Split backend and paddlejob abstraction (#374)

* publish files

* publish files

* fix travis error

* split backend and job abstraction

* try fix ci

paddlecloud/paddlejob/cloudprovider/k8s_provider.py

@@ -0,0 +1,309 @@
+from kubernetes import client, config
+from kubernetes.client.rest import ApiException
+# FIXME(typhoonzero): still need to import settings
+from django.conf import settings
+
+import copy
+import os
+import logging
+import traceback
+
+import utils
+import volume
+
+# FIXME(typhoonzero): need a base class to define the interfaces?
+class K8sProvider:
+    """
+        Kubernetes Cloud Porvider
+        Provide interfaces for manage jobs and resources.
+    """
+    def __init__(self):
+        pass
+
+    def get_jobs(self, username):
+        namespace = utils.email_escape(username)
+        api_instance =\
+            client.BatchV1Api(api_client=utils.get_user_api_client(username))
+        job_list = api_instance.list_namespaced_job(namespace)
+        # NOTE: when job is deleted, some pods of the job will be at "Terminating" status
+        # for a while, which may cause submit fail. Find all pods that are still "Terminating".
+        user_pod_list =\
+            client.CoreV1Api(api_client=utils.get_user_api_client(username))\
+            .list_namespaced_pod(namespace)
+        terminating_jobs = []
+        for pod in user_pod_list.items:
+            jobname = ""
+            if not pod.metadata.labels:
+                continue
+            if "paddle-job" in pod.metadata.labels:
+                jobname = pod.metadata.labels["paddle-job"]
+            elif "paddle-job-master" in pod.metadata.labels:
+                jobname = pod.metadata.labels["paddle-job-master"]
+            elif "paddle-job-pserver" in pod.metadata.labels:
+                jobname = pod.metadata.labels["paddle-job-pserver"]
+            if pod.metadata.deletion_timestamp and jobname:
+                if jobname not in terminating_jobs:
+                    terminating_jobs.append(jobname)
+        # NOTE: put it in the original dict for backward compability
+        ret_dict = copy.deepcopy(job_list.to_dict())
+        ret_dict["terminating"] = terminating_jobs
+        return ret_dict
+
+    def __setup_volumes(self, paddlejob, username):
+        volumes = []
+        for k, cfg in settings.DATACENTERS.items():
+            if k != paddlejob.dc and k != "public":
+                continue
+            fstype = cfg["fstype"]
+            if fstype == settings.FSTYPE_CEPHFS:
+                if k == "public":
+                    mount_path = cfg["mount_path"] % paddlejob.dc
+                    cephfs_path = cfg["cephfs_path"]
+                else:
+                    mount_path = cfg["mount_path"] % (paddlejob.dc, username)
+                    cephfs_path = cfg["cephfs_path"] % username
+                volumes.append(volume.get_volume_config(
+                    fstype = fstype,
+                    name = k.replace("_", "-"),
+                    monitors_addr = cfg["monitors_addr"],
+                    secret = cfg["secret"],
+                    user = cfg["user"],
+                    mount_path = mount_path,
+                    cephfs_path = cephfs_path,
+                    admin_key = cfg["admin_key"],
+                    read_only = cfg.get("read_only", False)
+                ))
+            elif fstype == settings.FSTYPE_HOSTPATH:
+                if k == "public":
+                    mount_path = cfg["mount_path"] % paddlejob.dc
+                    host_path = cfg["host_path"]
+                else:
+                    mount_path = cfg["mount_path"] % (paddlejob.dc, username)
+                    host_path = cfg["host_path"] % username
+
+                volumes.append(volume.get_volume_config(
+                    fstype = fstype,
+                    name = k.replace("_", "-"),
+                    mount_path = mount_path,
+                    host_path = host_path
+                ))
+            else:
+                pass
+        paddlejob.volumes = volumes
+
+    def submit_job(self, paddlejob, username):
+        namespace = utils.email_escape(username)
+        api_client = utils.get_user_api_client(username)
+        self.__setup_volumes(paddlejob, username)
+        if not paddlejob.registry_secret:
+            paddlejob.registry_secret = settings.JOB_DOCKER_IMAGE.get("registry_secret", None)
+        if not paddlejob.image:
+            if paddlejob.gpu > 0:
+                paddlejob.image = settings.JOB_DOCKER_IMAGE["image_gpu"]
+            else:
+                paddlejob.image = settings.JOB_DOCKER_IMAGE["image"]
+        # jobPackage validation: startwith /pfs
+        # NOTE: job packages are uploaded to /pfs/[dc]/home/[user]/jobs/[jobname]
+        package_in_pod = os.path.join("/pfs/%s/home/%s"%(paddlejob.dc, username), "jobs", paddlejob.name)
+
+        logging.info("current package: %s", package_in_pod)
+        # package must be ready before submit a job
+        current_package_path = package_in_pod.replace("/pfs/%s/home"%paddlejob.dc, settings.STORAGE_PATH)
+        if not os.path.exists(current_package_path):
+            current_package_path = package_in_pod.replace("/pfs/%s/home/%s"%(paddlejob.dc, username), settings.STORAGE_PATH)
+            if not os.path.exists(current_package_path):
+                raise Exception("package not exist in cloud: %s"%current_package_path)
+        logging.info("current package in pod: %s", current_package_path)
+        # GPU quota management
+        # TODO(Yancey1989) We should move this to Kubernetes
+        if 'GPU_QUOTA' in dir(settings) and int(paddlejob.gpu) > 0:
+            gpu_usage = 0
+            pods = client.CoreV1Api(api_client=api_client).list_namespaced_pod(namespace=namespace)
+            for pod in pods.items:
+                # only statistics trainer GPU resource, pserver does not use GPU
+                if pod.metadata.labels and 'paddle-job' in pod.metadata.labels and \
+                    pod.status.phase == 'Running':
+                    gpu_usage += int(pod.spec.containers[0].resources.limits.get('alpha.kubernetes.io/nvidia-gpu', '0'))
+            if username in settings.GPU_QUOTA:
+                gpu_quota = settings.GPU_QUOTA[username]['limit']
+            else:
+                gpu_quota = settings.GPU_QUOTA['DEFAULT']['limit']
+            gpu_available = gpu_quota - gpu_usage
+            gpu_request = int(paddlejob.gpu) * int(paddlejob.parallelism)
+            logging.info('gpu available: %d, gpu request: %d' % (gpu_available, gpu_request))
+            if gpu_available < gpu_request:
+                raise Exception("You don't have enought GPU quota," + \
+                    "request: %d, usage: %d, limit: %d" % (gpu_request, gpu_usage, gpu_quota))
+
+        # add Nvidia lib volume if training with GPU
+        if paddlejob.gpu > 0:
+            volumes.append(volume.get_volume_config(
+                fstype = settings.FSTYPE_HOSTPATH,
+                name = "nvidia-libs",
+                mount_path = "/usr/local/nvidia/lib64",
+                host_path = settings.NVIDIA_LIB_PATH
+            ))
+        # ========== submit master ReplicaSet if using fault_tolerant feature ==
+        # FIXME: alpha features in separate module
+        if paddlejob.fault_tolerant:
+            try:
+                ret = client.ExtensionsV1beta1Api(api_client=api_client).create_namespaced_replica_set(
+                    namespace,
+                    paddlejob.new_master_job())
+            except ApiException, e:
+                logging.error("error submitting master job: %s", traceback.format_exc())
+                raise e
+        # ========================= submit pserver job =========================
+        try:
+            ret = client.ExtensionsV1beta1Api(api_client=api_client).create_namespaced_replica_set(
+                namespace,
+                paddlejob.new_pserver_job())
+        except ApiException, e:
+            logging.error("error submitting pserver job: %s ", traceback.format_exc())
+            raise e
+        # ========================= submit trainer job =========================
+        try:
+            ret = client.BatchV1Api(api_client=api_client).create_namespaced_job(
+                namespace,
+                paddlejob.new_trainer_job())
+        except ApiException, e:
+            logging.error("error submitting trainer job: %s" % traceback.format_exc())
+            raise e
+        return ret
+
+    def delete_job(self, jobname, username):
+        namespace = utils.email_escape(username)
+        api_client = utils.get_user_api_client(username)
+        if not jobname:
+            return utils.simple_response(500, "must specify jobname")
+        # FIXME: options needed: grace_period_seconds, orphan_dependents, preconditions
+        # FIXME: cascade delteing
+        delete_status = []
+        # delete job
+        trainer_name = jobname + "-trainer"
+        try:
+            u_status = client.BatchV1Api(api_client=api_client)\
+                .delete_namespaced_job(trainer_name, namespace, {})
+        except ApiException, e:
+            logging.error("error deleting job: %s, %s", jobname, str(e))
+            delete_status.append(str(e))
+
+        # delete job pods
+        try:
+            job_pod_list = client.CoreV1Api(api_client=api_client)\
+                .list_namespaced_pod(namespace,
+                                     label_selector="paddle-job=%s"%jobname)
+            for i in job_pod_list.items:
+                u_status = client.CoreV1Api(api_client=api_client)\
+                    .delete_namespaced_pod(i.metadata.name, namespace, {})
+        except ApiException, e:
+            logging.error("error deleting job pod: %s", str(e))
+            delete_status.append(str(e))
+
+        # delete pserver rs
+        pserver_name = jobname + "-pserver"
+        try:
+            u_status = client.ExtensionsV1beta1Api(api_client=api_client)\
+                .delete_namespaced_replica_set(pserver_name, namespace, {})
+        except ApiException, e:
+            logging.error("error deleting pserver: %s" % str(e))
+            delete_status.append(str(e))
+
+        # delete pserver pods
+        try:
+            # pserver replica set has label with jobname
+            job_pod_list = client.CoreV1Api(api_client=api_client)\
+                .list_namespaced_pod(namespace,
+                                     label_selector="paddle-job-pserver=%s"%jobname)
+            for i in job_pod_list.items:
+                u_status = client.CoreV1Api(api_client=api_client)\
+                    .delete_namespaced_pod(i.metadata.name, namespace, {})
+        except ApiException, e:
+            logging.error("error deleting pserver pods: %s" % str(e))
+            delete_status.append(str(e))
+
+        # delete master rs
+        master_name = jobname + "-master"
+        try:
+            u_status = client.ExtensionsV1beta1Api(api_client=api_client)\
+                .delete_namespaced_replica_set(master_name, namespace, {})
+        except ApiException, e:
+            logging.error("error deleting master: %s" % str(e))
+            # just ignore deleting master failed, we do not set up master process
+            # without fault tolerant mode
+            #delete_status.append(str(e))
+
+        # delete master pods
+        try:
+            # master replica set has label with jobname
+            job_pod_list = client.CoreV1Api(api_client=api_client)\
+                .list_namespaced_pod(namespace,
+                                     label_selector="paddle-job-master=%s"%jobname)
+            for i in job_pod_list.items:
+                u_status = client.CoreV1Api(api_client=api_client)\
+                    .delete_namespaced_pod(i.metadata.name, namespace, {})
+        except ApiException, e:
+            logging.error("error deleting master pods: %s" % str(e))
+            # just ignore deleting master failed, we do not set up master process
+            # without fault tolerant mode
+            #delete_status.append(str(e))
+
+        if len(delete_status) > 0:
+            retcode = 500
+        else:
+            retcode = 200
+        return retcode, delete_status
+
+    def get_pservers(self, username):
+        namespace = utils.email_escape(username)
+        api_instance = client.ExtensionsV1beta1Api(api_client=utils.get_user_api_client(username))
+        return api_instance.list_namespaced_replica_set(namespace).to_dict()
+
+    def get_logs(self, jobname, num_lines, worker, username):
+        def _get_pod_log(api_client, namespace, pod_name, num_lines):
+            try:
+                if num_lines:
+                    pod_log = client.CoreV1Api(api_client=api_client)\
+                        .read_namespaced_pod_log(
+                            pod_name, namespace, tail_lines=int(num_lines))
+                else:
+                    pod_log = client.CoreV1Api(api_client=api_client)\
+                        .read_namespaced_pod_log(i.metadata.name, namespace)
+                return pod_log
+            except ApiException, e:
+                return str(e)
+
+        namespace = utils.email_escape(username)
+        api_client = utils.get_user_api_client(username)
+        job_pod_list = client.CoreV1Api(api_client=api_client)\
+            .list_namespaced_pod(namespace, label_selector="paddle-job=%s"%jobname)
+        total_job_log = ""
+        if not worker:
+            for i in job_pod_list.items:
+                total_job_log = "".join((total_job_log, 
+                    "==========================%s==========================" % i.metadata.name))
+                pod_log = _get_pod_log(api_client, namespace, i.metadata.name, num_lines)
+                total_job_log = "\n".join((total_job_log, pod_log))
+        else:
+            total_job_log = _get_pod_log(api_client, namespace, worker, num_lines)
+        return total_job_log
+
+    def get_workers(self, jobname, username):
+        namespace = utils.email_escape(username)
+        job_pod_list = None
+        api_client = utils.get_user_api_client(username)
+        if not jobname:
+            job_pod_list = client.CoreV1Api(api_client=api_client)\
+                .list_namespaced_pod(namespace)
+        else:
+            selector = "paddle-job=%s"%jobname
+            job_pod_list = client.CoreV1Api(api_client=api_client)\
+                .list_namespaced_pod(namespace, label_selector=selector)
+        return job_pod_list.to_dict()
+
+    def get_quotas(self, username):
+        namespace = utils.email_escape(username)
+        api_client = utils.get_user_api_client(username)
+        quota_list = client.CoreV1Api(api_client=api_client)\
+            .list_namespaced_resource_quota(namespace)
+        return quota_list.to_dict()

paddlecloud/paddlejob/cloudprovider/utils.py

@@ -0,0 +1,52 @@
+import kubernetes
+from kubernetes import client, config
+from kubernetes.client.rest import ApiException
+import os
+# FIXME(typhoonzero): still need to import settings
+from django.conf import settings
+
+def email_escape(email):
+    """
+        Escape email to a safe string of kubernetes namespace
+    """
+    safe_email = email.replace("@", "-")
+    safe_email = safe_email.replace(".", "-")
+    safe_email = safe_email.replace("_", "-")
+    return safe_email
+
+def get_user_api_client(username):
+    """
+        Update kubernetes client to use current logined user's crednetials
+    """
+
+    conf_obj = kubernetes.client.Configuration()
+    conf_obj.host = settings.K8S_HOST
+    conf_obj.ssl_ca_cert = os.path.join(settings.CA_PATH)
+    conf_obj.cert_file = os.path.join(settings.USER_CERTS_PATH, username, "%s.pem"%username)
+    conf_obj.key_file = os.path.join(settings.USER_CERTS_PATH, username, "%s-key.pem"%username)
+    api_client = kubernetes.client.ApiClient(config=conf_obj)
+    return api_client
+
+def get_admin_api_client():
+    """
+        Update kubernetes client to use admin user to create namespace and authorizations
+    """
+
+    conf_obj = kubernetes.client.Configuration()
+    conf_obj.host = settings.K8S_HOST
+    conf_obj.ssl_ca_cert = os.path.join(settings.CA_PATH)
+    conf_obj.cert_file = os.path.join(settings.USER_CERTS_PATH, "admin.pem")
+    conf_obj.key_file = os.path.join(settings.USER_CERTS_PATH, "admin-key.pem")
+    api_client = kubernetes.client.ApiClient(config=conf_obj)
+    return api_client
+
+def user_certs_exist(username):
+    """
+        Return True if the user's certs already generated. User's keys are of pairs.
+    """
+    has_cert = os.path.isfile(os.path.join(settings.USER_CERTS_PATH, username, "%s.pem"%username))
+    has_key = os.path.isfile(os.path.join(settings.USER_CERTS_PATH, username, "%s-key.pem"%username))
+    if has_cert and has_key:
+        return True
+    else:
+        return False