Oracle Cloud Rate Limits
SkillDev tools'Handle OCI API rate limits with defensive retry patterns and known limits
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Overview
OCI API rate limits vary by service and are not well documented. A 429 TooManyRequests response kills your automation, and unlike AWS or Azure, OCI does not return a Retry-After header. This skill maps known limits by service, implements exponential backoff with jitter, and provides circuit breaker patterns for bulk operations.
Purpose: Build resilient OCI API clients that handle throttling gracefully without data loss.
Prerequisites
- OCI Python SDK —
pip install oci - OCI config file at
~/.oci/configwith valid credentials (user, fingerprint, tenancy, region, key_file) - Python 3.8+
- Understanding of which OCI service you are calling (limits vary per service)
Instructions
Step 1: Know the Limits
OCI publishes some rate limits, but many are undocumented. Here are the known limits observed in production:
| Service | Endpoint Type | Observed Limit | Notes |
|---|---|---|---|
| Compute | List/Get | ~20 req/sec | Per-tenancy, not per-user |
| Compute | Create/Update/Delete | ~10 req/sec | Stricter for mutating operations |
| Object Storage | List/Get | ~100 req/sec | Per-bucket namespace |
| Object Storage | Put/Delete | ~50 req/sec | Varies by region load |
| Identity | List/Get | ~10 req/sec | Tenancy-wide shared limit |
| Identity | Create/Update | ~5 req/sec | Very conservative |
| Database | All operations | ~10 req/sec | Shared across DB family |
| Networking (VCN) | All operations | ~20 req/sec | Per-compartment |
| Monitoring | Post metrics | ~50 req/sec | Per-metric namespace |
| Events | Rule CRUD | ~10 req/sec | Per-compartment |
Critical: These are observed limits, not guaranteed SLAs. OCI may throttle lower under load.
Step 2: Implement Exponential Backoff with Jitter
OCI returns no Retry-After header on 429 responses, so you must implement your own backoff. The SDK's built-in retry handles some cases, but for bulk operations you need explicit control:
import oci
import time
import random
config = oci.config.from_file("~/.oci/config")
def call_with_retry(fn, max_retries=5, base_delay=1.0):
"""Call an OCI SDK function with exponential backoff and jitter.
OCI returns 429 TooManyRequests with NO Retry-After header,
so we implement our own backoff strategy.
"""
for attempt in range(max_retries):
try:
return fn()
except oci.exceptions.ServiceError as e:
if e.status == 429:
# Exponential backoff with full jitter
delay = base_delay * (2 ** attempt)
jitter = random.uniform(0, delay)
wait_time = delay + jitter
print(f"Rate limited (429). Attempt {attempt + 1}/{max_retries}. "
f"Waiting {wait_time:.1f}s")
time.sleep(wait_time)
elif e.status >= 500:
# Server errors — retry with backoff
delay = base_delay * (2 ** attempt)
print(f"Server error ({e.status}). Retrying in {delay}s")
time.sleep(delay)
else:
raise # 4xx errors (except 429) are not retryable
raise Exception(f"Max retries ({max_retries}) exceeded")
Step 3: Use the SDK's Built-in Retry Configuration
The OCI Python SDK supports retry configuration natively. Use this for simple cases:
import oci
from oci.retry import RetryStrategyBuilder
config = oci.config.from_file("~/.oci/config")
# Build a custom retry strategy
retry_strategy = 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=1,
service_error_check=True,
service_error_retry_on_any_5xx=True,
service_error_retry_config={429: []}, # Retry on 429 with any message
backoff_type=oci.retry.BACKOFF_DECORRELATED_JITTER
).get_retry_strategy()
compute = oci.core.ComputeClient(config, retry_strategy=retry_strategy)
# All calls through this client will automatically retry on 429 and 5xx
instances = compute.list_instances(
compartment_id="ocid1.compartment.oc1..example"
)
Step 4: Implement a Circuit Breaker for Bulk Operations
For operations that process hundreds of resources, a circuit breaker prevents cascading failures:
import oci
import time
import random
class OCICircuitBreaker:
"""Circuit breaker for bulk OCI API operations."""
def __init__(self, failure_threshold=5, reset_timeout=60):
self.failure_count = 0
self.failure_threshold = failure_threshold
self.reset_timeout = reset_timeout
self.last_failure_time = 0
self.state = "closed" # closed = normal, open = blocking
def call(self, fn, max_retries=3, base_delay=1.0):
if self.state == "open":
if time.time() - self.last_failure_time > self.reset_timeout:
self.state = "half-open"
print("Circuit half-open — testing one request")
else:
remaining = self.reset_timeout - (time.time() - self.last_failure_time)
raise Exception(f"Circuit open. Retry in {remaining:.0f}s")
try:
result = call_with_retry(fn, max_retries=max_retries, base_delay=base_delay)
if self.state == "half-open":
self.state = "closed"
self.failure_count = 0
print("Circuit closed — resuming normal operation")
return result
except Exception:
self.failure_count += 1
self.last_failure_time = time.time()
if self.failure_count >= self.failure_threshold:
self.state = "open"
print(f"Circuit OPEN after {self.failure_count} failures. "
f"Pausing for {self.reset_timeout}s")
raise
# Usage for bulk listing
breaker = OCICircuitBreaker(failure_threshold=3, reset_timeout=30)
config = oci.config.from_file("~/.oci/config")
compute = oci.core.ComputeClient(config)
compartment_ids = ["ocid1.compartment.oc1..aaa", "ocid1.compartment.oc1..bbb"]
all_instances = []
for cid in compartment_ids:
result = breaker.call(
lambda c=cid: compute.list_instances(compartment_id=c)
)
all_instances.extend(result.data)
time.sleep(0.1) # Courtesy delay between bulk calls
Step 5: Batch Operations with Rate Limiting
For operations that must process many items (e.g., tagging all instances), throttle proactively:
import oci
import time
config = oci.config.from_file("~/.oci/config")
compute = oci.core.ComputeClient(config)
def batch_with_throttle(items, operation, requests_per_second=5):
"""Process items with proactive rate limiting."""
delay = 1.0 / requests_per_second
results = []
for i, item in enumerate(items):
result = call_with_retry(lambda it=item: operation(it))
results.append(result)
if (i + 1) % 50 == 0:
print(f"Processed {i + 1}/{len(items)}")
time.sleep(delay)
return results
Output
Successful implementation produces:
- A retry wrapper function that handles 429 responses with exponential backoff and jitter
- SDK-level retry configuration applied to all OCI client calls
- A circuit breaker that prevents cascading failures during bulk operations
- Proactive rate limiting for batch processing scripts
Error Handling
| Error | Code | Cause | Solution |
|---|---|---|---|
| TooManyRequests | 429 | API rate limit exceeded (no Retry-After header) | Use exponential backoff with jitter — start at 1s, max 30s |
| NotAuthenticated | 401 | Bad config or expired key | Verify ~/.oci/config credentials |
| NotAuthorizedOrNotFound | 404 | Missing IAM policy or wrong OCID | Check compartment OCID and IAM policies |
| InternalError | 500 | OCI service error | Retry with backoff; check https://ocistatus.oraclecloud.com |
| ServiceError (status -1) | -1 | Request timeout | Increase SDK timeout or reduce request payload |
| CERTIFICATE_VERIFY_FAILED | — | SSL certificate issue | Update CA certificates: pip install certifi |
Examples
Quick 429 test — intentionally trigger rate limiting:
import oci
config = oci.config.from_file("~/.oci/config")
compute = oci.core.ComputeClient(config)
# Rapid-fire requests to observe throttling behavior
for i in range(100):
try:
compute.list_instances(compartment_id="ocid1.compartment.oc1..example")
except oci.exceptions.ServiceError as e:
if e.status == 429:
print(f"Throttled at request {i + 1}")
break
Check current OCI SDK retry defaults:
import oci
print(f"SDK version: {oci.__version__}")
# Default retry: NoneRetryStrategy (no retries unless configured)
# Always set explicit retry strategies for production code
Resources
- OCI API Request Limits — official rate limit documentation
- Python SDK Retry Configuration — RetryStrategyBuilder reference
- SDK Troubleshooting — common SDK errors
- OCI Known Issues — known service issues
- OCI Status — service health dashboard
Next Steps
After implementing rate limit handling, see oraclecloud-security-basics for IAM policy patterns, or oraclecloud-observability for monitoring your API call patterns and error rates.
Signals
- GitHub stars
- 3k
- Forks
- 415
- Last commit
- Oct 2026
Ahel review
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Advanced
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- Key
oraclecloud-rate-limits- Source
- github.com/jeremylongshore/tons-of-skills-marketplace
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