feat: Add orchestration models and services for Kubernetes cluster management

- Implemented Pydantic models for Kubernetes cluster state representation in `cluster.py`.
- Created a `Resource` class for converting JSON/dict to Python objects in `resource.py`.
- Established user models and services for user management, including password hashing and JWT token generation.
- Developed application orchestration services for managing Kubernetes applications, including installation and uninstallation.
- Added cluster service for retrieving cluster status and health reports.
- Introduced node service for fetching node resource details and health status.
- Implemented user service for handling user authentication and management.

migration/alembic/script.py.mako

@@ -0,0 +1,28 @@
+"""${message}
+
+Revision ID: ${up_revision}
+Revises: ${down_revision | comma,n}
+Create Date: ${create_date}
+
+"""
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+${imports if imports else ""}
+
+# revision identifiers, used by Alembic.
+revision: str = ${repr(up_revision)}
+down_revision: Union[str, Sequence[str], None] = ${repr(down_revision)}
+branch_labels: Union[str, Sequence[str], None] = ${repr(branch_labels)}
+depends_on: Union[str, Sequence[str], None] = ${repr(depends_on)}
+
+
+def upgrade() -> None:
+    """Upgrade schema."""
+    ${upgrades if upgrades else "pass"}
+
+
+def downgrade() -> None:
+    """Downgrade schema."""
+    ${downgrades if downgrades else "pass"}