Disaster recovery replication: Data strategy

Some may wax nostalgic for the old days when, in the event of a disaster, business owners simply had to grab their Rolodex and run. Today’s businesses operate within a complex web of digital data, which must remain intact and accessible after a disaster if operations are to continue. Disaster recovery replication involves creating exact copies of data to ensure seamless failover and minimal data loss.

That is where data replication comes in as a critical part of your larger IT disaster recovery efforts. The primary site is the main location where data resides, and data is replicated to a target location for disaster recovery. By creating replicated copies of applications and data from a database on one server to another located outside of the business (ideally in another geographical region) and typically in real-time or near real-time, a business can achieve redundancy and ensure business continuity in the event of everything from hurricanes to hackers.

Replication is the process of copying and maintaining database objects in multiple locations to ensure data redundancy and availability, which protects against data loss and enhances data accessibility.

What is data replication?

Data replication isn’t as basic as copying and moving all of your data all of the time. First, replicating all of an organization’s data is prohibitively expensive. Therefore, a key component of a data replication strategy is to make sure that essential applications, processes, and data are highest on the priority list. For example, email, CRM, and financial systems are core applications that typically can’t be down for more than a few hours. Backup is also an essential part of data protection strategies and complements replication by providing an additional safety net in case of data loss or corruption, especially when combined with robust data encryption and backup practices.

Nor is the data replication itself the only part of a replication strategy to take seriously. In addition to identifying your must-have data, you need to know how you will access that data. A robust disaster recovery plan should include replication as a key component, outlining steps to recover data and resume operations in case of a disaster. When disasters occur, you might think, “It’s replicated. No problem!” But how will you get to that data in a failover state? And prior to that, how will you ensure that your strategy will work when you need it? A hybrid approach to disaster recovery often involves replicating backups from on-premises systems to a secondary location, which could be in the cloud or another physical site, to ensure data protection and recovery.

Do you need an MPLS circuit at your DR site, or VPN tunnels? Larger organizations typically have a private network that connects their offices around the country. If they use that network to talk to their server infrastructure in the production data center, the disaster recovery data center will need to be connected to that same MPLS network for their users to communicate to it. Organizations may need to configure their disaster recovery workflows and replication jobs, including network mapping, retention policies, and other parameters to ensure effective planning and execution. If an organization needs a more cost-effective way of talking to the DR data center, VPN tunnels over the Internet are another option. Cloud computing enables seamless integration between on-premises and cloud environments, supporting multi-cloud strategies and hybrid IT approaches that balance cloud and on-premises environments, and data synchronization across more than one location. Data may reside in one location or be distributed across multiple sites, and on-premises infrastructure is often integrated with cloud platforms for disaster recovery.

Types of data replication

Building on broader disaster recovery best practices and planning, data replication is a key component of disaster recovery strategies, providing organizations with the ability to ensure data availability and minimize downtime in the face of unexpected disruptions. There are several replication methods, each with its own strengths and ideal use cases:

Data replication is a key component of disaster recovery strategies, providing organizations with the ability to ensure data availability and minimize downtime in the face of unexpected disruptions. There are several replication methods, each with its own strengths and ideal use cases:

Synchronous Replication: Synchronous replication involves copying data in real time from the primary system to a secondary location. This ensures that both sites always have the same data, making it ideal for high-availability systems where data consistency is critical. Because every write operation must be confirmed at both locations before it is considered complete, synchronous replication minimizes the risk of data loss but can require significant network bandwidth and is typically best suited for environments where the primary and secondary sites are geographically close.

Asynchronous Replication: With asynchronous replication, data is copied from the primary to the secondary location with a slight delay. This method is commonly used in disaster recovery scenarios where some data loss is acceptable in exchange for reduced network requirements and greater flexibility in site location. Asynchronous replication is particularly useful for organizations with geographically distant data centers or those looking to optimize network bandwidth while still ensuring data availability.

Near-Synchronous Replication: Near-synchronous replication strikes a balance between synchronous and asynchronous methods. It aims to minimize the time lag between the primary and secondary sites, optimizing replication efficiency while maintaining a high level of data consistency. This approach is often chosen when organizations need to minimize downtime and data loss but cannot support the network demands of full synchronous replication.

Block-Based Replication: Block-based replication operates at the storage block level, replicating only the changed blocks rather than entire files. This method can significantly improve replication speed and reduce network bandwidth usage, making it suitable for large datasets and environments with high change rates. Block-based replication is often used in high-performance disaster recovery solutions where efficiency and minimizing downtime are top priorities.

File-Based Replication: File-based replication copies entire files from the primary to the secondary location. While this approach can be more resource-intensive and slower than block-based replication, it is straightforward to implement and works well for smaller datasets or less critical applications. File-based replication is typically used when data change rates are low, and the focus is on ensuring the availability of specific files rather than large volumes of data.

By understanding the different types of data replication, organizations can select the method that best aligns with their disaster recovery objectives, data consistency requirements, and network capabilities, ensuring that critical data remains protected and accessible when it matters most.

Best practices for data replication and recovery

Here are three important best practices to keep in mind to make sure your data gets back up and running efficiently and effectively. In many cases, these practices must align with broader data center operations and best practices to ensure resilience end-to-end.

Here are three important best practices to keep in mind to make sure your data gets back up and running efficiently and effectively. Data synchronization is essential for maintaining data consistency and availability across on-premises and cloud systems, especially in hybrid cloud environments. Replication helps maintain business continuity by ensuring that data is consistently available across different systems and locations, providing a backup in case the primary data source becomes unavailable.

1. Tier data sets in order of importance

Placing your applications in the correct order of importance helps to optimize your budget. Tiering data sets in order of importance ensures that essential applications and processes are prioritized for replication in disaster recovery strategies. Due to high costs, data replication is typically reserved only for essential applications and processes, making it important to understand how Backup as a Service vs. Disaster Recovery as a Service fits into your overall protection strategy. Incremental replication is a practical approach for ongoing data replication, as it starts with a full-size replication and subsequently only copies over the changes. Defining recovery time objectives and recovery point objectives is essential - you need to know how long you can go without your most critical applications and how much data loss your business can handle, as well as how you will manage the failback process when returning workloads from a DR environment.

For example, you need to have your Exchange email server running all the time, even during a disaster. So it should be Tier 0, or a mission-critical application. Tier 1 applications might include your billing or order entry system, so you can take orders even when your production environment is down.

You also need to make sure everyone understands where these files, in all tiers, exist in order to be backed up. Are they in database files that need to go on a server? Are they properly set up?

2. Determine the optimal sequence for bringing resources back up

In the event of a disaster, replicated data must be brought back up in a carefully determined sequence and pace. Certain applications are dependent on others to start. If you replicated 50 different servers, you can't simply start them all up at once.

Instead, bringing resources back up in a cloud recovery scenario is almost like a dance — a slow waltz is a good example — as applications come back up step by step. For instance, domain controllers have to come up first. Authentication has to be done early. Then an Exchange email server that houses email might come up next. Finally, ancillary systems can get in line.

3. Test your data replication and DR plan

An often-ignored aspect of DR is testing your plan. So, if your strategy includes replicating entire VMs, you should test the data center disaster recovery plan to make sure you have addressed infrastructure changes that may have occurred throughout the year. You could have 50 systems and replicate 20 of them, but when you fire everything up after declaring a disaster, what if you forgot to replicate one core system that all of the other 20 systems depend on?

For guaranteed data replication success, you need to go beyond testing the validity of the data. Test the order of operations to ensure all systems communicate properly. Access the replicated files often to make sure they are not corrupted.

Common challenges and solutions

Implementing data replication for disaster recovery is not without its challenges. Organizations must address a range of technical and operational hurdles to ensure that replicated data is reliable, consistent, and available when needed. Here are some of the most common challenges and practical solutions:

Data Corruption: Replicated data can become corrupted during transfer, threatening data integrity and recovery efforts. To combat this, organizations should implement robust data validation and verification processes as part of their replication strategy. Regular integrity checks and automated monitoring can help detect and resolve inconsistencies before they impact recovery.

Network Bandwidth: Limited network bandwidth can slow down replication processes, especially in environments with high data change rates. To optimize bandwidth usage, consider leveraging data compression, deduplication, and network acceleration technologies. These techniques reduce the amount of data transmitted, making replication more efficient and cost-effective.

Recovery Time Objectives (RTO): Meeting strict recovery time objectives can be challenging, particularly in complex IT environments. To ensure RTO compliance, organizations should define clear recovery time objectives, automate replication and failover processes, and conduct regular disaster recovery scenario testing. This proactive approach helps minimize downtime and ensures systems are restored within acceptable timeframes.

Recovery Point Objectives (RPO): Achieving tight recovery point objectives—minimizing the amount of data loss in a disaster—requires careful planning. Implementing incremental backups and frequent replication cycles can help reduce the risk of data loss. Automated data validation processes further ensure that the most recent and accurate data is always available for recovery.

Data Loss: Data loss can result from hardware failures, software errors, or cyber attacks, making it critical to implement comprehensive data loss prevention strategies and tools. To mitigate this risk, organizations should combine data replication with regular backups and comprehensive disaster recovery processes. This layered approach enhances data protection and supports business continuity, even in the face of unexpected disruptions.

Cloud Replication: Replicating data to cloud environments introduces additional complexity, especially in hybrid or multi-cloud setups, and underscores the need for regular disaster recovery testing to validate cloud failover and recovery. Success in cloud replication depends on selecting the right cloud provider, automating replication and recovery workflows, and regularly testing disaster recovery scenarios to ensure seamless failover and data accessibility.

IP Address Management: Managing IP addresses during failover can be complicated, particularly in large or distributed networks. Automated IP address management tools and the use of IP address pools can streamline the process, ensuring that systems remain accessible and reducing the risk of configuration errors during disaster recovery.

Monitoring and Management: Continuous monitoring and effective management of replication processes are essential for early detection of issues and maintaining data consistency, and they depend heavily on a well-structured disaster recovery team with clearly defined roles. Implementing automated monitoring solutions and using specialized replication software can provide real-time insights, alerting IT teams to potential problems and enabling rapid response.

By proactively addressing these challenges, organizations can optimize their data replication strategies, safeguard critical data, and ensure rapid recovery in any disaster recovery scenario, which is particularly vital in highly regulated, data-intensive sectors such as healthcare disaster recovery planning.

Consult an expert

A cloud recovery solution such as Flexential Disaster Recovery as a Service (DRaaS) can help you identify your Recovery Time Objective and Recovery Point Objective, as well as make sure all of your data replication and DR plans are properly and regularly tested.

Contact one of our experts today!