A system API is deployed to a primary environment as well as to a disaster recovery (DR) environment, with different DNS names in each environment. A process API is a client to the system API and is being rate limited by the system API, with different limits in each of the environments. The system API's DR environment provides only 20% of the rate limiting offered by the primary environment. What is the best API fault-tolerant invocation strategy to reduce overall errors in the process API, given these conditions and constraints?
Answer(s): A
Correct Answer: Invoke the system API deployed to the primary environment; add timeout and retry logic to the process API to avoid intermittent failures; if it still fails, invoke the system API deployed to the DR environment*****************************************There is one important consideration to be noted in the question which is - System API in DR environment provides only 20% of the rate limiting offered by the primary environment. So, comparitively, very less calls will be allowed into the DR environment API opposed to its primary environment. With this in mind, lets analyse what is the right and best fault-tolerant invocation strategy.1. Invoking both the system APIs in parallel is definitely NOT a feasible approach because of the 20% limitation we have on DR environment. Calling in parallel every time would easily and quickly exhaust the rate limits on DR environment and may not give chance to genuine intermittent error scenarios to let in during the time of need.2. Another option given is suggesting to add timeout and retry logic to process API while invoking primary environment's system API. This is good so far. However, when all retries failed, the option is suggesting to invoke the copy of process API on DR environment which is not right or recommended. Only system API is the one to be considered for fallback and not the whole process API. Process APIs usually have lot of heavy orchestration calling many other APIs which we do not want to repeat again by calling DR's process API. So this option is NOT right.3. One more option given is suggesting to add the retry (no timeout) logic to process API to directly retry on DR environment's system API instead of retrying the primary environment system API first. This is not at all a proper fallback. A proper fallback should occur only after all retries are performed and exhausted on Primary environment first. But here, the option is suggesting to directly retry fallback API on first failure itself without trying main API. So, this option is NOT right too.This leaves us one option which is right and best fit.- Invoke the system API deployed to the primary environment- Add Timeout and Retry logic on it in process API- If it fails even after all retries, then invoke the system API deployed to the DR environment.
What Anypoint Platform Capabilities listed below fall under APIs and API Invocations/Consumers category? Select TWO.
Answer(s): D
Correct Answers: API Design and Development and API Runtime Execution and Hosting *****************************************>> API Design and Development - Anypoint Studio, Anypoint Design Center, Anypoint Connectors >> API Runtime Execution and Hosting - Mule Runtimes, CloudHub, Runtime Services>> API Operations and Management - Anypoint API Manager, Anypoint Exchange>> API Consumer Management - API Contracts, Public Portals, Anypoint Exchange, API NotebooksCorrect Answers: API Operations and Management and API Consumer Engagement *****************************************>> API Design and Development - Anypoint Studio, Anypoint Design Center, Anypoint Connectors >> API Runtime Execution and Hosting - Mule Runtimes, CloudHub, Runtime Services >> API Operations and Management - Anypoint API Manager, Anypoint Exchange >> API Consumer Management - API Contracts, Public Portals, Anypoint Exchange, API NotebooksBottom of FormTop of Form
Select the correct Owner-Layer combinations from below options
Answer(s): C
1. App Developers owns and focuses on Experience Layer APIs2. LOB IT owns and focuses on Process Layer APIs3. Central IT owns and focuses on System Layer APIs
https://blogs.mulesoft.com/biz/api/experience-api-ownership/ https://blogs.mulesoft.com/biz/api/process-api-ownership/ https://blogs.mulesoft.com/biz/api/system-api-ownership/
Which layer in the API-led connectivity focuses on unlocking key systems, legacy systems, data sources etc and exposes the functionality?
Correct Answer: System LayerThe APIs used in an API-led approach to connectivity fall into three categories:System APIs these usually access the core systems of record and provide a means of insulating the user from the complexity or any changes to the underlying systems. Once built, many users, can access data without any need to learn the underlying systems and can reuse these APIs in multiple projects.Process APIs These APIs interact with and shape data within a single system or across systems (breaking down data silos) and are created here without a dependence on the source systems from which that data originates, as well as the target channels through which that data is delivered. Experience APIs Experience APIs are the means by which data can be reconfigured so that it is most easily consumed by its intended audience, all from a common data source, rather than setting up separate point-to-point integrations for each channel. An Experience API is usually created with API- first design principles where the API is designed for the specific user experience in mind.
A Mule application exposes an HTTPS endpoint and is deployed to three CloudHub workers that do not use static IP addresses. The Mule application expects a high volume of client requests in short time periods. What is the most cost-effective infrastructure component that should be used to serve the high volume of client requests?
Answer(s): B
Correct Answer: The CloudHub shared load balancer*****************************************The scenario in this question can be split as below:>> There are 3 CloudHub workers (So, there are already good number of workers to handle high volume of requests)>> The workers are not using static IP addresses (So, one CANNOT use customer load-balancing solutions without static IPs)>> Looking for most cost-effective component to load balance the client requests among the workers.Based on the above details given in the scenario:>> Runtime autoscaling is NOT at all cost-effective as it incurs extra cost. Most over, there are already 3 workers running which is a good number.>> We cannot go for a customer-hosted load balancer as it is also NOT most cost-effective (needs custom load balancer to maintain and licensing) and same time the Mule App is not having Static IP Addresses which limits from going with custom load balancing. >> An API Proxy is irrelevant there as it has no role to play w.r.t handling high volumes or load balancing.So, the only right option to go with and fits the purpose of scenario being most cost-effective is - using a CloudHub Shared Load Balancer.
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