Learn the best AWS architecture for a massive multiplayer game leaderboard requiring microsecond reads, single-digit-millisecond writes, multi-TB datasets, and high availability.
Table of Contents
Question
A company is migrating infrastructure for its massive multiplayer game to AWS. The game’s application features a leaderboard where players can see rankings in real time. The leaderboard requires microsecond reads and single-digit-millisecond write latencies. The datasets are single-digit terabytes in size and must be available to accept writes in less than a minute if a primary node failure occurs.
The company needs a solution in which data can persist for further analytical processing through a data pipeline.
Which solution will meet these requirements with the LEAST operational overhead?
B. Create an Amazon ROS database with a read replica. Configure the application to point writes to the writer endpoint. Configure the application to point reads to the reader endpoint.
C. Create an Amazon MemoryDB for Redis cluster in Muit-AZ mode Configure the application to interact with the primary node.
D. Create multiple Redis nodes on Amazon EC2 instances that are spread across multiple Availability Zones. Configure backups to Amazon S3.
Answer
C. Create an Amazon MemoryDB for Redis cluster in Muit-AZ mode Configure the application to interact with the primary node.
Explanation
Amazon MemoryDB for Redis is a fully managed, Redis-compatible, in-memory database service that delivers ultra-fast performance with microsecond read and single-digit millisecond write latencies. It supports Multi-AZ replication for high availability and durability. If the primary node fails, MemoryDB automatically fails over to a replica node in less than a minute.
MemoryDB can handle large datasets up to 128 TB in size. It provides a primary endpoint that the application can interact with for both reads and writes. This minimizes complexity compared to using separate read and write endpoints.
For analytical processing, MemoryDB supports exporting snapshots to Amazon S3. This allows persisting data from MemoryDB to S3 for further analysis through a data pipeline.
The other options are not ideal:
B. Amazon RDS databases like MySQL, PostgreSQL, etc. cannot provide the required microsecond read and millisecond write speeds. They are better suited for transactional workloads rather than a real-time leaderboard.
D. Running Redis on Amazon EC2 instances requires significant operational overhead to set up replication, backup, monitoring, scaling, etc. compared to the fully managed MemoryDB service. It’s better to leverage a managed service to reduce operational complexity.
Therefore, creating an Amazon MemoryDB for Redis cluster in Multi-AZ mode is the best solution for the given requirements and constraints. Let me know if you have any other questions!
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