Why caching improves performance in Azure - Visual Breakdown

Process Flow - Why caching improves performance

Request arrives

↓

Check cache for data

↓

Request complete

When a request comes, the system first looks in the cache. If data is found, it returns quickly. If not, it fetches from the source, stores it in cache, then returns. This reduces wait time on repeated requests.

Execution Sample

Azure

1. Request data
2. Check cache
3. If cached, return data
4. Else fetch from source
5. Store in cache
6. Return data

This simple flow shows how caching avoids repeated slow data fetches by storing and reusing data.

Process Table

Step	Action	Cache State	Data Source Accessed	Response Time
1	Request data	Empty	Yes (source)	Slow
2	Store data in cache	Data stored	No	N/A
3	Request data again	Data present	No	Fast
4	Return cached data	Data present	No	Fast
5	Request new data	Data present	Yes (source)	Slow
6	Update cache with new data	Updated data	No	N/A
7	Request new data again	Updated data	No	Fast

💡 Requests stop when data is served either from cache or source; cache reduces source access and speeds response.

Status Tracker

Variable	Start	After Step 2	After Step 4	After Step 6	After Step 7
Cache	Empty	Has initial data	Has initial data	Has updated data	Has updated data
Data Source Accessed	Yes	No	No	Yes	No
Response Time	Slow	N/A	Fast	Slow	Fast

Key Moments - 2 Insights

Why does the response time become fast after the first request?

Because after the first request, data is stored in the cache (see Step 2 and Step 4 in execution_table), so subsequent requests get data directly from cache without accessing the slower source.

What happens if the requested data is not in the cache?

The system accesses the data source to fetch the data (see Step 1 in execution_table), which takes longer, then stores it in cache for future fast access.

Visual Quiz - 3 Questions

Look at the execution_table, at which step is data first stored in the cache?

A Step 1

B Step 2

C Step 3

D Step 4

💡 Hint

Check the 'Cache State' column to see when data changes from empty to stored.

At which step does the response time become fast due to cache usage?

A Step 5

B Step 1

C Step 3

D Step 6

💡 Hint

Look at the 'Response Time' column and find the first 'Fast' after data is cached.

If the cache was empty at Step 3, what would happen to the response time?

A It would be slow

B It would not change

C It would be fast

D It would be instant

💡 Hint

Refer to 'Response Time' when data source is accessed in the execution_table.

Concept Snapshot

Caching stores data temporarily to avoid repeated slow fetches.
When data is requested, cache is checked first.
If data is cached, response is fast.
If not, data is fetched from source and cached.
This reduces load and improves performance.

Full Transcript

Caching improves performance by storing data temporarily so repeated requests do not need to fetch data from the original source every time. When a request arrives, the system checks if the data is in cache. If yes, it returns the cached data quickly. If no, it fetches the data from the source, stores it in cache, then returns it. This process reduces response time and load on the source. The execution table shows steps where data is fetched, cached, and served, highlighting how response time improves after caching. Key moments clarify why response time changes and what happens when data is not cached. The visual quiz tests understanding of these steps.