Scalable Drupal infrastructure

Designing, Scoping, and Conﬁguring Scalable Drupal Infrastructure Presented 2009-05-30 by David Strauss

Understanding Load Distribution

Predicting peak traffic Traffic over the day can be highly irregular. To plan for peak loads, design as if all traffic were as heavy as the peak hour of load in a typical month -- and then plan for some growth.

Analyzing hit distribution 40% 30% Hu man e nt nt 3% icC o 50% t Sta t en W t m eb rea al T Cr 100% ci aw pe s ou S le No r ym 10% on Dy n An am “P i cP ay W ag al l” es By pa ss 70% Auth entic ated 7% 20%

Throughput vs. Delivery Methods Green Yellow Red (Static) (Dynamic, Cacheable) (Dynamic) 2 Content Delivery Network ●●●●●●●●●● ✖ ✖ Reverse Proxy Cache ●●●●●●● ●●●●●●● ✖ 1000 req/s 1 Drupal + Page Cache + memcached ●●● ●●● ✖ 1 Drupal + Page Cache ●●● ●● ✖ 1 Drupal ●●● ● ● 10 req/s 1 Delivered by Apache without Drupal More dots = More throughput 2 Some actually can do this.

Objective Deliver hits using the fastest, most scalable method available.

Layering: Less Traﬃc at Each Step Your Datacenter Load Reverse Application Traﬃc Balancer Proxy Server Cache DNS Round Robin CDN Database

Oﬄoad from the master database Search Your master database is the single greatest limitation on scalability. Application Slave Server Database Master Memory Cache Database

Tools to use ‣ Apache Solr for search. (Acquia oﬀers hosting of this now.) ‣ Squid or Varnish for reverse proxy caching. ‣ Any third-party service for CDN.

Do the math ‣ All non-CDN traffic travels through your load balancers and reverse proxy caches. Even traffic passed through to application servers must run through the initial layers. Load Reverse Application Traffic Balancer Proxy Server Cache What hit rate is each layer geing? How many servers share the load?

Get a management/monitoring box Load (maybe two or three Balancer and have them specialized or redundant) Application Database Management Server Reverse Proxy Cache

Planning + Scoping

Infrastructure goals ‣ Redundancy ‣ Scalability ‣ Performance ‣ Manageability

Redundancy ‣ When one server fails, the website should be able to recover without taking too long. ‣ This requires N+1, putting a ﬂoor on system requirements. ‣ How long can your site be down? ‣ Automatic versus manual failover

Performance ‣ Find the “sweet spot” for hardware. This is the best price/performance point. ‣ Avoid overspending on any type of component ‣ Yet, avoid creating bottlenecks ‣ Swapping memory to disk is very dangerous

Relative importance Processors/Cores Memory Disk Speed Reverse Proxy Cache ● ●●● ●● Web Server ●●●●● ●● ● Database Server ●● ●●●● ●●●● Monitoring ● ● ●

Reverse proxy caches ‣ Squid makes poor use of multiple cores. Focus on getting the highest per-core performance. The best per-core performance is often on dual-core processors with high clock rates and lots of cache. ‣ Varnish is much more multithreaded. ‣ 4-8 GB memory, total ‣ Expect 1000 requests per second, per Squid ‣ 64-bit operating system if more than 2 GB RAM

Web servers ‣ Apache 2.2 + mod_php + memcached ‣ Many processors + many cores is best ‣ 25 Apache threads per core ‣ 50 MB memory per thread, system-wide ‣ 1 GB memory for system ‣ 1 GB memory for memcached ‣ Conﬁgure MaxClients in Apache to maximum system-wide thread count ‣ Expect 1 request per thread, per second

Database servers ‣ MySQL 5.0 cannot use more than eight cores eﬀectively but gets good gains from at least quad- core processors. ‣ Depend on each Apache thread needing one connection, and add another 50. ‣ Each MySQL connection needs around 6 MB. ‣ MySQL with InnoDB needs a buﬀer pool large enough to cache all indexes. Start by giving the pool most remaining database server memory and working from there. ‣ 64-bit operating system if more than 2 GB RAM

Monitoring server ‣ Very low hardware requirements ‣ Choose hardware that is inexpensive but essentially similar to the rest of the cluster to reduce management overhead ‣ Reliability and fast failover are typically low priorities for monitoring services

Assembling the numbers ‣ Start with an architecture providing redundancy. ‣ Two servers, each running the whole stack ‣ Increase the number of proxy caches based on anonymous and search engine traﬃc. ‣ Increase the number of web servers based on authenticated traﬃc. ‣ Databases are harder to predict, but large sites should run them on at least two separate boxes with replication.

Pressﬂow Make Drupal sites scale by upgrading core with a compatible, powerful replacement.

Common large-site issues ‣ Drupal core requires patching to effectively support the advanced scalability techniques discussed here. ‣ Patches often conflict and have to be reapplied with each Drupal upgrade. ‣ The original patches are often unmaintained. ‣ Sites stagnate, running old, insecure versions of Drupal core because updating is too difficult.

What is Pressflow? ‣ Pressflow is a derivative of Drupal core that integrates the most popular performance and scalability enhancements. ‣ Pressflow is completely compatible with existing Drupal 5 and 6 modules, both standard and custom. ‣ Pressflow installs as a drop-in replacement for standard Drupal. ‣ Pressflow is free as long as the matching version of Drupal is also supported by the community.

What are the enhancements? ‣ Reverse proxy support ‣ Database replication support ‣ Lower database and session management load ‣ More eﬃcient queries ‣ Testing and optimization by Four Kitchens with standard high-performance software and hardware conﬁguration ‣ Industry-leading scalability support by Four Kitchens and Tag1 Consulting

Four Kitchens + Tag1 ‣ Provide the development, support, scalability, and performance services behind Pressﬂow ‣ Comprise most members of the Drupal.org infrastructure team ‣ Have the most experience scaling Drupal sites of all sizes and all types

Ready to scale? ‣ Learn more about Pressﬂow: ‣ Pick up pamphlets in the lobby ‣ Request Pressﬂow releases at fourkitchens.com ‣ Get the help you need to make it happen: ‣ Talk to me (David) or Todd here at DrupalCamp ‣ Email shout@fourkitchens.com

Managing the Cluster

The problem Soware and Conﬁguration Application Application Application Application Application Server Server Server Server Server Objectives: Fast, atomic deployment and rollback Minimize single points of failure and contention Restart services Integrate with version control systems

Manual updates and deployment Human Human Human Human Human Application Application Application Application Application Server Server Server Server Server Why not: slow deployment, non-atomic/diﬃcult rollbacks

Shared storage Application Application Application Application Application Server Server Server Server Server NFS Why not: single point of contention and failure

rsync Synchronized with rsync Application Application Application Application Application Server Server Server Server Server Why not: non-atomic, does not manage services

Capistrano Deployed with Capistrano Application Application Application Application Application Server Server Server Server Server Capistrano provides near-atomic deployment, service restarts, automated rollback, test automation, and version control integration (tagged releases).

Multistage deployment Deployments Deployed with Deployed with Capistrano can be staged. Capistrano cap staging deploy cap production deploy Development Integration Deployed with Staging Capistrano Application Application Application Application Application Server Server Server Server Server

But your application isn’t the only thing to manage.

Beneath the application Reverse Cluster-level Proxy Database configuration Cache Application Application Application Application Application Server Server Server Server Server Cluster management applies to package management, updates, and soware configuration. cfengine and bcfg2 are popular cluster-level system configuration tools.

System configuration management ‣ Deploys and updates packages, cluster-wide or selectively. ‣ Manages arbitrary text configuration files ‣ Analyzes inconsistent configurations (and converges them) ‣ Manages device classes (app. servers, database servers, etc.) ‣ Allows confident configuration testing on a staging server.

All on the management box { Development Integration Staging Management Deployment Tools Monitoring

Monitoring

Types of monitoring Failure Capacity/Load Analyzing Downtime Analyzing Trends Viewing Failover Predicting Load Troubleshooting Checking Results of Conﬁguration and Notiﬁcation Soware Changes

Everyone needs both.

What to use Failure/Uptime Capacity/Load Nagios Cacti Hyperic Munin

Nagios ‣ Highly recommended. ‣ Used by Four Kitchens and Tag1 Consulting for client work, Drupal.org, Wikipedia, etc. ‣ Easy to install on CentOS 5 using EPEL packages. ‣ Easy to install nrpe agents to monitor diverse services. ‣ Can notify administrators on failure. ‣ We use this on Drupal.org

Hyperic ‣ I haven’t used this much, but it’s fairly popular. ‣ More diﬃcult to set up than Nagios.

Cacti ‣ Highly annoying to set up. ‣ One instance generally collects all statistics. (No “agents” on the systems being monitored.) ‣ Provides ﬂexible graphs that can be customized on demand. ‣ Optimized database for perpetual statistics collection. ‣ We use this on Drupal.org and for client sites.

Munin ‣ Fairly easy to set up. ‣ One instance generally collects all statistics. (No “agents” on the systems being monitored.) ‣ Provides static graphs that cannot be customized.

Cluster Problems

Cache/session coherency ‣ Systems that run properly on single boxes may lose coherency when run on a networked cluster. ‣ Some caches, like APC’s object cache, have no ability to handle network-level coherency. (APC’s opcode cache is safe to use on clusters.) ‣ memcached, if misconfigured, can hash values inconsistently across the cluster, resulting in different servers using different memcached instances for the same keys. ‣ Session coherency can be helped with load balancer affinity.

Cache regeneration races ‣ Downside to network cache coherency: synched expiration ‣ Hard to solve All servers regenerating the item. Old Cached Item Expiration { New Cached Item Time

Broken replication ‣ MySQL slave servers get out of synch, fall further behind ‣ No means of automated recovery ‣ Only solvable with good monitoring and recovery procedures ‣ Can automate removal from use, but requires cluster management tools

Server failure ‣ Load balancers can remove broken or overloaded application reverse proxy caches. ‣ Reverse proxy caches like Varnish can automatically use only functional application servers. ‣ Cluster management tools like heartbeat2 can manage service IPs on MySQL servers to automate failover. ‣ Conclusion: Each layer intelligently monitors and uses the servers beneath it.

Scalable Drupal infrastructure

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