Complete the code to identify the anti-pattern where services are tightly coupled and deploy together.
if system_architecture == '[1]': print("Warning: Services are tightly coupled and not independently deployable.")
The distributed monolith anti-pattern occurs when microservices are tightly coupled and cannot be deployed independently.
Complete the code to detect an anti-pattern where services make too many small calls to each other.
if service_calls_per_request > [1]: print("Warning: Chatty services detected, consider reducing inter-service calls.")
More than 10 calls per request often indicates chatty services, which can cause latency and complexity.
Fix the error in the code that wrongly identifies chatty services by comparing calls incorrectly.
if total_calls_per_request [1] 10: print("Chatty services detected")
We want to detect when calls are greater than or equal to 10 to flag chatty services.
Fill both blanks to create a dictionary comprehension that maps service names to their call counts, filtering only chatty services.
chatty_services = {service: calls for service, calls in service_calls.items() if calls [1] [2]This comprehension filters services with calls greater than 10, identifying chatty services.
Fill all three blanks to create a function that detects distributed monolith by checking if services share the same database and have high coupling.
def is_distributed_monolith(services): shared_db = any(s['db'] == [1] for s in services) high_coupling = any(s['calls'] [2] [3] for s in services) return shared_db and high_coupling
The function checks if any service uses the central shared database and makes more than 10 calls, indicating a distributed monolith.