Exam AWS Certified Developer Associate topic 1 question 110 discussion

C. This is write through strategy

its D There is a cache miss penalty. Each cache miss results in three trips: Initial request for data from the cache Query of the database for the data Writing the data to the cache These misses can cause a noticeable delay in data getting to the application. https://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/Strategies.html Lazy loading

The primary concern is increased db load and not cache size and that eliminates C.

C) Eliminated - Question does not mention that the cache stores infrequently requested data unnecessarily.

C: The cache will be updated with every change in DB although that data is not being read frequently. This is write-through strategy D cannot be the right answer since the cache is being updated with DB change, not on cache miss

there would be lot of writes

imo it's A It's only obvious answer, per write you have to read the updated record from database - because not every update has to be a full record, and in relational databases update operation returns number of rows updated, not whole entities. So you have to follow up with a read op B - this behavior isn't defined in the question C - how do we know there is infrequently accessed data at all? how do we know TTL in cache? we don't know D - "cache is updated only after a cache miss" this behavior wasn't defined in a question, cache is updated only on updates regardless of cache key missing or not

C, each update to the database is also reversed to the cache (write through instead of lazy loading cache strategy). Given that each update/write to the DB is reversed also to the cache, also for really infrequent data, we have as result a really heavy cache

D, When the cache cannot find the requested data, it is referred to as a cache miss. In this scenario, after the primary database is updated, the cache is immediately updated. However, if a read query is made and the requested data is not found in the cache, there will be a cache miss, which will cause overhead in the initial response time. The cache will then be updated with the requested data, and subsequent read queries for the same data will be faster because the data is already in the cache.

C . Cache will become expensive and huge.

Answer here is A. Option C is incorrect because infrequently requested data should not be written to the cache, as this can cause the cache to become bloated and inefficient. Option D is incorrect because the entryPoint parameter is used to specify a command that is run when the container starts, and is not related to passing environment variables to the container.

C. This is Write Through strategy. As described in the course by Stephane Maarek on Udemi this approach has the following Cons: "Cache churn – a lot of the data will never be read"

the scenario is about write through, so C. D is about lazy loading, it's not mentioned

it can not be D. because strategy used in question is cache is updated for each data update in databae not when cache is missing.

I would go for C.

Elasticache can implement both write-through and lazy loading. The key phrase was: to update the cache immediately following the primary database update. This is write-through. Look at "Cache churn." https://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/Strategies.html

It would be C if it didn't include ElastiCache, this technique is called write-through. As it mentions ElastiCache the technique is Lazy Loading, so the answer is D. Look at the official documentationl: https://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/Strategies.html