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Refer to the exhibit.
A retail company is using an Order API to accept new orders. The Order API uses a JMS queue to submit orders to a backend order management service. The normal load for orders is being handled using two (2) CloudHub workers, each configured with 0.2 vCore. The CPU load of each CloudHub worker normally runs well below 70%. However, several times during the year the Order API gets four times (4x) the average number of orders. This causes the CloudHub worker CPU load to exceed 90% and the order submission time to exceed 30 seconds. The cause, however, is NOT the backend order management service, which still responds fast enough to meet the response SLA for the Order API. What is the MOST resource-efficient way to configure the Mule application's CloudHub deployment to help the company cope with this performance challenge?
What is true about automating interactions with Anypoint Platform using tools such as Anypoint Platform REST APIs, Anypoint CU, or the Mule Maven plugin?
Traffic is routed through an API proxy to an API implementation. The API proxy is managed by API Manager and the API implementation is deployed to a CloudHub VPC using Runtime Manager. API policies have been applied to this API. In this deployment scenario, at what point are the API policies enforced on incoming API client requests?
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Name: | MuleSoft Certified Platform Architect - Level 1 MAINTENANCE |
Exam Code: | MCPA-Level-1-Maintenance |
Certification: | MuleSoft Certified Platform Architect |
Vendor: | MuleSoft |
Total Questions: | 80 |
Last Updated: | Apr 22, 2024 |
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