CPS-1017 Explore and Compare various caches

Owned by Priyank Maheshwari
Last updated: May 06, 2022
1 min read

CPS-1015: Implement Distributed Caching SystemClosed

Use Case

Using a Spring distributed cache to prevent watchdogs working on the same ADVISED cm handles during model sync, since we don't have an in-between state from ADVISED to READY.

Eg:

Watchdog A wakes up, works on Cm-Handle-1 which has state of ADVISED and stores this in memory

Watchdog B wakes up, attempts to work on Cm-Handle-1, which still has a state of ADVISED, but is being worked on by Watchdog A, so this then moves on to Cm-Handle-2

Overview

Sr No.

Type

Example

Feature

Sr No.

Type

Example

Feature

1

Embedded

Caffeine , Ehcache , Guava Library for Cache etc

Data is in memory. Not distributed among multiple instances. 

2

Embedded Distributed

Hazelcast

Data is in memory and distributed across multiple instances.(Scalability of cache goes hand in hand with app instances)

3

Client-Server Topology

Hazelcast , Redis , Memcached , Coherence

Separate cache cluster can be managed.
Client is our application and Server is the cache cluster.

4

Cloud (Client-Server)

Redis on AWS etc.

Cluster managed by leading cloud provider



Issues and decisions

#

Questions/Open Issues

Notes

Decision/Answer

#

Questions/Open Issues

Notes

Decision/Answer

1

#2 Embedded Distributed.

We will be storing small amount of data( just the cmHandle id's ) and we don't need persistence of the data (once the application restarts the data will be gone)

Start with a POC on #2 , also check any recommendation from ONAP.