Manage Couchbase 6 Servers and Clusters
Cluster and node management is a crucial topic for a Couchbase administrator. This course delves into handling node failures, data transfers, cluster backups, and the setting up of remote replicas to ensure the availability of your data.
Managing a Couchbase cluster requires a wide array of factors to be considered, ranging from testing its performance to recovering from node failures or data loss. In this course, Manage Couchbase Servers and Clusters, you’ll learn a number of options available with regards to cluster management from a theoretical and also a hands-on perspective. First, you’ll discover how to set up a multi-node Couchbase cluster and test its performance while subjected to a load using cbworkloadgen. You’ll also cover the encryption of traffic between cluster nodes. Next, you’ll explore the variety of ways in which node failures can be handled in a cluster by performing failovers in order to recover data from their replicas. This includes hard failovers where nodes fail unexpectedly and graceful failovers where node removal is planned. Then, you’ll move to backing up the contents of a cluster including the use of cbtransfer to migrate data between clusters and performing a more structured backup using cbbackupmgr. This includes restoring a cluster to a prior state using one of the available backups. Finally, you’ll learn the setting up of cross data center replication, or XDCR, and how the cbrecovery utility can be used to recover from the failure of multiple nodes. When you’re done with this course, you’ll have a better understanding in managing different forms of replication, generating backups of your cluster, and significantly – you will have the knowledge and skills to recover from failures or data loss on your Couchbase cluster.
Author Name: Kishan Iyer
Author Description:
I have a Masters in Computer Science from Columbia University and have worked previously as a developer and DevOps engineer. I now work at Loonycorn which is a studio for high-quality video content. My interests lie in the broad categories of Big Data, ML and Cloud.
There are no reviews yet.