20357994067

Committed 18 Dec 2025 10:01PM UTC coverage: 86.913% (-0.02%) from 86.929%

Build # 20357994067

Build Type

push

github

Committed by

web-flow

Commit Message

Fix CloudWatch model annotation (#13545)

Run Details

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94.12

/localstack-core/localstack/services/lambda_/invocation/assignment.py

import contextlib
import logging
from collections import defaultdict
from concurrent.futures import Future, ThreadPoolExecutor

from localstack.services.lambda_.invocation.execution_environment import (
    EnvironmentStartupTimeoutException,
    ExecutionEnvironment,
    InvalidStatusException,
)
from localstack.services.lambda_.invocation.executor_endpoint import StatusErrorException
from localstack.services.lambda_.invocation.lambda_models import (
    FunctionVersion,
    InitializationType,
    OtherServiceEndpoint,
)

LOG = logging.getLogger(__name__)


class AssignmentException(Exception):
    pass


class AssignmentService(OtherServiceEndpoint):
    """
    scope: LocalStack global
    """

    # function_version manager id => runtime_environment_id => runtime_environment
    environments: dict[str, dict[str, ExecutionEnvironment]]

    # Global pool for spawning and killing provisioned Lambda runtime environments
    provisioning_pool: ThreadPoolExecutor

    def __init__(self):
        self.environments = defaultdict(dict)
        self.provisioning_pool = ThreadPoolExecutor(thread_name_prefix="lambda-provisioning-pool")

    @contextlib.contextmanager
    def get_environment(
        self,
        version_manager_id: str,
        function_version: FunctionVersion,
        provisioning_type: InitializationType,
    ) -> contextlib.AbstractContextManager[ExecutionEnvironment]:
        applicable_envs = (
            env
            for env in self.environments[version_manager_id].values()
            if env.initialization_type == provisioning_type
        )
        execution_environment = None
        for environment in applicable_envs:
            try:
                environment.reserve()
                execution_environment = environment
                break
            except InvalidStatusException:
                pass

        if execution_environment is None:
            if provisioning_type == "provisioned-concurrency":
                raise AssignmentException(
                    "No provisioned concurrency environment available despite lease."
                )
            elif provisioning_type == "on-demand":
                execution_environment = self.start_environment(version_manager_id, function_version)
                self.environments[version_manager_id][execution_environment.id] = (
                    execution_environment
                )
                execution_environment.reserve()
            else:
                raise ValueError(f"Invalid provisioning type {provisioning_type}")

        try:
            yield execution_environment
            execution_environment.release()
        except InvalidStatusException as invalid_e:
            LOG.error("InvalidStatusException: %s", invalid_e)
        except Exception as e:
            LOG.error(
                "Failed invocation <%s>: %s", type(e), e, exc_info=LOG.isEnabledFor(logging.DEBUG)
            )
            self.stop_environment(execution_environment)
            raise e

    def start_environment(
        self, version_manager_id: str, function_version: FunctionVersion
    ) -> ExecutionEnvironment:
        LOG.debug("Starting new environment")
        initialization_type = "on-demand"
        if function_version.config.CapacityProviderConfig:
            initialization_type = "lambda-managed-instances"
        execution_environment = ExecutionEnvironment(
            function_version=function_version,
            initialization_type=initialization_type,
            on_timeout=self.on_timeout,
            version_manager_id=version_manager_id,
        )
        try:
            execution_environment.start()
        except StatusErrorException:
            raise
        except EnvironmentStartupTimeoutException:
            raise
        except Exception as e:
            message = f"Could not start new environment: {type(e).__name__}:{e}"
            raise AssignmentException(message) from e
        return execution_environment

    def on_timeout(self, version_manager_id: str, environment_id: str) -> None:
        """Callback for deleting environment after function times out"""
        del self.environments[version_manager_id][environment_id]

    def stop_environment(self, environment: ExecutionEnvironment) -> None:
        version_manager_id = environment.version_manager_id
        try:
            environment.stop()
            self.environments.get(version_manager_id).pop(environment.id)
        except Exception as e:
            LOG.debug(
                "Error while stopping environment for lambda %s, manager id %s, environment: %s, error: %s",
                environment.function_version.qualified_arn,
                version_manager_id,
                environment.id,
                e,
            )

    def stop_environments_for_version(self, version_manager_id: str):
        # We have to materialize the list before iterating due to concurrency
        environments_to_stop = list(self.environments.get(version_manager_id, {}).values())
        for env in environments_to_stop:
            self.stop_environment(env)

    def scale_provisioned_concurrency(
        self,
        version_manager_id: str,
        function_version: FunctionVersion,
        target_provisioned_environments: int,
    ) -> list[Future[None]]:
        current_provisioned_environments = [
            e
            for e in self.environments[version_manager_id].values()
            if e.initialization_type == "provisioned-concurrency"
        ]
        # TODO: refine scaling loop to re-use existing environments instead of re-creating all
        # current_provisioned_environments_count = len(current_provisioned_environments)
        # diff = target_provisioned_environments - current_provisioned_environments_count

        # TODO: handle case where no provisioned environment is available during scaling
        # Most simple scaling implementation for now:
        futures = []
        # 1) Re-create new target
        for _ in range(target_provisioned_environments):
            execution_environment = ExecutionEnvironment(
                function_version=function_version,
                initialization_type="provisioned-concurrency",
                on_timeout=self.on_timeout,
                version_manager_id=version_manager_id,
            )
            self.environments[version_manager_id][execution_environment.id] = execution_environment
            futures.append(self.provisioning_pool.submit(execution_environment.start))
        # 2) Kill all existing
        for env in current_provisioned_environments:
            # TODO: think about concurrent updates while deleting a function
            futures.append(self.provisioning_pool.submit(self.stop_environment, env))

        return futures

    def stop(self):
        self.provisioning_pool.shutdown(cancel_futures=True)

1	import contextlib	2✔
2	import logging	2✔
3	from collections import defaultdict	2✔
4	from concurrent.futures import Future, ThreadPoolExecutor	2✔
5
6	from localstack.services.lambda_.invocation.execution_environment import (	2✔
7	EnvironmentStartupTimeoutException,
8	ExecutionEnvironment,
9	InvalidStatusException,
10	)
11	from localstack.services.lambda_.invocation.executor_endpoint import StatusErrorException	2✔
12	from localstack.services.lambda_.invocation.lambda_models import (	2✔
13	FunctionVersion,
14	InitializationType,
15	OtherServiceEndpoint,
16	)
17
18	LOG = logging.getLogger(__name__)	2✔
19
20
21	class AssignmentException(Exception):	2✔
22	pass	2✔
23
24
25	class AssignmentService(OtherServiceEndpoint):	2✔
26	"""
27	scope: LocalStack global
28	"""
29
30	# function_version manager id => runtime_environment_id => runtime_environment
31	environments: dict[str, dict[str, ExecutionEnvironment]]	2✔
32
33	# Global pool for spawning and killing provisioned Lambda runtime environments
34	provisioning_pool: ThreadPoolExecutor	2✔
35
36	def __init__(self):	2✔
37	self.environments = defaultdict(dict)	2✔
38	self.provisioning_pool = ThreadPoolExecutor(thread_name_prefix="lambda-provisioning-pool")	2✔
39
40	@contextlib.contextmanager	2✔
41	def get_environment(	2✔
42	self,
43	version_manager_id: str,
44	function_version: FunctionVersion,
45	provisioning_type: InitializationType,
46	) -> contextlib.AbstractContextManager[ExecutionEnvironment]:
47	applicable_envs = (	2✔
48	env
49	for env in self.environments[version_manager_id].values()
50	if env.initialization_type == provisioning_type
51	)
52	execution_environment = None	2✔
53	for environment in applicable_envs:	2✔
54	try:	2✔
55	environment.reserve()	2✔
56	execution_environment = environment	2✔
57	break	2✔
58	except InvalidStatusException:	2✔
59	pass	2✔
60
61	if execution_environment is None:	2✔
62	if provisioning_type == "provisioned-concurrency":	2✔
63	raise AssignmentException(	×
64	"No provisioned concurrency environment available despite lease."
65	)
66	elif provisioning_type == "on-demand":	2✔
67	execution_environment = self.start_environment(version_manager_id, function_version)	2✔
68	self.environments[version_manager_id][execution_environment.id] = (	2✔
69	execution_environment
70	)
71	execution_environment.reserve()	2✔
72	else:
73	raise ValueError(f"Invalid provisioning type {provisioning_type}")	×
74
75	try:	2✔
76	yield execution_environment	2✔
77	execution_environment.release()	2✔
78	except InvalidStatusException as invalid_e:	2✔
UNCOV 79	LOG.error("InvalidStatusException: %s", invalid_e)	×
80	except Exception as e:	2✔
81	LOG.error(	2✔
82	"Failed invocation <%s>: %s", type(e), e, exc_info=LOG.isEnabledFor(logging.DEBUG)
83	)
84	self.stop_environment(execution_environment)	2✔
85	raise e	2✔
86
87	def start_environment(	2✔
88	self, version_manager_id: str, function_version: FunctionVersion
89	) -> ExecutionEnvironment:
90	LOG.debug("Starting new environment")	2✔
91	initialization_type = "on-demand"	2✔
92	if function_version.config.CapacityProviderConfig:	2✔
93	initialization_type = "lambda-managed-instances"	×
94	execution_environment = ExecutionEnvironment(	2✔
95	function_version=function_version,
96	initialization_type=initialization_type,
97	on_timeout=self.on_timeout,
98	version_manager_id=version_manager_id,
99	)
100	try:	2✔
101	execution_environment.start()	2✔
102	except StatusErrorException:	2✔
103	raise	2✔
104	except EnvironmentStartupTimeoutException:	2✔
105	raise	2✔
106	except Exception as e:	2✔
107	message = f"Could not start new environment: {type(e).__name__}:{e}"	2✔
108	raise AssignmentException(message) from e	2✔
109	return execution_environment	2✔
110
111	def on_timeout(self, version_manager_id: str, environment_id: str) -> None:	2✔
112	"""Callback for deleting environment after function times out"""
113	del self.environments[version_manager_id][environment_id]	×
114
115	def stop_environment(self, environment: ExecutionEnvironment) -> None:	2✔
116	version_manager_id = environment.version_manager_id	2✔
117	try:	2✔
118	environment.stop()	2✔
119	self.environments.get(version_manager_id).pop(environment.id)	2✔
120	except Exception as e:	2✔
121	LOG.debug(	2✔
122	"Error while stopping environment for lambda %s, manager id %s, environment: %s, error: %s",
123	environment.function_version.qualified_arn,
124	version_manager_id,
125	environment.id,
126	e,
127	)
128
129	def stop_environments_for_version(self, version_manager_id: str):	2✔
130	# We have to materialize the list before iterating due to concurrency
131	environments_to_stop = list(self.environments.get(version_manager_id, {}).values())	2✔
132	for env in environments_to_stop:	2✔
133	self.stop_environment(env)	2✔
134
135	def scale_provisioned_concurrency(	2✔
136	self,
137	version_manager_id: str,
138	function_version: FunctionVersion,
139	target_provisioned_environments: int,
140	) -> list[Future[None]]:
141	current_provisioned_environments = [	2✔
142	e
143	for e in self.environments[version_manager_id].values()
144	if e.initialization_type == "provisioned-concurrency"
145	]
146	# TODO: refine scaling loop to re-use existing environments instead of re-creating all
147	# current_provisioned_environments_count = len(current_provisioned_environments)
148	# diff = target_provisioned_environments - current_provisioned_environments_count
149
150	# TODO: handle case where no provisioned environment is available during scaling
151	# Most simple scaling implementation for now:
152	futures = []	2✔
153	# 1) Re-create new target
154	for _ in range(target_provisioned_environments):	2✔
155	execution_environment = ExecutionEnvironment(	2✔
156	function_version=function_version,
157	initialization_type="provisioned-concurrency",
158	on_timeout=self.on_timeout,
159	version_manager_id=version_manager_id,
160	)
161	self.environments[version_manager_id][execution_environment.id] = execution_environment	2✔
162	futures.append(self.provisioning_pool.submit(execution_environment.start))	2✔
163	# 2) Kill all existing
164	for env in current_provisioned_environments:	2✔
165	# TODO: think about concurrent updates while deleting a function
166	futures.append(self.provisioning_pool.submit(self.stop_environment, env))	2✔
167
168	return futures	2✔
169
170	def stop(self):	2✔
171	self.provisioning_pool.shutdown(cancel_futures=True)	2✔

localstack / localstack / 20357994067

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