What it's good for Memorystore for Redis provides a fast, in-memory store for use cases that require fast, real-time processing of data. From simple caching use cases to real time analytics, Memorystore for Redis provides the performance you need.
Caching: Cache is an integral part of modern application architectures. Memorystore for Redis provides low latency access and high throughput for heavily accessed data, compared to accessing the data from a disk based backend store. Session management, frequently accessed queries, scripts, and pages are common examples of caching.
https://cloud.google.com/memorystore/docs/redis/redis-overview#what_its_good_for

Provides permissions to run jobs, including queries, within the project. This role can check the existence of all jobs, enumerate their own jobs, and cancel their own jobs.
https://cloud.google.com/bigquery/docs/access-control

First of all you can define quotas on project or user level and 2nd one is you can change from on demand to flat rate model and define the parameters based on your requirement.
https://cloud.google.com/bigquery/docs/custom-quotas
https://cloud.google.com/bigquery/pricing#flat_rate_pricing

Use separate health checks for load balancing and for autohealing. Health checks for load balancing detect unresponsive instances and direct traffic away from them. Health checks for autohealing detect and recreate failed instances, so they should be less aggressive than load balancing health checks. Using the same health check for these services would remove the distinction between unresponsive instances and failed instances, causing unnecessary latency and unavailability for your users.
https://cloud.google.com/compute/docs/tutorials/high-availability-autohealing