GKE Data Cache, now GA, accelerates stateful apps

Using GKE Data Cache with Postgres we have seen:

• Up to a 480% increase in transactions per second for PostgreSQL on GKE
• Up to a 80% latency reduction for PostgreSQL on GKE

“The launch of GKE Persistent Disk with Data Cache enables significant improvements in vector search performance. Specifically, we’ve observed that Qdrant search response times are a remarkable 10x faster compared to balanced disks, and 2.5x faster compared to premium SSDs, particularly when operating directly from disk without caching all data and indexes in RAM. Qdrant Hybrid Cloud users on Google Cloud can leverage this advancement to efficiently handle massive datasets, delivering unmatched scalability and speed without relying on full in-memory caching.” – Bastian Hofmann, Director of Engineering, Qdrant 

Stateful applications like databases, analytics platforms, and content management systems are critical to many businesses. However, their performance can often be limited by the I/O speed of the underlying storage. While persistent disks provide durability and flexibility, read-intensive workloads can experience bottlenecks, impacting application responsiveness and scalability. 

GKE Data Cache addresses this challenge head-on, providing a managed block storage solution that integrates with your existing Persistent Disk or Hyperdisk volumes. When you enable GKE Data Cache on your node pools and configure your workloads to use it, frequently accessed data is automatically cached on the low-latency local SSDs attached to your GKE nodes.

This caching layer serves read requests directly from the local SSDs whenever the data is available, significantly reducing the need to access the underlying persistent disk and potentially allowing for the use of less system memory cache (RAM) to service requests in a timely manner.