An organization is sizing an Anypoint VPC to extend their internal network to Cloudhub.
For this sizing calculation, the organization assumes 150 Mule applications will be deployed among three(3) production environments and will use Cloudhub's default zero-downtime feature. Each Mule application is expected to be configured with two(2) Cloudhub workers.This is expected to result in several Mule application deployments per hour.
What is an advantage of using OAuth 2.0 client credentials and access tokens over only API keys for API authentication?
A new Mule application under development must implement extensive data transformation logic. Some of the data transformation functionality is already available as external transformation services that are mature and widely used across the organization; the rest is highly specific to the new Mule application.
The organization follows a rigorous testing approach, where every service and application must be extensively acceptance tested before it is allowed to go into production.
What is the best way to implement the data transformation logic for this new Mule application while minimizing the overall testing effort?
What approach configures an API gateway to hide sensitive data exchanged between API consumers and API implementations, but can convert tokenized fields back to their original value for other API requests or responses, without having to recode the API implementations?
The ABC company has an Anypoint Runtime Fabric on VMs/Bare Metal (RTF-VM) appliance installed on its own customer-hosted AWS infrastructure.
Mule applications are deployed to this RTF-VM appliance. As part of the company standards, the Mule application logs must be forwarded to an external log management tool (LMT).
Given the company's current setup and requirements, what is the most idiomatic (used for its intended purpose) way to send Mule application logs to the external LMT?
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