Read Replicas

In Amazon's cloud, the store relies on the Amazon Relational Database Service (RDS), which greatly simplifies setting up, operating, and scaling relational databases [4]. It can be configured via the AWS Management Console, the interface for AWS. For read-intensive queries – and they occur far more frequently than writes – admins can, for example, call Create Read Replica to create multiple slave database instances (Figure 2). These instances rely on the master-slave MySQL replication model; however, Rovio uses the read replicas exclusively for generating reports.

Figure 2: You can set up read replicas of databases at the press of a button and buffer the load on the master instance.

The read slaves prevent database locks and deadlocks occurring when generating reports by introducing a kind of load balancing. Updates to the database are thus first written to the master instance and are then distributed asynchronously to the read slaves.

Caching

Caching relieves the load on the Magento database. The store achieves high availability, while at the same time minimizing database queries through the use of Varnish Cache [5]. The service is responsible for load balancing: it removes overloaded servers that respond slowly, or not at all, from load balancing and automatically replaces them with new instances. The AOE developers have also made pages statically cacheable in a large part of the Rovio store. Intelligent use of the browser cache and a reverse proxy cache means that clients handle some of the work. Shopping carts, the checkout process, payment functions, and user profiles are dynamically generated by the store.

If 5,000 visitors really do visit the store at the same time, the Varnish cache only queries the back end once per page or cache lifetime (TTL); it otherwise delivers cached content to the visitors. Varnish only allows dynamic requests through to Magento, which boosts speed all told about 400-fold. The application also offers potential for optimization: Reducing the log level, disabling logging functions, and regularly cleaning data (logs, expired cache content) also provide a speed boost.

To relieve the main database, the store's developers initially worked with a separate database until eventually replacing the cache back end with Redis. The NoSQL database stores key-value pairs directly in memory and thus accelerates the requests.

Setting Up Amazon's Databases

Configuring Amazon's database services is a fairly easy process using the Management Console. New instances are easily started, and the database is easily selected (Figure 3).

Figure 3: Setting up a database instance in the AWS Management Console.

Security Groups control access to the instances, thus ensuring the necessary security. Admins can use the Groups parameters where needed to modify individual database configuration parameters. Once AWS is set up, it defines database parameters, such as the host, user, and password specifically for the environment (production or staging) and then enables the database for online access. For Magento, it ultimately does not matter whether its own database runs in a virtual environment such as Amazon RDS or on a dedicated server.

Importing data to the cloud is handled by a MySQL client, as you might expect. The system is limited by the partly static nature of the database. It cannot dynamically field surprising visitor storms, even though the application servers scale automatically. It is thus important to compute your needs correctly on a project-specific basis, because changes in the operation involve some downtime. The available instance sizes offer 5 to 3,370GB of storage with selectable CPU power and RAM.

New to Amazon is an option for guaranteed I/O performance [6], which does cause additional cost but offers significantly improved performance. Standby replicas [7] ensure more reliability and seamless operation without downtime; Amazon creates standby replicas automatically in separate data centers, which it refers to as Availability Zones (AZ). They allow you to handle and compensate for planned maintenance windows for the database. If the main data center fails, the standby database in another zone automatically steps in (hot standby), so that operation continues without intervention.