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Latest revision as of 13:26, 11 December 2017

Tags Analytics, Data Center, Infrastructure, Job Queue, Multi-Datacenter, Performance
Primary Session Evolving the MediaWiki Architecture
Secondary Sessions

The future of the MediaWiki infrastructure at the wikimedia foundation.

MediaWiki is at the core of the infrastructure that serves all of the Wikimedia projects, and the current setup of MediaWiki in production poses various challenges: from the future of our current runtime (HHVM), to the to ability to serve MediaWiki from multiple DataCenters, to long standing issues as resource usage efficiency and flexibility.

Here are some of the things we have to tackle in the future.

Transition off of HHVM:

Since the HHVM team has made it clear they're parting ways with full PHP compatibility, and that maintaining support for both HHVM and PHP in MediaWiki would be arduous, we need to make plans to move off of HHVM, back to PHP 7.x. This transition, while technically necessary, should not come at a cost for our users: page load times should not degrade. We can proceed by marking responses coming from either engine, collecting metrics and analyzing data. In order to achieve this, we should run the two runtimes in parallel on the same servers (which have plenty of capacity, given no MediaWiki cluster has an utilization over 40%), and we will then be able to programmatically route individual users or a percentage of traffic, or even specific wikis, to one or the other. The deadline for this transition is set for the end of 2018 (EOL of the last compatible version of HHVM), and planning and resources should be allocated to this goal.

Multi-Datacenter support:

We currently are using our datacenters in a active/passive setting, as far as MediaWiki is concerned. While this is ok in line of principle, this is a huge waste of resources and means we both have 50% of our servers doing nothing at all, and also limits our ability to expand the number of core datacenters we can use. Diverting the read load to secondary datacenters could also allow us to use caching in a less aggressive way when not needed. There is already a program underway to add first-class multi-DC support to MediaWiki, so we can focus on what specifically needs to be done in order to achieve this longtime goal: our final goal should be to serve reader's traffic from all datacenters, and to be able to switch the "master" datacenter in matter of minutes.

Elasticity, resource usage efficiency

At the moment , our infrastructure is plainly inadequate to react to sudden spikes of non-wiki content production and to changes that generate a lot of asynchrounous jobs, as a change of a popular template. The issues with the current jobqueue are widely known and publicized, but even the current transition to a new model won't solve the starvation of resources that result in a degraded user experience. Moreover, a single editor uploading videos via video2commons can easily overflow our media processing capacity for weeks. This happens because we allocate our resource statically (we have 4 vidoesclaers per datcenter, for example), we have an inefficient resource consumption, and reallocating servers requires time and effort. Modern applications stacks are elastic, meaning the operation of scaling up or down the capacity of a single cluster or functionality can be handled programmatically and/or manually whenever the need occurs, allowing the infrastructure to react to such changes. For economic and privacy/security reasons, Wikimedia doesn't make use of external cloud services, so the only way to achieve such flexibility is to build a serviceable infrastructure that can serve MediaWiki and any other project Wikimedia will support: the effort to do that is underway with the rollout of our Kubernetes-based IaaS in production. I think we should work, sooner than later, at moving the MediaWiki application stack (and maybe its semi-ephemeral caching) to the kubernetes platform. While the advantages of such an approach seem clear, it won't come without costs: specifically habits around code deployment, testing and configuration changes will need to be completely revisited and superseded by new approaches.