Continuous Data Protection (CDP) is a technology that has been around for some time and has gained popularity in recent years. It offers many advantages, but it also comes with its own set of trade-offs. In this blog post, we will look at the fundamentals of CDP, why businesses may or may not require it as part of their data protection and recovery plans, and what are the benefits and drawbacks of using it.

Firstly, the concept of CDP can be compared to any sort of replication technology. We have a critical item or subset of data that needs to be highly available in case of some event that might put that data at risk. In its most basic form, we think about DFS-R in Windows and how files and folders are replicated in near real time from one server to another. This can be said for any form of replication technology that achieves the same thing.

However, over the past ten to fifteen years, CDP has been synonymous with virtual machines (VMs) and the ability to replicate whole VMs from a source site to a target site with ultra-low Restore Time Objectives (RPOs). The other trait of CDP for VMs is that the RTO is low as well. This means these technologies aim to reduce data loss while being able to get to the data quicker than traditional backup mechanisms. CDP maintains a journal of data changes, which makes it possible to restore a machine to any previous point in time.

With most CDP technologies, replicated data is kept in a journal that allows recovery from granular points in time by keeping the intervals dictated by the RPO. The lower the RPO, the more network throughput required to handle the streams of data at smaller intervals. There are technologies that look to optimize data transfer between the source and target but CDP does mean more network pressure.

Storage is the other major factor to consider in that the journal holds more points of time, again dictated by the RPO. The longer the journal window, the more storage required, and also the lower the RPO, the more points in time captured to be stored in that journal. There is also the potential for more compute resources required in terms of CPU and memory as there are more calculations required to move the data from source to target.

Granular recovery and quick restore times highlight the main benefits of CDP. This ensures business continuity in case of an event taking place that puts the data or workload at risk. Not only can recovery take place at set RPO intervals, but the time to recover is almost instant due to the fact that whole virtual machines are ready to be brought up at the target end without having to restore from a backup repository. This allows businesses to meet internal and external service level agreements (SLAs) that result in an expected outcome after events take place.

Leveraging CDP allows for granular point-in-time recovery of applications, data, and servers. One of the other benefits of CDP over more traditional replication technologies, especially in a virtual world, is that VMs are not impacted by snapshot creation or consolidation stuns.

So when is CDP required, and what types of workloads are candidates for CDP? The idea is that every workload can be protected with CDP, but the reality differs in practicality. Because of the overheads mentioned above and the associated costs involved, CDP should only be used to protect the most critical Tier-1 workloads as dictated by business requirements.

Not all workloads need per-second RPOs, and this is where the categorization of workloads comes into play. The idea being that you apply different data protection policies to sub-sets of virtual machines and only add those deemed to be most critical to the business to CDP policies. The majority of workloads should be able to be backed up with more traditional point-in-time snapshots and even non-CDP based replication leveraging snapshots.

In conclusion, CDP offers many advantages but comes with its own set of trade-offs. It is important to understand the fundamentals of CDP, why businesses may or may not require it as part of their data protection and recovery plans, and what are the benefits and drawbacks of using it. By applying different data protection policies to sub-sets of virtual machines and only adding those deemed most critical to CDP policies, organizations can ensure business continuity in case of an event that puts the data or workload at risk while meeting internal and external SLA’s.