5/14/22

Improve App Performance with In-Memory Cache and Real-Time Integration


In the presentation, we discuss some of the performance problems that exists when using an API to SQL Server integration on a high transaction systems with thousands of concurrent clients and several client tools that are used for statistical analysis.

ozkary-telemetry

Telemetry Data Story

Devices send telemetry data via API integration with SQL Server. These devices can send thousands of transactions every minute.  There are inherit performance problems with a disk-based database when there are lots of writes and reads on the same table of a database. 

To manage the performance issues, we start by moving away from a polling system into a real-time integration using Web Sockets. This enables the client application to receive events on a bidirectional channel, which in turns removes the need to have to poll the APIs at a certain frequency.

To continue to enhance the system, we introduce the concept of an enterprise in-memory cache, Redis. The in-memory cache can be used to separate the reads and writes operations from the storage engine. 

At the end, we take a look at a Web farm environment with a load balancer, and we discuss the need to centralize the socket messages using Redis Publish and Subscribe feature. This enables all client with a live connection to be notified of the changes in real-time.

ozkary-redis-integration

Database Optimization and Challenges

Slow Queries  on disk-based storage
  • Effort on index optimization
  • Database Partition strategies
  • Double-digit millisecond  average speed (physics on data disks)
Simplify data access strategies
  • Relational data is not optimal for high data read systems (joins?)
  • Structure needs to be de-normalized
  • Often views are created to shape the data, date range limit

Database Contention
  • Read isolation levels (nolock)
  • Reads competing with inserts

Cost to Scale
  • Vertical and horizontal scaling up on resources
  • Database read-replicas to separate reads and writes
  • Replication workloads/tasks
  • Data lakes and data warehouse

What is Socket.io, WebSockets?

Enables real-time bidirectional communication.
Push data to clients as events take place on the server
Data streaming
Connection starts as HTTP is them promoted to WebSockets 


Why Use a Cache?

  • Data is stored in-memory
  • Sub-millisecond average speed
  • Cache-Aside Pattern
    • Read from cache first (cache-hit) fail over to database (cache miss)
    • Update cache on cache miss
  • Write-Through
    • Write to cache and database
    •  Maintain both systems updated
  • Improves app performance
  • Reduces load on Database

What is Redis?

  • Key-value store, keys can contain strings (JSON), hashes, lists, sets, & sorted sets
  • Redis supports a set of atomic operations on these data types (available until commited)
  • Other features include transactions, publish/subscribe, limited time to live -TTL 
  • You can use Redis from most of today's programming languages (Libs)
Code Repo

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Originally published by ozkary.com

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