From oraclecloud-pack
Implements OCI Python SDK patterns for thread-safe client singletons, retry/backoff logic, and timeouts to prevent memory leaks in long-running services.
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Production patterns for the OCI Python SDK that avoid the most common pitfalls: memory leaks from Instance Principal authentication (~10 MiB/hour if clients are recreated per request), missing retry logic for 429/500 errors, and timeout misconfiguration across different service clients. The OCI SDK has different timeout defaults depending on the service (Compute: 60s, Object Storage: 300s for u...
Production patterns for the OCI Python SDK that avoid the most common pitfalls: memory leaks from Instance Principal authentication (~10 MiB/hour if clients are recreated per request), missing retry logic for 429/500 errors, and timeout misconfiguration across different service clients. The OCI SDK has different timeout defaults depending on the service (Compute: 60s, Object Storage: 300s for uploads), and none of them set connection timeouts by default.
Purpose: Provide correct client lifecycle (create once, reuse, close), exponential backoff retry, singleton patterns that prevent the Instance Principal memory leak, and per-service timeout configuration.
oraclecloud-install-auth — valid ~/.oci/configpip install ociComputeClient, ObjectStorageClient, etc.)Instance Principal authentication allocates new security tokens on each client instantiation. Creating clients per-request leaks ~10 MiB/hour. Use a singleton:
import oci
import threading
class OCIClients:
"""Thread-safe singleton for OCI service clients.
Prevents the Instance Principal memory leak by reusing clients
instead of creating new ones per request.
"""
_lock = threading.Lock()
_instance = None
def __init__(self):
self._config = oci.config.from_file("~/.oci/config")
oci.config.validate_config(self._config)
# Create clients once — reuse everywhere
self._compute = None
self._network = None
self._object_storage = None
self._identity = None
@classmethod
def get(cls):
if cls._instance is None:
with cls._lock:
if cls._instance is None:
cls._instance = cls()
return cls._instance
@property
def config(self):
return self._config
@property
def compute(self):
if self._compute is None:
self._compute = oci.core.ComputeClient(
self._config, retry_strategy=oci.retry.DEFAULT_RETRY_STRATEGY
)
return self._compute
@property
def network(self):
if self._network is None:
self._network = oci.core.VirtualNetworkClient(
self._config, retry_strategy=oci.retry.DEFAULT_RETRY_STRATEGY
)
return self._network
@property
def object_storage(self):
if self._object_storage is None:
self._object_storage = oci.object_storage.ObjectStorageClient(
self._config, retry_strategy=oci.retry.DEFAULT_RETRY_STRATEGY
)
return self._object_storage
@property
def identity(self):
if self._identity is None:
self._identity = oci.identity.IdentityClient(
self._config, retry_strategy=oci.retry.DEFAULT_RETRY_STRATEGY
)
return self._identity
# Usage: never create clients directly
clients = OCIClients.get()
instances = clients.compute.list_instances(
compartment_id=clients.config["tenancy"]
)
OCI SDK has no connection timeout by default. Set both connection and read timeouts explicitly:
import oci
config = oci.config.from_file("~/.oci/config")
# Compute: 10s connect, 60s read
compute = oci.core.ComputeClient(
config,
timeout=(10, 60) # (connect_timeout, read_timeout) in seconds
)
# Object Storage: 10s connect, 300s read (large uploads)
object_storage = oci.object_storage.ObjectStorageClient(
config,
timeout=(10, 300)
)
# Database: 10s connect, 120s read (long queries)
database = oci.database.DatabaseClient(
config,
timeout=(10, 120)
)
The built-in DEFAULT_RETRY_STRATEGY retries on 429, 500, 502, 503, 504. For custom control:
import oci
custom_retry = oci.retry.RetryStrategyBuilder(
max_attempts_check=True,
max_attempts=5,
total_elapsed_time_check=True,
total_elapsed_time_seconds=300,
retry_max_wait_between_calls_seconds=30,
retry_base_sleep_time_seconds=2,
service_error_check=True,
service_error_retry_on_any_5xx=True,
service_error_retry_config={
429: [] # Retry on all 429 errors (no Retry-After header in OCI)
},
backoff_type=oci.retry.BACKOFF_DECORRELATED_JITTER
).get_retry_strategy()
compute = oci.core.ComputeClient(config, retry_strategy=custom_retry)
For fine-grained control over which errors to retry:
import time
import random
import oci
def call_with_retry(fn, max_retries=5, base_delay=2):
"""Execute an OCI SDK call with exponential backoff.
Retries on: 429 TooManyRequests, 500 InternalError, -1 timeout.
Raises immediately on: 401, 404, 400.
"""
for attempt in range(max_retries):
try:
return fn()
except oci.exceptions.ServiceError as e:
if e.status in (429, 500, 502, 503, 504) or e.status == -1:
delay = base_delay * (2 ** attempt) + random.uniform(0, 1)
print(f"Attempt {attempt + 1} failed ({e.status}). Retry in {delay:.1f}s")
time.sleep(delay)
else:
raise # 401, 404, 400 — don't retry
raise RuntimeError(f"Failed after {max_retries} retries")
# Usage
config = oci.config.from_file("~/.oci/config")
compute = oci.core.ComputeClient(config)
instances = call_with_retry(
lambda: compute.list_instances(compartment_id=config["tenancy"])
)
OCI API responses are paginated. Use the built-in paginator instead of manual opc-next-page handling:
import oci
config = oci.config.from_file("~/.oci/config")
compute = oci.core.ComputeClient(config)
# Automatic pagination — returns ALL instances
all_instances = oci.pagination.list_call_get_all_results(
compute.list_instances,
compartment_id=config["tenancy"]
).data
print(f"Total instances: {len(all_instances)}")
# Lazy pagination — yields pages (memory-efficient for large datasets)
for page in oci.pagination.list_call_get_all_results_generator(
compute.list_instances,
"response",
compartment_id=config["tenancy"]
):
for inst in page.data:
print(f"{inst.display_name}: {inst.lifecycle_state}")
Use composite clients to launch-and-wait in one call:
import oci
config = oci.config.from_file("~/.oci/config")
compute = oci.core.ComputeClient(config)
compute_composite = oci.core.ComputeClientCompositeOperations(compute)
# Launch and wait for RUNNING state
launch_details = oci.core.models.LaunchInstanceDetails(
compartment_id=config["tenancy"],
availability_domain="Uocm:US-ASHBURN-AD-1",
display_name="sdk-pattern-demo",
shape="VM.Standard.E4.Flex",
shape_config=oci.core.models.LaunchInstanceShapeConfigDetails(
ocpus=1, memory_in_gbs=8
),
source_details=oci.core.models.InstanceSourceViaImageDetails(
image_id="ocid1.image.oc1.iad.aaaa..."
),
create_vnic_details=oci.core.models.CreateVnicDetails(
subnet_id="ocid1.subnet.oc1.iad.aaaa..."
)
)
response = compute_composite.launch_instance_and_wait_for_state(
launch_details,
wait_for_states=[
oci.core.models.Instance.LIFECYCLE_STATE_RUNNING
]
)
print(f"Instance running: {response.data.id}")
After applying these patterns you have:
| Error | Code | Retry? | Notes |
|---|---|---|---|
| TooManyRequests | 429 | Yes | OCI does not send Retry-After; use decorrelated jitter |
| InternalError | 500 | Yes | Transient OCI service error |
| NotAuthenticated | 401 | No | Config or key issue — fix credentials first |
| NotAuthorizedOrNotFound | 404 | No | IAM policy or wrong OCID |
| ServiceError status -1 | -1 | Yes | Connection timeout — increase timeout tuple |
| CERTIFICATE_VERIFY_FAILED | — | No | SSL issue; see oraclecloud-common-errors |
Quick health check with timeout and retry:
import oci
config = oci.config.from_file("~/.oci/config")
identity = oci.identity.IdentityClient(
config,
timeout=(5, 15),
retry_strategy=oci.retry.DEFAULT_RETRY_STRATEGY
)
regions = identity.list_regions().data
print(f"Connected. {len(regions)} regions available.")
Apply these patterns in oraclecloud-hello-world for compute, or see oraclecloud-common-errors for the complete error diagnostic reference when retry strategies surface persistent failures.
npx claudepluginhub jeremylongshore/claude-code-plugins-plus-skills --plugin oraclecloud-packManages OCI API rate limits with service-specific observed limits and exponential backoff jitter for 429 errors. For resilient bulk operations using OCI Python SDK.
Provides expert guidance on Oracle Cloud Infrastructure services, architecture patterns, cost optimization, and deployment strategies for building scalable, secure, and cost-effective solutions.
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