verify completion of an initial deployment, a scale operation, or an update operation
515 return dep_status.status.available_replicas == dep_status.spec.replicas and dep_status.status.updated_replicas == dep_status.spec.replicas
517 def scale(deployment_description, replicas):
518 ''' Trigger a scaling operation by updating the replica count for the Deployment '''
520 def update_replica_count(spec):
521 spec.spec.replicas = replicas
524 _patch_deployment(deployment_description["namespace"], deployment_description["deployment"], update_replica_count)
526 def upgrade(deployment_description, image, container_index = 0):
527 ''' Trigger a rolling upgrade by sending a new image name/tag to k8s '''
529 def update_image(spec):
530 spec.spec.template.spec.containers[container_index].image = image
533 _patch_deployment(deployment_description["namespace"], deployment_description["deployment"], update_image)
535 def rollback(deployment_description, rollback_to=0):
537 Undo upgrade by rolling back to a previous revision of the deployment.
538 By default, go back one revision.
539 rollback_to can be used to supply a specific revision number.
540 Returns the image for the app container and the replica count from the rolled-back deployment
544 Currently this does not work due to a bug in the create_namespaced_deployment_rollback() method.
545 The k8s python client code throws an exception while processing the response from the API.
547 - https://github.com/kubernetes-client/python/issues/491
548 - https://github.com/kubernetes/kubernetes/pull/63837
549 The fix has been merged into the master branch but is not in the latest release.
552 deployment = deployment_description["deployment"]
553 namespace = deployment_description["namespace"]
555 # Initiate the rollback
556 client.ExtensionsV1beta1Api().create_namespaced_deployment_rollback(
559 client.AppsV1beta1DeploymentRollback(name=deployment, rollback_to=client.AppsV1beta1RollbackConfig(revision=rollback_to)))
561 # Read back the spec for the rolled-back deployment
562 spec = client.ExtensionsV1beta1Api().read_namespaced_deployment(deployment, namespace)
563 return spec.spec.template.spec.containers[0].image, spec.spec.replicas
565 def execute_command_in_deployment(deployment_description, command):
567 Enumerates the pods in the k8s deployment identified by "deployment_description",
568 then executes the command (represented as an argv-style list) in "command" in
569 container 0 (the main application container) each of those pods.
571 Note that the sets of pods associated with a deployment can change over time. The
572 enumeration is a snapshot at one point in time. The command will not be executed in
573 pods that are created after the initial enumeration. If a pod disappears after the
574 initial enumeration and before the command is executed, the attempt to execute the
575 command will fail. This is not treated as a fatal error.
577 This approach is reasonable for the one current use case for "execute_command": running a
578 script to notify a container that its configuration has changed as a result of a
579 policy change. In this use case, the new configuration information is stored into
580 the configuration store (Consul), the pods are enumerated, and the command is executed.
581 If a pod disappears after the enumeration, the fact that the command cannot be run
582 doesn't matter--a nonexistent pod doesn't need to be reconfigured. Similarly, a pod that
583 comes up after the enumeration will get its initial configuration from the updated version
586 The optimal solution here would be for k8s to provide an API call to execute a command in
587 all of the pods for a deployment. Unfortunately, k8s does not provide such a call--the
588 only call provided by k8s operates at the pod level, not the deployment level.
590 Another interesting k8s factoid: there's no direct way to list the pods belong to a
591 particular k8s deployment. The deployment code above sets a label ("k8sdeployment") on
592 the pod that has the k8s deployment name. To list the pods, the code below queries for
593 pods with the label carrying the deployment name.
597 deployment = deployment_description["deployment"]
598 namespace = deployment_description["namespace"]
600 # Get names of all the running pods belonging to the deployment
601 pod_names = [pod.metadata.name for pod in client.CoreV1Api().list_namespaced_pod(
602 namespace = namespace,
603 label_selector = "k8sdeployment={0}".format(deployment),
604 field_selector = "status.phase=Running"
607 def do_execute(pod_name):
608 return _execute_command_in_pod(namespace, pod_name, command)
610 # Execute command in the running pods
611 return map(do_execute, pod_names)