Drupal 8 can scale well and serve pages fast to many users, especially by offloading parts of the work load from the main SQL database to NoSQL solutions.
This presentation describes the strategies and technologies usable to achieve such gains, including specific configuration, contributed modules and custom coding strategies.
3. Topic ?
Simple idea: “No SQL”
● Alternate storage engines: KV, Structures, Document,
Graph, Columnar…
● No standard, often no fixed schema, no joins, no FKs
● → Engine-specific application design
● Drupal architecture ?
Evolved idea: Not Only SQL
● For engines, add equivalent features to SQL
● For Drupal, combine SQL et NoSQL solutions
● Start from the default SQL-based architecture
● Offload services to non-SQL implementations
○ front-end caches, search engines, queue servers
○ specialized storage: cache, KV, lock, sessions…
● Often involves NoSQL as cache for SQL
espace 1 espace 2
4. NOSQL: do you need it ?
● Start by observing the current state
○ Database queries → devel + webprofiler
○ Cache → heisencache (D7), webprofiler (D8)
○ Build cacheability → renderviz
● Observe behaviour
○ Core observability built-in: DBTNG logging, cache decorators, QueryInterface for KV, config, content…
○ Monitoring module (400 sites) by Karan Poddar (Google SoC) and MD Systems
○ Add your choice of time-series store (e.g. Prometheus, InfluxDB) and UI (e.g. Grafana)
○ ⇨ Use it !
● You want to see this when it happens ⟶
6. Fixing an identified problem is cheaper than “trying things”
Fix from acquired information
● It /MAY/ involve taking queries off the main DB to a NoSQL solution
● But poorly configured NoSQL may make it worse.
7. “Just do it” ?
● Drupal is built on SQL:
○ Views depends on it by default
○ Most sites rely on Views data model awareness
○ → Contrib often assumes SQL, injects @database
○ NoSQL support doable, rarely done
● Contrib support level is limited
○ Most NoSQL contrib not ported from D7 to D8
○ Drupalshop knowledge limited except biggest or
specialized
○ Products may die… e.g. RethinkDB
● Pro support from publishers = costs. Availability.
● Extra support needed = costs
NoSQL == added build costs
→ balance gains vs costs
Example case: RethinkDB
At DevDays Milan 2016, after lots of work, Gizra’s @RoySegall
demoed a Drupal 8 ORM/ODM for RethinkDB.
Then, this happened...
10. Caching ahead of real work
Default situation with SQL
● Browser caching, limited
● Internal / dynamic page cache in main SQL DB
● Need DB connection, a few SELECT queries
● Fetch cache from DB
● All data from main storage
● ⇨ Serve cached pages in about 20 msec
All this work makes DoS-ing comparatively cheap.
NoSQL improvements
● Add caching ahead of site itself
○ Browser
■ Optimized browser caching (Cache-Control)
■ PWA: use browser local storage
○ CDN
■ CDN module (2k sites)
■ Akamai module (600 sites)
■ ⇨ Serve cached pages in about 15 msec (TTFB)
■ Web-scale
○ Varnish and other reverse proxies
■ ⇨ Serve cached pages in about 10 msec (TTFB)
■ Core support
■ Varnish Purger (3k sites)
● ⇨ Most request will mean 0 SQL queries
○ DoS-ing more costly, especially with CDN
● Move page caches off main DB: next section
13. Storage: the “Big 3”
The most active NoSQL suites for Drupal 8.x
Redis
● Type: Key-value (structure server)
● Module
○ redis
● DB-Engines ranking:
○ #1 Key-value store
● Usage
○ Drupal 7: 10k sites
○ Drupal 8: 10k sites
● Supported by
○ Drupal 7: Makina Corpus
○ Drupal 8: MD Systems
Memcached
● Type: Key-value
● Module
○ memcache
● DB-Engines ranking:
○ #3 Key-value store
○ #5 Key-value store (Hazelcast)
● Usage (memcache_storage)
○ Drupal 7: 32k (2k) sites
○ Drupal 8: 15k (800) sites
● Supported by:
○ Acquia
○ Tag1 Consulting
MongoDB / CosmosDB
● Type: Document store
● Module
○ mongodb
● DB-Engines ranking:
○ #1 Document store (MongoDB)
○ #4 Document store (CosmosDB)
● Usage
○ Drupal 7: 300 sites
○ Drupal 8: 50 sites
● Supported by
○ OSInet
14. Redis
https://www.drupal.org/project/redis
● Driver support
○ phpredis and predis both supported
● Supported Services
○ Driver adapter for custom code
○ Cache, including invalidations
○ Flood
○ Lock
○ Lock.Persistent
○ Queue
● CLI support
○ Not included
● Other modules
○ Redis Watchdog: logger + UI
Recent events (from @Berdir)
● Deadlock/race condition on node_list invalidations
(#2966607) finally fixed in core 8.8.x with latest
release
● php-redis 5.0 broke module, fixed in latest 8.x and 7.x
releases
● Module users: please test and report !
15. Performance / scalability
Redis
https://www.drupal.org/project/redis
● Performance, single-server
○ Memory-only implementation
■ Usually among the fastest
■ Often the fastest
■ Even with concurrent access
○ Persistent
■ A bit slower even with just RDB
■ Slower with AOF
● Persistence, single instance
○ RDB:
■ compact snapshots, shippable off-site
■ data loss: since latest snapshot
○ AOF
■ up to last-second fsync’ed journal
■ less compact
● Fault-tolerance: Sentinel 2
○ master/slave supervision
○ automatic failover possible
○ observability support
● Scaling
○ Cluster-based sharding
○ Master → Slaves → Slaves
○ No strong consistency
○ Recommended config: 6 servers
● Cloud-native:
○ Redis Enteprise Cloud
○ AWS Elasticache, Azure, Google Memorystore
○ many others
16. Redis
https://www.drupal.org/project/memcache
● Driver support
○ memcache extension (limited availability)
○ memcached extension
○ PHP ≥ 5.6
● Supported Services
○ Driver adapter for custom code
○ Cache, including invalidations
○ Lock
○ Lock.Persistent removed in #2995907
○ Sessions ported, then removed in 7.x
○ Monitoring UI
● CLI support
○ Not included: core commands
● Other module: memcache_storage
○ Cache with core SQL invalidations
○ No lock
○ Monitoring UI
Recent events (from @Berdir)
● Deadlock/race condition on node_list invalidations
(#2966607) finally fixed in core 8.8.x with latest
release, based on Redis fix.
17. ● Performance, single-server
○ Memory-only implementation
■ Usually among the fastest
■ Slower than in-memory Redis
■ A bit faster than to MySQL / MongoDB K/V
○ Persistence: extstore NVRAM support
■ No significant slowdown
■ Usually a bad idea (expectations)
■ https://memcached.org/blog/persistent-m
emory/
● Fault-tolerance
○ Module support for sharded clusters
○ Consistent hashing: avoid thundering herd prob.
○ Replication: with Hazelcache
Performance / scalability
Redis
https://www.drupal.org/project/memcache
● Scaling
○ Cluster-based sharding
○ Consistent hashing allows elastic scaling
○ Recommended config: 2 instances per
cluster, 1 cluster per bin, with some
exceptions: usually 10-20 instances per D8 site
○ Some bins must stay in core (form, update)
● Monitoring
○ Instant: module-provided memcache_admin
○ Evolved: phpmemcacheadmin
● Cloud-native
○ AWS Elasticache
○ Azure Memcached Cloud
○ Google AppEngine Memcache
22. Other NoSQL support modules
NoSQL Product Module Wrapper Features 7.x 8.x Supported ?
Neo4J neo4j Y - Y Y N
RethinkDB renthinkdb Y ORM N Y ?
CouchDB couchdb Y Node export Y N N
Couchbase couchbase Y Logger + UI Y N ?
ElasticSearch elasticsearch_connector Y Logger + improved UI,
Statistics, Views
Y N Y
SearchAPI Y Y
AWS DynamoDB dynamodb N Cache Y N ?
AWS SimpleDB awssdk, creeper Y - Y N ?
Riak riak_field_storage Y Field storage, map-reduce Y N unsupported
Apache Cassandra cassandra Y Example app 6.x N unsupported
Tokyo Tyrant node/844354 N Logger + UI 6.x N unapproved
24. NoSQL Sessions ?
● Why the weak/removed session support, especially for memcache ?
○ Memcache session support is baked in PHP memcached extension
○ It was popular in Drupal 6.x time
○ It is popular in Symfony, even documented on symfony.com
○ So ?
● Experience
○ Session data
○ Instance restart → all sessions data on instance lost
○ Bigger session data saturating bin → evictions
○ LRU means vulnerability to DoS-ing and blocking admins via evictions
○ DB load is bigger in Drupal than most frameworks
■ Session DB load is a smaller part of load for us
26. Logs in core
The “SQL” problem
● All sites really need some sort of logging feature
● Smaller sites only have a database
○ ⇨ Database Logging default-enabled
● Code is not perfect, throws notices, errors
● Modules are verbose, log debug info
● “Drupal is too slow, please help, agency is stuck”
○ ⇨ Audit : 1500 inserts/min in watchdog table
○ ⇨ Other audits: watchdog > 99% of site size
● DBlog inserts compete with content work
● Owner disables logging
○ ⇨ now misses essential info
● Does not disable logging
○ ⇨ now can’t find essential info buried in noise
The core NoSQL module
● Core has been bundling a syslog client since 6.0
● Decouple logs from DB load
○ ⇨ No more SQL logs workload
● But where do they go ?
○ ⇨ Needs OS-level configuration
● How are logs cleaned ?
○ ⇨ Needs OS-level configuration
● Where is the UI ?
○ ⇨ Needs extra tools
● Solutions ?
○ D7 has logging hook
○ D8 has PSR/3 standard logging
○ ⇨ Contributions
27. NoSQL on-site logs
(mongodb|redis)_watchdog
● mongodb_watchdog
○ Logger service
■ Standard Drupal PSR/3 logs backend
■ Pre-storage filtering
■ Uses capped collections: auto-rotation, no ops
■ Dedicated database: zero contention
■ Per-request event tracing
○ Improved logs UI
■ Based on core UI
■ Groups recurring events on single line
■ Details page for occurrences
■ Per-HTTP-request log page
○ Most common reason to deploy MongoDB on D8
● redis_watchdog
○ Logger service
○ Logs UI based on core UI
○ Usage: 1 site
28. Off-site logs: BELK stack
BELK stack
● Beats (typically FileBeat)
● Elastic Search
● Logstash
● Kibana
Operation
● Drupal syslog → local syslog server → local logs
● DON’T log straight from Drupal
● Filebeat pulls logs, sends to Logstash
● Logstash massages logs, sends to ES
● ES provides storage, indexing
● Kibana provides UI
Deployment
● Hosted with site
● SaaS: Loggly, Logz.io, ...
29. Off-site logs: Graylog
Graylog
● Dual server: ES (logs, search) + MongoDB (meta, conf)
● Includes GROK log handling
● Accept syslog or GELF input
● Designed from Splunk
Operation
● Drupal syslog → local syslog server → local logs
● DON’T log straight from Drupal via monolog_gelf
● Local syslog forwards to Graylog2
● Graylog2 massages logs, sends to ES
● ES provides storage, indexing
● Graylog2 provides UI
Deployment
● Hosted with site
● SaaS: StackHero
31. Non-SQL Logs: do I need them ?
● Small site, little traffic, single webmaster: just use dblog
● Any other site: upgrade to something else
○ Hosting company provides a logs dashboard (e.g. Splunk): use it
■ syslog into their stack, via local syslog then pull
○ Have an internal ops team ?
■ syslog into internal BELK or Graylog
○ No ops expertise ? don’t have time to learn Kibana/Graylog ? hosting company
doesn’t provide real time logs access ?
■ Want to minimize costs and/or have logs in-site ?
● use mongodb_watchdog
■ Otherwise, use SaaS logs vendor
● Datadog, Scalyr, Loggly or Papertrail (SolarWinds), Logz.io...
33. Queue API services
● Core: mostly for Batch API
● General D8 use: proxy invalidation
○ Invalidation queues
● Commerce sites
○ ERP links
○ Third-party catalog/inventory
● Media sites
○ Real time news feeds ingestion
○ Deferred derived media generation
34. Queue modules
SQL and NoSQL
SQL
● Core bundled: queue.database service
○ used by all Drupal sites
● advanced_queue project
○ created for Drupal Commerce projects
○ used by Commerce 2.x
NoSQL: storage-based
● Core bundled: queue.memory service
● Redis:
○ 7.x: redis_queue project
○ 8.x: redis project
● MongoDB
○ 7.x: mongodb project
NoSQL: message servers
● Beanstalkd
○ 6.x/7.x: popular, used by drupal.org itself
○ 8.x complete port, but no users (?)
● RabbitMQ
○ 7.x: little used, 8.x: most popular
○ Users include public TV, major french e-tailer
○ Hardened by production at these levels
● AWS SQS
○ 7.x: some use, but no 8.x port
● Apache Kafka
○ 8.x only
○ Created for largest french retail chain
● Other queue services
○ Less used: Gearman, IronMQ, 0MQ
○ No 8.x versions
36. NoSQL Queue: do I need it ?
● Mainstream Drupal site without Varnish / CDN
○ probably not, advancedqueue is still a nice improvement though
● Content site with a lot of generated content, Varnish and/or CDN
○ consider using Redis (D8), MongoDB (D7), RabbitMQ (D8)
○ or use Kafka (D8) if you need to (e.g. corporate mandate)
● Drupal Commerce standalone
○ advancedqueue is normally enough
● Site generating lots of dynamic media (image, video, sound) ...or ingesting fast feeds (> 1 item/sec)
○ need a dedicated message server
37. NoSQL Queue: which should I use ?
● The one your ops team supports best
○ Content management has a low event rate (< 1 event/sec)
● Kafka-class is for high-throughput queues
○ Think LinkedIn, Twitter, Netflix, Spotify, Airbnb, Paypal…
● RabbitMQ is solid
○ usually well known and monitored
○ D8 driver used for years on Cyber Monday, Black Friday, Olympic games...
● Beanstalkd is simple
○ It “just works”
○ Good first queue upgrading from DB
39. SQL-based search
● Search has long been the weakest core feature in Drupal
○ In spite of improvements with each version
● Relevant issues
○ Good recall, but bad precision
○ Multilingual support, but no language awareness
○ Low awareness of language inflections → preprocessing API
○ Limited ability to handle asian (CJK) languages
○ Slow updates, cron-based pull mode
○ Indexing costs impacting site users
○ Indexed search for content only → search plugins
○ Other entity types limited to unindexed search by default
○ No support for restricted content search
● Useful complements: porterstemmer, snowball_stemmer
● SQL Alternative: Search API database search. Similar.
40. NoSQL search solutions
Cloud-based / SaaS
● SaaS offerings:
○ Algolia
○ Google CSE
● Drupal Hosting offerings (alphabetic order):
○ Acquia Search SOLR
○ Amazee.io SOLR
○ Pantheon SOLR
○ Platform.sh ElasticSearch / SOLR
On-site / near-site
● Core support: Search API (14% of D7, 16% of D8 sites)
● Standard solution:
○ Local SOLR
○ Multilingual search supported
● Alternatives:
○ Elastic Search → heart of BELK suite
○ Xunsearch: Xapian for Chinese
○ Xapian (8.x dev)
● D7 backends not on D8:
○ Elastic Search via Elastica
○ Google Search Appliance: killed by Google
○ MongoDB via MongoDB module
○ Sphinx
● Proprietary search engine publishers have custom,
unpublished, non-GPL (!) Drupal modules
42. Non-core search: which should I use ?
● Any content deserves search
● SQL
○ Core for small content quantities
○ Search API DB backend used by drupal.org
● SaaS
○ For entry level: Algolia/Google = 0 recurring cost, near 0 set-up cost
○ Both perform better than core, but non-free
● Drupal PaaS have managed ES/SOLR
● Others: cost equilibrium
○ ES/SOLR have setup and recurring costs of possession (server load)
○ SaaS has lower set-up costs, but recurring fees
○ Core search has the cost of lost opportunity
44. Best current practice: NoSQL in general
Drupal 8 core tries hard to be SQL-agnostic
● Every use of the DB goes through @database
○ So anything able to pass for a SQL engine may be used
○ The mongodb_dbtng, mongodb 8.x-1.x, and Drumongous projects do just that
● Even Views has a query plugin. Project efq_views (7.x, 8.x) supports NoSQL engines that way
● No service except “storage” services should receive databases
○ Write a storage service for your data, defining its interface
○ Write a SQL provider implementing it, receiving @database
○ Tag the service as “backend_overridable”
○ Core mostly does it, custom code should always do it.
● References:
○ https://www.drupal.org/project/drupal/issues/2302617
○ https://www.drupal.org/node/2306083
45. Best current practice: MongoDB
● Connecting to MongoDB with 8.x-2.x
○ Using multiple databases ? Use @mongodb.client_factory
■ The client you get is a standard mongodb/mongodb Client instance
■ You have to handle topology
○ Using single database ? Use @mongodb.database_factory
■ The database you get is a standard mongodb/mongodb Database instance
■ Your DB topology is now configurable in settings
○ You probably don’t want to use Doctrine ODM, especially when interacting with Drupal data
● Designing a custom schema
○ Start from the queries, not from some canonicalization
○ For large scale data sets, consider:
■ Splitting live and archive data for sharding
■ Having a write DB and a read DB, and a CLI-based service between them - read about CQRS
○ Never use a monotonic increasing key for sharding
○ In most cases, joined data in lists don’t need to be as up-to-date as primary views
■ Embed “light” versions of dependent objects for lists, only use $lookup and DBRef joins on full datum view
46. “ “
There, I said it !
Contribution is
its own reward
47.
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