• Share
  • Email
  • Embed
  • Like
  • Private Content
Game Analytics with AWS - GDC 2014
 

Game Analytics with AWS - GDC 2014

on

  • 556 views

Free to play is now the standard for mobile and social games. But succeeding in free-to-play is not easy: You need in-depth data analytics to gain insight into your players so you can monetize your ...

Free to play is now the standard for mobile and social games. But succeeding in free-to-play is not easy: You need in-depth data analytics to gain insight into your players so you can monetize your game. Learn how to leverage new features of AWS services such as Elastic MapReduce, Amazon S3, Kinesis, and Redshift to build an end-to-end analytics pipeline. Plus, we'll show you how to easily integrate analytics with other AWS services in your game.

Statistics

Views

Total Views
556
Views on SlideShare
556
Embed Views
0

Actions

Likes
2
Downloads
16
Comments
0

0 Embeds 0

No embeds

Accessibility

Categories

Upload Details

Uploaded via as Adobe PDF

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

    Game Analytics with AWS - GDC 2014 Game Analytics with AWS - GDC 2014 Presentation Transcript

    • AWS Gaming Solutions | GDC 2014 Game Analytics with AWS Or, How to learn what your players love so they will love your game Nate Wiger @nateware | Principal Gaming Solutions Architect
    • AWS Gaming Solutions | GDC 2014 Mobile Game Landscape • Free To Play • In-App Purchases • Long-Tail • Cross-Platform • Go Global • User Retention = Revenue
    • AWS Gaming Solutions | GDC 2014 Projected Mobile App Revenue 0 10000 20000 30000 40000 50000 60000 70000 80000 90000 2011 2012 2013 2014 2015 2016 2017 Ads IAP Paid Source: Gartner
    • AWS Gaming Solutions | GDC 2014 Winning at Free to Play • Phase 1: Collect Data • Phase 2: Analyze • Phase 3: Profit
    • AWS Gaming Solutions | GDC 2014 Analyze What? Emotions • Enjoying game • Engaged • Like/dislike new content • Stuck on a level • Bored • Abandonment Behaviors • Hours played day/week • Number of sessions/day • Level progression • Friend invites/referrals • Response to mobile push • Money spent/week
    • AWS Gaming Solutions | GDC 2014 Example: Level Progression (One Metric) 0 2 4 6 8 10 L1 L2 L3 L4 L5 L6 L7 L8 L9 L10 Tries / Level # of Tries
    • AWS Gaming Solutions | GDC 2014 Example: Level Progression (Two Metrics) 0 10 20 30 40 50 60 0 2 4 6 8 10 L1 L2 L3 L4 L5 L6 L7 L8 L9 L10 Tries / Level % Highest Level # of Tries
    • AWS Gaming Solutions | GDC 2014 Key Takeaways • Multiple data sources • Correlate variables • Deltas vs absolutes • Settle on terminology (game vs level) • Time matters
    • AWS Gaming Solutions | GDC 2014
    • AWS Gaming Solutions | GDC 2014 Events & Metrics • Event = Moment in Time – Login/quit – Game start/end – Level up – In-app purchase • Metrics = What to Measure – KISS – Numbers – Booleans – Strings (Enums) • Always Include (ALWAYS) – User – Action – Session (context-dependent) – Timestamp in ISO8601 2014-03-16T16:28:26
    • AWS Gaming Solutions | GDC 2014 Off The Shelf Analytics • Easy To Integrate • Pre-Baked Reports • Rate Limits • Retention Windows • Data Lock-In
    • AWS Gaming Solutions | GDC 2014 Ok, A Real Business Plan Ingest Store Process Analyze
    • AWS Gaming Solutions | GDC 2014 Ok, A Real Business Plan Ingest • HTTP PUT • Kafka • Kinesis • Scribe Store • S3 • DynamoDB • HDFS • Redshift Process • EMR (Hadoop) • Spark • Storm Analyze • Tableau • Pentaho • Jaspersoft
    • AWS Gaming Solutions | GDC 2014 • Write Events File on Device • Periodically Upload to S3 • Process into Redshift • Point GUI Tool to Redshift Start Simple 2014-01-24,nateware,e4df,login 2014-01-24,nateware,e4df,gamestart 2014-01-24,nateware,e4df,gameend 2014-01-25,nateware,a88c,login 2014-01- 25,nateware,a88c,friendlist 2014-01-25,nateware,a88c,gamestart Profit!
    • AWS Gaming Solutions | GDC 2014 Redshift at a Glance 10 GigE (HPC) Ingestion Backup Restore JDBC/ODBC • Leader Node – SQL endpoint – Stores metadata – Coordinates query execution • Compute Nodes – Columnar table storage – Load, backup, restore via Amazon S3 – Parallel load from Amazon DynamoDB • Single node version available
    • AWS Gaming Solutions | GDC 2014 Tableau + Redshift
    • AWS Gaming Solutions | GDC 2014 Plumbing ① Create S3 bucket ("mygame-analytics-events") ② Request a security token for your mobile app: http://docs.aws.amazon.com/STS/latest/UsingSTS/Welcome.html ③ Upload data from your users' devices ④ Run a scheduled copy to Redshift ⑤ Setup Tableau to access Redshift ⑥ Go to the Beach
    • AWS Gaming Solutions | GDC 2014 Loading Redshift from S3 copy events from 's3://mygame-analytics-events' credentials 'aws_access_key_id=<access-key-id>; aws_secret_access_key=<secret-access-key>' delimiter=','; Scheduled Redshift Load using Data Pipeline: http://aws.amazon.com/articles/1143507459230804
    • AWS Gaming Solutions | GDC 2014 • Also Collect Server Logs • Periodically Upload to S3 • Stuff into Redshift • External Analytics Data Too More Data Sources EC2 External Analytics
    • AWS Gaming Solutions | GDC 2014 Logrotate to S3 /var/log/apache2/*.log { sharedscripts postrotate sudo /usr/sbin/apache2ctl graceful s3cmd sync /var/log/*.gz s3://mygame-logs/ endscript } Blog Entry on Log Rotation: http://www.dowdandassociates.com/blog/content/howto-rotate-logs-to-s3/ And/or, Use ELB Access Logs: http://docs.aws.amazon.com/ElasticLoadBalancing/latest/DeveloperGuide/acce ss-log-collection.html
    • AWS Gaming Solutions | GDC 2014 • Different File Formats • Device vs Apache vs CDN • Cleanup with EMR Job • Output to Clean Bucket • Load into Redshift Dealing With Messy Data EC2
    • AWS Gaming Solutions | GDC 2014 Redshift vs Elastic MapReduce Redshift • Columnar DB • Familiar SQL • Structured Data • Batch Load • Faster to Query • Long-term Storage Elastic MapReduce • Hadoop • Hive/Pig are SQL-like • Unstructured Data • Streaming Loop • Scales > PB's • Transient
    • AWS Gaming Solutions | GDC 2014 • Integrate Game DB • Load Directly into Redshift • Redshift does Intelligent Merge • Tracks Hash Keys, Columns Direct From DynamoDB EC2
    • AWS Gaming Solutions | GDC 2014 • Integrate Game DB • Load Directly into Redshift • Redshift does Intelligent Merge • Tracks Hash Keys, Columns • Or Stream into EMR Direct From DynamoDB EC2
    • AWS Gaming Solutions | GDC 2014 Loading Redshift from DynamoDB copy games from 'dynamodb://games' credentials 'aws_access_key_id=<access-key-id>; aws_secret_access_key=<secret-access-key>'; copy events from 's3://mygame-analytics-events' credentials 'aws_access_key_id=<access-key-id>; aws_secret_access_key=<secret-access-key>' delimiter=',';
    • AWS Gaming Solutions | GDC 2014
    • AWS Gaming Solutions | GDC 2014 Funnel Cake
    • AWS Gaming Solutions | GDC 2014 Back To Basics 2014-01-24,nateware,e4df,login 2014-01-24,nateware,e4df,gamestart 2014-01-24,nateware,e4df,gameend 2014-01-25,nateware,a88c,login 2014-01- 25,nateware,a88c,friendlist 2014-01-25,nateware,a88c,gamestart
    • AWS Gaming Solutions | GDC 2014 Measure Retention: Repeated Plays create view events_by_user_by_month as select user_id, date_trunc('month', event_date) as month_active, count(*) as total_events from events group by user_id, month_active;
    • AWS Gaming Solutions | GDC 2014 First-Pass Retention – Too Noisy 0 5 10 15 20 25 30 35 40 # Play Sessions / Month nateware Lazyd0g AK187 3strikes
    • AWS Gaming Solutions | GDC 2014 Cohorts & Cambria • Enables calculating relative metrics • Group users by a common attribute – Month game installed – Demographics • Run analysis by cohort – Join with metrics • Use Redshift as it's SQL – Example of where SQL is a good fit
    • AWS Gaming Solutions | GDC 2014 Creating Cohorts with Redshift create view cohort_by_first_event_date as select user_id, date_trunc('month', min(event_date)) as first_month from events group by user_id; http://snowplowanalytics.com/analytics/customer- analytics/cohort-analysis.html
    • AWS Gaming Solutions | GDC 2014 Retention by Cohort – Join Events with Cohort 0 5 10 15 20 25 Week 1 Week 2 Week 3 Week 5 Week 6 Week 7 # Sessions / Week 2013-11 2013-12 2014-01 2014-02 2014-03 2014-04
    • AWS Gaming Solutions | GDC 2014 Moar Cohorts • Define multiple cohorts – By activity, time, demographics – As many as you like • Change cohort depending on analysis • Join same metrics with different cohorts – Retention by date – Retention by demographic – Retention by average plays/month quartile
    • AWS Gaming Solutions | GDC 2014 Example Event Stream 2014-03-17T09:52:08-07:00,nateware,e4b5,login 2014-03-17T09:52:54-07:00,nateware,e4b5,gamestart 2014-03-17T09:53:15-07:00,nateware,e4b5,levelup 2014-03-17T09:54:06-07:00,nateware,e4b5,gameend 2014-03-17T09:54:23-07:00,nateware,30a4,gamestart 2014-03-17T09:55:14-07:00,nateware,30a4,gameend 2014-03-17T09:55:41-07:00,nateware,30a4,gamestart 2014-03-17T09:57:12-07:00,nateware,6ebd,levelup 2014-03-17T09:58:50-07:00,nateware,6ebd,levelup 2014-03-17T09:59:52-07:00,nateware,6ebd,gameend
    • AWS Gaming Solutions | GDC 2014 Example Event Stream 2014-03-17T09:52:08-07:00,nateware,e4b5,login 2014-03-17T09:52:54-07:00,nateware,e4b5,gamestart 2014-03-17T09:53:15-07:00,nateware,e4b5,levelup 2014-03-17T09:54:06-07:00,nateware,e4b5,gameend 2014-03-17T09:54:23-07:00,nateware,30a4,gamestart 2014-03-17T09:55:14-07:00,nateware,30a4,gameend 2014-03-17T09:55:41-07:00,nateware,30a4,gamestart 2014-03-17T09:57:12-07:00,nateware,6ebd,levelup 2014-03-17T09:58:50-07:00,nateware,6ebd,levelup 2014-03-17T09:59:52-07:00,nateware,6ebd,gameend
    • AWS Gaming Solutions | GDC 2014 Cohorts by Type of Activity create view cohort_by_first_play_date as select user_id, date_trunc('month', min(event_date)) as first_month from events where action = 'gamestart' group by user_id;
    • AWS Gaming Solutions | GDC 2014
    • AWS Gaming Solutions | GDC 2014 Post-Match Heatmaps
    • AWS Gaming Solutions | GDC 2014 Real-Time Analytics Batch • What game modes do people like best? • How many people have downloaded DLC pack 2? • Where do most people die on map 4? • How many daily players are there on average? Real-Time • What game modes are people playing now? • Are more or less people downloading DLC today? • Are people dying in the same places? Different? • How many people are playing today? Variance?
    • AWS Gaming Solutions | GDC 2014 Why Real-Time Analytics? 30x in 24 hours What if you ran a promo?
    • AWS Gaming Solutions | GDC 2014 Real-Time Tools Spark • High-Performance Hadoop Alternative • Berkeley.edu • Compatible with HiveQL • 100x faster than Hadoop • Runs on EMR Kinesis • Amazon fully-managed streaming data layer • Similar to Kafka • Streams contain Shards • Each Shard ingests data up to 1MB/sec, 1000 TPS • Data stored for 24 hours
    • AWS Gaming Solutions | GDC 2014 • Always Batch Due to S3 Back To Basics [Dubstep Remix] EC2
    • AWS Gaming Solutions | GDC 2014 • Stream Data With Kinesis • Multiple Writers and Readers • Still Output to Redshift Need Data Faster! EC2
    • AWS Gaming Solutions | GDC 2014 • Stream Data With Kinesis • Multiple Writers and Readers • Still Output to Redshift • Stream to Spark on EMR • Storm via Kinesis Spout • Custom EC2 Workers Lots of Ins and Outs EC2 EC2
    • AWS Gaming Solutions | GDC 2014 Data Sources App.4 [Machine Learning] AWSEndpoint App.1 [Aggregate & De-Duplicate] Data Sources Data Sources Data Sources App.2 [Metric Extraction] S3 DynamoDB Redshift App.3 [Sliding Window Analysis] Data Sources Availability Zone Shard 1 Shard 2 Shard N Availability Zone Availability Zone Introducing Amazon Kinesis Service for Real-Time Big Data Ingestion
    • AWS Gaming Solutions | GDC 2014 Putting Data into Kinesis • Producers use PUT to send data to a Stream • PutRecord {Data, PartitionKey, StreamName} • Partition Key distributes PUTs across Shards • Unique Sequence # returned on PUT call • Documentation: http://docs.aws.amazon.com/kinesis/latest/dev/ introduction.html
    • AWS Gaming Solutions | GDC 2014 Writing to a Kinesis Stream POST / HTTP/1.1 Host: kinesis.<region>.<domain> x-amz-Date: <Date> Authorization: AWS4-HMAC-SHA256 Credential=<Credential>, SignedHeaders=content- type;date;host;user-agent;x-amz-date;x-amz-target;x-amzn-requestid, Signature=<Signature> User-Agent: <UserAgentString> Content-Type: application/x-amz-json-1.1 Content-Length: <PayloadSizeBytes> Connection: Keep-Alive X-Amz-Target: Kinesis_20131202.PutRecord { "StreamName": "exampleStreamName", "Data": "XzxkYXRhPl8x", "PartitionKey": "partitionKey" }
    • AWS Gaming Solutions | GDC 2014 Kinesis + Spark http://aws.amazon.com/articles/4926593393724923
    • AWS Gaming Solutions | GDC 2014 Death in Real-Time PUT "kills" {"game_id":"e4b5","map":"Boston","killer":38,"victim":39,"coord":"274,591,48"} PUT "kills" {"game_id":"e4b5","map":"Boston","killer":13,"victim":27,"coord":"101,206,35"} PUT "kills" {"game_id":"e4b5","map":"Boston","killer":38,"victim":39,"coord":"165,609,17"} PUT "kills" {"game_id":"e4b5","map":"Boston","killer":6,"victim":29,"coord":"120,422,26"} PUT "kills" {"game_id":"30a4","map":"Los Angeles","killer":34,"victim":18,"coord":"163,677,18"} PUT "kills" {"game_id":"30a4","map":"Los Angeles","killer":20,"victim":37,"coord":"71,473,20"} PUT "kills" {"game_id":"30a4","map":"Los Angeles","killer":21,"victim":19,"coord":"332,381,17"} PUT "kills" {"game_id":"30a4","map":"Los Angeles","killer":0,"victim":10,"coord":"14,108,25"} PUT "kills" {"game_id":"6ebd","map":"Seattle","killer":32,"victim":18,"coord":"13,685,32"} PUT "kills" {"game_id":"6ebd","map":"Seattle","killer":7,"victim":14,"coord":"16,233,16"} PUT "kills" {"game_id":"6ebd","map":"Seattle","killer":27,"victim":19,"coord":"16,498,29"} PUT "kills" {"game_id":"6ebd","map":"Seattle","killer":1,"victim":38,"coord":"138,732,21"}
    • AWS Gaming Solutions | GDC 2014 Real-Time Heatmaps
    • AWS Gaming Solutions | GDC 2014 But A Bow On It • Collect data from the start • Store it even if you can't process it (yet) • Start simple – S3 + Redshift • Add data sources – process with EMR • Real-time – Kinesis + Spark • Tons of untapped potential for gaming
    • AWS Gaming Solutions | GDC 2014 Fallback Plan Cheers – Nate Wiger @nateware