🐛🎨Computational autoscaling: allow multi-machining/processing

packages/aws-library/src/aws_library/ec2/client.py

@@ -90,9 +90,13 @@ async def get_ec2_instance_capabilities(
                     list_instances.append(
                         EC2InstanceType(
                             name=instance["InstanceType"],
-                            cpus=instance["VCpuInfo"]["DefaultVCpus"],
-                            ram=ByteSize(
-                                int(instance["MemoryInfo"]["SizeInMiB"]) * 1024 * 1024
+                            resources=Resources(
+                                cpus=instance["VCpuInfo"]["DefaultVCpus"],
+                                ram=ByteSize(
+                                    int(instance["MemoryInfo"]["SizeInMiB"])
+                                    * 1024
+                                    * 1024
+                                ),
                             ),
                         )
                     )
@@ -173,9 +177,7 @@ async def start_aws_instance(
                     tags=parse_obj_as(
                         EC2Tags, {tag["Key"]: tag["Value"] for tag in instance["Tags"]}
                     ),
-                    resources=Resources(
-                        cpus=instance_config.type.cpus, ram=instance_config.type.ram
-                    ),
+                    resources=instance_config.type.resources,
                 )
                 for instance in instances["Reservations"][0]["Instances"]
             ]
@@ -234,10 +236,7 @@ async def get_instances(
                         else None,
                         type=instance["InstanceType"],
                         state=instance["State"]["Name"],
-                        resources=Resources(
-                            cpus=ec2_instance_types[0].cpus,
-                            ram=ec2_instance_types[0].ram,
-                        ),
+                        resources=ec2_instance_types[0].resources,
                         tags=parse_obj_as(
                             EC2Tags,
                             {tag["Key"]: tag["Value"] for tag in instance["Tags"]},

packages/aws-library/src/aws_library/ec2/models.py

@@ -13,13 +13,12 @@
     Extra,
     Field,
     NonNegativeFloat,
-    PositiveInt,
     validator,
 )
 from types_aiobotocore_ec2.literals import InstanceStateNameType, InstanceTypeType
 
 
-class Resources(BaseModel):
+class Resources(BaseModel, frozen=True):
     cpus: NonNegativeFloat
     ram: ByteSize
 
@@ -53,12 +52,16 @@ def __sub__(self, other: "Resources") -> "Resources":
             }
         )
 
+    @validator("cpus", pre=True)
+    @classmethod
+    def _floor_cpus_to_0(cls, v: float) -> float:
+        return max(v, 0)
 
-@dataclass(frozen=True)
+
+@dataclass(frozen=True, kw_only=True, slots=True)
 class EC2InstanceType:
     name: InstanceTypeType
-    cpus: PositiveInt
-    ram: ByteSize
+    resources: Resources
 
 
 InstancePrivateDNSName: TypeAlias = str

packages/models-library/src/models_library/api_schemas_clusters_keeper/ec2_instances.py

@@ -1,10 +1,10 @@
 from dataclasses import dataclass
 
-from pydantic import ByteSize, PositiveInt
+from pydantic import ByteSize, NonNegativeFloat
 
 
 @dataclass(frozen=True)
 class EC2InstanceTypeGet:
     name: str
-    cpus: PositiveInt
+    cpus: NonNegativeFloat
     ram: ByteSize

packages/pytest-simcore/src/pytest_simcore/dask_scheduler.py

@@ -75,7 +75,7 @@ async def dask_spec_local_cluster(
         scheduler_address = URL(cluster.scheduler_address)
         monkeypatch.setenv(
             "COMPUTATIONAL_BACKEND_DEFAULT_CLUSTER_URL",
-            f"{scheduler_address}" or "invalid",
+            f"{scheduler_address or 'invalid'}",
         )
         yield cluster
 
@@ -95,7 +95,7 @@ async def dask_local_cluster_without_workers(
         scheduler_address = URL(cluster.scheduler_address)
         monkeypatch.setenv(
             "COMPUTATIONAL_BACKEND_DEFAULT_CLUSTER_URL",
-            f"{scheduler_address}" or "invalid",
+            f"{scheduler_address or 'invalid'}",
         )
         yield cluster
 

services/autoscaling/docker/entrypoint.sh

@@ -71,8 +71,8 @@ if [ "${SC_BUILD_TARGET}" = "development" ]; then
 fi
 
 if [ "${SC_BOOT_MODE}" = "debug-ptvsd" ]; then
-  # NOTE: production does NOT pre-installs ptvsd
-  pip install --no-cache-dir ptvsd
+  # NOTE: production does NOT pre-installs debugpy
+  pip install --no-cache-dir debugpy
 fi
 
 # Appends docker group if socket is mounted

services/autoscaling/src/simcore_service_autoscaling/core/application.py

@@ -1,6 +1,7 @@
 import logging
 
 from fastapi import FastAPI
+from models_library.basic_types import BootModeEnum
 from servicelib.fastapi.prometheus_instrumentation import (
     setup_prometheus_instrumentation,
 )
@@ -21,6 +22,7 @@
 from ..modules.ec2 import setup as setup_ec2
 from ..modules.rabbitmq import setup as setup_rabbitmq
 from ..modules.redis import setup as setup_redis
+from ..modules.remote_debug import setup_remote_debugging
 from .settings import ApplicationSettings
 
 logger = logging.getLogger(__name__)
@@ -46,6 +48,8 @@ def create_app(settings: ApplicationSettings) -> FastAPI:
         setup_prometheus_instrumentation(app)
 
     # PLUGINS SETUP
+    if settings.SC_BOOT_MODE == BootModeEnum.DEBUG:
+        setup_remote_debugging(app)
     setup_api_routes(app)
     setup_docker(app)
     setup_rabbitmq(app)

services/autoscaling/src/simcore_service_autoscaling/core/settings.py

@@ -8,6 +8,7 @@
     BootModeEnum,
     BuildTargetEnum,
     LogLevel,
+    PortInt,
     VersionTag,
 )
 from models_library.docker import DockerLabelKey
@@ -182,6 +183,7 @@ class ApplicationSettings(BaseCustomSettings, MixinLoggingSettings):
     AUTOSCALING_DEBUG: bool = Field(
         default=False, description="Debug mode", env=["AUTOSCALING_DEBUG", "DEBUG"]
     )
+    AUTOSCALING_REMOTE_DEBUG_PORT: PortInt = PortInt(3000)
 
     AUTOSCALING_LOGLEVEL: LogLevel = Field(
         LogLevel.INFO, env=["AUTOSCALING_LOGLEVEL", "LOG_LEVEL", "LOGLEVEL"]

services/autoscaling/src/simcore_service_autoscaling/models.py

@@ -6,43 +6,68 @@
 from models_library.generated_models.docker_rest_api import Node
 
 
-@dataclass(frozen=True, kw_only=True)
-class AssignedTasksToInstance:
-    instance: EC2InstanceData
-    available_resources: Resources
-    assigned_tasks: list
+@dataclass(frozen=True, slots=True, kw_only=True)
+class _TaskAssignmentMixin:
+    assigned_tasks: list = field(default_factory=list)
+    available_resources: Resources = field(default_factory=Resources.create_as_empty)
 
+    def assign_task(self, task, task_resources: Resources) -> None:
+        self.assigned_tasks.append(task)
+        object.__setattr__(
+            self, "available_resources", self.available_resources - task_resources
+        )
 
-@dataclass(frozen=True, kw_only=True)
-class AssignedTasksToInstanceType:
+    def has_resources_for_task(self, task_resources: Resources) -> bool:
+        return bool(self.available_resources >= task_resources)
+
+
+@dataclass(frozen=True, kw_only=True, slots=True)
+class AssignedTasksToInstanceType(_TaskAssignmentMixin):
     instance_type: EC2InstanceType
-    assigned_tasks: list
 
 
-@dataclass(frozen=True)
-class AssociatedInstance:
-    node: Node
+@dataclass(frozen=True, kw_only=True, slots=True)
+class _BaseInstance(_TaskAssignmentMixin):
     ec2_instance: EC2InstanceData
 
+    def __post_init__(self) -> None:
+        if self.available_resources == Resources.create_as_empty():
+            object.__setattr__(self, "available_resources", self.ec2_instance.resources)
+
+
+@dataclass(frozen=True, kw_only=True, slots=True)
+class AssociatedInstance(_BaseInstance):
+    node: Node
+
+
+@dataclass(frozen=True, kw_only=True, slots=True)
+class NonAssociatedInstance(_BaseInstance):
+    ...
 
-@dataclass(frozen=True)
+
+@dataclass(frozen=True, kw_only=True, slots=True)
 class Cluster:
     active_nodes: list[AssociatedInstance] = field(
         metadata={
-            "description": "This is a EC2 backed docker node which is active (with running tasks)"
+            "description": "This is a EC2-backed docker node which is active and ready to receive tasks (or with running tasks)"
+        }
+    )
+    pending_nodes: list[AssociatedInstance] = field(
+        metadata={
+            "description": "This is a EC2-backed docker node which is active and NOT yet ready to receive tasks"
         }
     )
     drained_nodes: list[AssociatedInstance] = field(
         metadata={
-            "description": "This is a EC2 backed docker node which is drained (with no tasks)"
+            "description": "This is a EC2-backed docker node which is drained (cannot accept tasks)"
         }
     )
     reserve_drained_nodes: list[AssociatedInstance] = field(
         metadata={
-            "description": "This is a EC2 backed docker node which is drained in the reserve if this is enabled (with no tasks)"
+            "description": "This is a EC2-backed docker node which is drained in the reserve if this is enabled (with no tasks)"
         }
     )
-    pending_ec2s: list[EC2InstanceData] = field(
+    pending_ec2s: list[NonAssociatedInstance] = field(
         metadata={
             "description": "This is an EC2 instance that is not yet associated to a docker node"
         }
@@ -54,6 +79,23 @@ class Cluster:
     )
     terminated_instances: list[EC2InstanceData]
 
+    def can_scale_down(self) -> bool:
+        return bool(
+            self.active_nodes
+            or self.pending_nodes
+            or self.drained_nodes
+            or self.pending_ec2s
+        )
+
+    def total_number_of_machines(self) -> int:
+        return (
+            len(self.active_nodes)
+            + len(self.pending_nodes)
+            + len(self.drained_nodes)
+            + len(self.reserve_drained_nodes)
+            + len(self.pending_ec2s)
+        )
+
 
 DaskTaskId: TypeAlias = str