![]() Having your caching layer impacting the speed of your primary data store is not really acceptable. ![]() MySQL, on the other hand, is far more difficult to scale horizontally and is likely to also be being used as your primary data source. Key/value stores such as Memcached and Redis are great at dealing with large amounts of data, and Memcached in particular can be scaled horizontally simply by adding more servers. The true benefit becomes clearer as traffic to the site increases. ![]() For cache gets, this is often not the case-a well-tuned MySQL server can perform as well as or better than Memcache in some cases, although Memcache should almost always outperform MySQL for cache sets. One incorrect assumption that many people make is that replacing the cache backend will automatically make each individual cache request faster. Swapping out the cache backend can help improve both performance and scalability however, we should look closely at exactly what changes when the cache storage is replaced. Not only can these backends help to offload queries from MySQL, but they can be easily scaled out horizontally as your site grows.Īs introduced in Chapter 3, Drupal’s cache API stores data in MySQL by default, but it can be easily integrated with other technologies. There are multiple Drupal contributed projects that provide a way to pull cache entries out of MySQL and store them in an alternative storage backend, such as Memcached or Redis. This can cause increased network traffic and ultimately increase the load on the database servers. While this is generally fine for smaller sites, as the number of cache and session objects grows, frequent actions such as cache invalidation put a high demand on the database layer. Queries with a condition on one field that sort on another then have to join across multiple tables, which is very hard to optimize with a relational database.Īnother common performance bottleneck that particularly affects higher-traffic Drupal sites is that cache and session data are stored in MySQL tables by default. The entity/field storage provided by core provides one or two tables for each core entity, then two tables for each individual field (one for the current or “live” revision and one for older revisions). This is a very powerful set of features, but it can make getting great performance out of a traditional relational database quite difficult. Entity types such as nodes, users, and comments can be extended with configurable fields, and then the Views module allows those to be queried and presented-all without leaving the user interface. Drupal is very modular and flexible in terms of how data can be defined. MySQL provides a great database backend for Drupal, but there are certain issues that arise, especially as Drupal sites get larger. This includes low-level APIs such as caching and queues, as well as site content. Tags: Microsoft.Storage/storageAccounts, Microsoft.Storage/storageAccounts/fileServices/shares, Microsoft.Network/publicIPAddresses, Microsoft.Network/loadBalancers, Microsoft.Resources/deployments, Microsoft.Compute/virtualMachineScaleSets, CustomScript, LinuxDiagnostic, Microsoft.Chapter 16. Alternative Storage and Cache Backendsĭrupal uses MySQL as the default storage backend for all data on a site. Optionally adding nginx and memcache into the mix.Optionally supply new relic key as parameter, to send VM metrics to new relic. ![]() !(images/azureResourceExplorer.png"SSH into Drupal VMs") Backlog of Planned Changes You can use Resource Explorer to see the VMs in the VM scale set. So for VM 0 ssh in to port 50000, for VM 1 ssh to port 50001 and so on. You can ssh into the VMs in the VM scaleset if needed, using the inbound NAT Pool ports on the load balancer.!(images/AccessingDrupalSite.jpg"Access Drupal Site") The Drupal admin user name and password which were entered during the template deployment can be used for logging in as administrator. Access Drupal using the VMSS load balancer fully qualified domain name.SSH ports on the VMs are exposed through the load balancer (NAT ports) Deploys a load balancer in front of the Drupal VM Scaleset, so that the VMs are not directly exposed to the internet.The Template can be configured to use an existing MySQL server, or create a New MySQL server (using the MySQL Replication Template).The Drupal nodes mount the file share, where the settings file and files folder are stored The template also deploys an Azure file share.Maximum and minimum number of Drupal 8 VMs in the scaleset can be configured - each of these uses Ubuntu OS.This template deploys a Drupal 8 installation using a VM scale set.
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