Cloud Data Replication-using MySQL
Businesses are becoming increasingly reliant on data and one way to ensure its availability for business needs is through replication. Replication facilitates the availability of mission-critical data on time and ensures that the replicated data can be used for disaster recovery, reporting, and integration.
What is Data Replication?
Data replication is the process of storing data in more than one geographical location to improve its accessibility and system resilience. Data replication stores multiple copies of critical data and makes it available to users when they need it. This helps the replicated system synchronize, update, and process data without network latency or processing delays. In this blog, we will explain how replication can be achieved using MySQL.
Data replication can be full or partial, depending on business requirements. In full replication, the entire database is stored at every site, and in partial replication, only fragments of the data are replicated to the other locations using MySQL replication. MySQL replication maintains copies of MySQL data by duplicating them from a master database to a slave database in more than one location or server.
What are the Different Types of Data Replication?
Database replication depends upon your business requirements and can be implemented using different methods –
- Host-based – This replication is file-based, and application servers are paired with the software to create copies of data from one location to another.
- Hypervisor-based – This replication copies the entire Virtual Machines (VMs) from one host server to another, facilitating easy data recovery during failovers.
- Array-based – This replication uses built-in software in compatible storage arrays to replicate data automatically between them.
- Network-based – This replication work with all host platforms and needs an additional switch between the storage arrays and servers.
Why do we Need Data Replication?
Data replication ensures data availability all the time. This is particularly critical for global organizations with multiple offices. Data replication has multiple use cases –
- To avoid overload on the primary system
- During offloading of heavy query processing jobs to the backup site
- Using it as a reporting system
- To keep up with the audit and compliance policies
- While migrating away from a legacy system
- Using it as a backup system
Strategies for Data Replication
The data replication strategy can significantly impact data availability, accessibility and recovery. You do not need frequent updates that take too long to copy the data to the server and vice versa. Here are some widely accepted data replication strategies for your reference –
- Transactional Replication is a continuous process of sending and receiving data. In this process, data is copied from the publisher to the subscriber in real-time, maintaining the order of occurrence at the publisher site. This help to maintain transactional consistency and accuracy across the system. Such type of replication is helpful in site-to-site replication environments.
- Snapshot Replication as a process is ideal when the data changes infrequently and when the publisher and the subscriber do not always need to be in sync. When synchronization is initiated, a snapshot is generated and shared with the Subscribers.
- Merge Replication copies and distributes data from one SQL server to another by synchronizing the databases to maintain consistency. It allows different sites to work independently to provide a consistent result.
Realtime Data Replication Use Case
At Opteamix, we recently delivered a cloud-based replication project for a U.S-based banking client using MySQL Server. The Client needed a robust cloud replication technology to mirror its database server to AWS-EC2 Cloud from the AWS-RDS setup as they wanted to run their web application without interruptions. Opteamix successfully implemented a cost-effective data replication and High Availability (HA) solution to keep the operations online during periodic maintenance or disaster recovery procedures.
As per the requirement, we presented an asynchronous and row-based replication model, created in the Master-Salve format and is a good use case for the Active-Passive replication model. The highlights of the solution that we implemented were as follows –
- The slave server connects to the master server
- I/O threads ask for change data
- Binary Log (binlog) dump threads send contents to I/O threads
- SQL threads will apply the changed data
Replicating AWS-RDS server
This replication was set between AWS cloud environments, where the source was AWS-RDS and the target was RDS-EC2.
This setup required minimum dependency on third-party tools. We used mysqldump (for backup), MySQL command prompt (to run SQL queries), and MySQL for GTID-based replication.
The High-level steps in this process are –
- Backing up the data from Amazon RDS for MySQL DB instance and then restoring it on the EC2 instance.
- Setup the replication using GTID (Global Transaction Identifier).
- Validate the data in the source and target instances.
The result was an optimized AWS-EC2 architecture with multiple functional benefits leveraging the High-Availability database replicas. Opteamix helped the client service its customers 24*7*365 without interruption to business by using AWS data replication at a fraction of the cost.
Although data replication does not seem too complex, recent developments in cloud computing have highlighted the complexity of replicating data from one node to another. Every time a new feature is added, the system gets more complicated. It gets difficult to write clean code or even to understand everything that is going on. We need to implement the AWS cloud migration solution preserving the old setup without confronting any performance issues.
If you are encountering data replication challenges, Get in touch with us to speak with our cloud experts. We assure you that our Cloud Practice will help implement a cost-effective solution that ensures zero interruption to your business.
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