Description
Course info
Level
Beginner
Updated
Jan 11, 2019
Duration
1h 32m
Description

Due to its in-memory nature, Memorystore features some of the lowest latencies on the platform, down to sub-millisecond levels. This managed-Redis service is hosted on Google’s highly scalable infrastructure, which means that it can support instances up to 300 GB and network throughput of 12 Gbps. Memorystore offers an easy migration path for users of Redis, a technology that is fast gaining popularity, especially for use from within Docker containers running on Kubernetes. In this course, Leveraging Fully Managed Redis Datastores Using Google Cloud Memorystore, you'll examine all of these aspects of working with Memorystore, and learn how to get the best out of this powerful managed database service. First, you will explore the suite of storage products that are available on the GCP and where exactly Memorystore fits in. You will be introduced to the capabilities of using Redis to cache data for transactions, and as a publisher-subscriber message delivery system, and you will learn about the LRU eviction policies that Memorystore follows. Next, you will implement Memorystore integrations with applications that you host on Compute Engine VMs, App Engine, and on Google Kubernetes Engine clusters. These are the current options that the GCP supports for working with managed Redis. Finally, you will dive into how you can configure Memorystore for high-availability configurations. Memorystore offers two Redis tiers: basic tier and standard tier instances. Basic tier instances do not support cross-zone replication and failover, while standard tier applications are equipped with both features. In addition, the standard tier offers far lower downtime during scaling. You’ll also see how you can monitor Redis instances using Stackdriver. When you’re done with this course, you will have a good understanding of how you can use Memorystore to cache your data on the cloud and know how you can integrate managed Redis with your applications running on various compute options on the GCP.

About the author
About the author

An engineer and tinkerer, Vitthal has worked at Google, Credit Suisse, and Flipkart and studied at Stanford and INSEAD. He has worn many hats, each of which has involved writing code and building models. He is passionately devoted to his hobby of laughing at his own jokes.

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Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
Hi! My name is Vitthal Srinivasan, and I'd like to welcome you to this course on Leveraging Fully Managed Redis Datastores Using Google Cloud Memorystore. A little bit about myself. I have master's degrees in Financial Math and Electrical Engineering from Stanford University and have previously worked in companies such as Google in Singapore and Credit Suisse in New York. I am now co-founder at Loonycorn, a studio for high-quality video content based in Bangalore, India. Due to its in-memory nature, Memorystore features some of the lowest latencies on the platform down to the level of sub-milliseconds. This managed Redis service is hosted on Google's highly scalable infrastructure, which means that it can support instances of up to 300 GB and network throughput of 12 gbps. Memorystore offers an easy migration path for Redis users. That's a technology that is fast gaining popularity, especially for use from within Docker containers running on Kubernetes clusters. This course covers all of these aspects of working with Memorystore and explains how to get the best out of this powerful managed database service. First, you will understand the suite of storage products that are available on the GCP and know exactly where Memorystore fits in. You will be introduced to the capabilities of Redis for caching data, for transactions, as a publisher/subscriber message delivery system, and you will also understand the LRU eviction policies that Memorystore follows. Next, you will implement Memorystore integrations with applications hosted on Compute Engine VM instances, App Engine, and the Google Kubernetes Engine clusters. These are the current compute options on the GCP which support working with managed Redis. Finally, you'll understand how you can configure Memorystore for high-availability configurations. Memorystore offers two Redis tiers, basic and standard. Instances belong to one of these two tiers. Basic tier instances do not support cross-zone replication and failover, while standard tier applications are equipped with both these features. In addition, the standard tier offers far lower downtime during scaling. You'll also see how you can monitor Redis instances using Stackdriver. When you're done with this course, you'll have a good understanding of how you can use Memorystore to cache your data on the cloud and know how you can integrate managed Redis with your applications running on various compute options on the GCP.