Getting the most out of Spring and App Engine!!
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- Barnaby McCormick
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1 Getting the most out of Spring and App Engine!! Chris Ramsdale Product Manager, App Engine Google 2011 SpringOne 2GX All rights reserved. Do not distribute without permission.
2 Whatʼs on tap today? 0 - scaling in 5 mins Going a bit deeper Developing with the Spring Framework Adding relation data in the cloud Performance tweaks Whatʼs next?
3 0 - scaling in 5 mins A quick intro to App Engine
4 Traditional approach LAMP stack Developer (You) 4
5 App Engine to the rescue Easy to build Easy to manage Easy to scale 5
6 Demo: quick start Create a web application using Googleʼs Plugin for Eclipse Run the app locally Make changes Deploy to App Engine Test 6
7 Whatʼs in it for you? Focus on developer productivity So you can build apps Without the infrastructure headaches 7
8 Out of labs... weʼre growing up! Supported product 99.95% uptime guarantee (SLA) Paid operational support Platform certifications Growing fast... 8
9 200,000+ Apps 100,000+ Developers 1.5B Page views / day Memcache Python Runtime HTTPS Java Runtime Task Queues XMPP Appstats Namespaces API High Replication Datastore Channel API Go Runtime ISAE3402 Type II Certification Backends Pull Queues
10 Mobile/game backend... PocketGems 10
11 Web Gaming =
12 Large scale events 32K req/sec 37M pageviews 13M visitors 12
13 Success stories - Khan Academy SALMAN KHAN 13
14 Customer: WebFilings 14
15 Going a bit deeper App Engine features and functionality
16 Extended Language support through JVM Java Scala JRuby (Ruby) Groovy Quercus (PHP) Rhino (JavaScript) Jython (Python) Duke, the Java mascot Copyright Sun Microsystems Inc., all rights reserved. 16
17 Always free to get started Instance hours: 28/day High Replication Datastore: 1G Outgoing Bandwidth: 1G Incoming Bandwidth: 1G Datastore API: 50k free read/write/small Blobstore API: 5G API: 100 recipients XMPP API": 1000 stanzas Channel API: 100 channels opened 17
18 Feature overview Compute Frontends Backends Task Queues Cron Network URL Fetch XMPP Channel API Mail API Storage Datastore Memcache Namespaces Blobstore Cloud SQL Static content Services Images API App Identity Users API MapReduce API Pipeline API Prospective Search API 18
19 Frontends, Backends, Task Queue, Cron Compute Pull (Task) Queues Client Client Client Client 19 App App Engine Engine Frontend Frontend App App Engine Engine Backend Backend Push (Task) Queues / Cron App App Engine App Engine App Frontend Engine Frontend Engine Backend Backend
20 High Replication Datastore (HRD) Storage Schema-less Object datastore Entities & Entity Groups Query engine Standard & custom indexes Atomic transactions Features Highly scalable More distributed as more data is stored Highly reliable Synchronous, multi-datacenter replication Managed 20
21 URL Fetch HTTP/1.1 GET, POST, PUT, HEAD, and DELETE Maximum request deadlines 60s (default 5s): user facing (online) requests 10 minutes: cron, task queue (offline) requests Execution options Synchronous Async 21 Network
22 2011 SpringOne 2GX All rights reserved. Do not distribute without permission. Services
23 Developing with the Spring Framework Building on standards
24 Ensuring Portability Duke, the Java mascot Copyright Sun Microsystems Inc., all rights reserved. 24
25 Demo: simple Hello World Should feel very normal Create an empty web application using Googleʼs Plugin for Eclipse Add Spring dependencies Add controllers Add view Wire up dispatch servlet 25
26 Adding relational data in the cloud Using Google Cloud SQL
27 Google Cloud SQL: overview Highly available, self-managed, hosted SQL storage solution Replicates to multiple geographic regions JDBC compatible Available for Google App Engine applications that are written in Java or Python 27 Duke, the Java mascot Copyright Sun Microsystems Inc., all rights reserved.
28 Google Cloud SQL: features Ability to host your MySQL databases in the cloud Instances up to 10GB (early cap) Synchronous geographic replication Import or export databases using mysqldump Command line tool SQL prompt in the Google APIs Console 28
29 Google Cloud SQL: getting started Development A local MySQL instance/cluster Eclipse App Engine SDK Development app server Production No code changes Easy deployment from Eclipse Running on App Engine Persisting data to Googleʼs Cloud SQL 29
30 Google Cloud SQL: development Install MySQL Configure database/tables/test data Copy JDBC driver into App Engine SDK Add JDBC driver to the run/debug classpath Add the following VM args to your run/debug config: -Drdbms.server=local -Drdbms.driver=com.mysql.jdbc.Driver -Drdbms.url=jdbc:mysql://localhost:3306/testdb?user=root 30
31 Google Cloud SQL: production Sign-up for access Create an instance Enable access from your App Engine apps Deploy from Eclipse Done 31
32 Demo: simple Hello DB 32
33 Going a bit further: Pet Clinic sample Maven import and deploy...right? 33
34 Going a bit further: Pet Clinic sample A few tweaks to your workflow Need to supply similar VM args for local development Remove JMX monitoring Edit jdbc.properties Google Cloud SQL URL App Engine rdms driver Register App Engine JDBC driver 34
35 Performance tweaks Fine tuning your app for production
36 Caching with Memcache 2ms Client Client App App Engine Engine App Frontend App Frontend Engine Engine Backend Backend 20ms 36
37 Caching using standards Free lunch possibility And your users will be happier too Use memcache Only if you care about your users Static resource files Do not consume instance hours HTTP/1.1 caching Cache-Control: public, s-maxage=... Respected by browsers, ISPs and App Engine Saves bandwidth Replace dynamic content with Static content 37
38 Best practices in client-side code Avoid this! Clients all checking in at a specific time of day Spread out load: - Randomize client checkin times And this! Clients retry failures after a fixed interval Avoid a Denials-of-Service (DoS) on your app after a failure: - Use exponential back-off: 1s, 2s, 4s, 8s, 16s, - Use a fuzz factor: randomize retry times 38
39 Best practices in server-side code Efficient resource utilization Reduce instance hours Reduce request latency Use Memcache Datastore/Memcache batch get/put Async URL Fetch, Datastore, Memcache Parallelize RPCs Enable HTTP session async writes Spin up fewer instances Task queue rate and max_concurrent_requests X-AppEngine-FailFast 39
40 Best practices in server-side code Efficient resource utilization Enable concurrent requests Java appengine-web.xml Discounted reserved instances $0.08/hr $0.05/hr Scheduler knobs Max Idle Instances Min Pending Latency 40
41 Enable warming requests Request logs: /_ah/warmup Default behavior Enabled for Java apps All jar files are indexed in memory Initializes your application and filters Servlets marked in <load-on-startup> ServletContextListener filters Custom warmup servlet Override built-in _ah_warmup servlet <servlet> <servlet-name>_ah_warmup</servlet-name> <servlet-class>foo.mywarmupservlet</servletclass> 41
42 Manage 'datastore ops' costs Number of write ops in SDK Fewer indexes & indexed properties fewer write ops Take advantage of query planner improvements Replace queries with keys-only queries (cheaper) fetch-by-key (optimal) datastore cursors (for pagination) 42
43 Manage storage costs Discard stuff you no longer need Entities Indexes Blobs Tasks Drop unwanted indexes Vacuum custom indexes New query planner Explicitly mark properties as unindexed To migrate existing entities, put() again with:» Python: foo = db.stringproperty(indexed=false)» Java: entity.setunindexedproperty( foo, bar ) 43
44 Load testing: Guidelines Test traffic must be representative of real user traffic Ramp over a period of several minutes Don t do this! Nice! 44
45 Load testing: Basic recipe Send steady 5 qps traffic to your site Uncover basic problems, e.g. entity contention on global data Monitor for minutes and expect to see: Stable request latency <1000ms Zero quota denials Low error rate Tasks queues are keeping up No elevated datastore contention Slowly ramp up; increase traffic by 2x Uncover next application bottleneck, if any Repeat until serving desired qps Plan your next feature 45
46 Appstats 46
47 Custom error pages Avoid this: With this: <static-error-handlers> <handler file="default_error.html"/> <handler file="over_quota.html" error-code="over_quota"/> </static-error-handlers> 47
48 Whatʼs new? Latest updates for App Engine users
49 Release New! HRD apps Cross Group (XG) transactions Python 2.7 (experimental) Cloud SQL (preview) Full-Text Search (trusted tester) HRD Migration Tool Higher limits File uploads 10MB 32MB, URLFetch POST 1MB 5MB Frontend requests 30s 60s, URLFetch 10s 60s Max files 3,000 10,000 Other Google Storage File API 49
50 Other recent improvements New! Unlimited blob size Seamless backend config changes SDK eventual consistency simulation Country identification: X-AppEngine-Country Admin console logs in your time zone 50
51 Advanced query planner New! Datastore never requires an exploding index code.google.com/appengine/docs/python/datastore/ queries.html#big_entities_and_exploding_indexes dev_appserver Understands query planner changes Zigzag merge-join queries Will continue scanning for up to 30 sec No more "needs index" errors (although some may timeout) BuildingScalableComplexApps.html 51
52 The old query planner Index(Photo, owner_id, -date) Index(Photo, owner_id, -rating) Index(Photo, owner_id, -comments) Index(Photo, owner_id, -downloads) Index(Photo, size, -date) Index(Photo, size, -rating) Index(Photo, size, -comments) Index(Photo, size, -downloads) Tags Indexes 1 2^6*4 = ^7*4 = ^8*4 = Index(Photo, owner_id, size, -date) Index(Photo, owner_id, size, -rating) Index(Photo, owner_id, size, -comments) Index(Photo, owner_id, size, -downloads) Index(Photo, aspect, coloration, license, owner_id, size, -date) Index(Photo, aspect, coloration, license, owner_id, size, -rating) Index(Photo, aspect, coloration, license, owner_id, size, -comments) Index(Photo, aspect, coloration, license, owner_id, size, -downloads) = 2^(no. of filters) * (no. of different orders) = 2 ^ 6 * 4 = 256 indexes 52
53 The improved query planner Index(Photo, owner_id, -date) Index(Photo, owner_id, -rating) Index(Photo, owner_id, -comments) Index(Photo, owner_id, -downloads) Index(Photo, size, -date) Index(Photo, size, -rating) Index(Photo, size, -comments) Index(Photo, size, -downloads) Index(Photo, license, -date) Index(Photo, license, -rating) Index(Photo, license, -comments) Index(Photo, license, -downloads) Index(Photo, tag, -date) Index(Photo, tag, -rating) Index(Photo, tag, -comments) Index(Photo, tag, -downloads) = (number of filters) * (number of orders) = 6 * 4 = 24 indexes 53
54 Using the new query planner Upgrade to the latest SDK Turn off auto index generation Java: <datastore-indexes autogenerate="false"> Remove unnecessary custom index definitions Java: WEB-INF/datastore-indexes.xml WEB-INF/appengine-generated/datastore-indexes-auto.xml Test your app Deploy to production Judiciously run: appcfg vacuum_indexes 54
55 XG Transactions New! In a single transaction Access 1..5 entity groups - read and/or write Does not provide transactional ancestor-less query Does allow 1..5 separate ancestor queries within transaction Availability Only in HRD apps App Engine release 55
56 Whatʼs next? Upcoming features for App Engine users
57 Coming soon... SLA, custom domain SSL Configurable front-end sizes 57
58 Q&A
59 Resources App Engine SDK Google Plugin for Eclipse Eclipse Sample code checkout 59
60 Thank You! Chris Ramsdale 60
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