Application Protection
A Kubernetes application has to backup all Kubernetes control plane data stored in /etcd, all namespaces, and all persistent volumes that hold critical business data.
A critical component of a successful Kubernetes DR strategy starts with planning, testing, and documenting procedures, with a goal to automate wherever possible. In a Kubernetes world, traditional tooling can lead to a manual approach to DR. It is important to automate processes to reduce the recovery time to a minimum and restore apps functionality within minutes.
Disaster recovery (DR) is an organization's ability to respond to and recover from an event that negatively affects business operations. The goal of DR methods is to enable the organization to regain use of critical systems and IT infrastructure as soon as possible after a disaster occurs.
A Kubernetes application has to backup all Kubernetes control plane data stored in /etcd, all namespaces, and all persistent volumes that hold critical business data.
Using policy-driven automation to manage how backups are restored simplifies disaster recovery allowing developers and operations to lower risk and simplify execution.
Fully automated failovers and app redeploys are the ultimate goal, and can make the difference shifting from hours or days to minutes for recovery.
Centrally configure, automate and operationalize disaster recovery (DR)
Eliminate manual handling of backup credentials for enhanced security
Leverage easy to use workflows for creating and managing backups for the entire fleet of clusters
Have flexible controls to specify what data to include and exclude as part of the backup
Customize this plan for your K8s Operations POC
Having a backup and disaster recovery plan for enterprises has long been a best practice to minimize business risk and be able to quickly recover in the event of a cyber attack, system outage/failure, natural disaster, and more. … Read More
As enterprises move Kubernetes into production and increase the number of Kubernetes clusters and applications in use, they need to deliver the same “enterprise-level” services as for other production applications. Implementing Kubernetes backup is critical to protect your… Read More
Kubernetes is architected as a set of microservices that manage the lifecycle of containers and coordinate application management tasks such as configuration, deployment, service discovery, load balancing, scheduling, scaling, and monitoring across a fleet of clusters. The microservices-based architecture of… Read More
Rafay enables Automation Workflows for Backup & Restore of your Kubernetes clusters with reduced operational complexity. Leverage one step workflows to restore data from backups during disaster recovery events. Enabling backup for a cluster is as simple as enabling a toggle. The Backup agent will be automatically deployed to the cluster and configured with required backup credentials.
The concepts of backup and disaster recovery are quite distinct. A Backup process makes copies of data, applications, configurations and critical information multiple times on a periodical basis and requires a restore process in order to retrieve whenever it is required. A Disaster Recovery process has the objective of quickly reestablishing access to applications, data, and IT resources after an outage.
Two essential indicators to consider as part of a disaster recovery plan are Recovery Time Objective (RTO) and Recovery Point Objective (RPO). RTO is the length of downtime you can allow before recovery, and RPO is the amount of data you can afford to lose.
In the event of a ETCD failure, running workloads may continue operating, however the Kubernetes cluster cannot make any changes to its state given it won’t have where to register this. No new pods can be enabled or scheduled until the etcd cluster is recovered.
The master Kubernetes node controls all the worker nodes of a cluster. It is recommended that a cluster is set up with a multi-master architecture to ensure that if one master node fails, any other master node can ensure that your cluster continues to work smoothly. On a single-master architecture, if the master node fails it will not be possible to create new services, pods, etc. and the cluster might fail.