Detailed component design

Bottlenecks will come from the read path of our system. Meaning the cache and the database will be hit with a ton of traffic.

Both services are stateless, so it is easy to scale them by adding more servers.

Stateless: The service doesn't store client-specific state between requests. Each request must contain all the information needed to be processed.

1) Database consideration

We will use a relational db for our users and url tables
- we can shard the database using the hash of the short url as the shard key
- each shard will have a primary and secondary nodes - Two or three read replicas.
- redirect service will target these read replicas
- so now, the load will be shared with all these nodes since instead of just one node
We will use a database that can handle a lot of writes for our analytics table like cassandra
- we choose cassandra since it can handle huge amounts of writes
- it can handle huge amounts of writes since it uses a WAL and a LSM tree structure
  - optimized for writes

2) Cache consideration

Redirect service
- in memory cache like Redis for the redirect service
  - we will also deploy a Redis in a distributed manner
  - we will have multiple nodes, splitting keys using consistent hashing
- use refresh-ahead so that we can update the cache in advance
in CreationService

we do a write through, so that we can update the cache right away

Refresh-Ahead:

Proactively updates cache items before expiration.
Reduces cache misses by ensuring data is fresh when requested.

Freshness & Consistency:

Even if a cache entry isn’t evicted, it might become stale if the underlying data changes. Refresh-ahead updates the data before it expires, ensuring that every cache hit returns current information.

Avoiding Expiry Bursts:

Without refresh-ahead, if many entries expire at once, a sudden surge of cache misses could overwhelm your database. Refresh-ahead smooths out these peaks by updating entries in the background.

Improved Performance:

By proactively refreshing the cache, you reduce the likelihood that a user request will have to wait for a database query, thus maintaining low latency and a good user experience.

Write-Through:

Writes data to both the cache and the database simultaneously.
Maintains consistency between the cache and the database.

3) Load balancing

A few load balancing algorithms like round robin, least connections, least load, least response
we choose round robin for simplicity

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