Cache-aside pattern in Azure - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the Cache-aside pattern?

The Cache-aside pattern is a way to keep data in a fast storage (cache) separate from the main storage (database). The application checks the cache first. If data is missing, it loads from the database and puts it in the cache for next time.

beginner

In the Cache-aside pattern, what happens when data is not found in the cache?

The application loads the data from the main database, then stores it in the cache for future requests.

intermediate

Why is the Cache-aside pattern useful in cloud applications?

It helps reduce database load and speeds up data access by using a fast cache, improving performance and scalability.

intermediate

How does the Cache-aside pattern handle data updates?

When data changes, the application updates the database and then removes or updates the cache entry to keep data consistent.

beginner

Name a common Azure service used as a cache in the Cache-aside pattern.

Azure Cache for Redis is commonly used as a fast, in-memory cache service in Azure for implementing the Cache-aside pattern.

In the Cache-aside pattern, where does the application look first for data?

A Cache

B Database

C File storage

D Message queue

The application first checks the cache to find the data quickly before going to the database.

What should the application do after loading data from the database in Cache-aside?

A Send it to a message queue

B Delete the data

C Store it in the cache

D Ignore it

After loading data from the database, the application stores it in the cache for faster access next time.

Which Azure service is best suited as a cache in Cache-aside pattern?

A Azure Blob Storage

B Azure Functions

C Azure SQL Database

D Azure Cache for Redis

Azure Cache for Redis is a fast, in-memory cache service ideal for Cache-aside pattern.

How does Cache-aside pattern improve application performance?

A By storing all data in the database

B By reducing database calls using cache

C By sending data to users faster

D By deleting old data

Cache-aside reduces database calls by serving data from cache when available, speeding up responses.

What must happen to the cache when data is updated in the database?

A Cache is updated or removed

B Cache is backed up

C Cache is ignored

D Cache is cleared completely

To keep data consistent, the cache entry must be updated or removed after database changes.

Explain how the Cache-aside pattern works in a cloud application.

Think about how the app uses cache and database together.

Describe why using Azure Cache for Redis is beneficial in the Cache-aside pattern.

Focus on speed and cloud advantages.

Practice

1. What is the main purpose of the cache-aside pattern in Azure applications?

easy

A. To load data into cache only when it is requested

B. To preload all data into cache at application start

C. To automatically update cache without application control

D. To store data only in the database without caching

Solution

1. Step 1: Understand cache-aside pattern behavior

   The cache-aside pattern loads data into cache only when the application requests it and the data is not already cached.

2. Step 2: Compare options with this behavior

   To load data into cache only when it is requested matches this behavior. Options B and C describe other caching strategies, and A ignores caching.

3. Final Answer:

   To load data into cache only when it is requested -> Option A

4. Quick Check:

   Cache-aside loads on demand = D [OK]

Hint: Cache-aside means load cache only when needed [OK]

Common Mistakes:

• Thinking cache preloads all data
• Assuming cache updates automatically
• Confusing cache-aside with write-through caching

2. Which of the following is the correct sequence when using the cache-aside pattern in Azure?

easy

A. Return data -> Check cache -> Read database -> Store in cache

B. Read database -> Store in cache -> Return data -> Check cache

C. Store in cache -> Check cache -> Read database -> Return data

D. Check cache -> If miss, read database -> Store in cache -> Return data

Solution

1. Step 1: Recall cache-aside pattern steps

   The application first checks the cache. If data is missing (cache miss), it reads from the database, stores the data in cache, then returns it.

2. Step 2: Match the sequence with options

   Check cache -> If miss, read database -> Store in cache -> Return data correctly shows this sequence. Other options have steps in wrong order.

3. Final Answer:

   Check cache -> If miss, read database -> Store in cache -> Return data -> Option D

4. Quick Check:

   Cache check first, then DB read if miss = A [OK]

Hint: Cache check first, then DB read if miss [OK]

Common Mistakes:

• Reading database before checking cache
• Storing data in cache before reading database
• Returning data before checking cache

3. Consider this Azure cache-aside pseudocode:

data = cache.get('user123')
if data is None:
    data = database.read('user123')
    cache.set('user123', data)
return data

What happens if the cache contains stale data for 'user123'?

medium

A. The application reads fresh data from the database every time

B. The application returns the stale data without checking the database

C. The cache automatically updates stale data before returning

D. The application throws an error due to stale cache

Solution

1. Step 1: Analyze cache-aside code behavior

   The code returns cached data if present, without verifying freshness. It reads database only if cache miss.

2. Step 2: Understand stale data impact

   If cache has stale data, the application returns it directly, ignoring database updates until cache expires or is invalidated.

3. Final Answer:

   The application returns the stale data without checking the database -> Option B

4. Quick Check:

   Cache returns stale data if present = A [OK]

Hint: Cache returns data if present, even if stale [OK]

Common Mistakes:

• Assuming cache auto-refreshes stale data
• Thinking database is read every time
• Believing stale cache causes errors

4. You implemented cache-aside in Azure but notice your cache never updates after data changes in the database. What is the most likely cause?

medium

A. The application does not invalidate or update cache after database writes

B. The cache service is down and cannot store data

C. The database is not reachable for reads

D. The cache is set to expire data too frequently

Solution

1. Step 1: Understand cache-aside update responsibility

   In cache-aside, the application must update or invalidate cache after database changes to keep cache fresh.

2. Step 2: Identify cause of stale cache

   If cache never updates, likely the app is not managing cache invalidation after writes, causing stale data to persist.

3. Final Answer:

   The application does not invalidate or update cache after database writes -> Option A

4. Quick Check:

   App must update cache after DB changes = C [OK]

Hint: App must update cache after DB changes [OK]

Common Mistakes:

• Blaming cache service downtime without checking app logic
• Assuming database read issues cause stale cache
• Thinking frequent expiry causes no updates

5. You want to optimize an Azure app using cache-aside pattern for user profiles. Which approach best ensures cache consistency when profiles update frequently?

hard

A. Only update cache when the profile is requested next time

B. Set cache expiration to 24 hours and never update manually

C. After updating the database, immediately update or remove the cached profile

D. Preload all profiles into cache at app startup

Solution

1. Step 1: Consider cache consistency needs

   For frequently updated profiles, cache must reflect changes quickly to avoid stale data.

2. Step 2: Evaluate options for freshness

   After updating the database, immediately update or remove the cached profile updates or removes cache immediately after DB update, ensuring fresh data. Only update cache when the profile is requested next time delays update causing stale reads. Set cache expiration to 24 hours and never update manually relies on expiry only, which is slow. Preload all profiles into cache at app startup wastes resources and may cause stale data.

3. Final Answer:

   After updating the database, immediately update or remove the cached profile -> Option C

4. Quick Check:

   Immediate cache update after DB write = B [OK]

Hint: Update cache right after DB changes for freshness [OK]

Common Mistakes:

• Relying only on cache expiration for updates
• Delaying cache update until next read
• Preloading cache wastes memory and risks staleness