SlideShare ist ein Scribd-Unternehmen logo

How to scale your web app

•Als PPT, PDF herunterladen•
•
G
Georgio_1999

Scaling web applications, as present at Barcamp London 2 by George Palmer

Technologie
1 von 25
How to scale (with ruby on rails) George Palmer [email_address] 3dogsbark.com
Overview ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
How you start out ,[object Object],[object Object],[object Object],[object Object],DB Web Server Shared Hosting
Two servers ,[object Object],[object Object],[object Object],[object Object],DB Web Server
Scaling the database (1) ,[object Object],[object Object],[object Object],Master DB Web Server Slave Slave Slave
Scaling the database (2) ,[object Object],[object Object],[object Object],Master DB Web Server Master DB MySQL Cluster
Scaling the web server ,[object Object],DB Farm Worker thread Worker thread Worker thread Worker thread Web Server
Load balancing ,[object Object],[object Object],[object Object],[object Object],[object Object],DB Farm App Server App Server App Server Load balancer
The story so far… ,[object Object],App Server App Server App Server Load balancer Master DB Slave Slave Slave
User Clusters ,[object Object],[object Object],[object Object],[object Object]
User Clusters (2) App Server Master DB User Cluster 1 User Cluster 2 User clusters are themselves one of the two database setups outlined earlier SELECT * FROM users WHERE username=‘Bob’ AND … user_id=91732db_cluster=2
User Clusters (3) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The final architecture ,[object Object],[object Object],[object Object],[object Object],[object Object]
The final architecture (2) Load balancer Master DB App Server 1 App Server 2 App Server 50 … DB Connection Manager Master DB Session DB Search DB NLS DB Master Slave Slave Slave Master Slave Slave Slave User Cluster 2 User Cluster 1 NFS/SAN
Issues ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Making the most of your assets ,[object Object],[object Object],[object Object],[object Object],[object Object]
Squid ,[object Object],[object Object],[object Object],Squid App Server 1 App Server 2 NFS/SAN In cache Not in cache …
Memcached ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],App Server DB Farm Memcached Physical Machine App Server Memcached Physical Machine (Not in memcached)
Cached Architecture ,[object Object],[object Object],[object Object],[object Object],[object Object]
Cached architecture Squid Master DB App Server 1 App Server 2 App Server 50 … DB Connection Manager Master DB Session DB Search DB NLS DB Master Slave Slave Slave Master Slave Slave Slave User Cluster 2 User Cluster 1 NFS/SAN M C M C M C MC=memcached
Cached architecture ,[object Object],[object Object],[object Object],[object Object]
Cached architecture – 1 machine Squid Master DB App Server 1 App Server 2 App Server 5 … DB Connection Manager Master DB Session DB Search DB NLS DB Master Slave Slave Slave User Cluster 1 NFS/SAN Memcached Physical Machine
How far can it go? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Useful Links ,[object Object],[object Object],[object Object],[object Object]
Questions?

Empfohlen

Cassandra & puppet, scaling data at $15 per month
Cassandra & puppet, scaling data at $15 per monthCassandra & puppet, scaling data at $15 per month
Cassandra & puppet, scaling data at $15 per monthdaveconnors
 
High Concurrency Architecture and Laravel Performance Tuning
High Concurrency Architecture and Laravel Performance TuningHigh Concurrency Architecture and Laravel Performance Tuning
High Concurrency Architecture and Laravel Performance TuningAlbert Chen
 
Real-time Data Pipeline: Kafka Streams / Kafka Connect versus Spark Streaming
Real-time Data Pipeline: Kafka Streams / Kafka Connect versus Spark StreamingReal-time Data Pipeline: Kafka Streams / Kafka Connect versus Spark Streaming
Real-time Data Pipeline: Kafka Streams / Kafka Connect versus Spark StreamingAbdelhamide EL ARIB
 
Kafka Multi-Tenancy - 160 Billion Daily Messages on One Shared Cluster at LINE
Kafka Multi-Tenancy - 160 Billion Daily Messages on One Shared Cluster at LINEKafka Multi-Tenancy - 160 Billion Daily Messages on One Shared Cluster at LINE
Kafka Multi-Tenancy - 160 Billion Daily Messages on One Shared Cluster at LINEkawamuray
 
HBaseConEast2016: Coprocessors – Uses, Abuses and Solutions
HBaseConEast2016: Coprocessors – Uses, Abuses and SolutionsHBaseConEast2016: Coprocessors – Uses, Abuses and Solutions
HBaseConEast2016: Coprocessors – Uses, Abuses and SolutionsMichael Stack
 
Introducing HerdDB - a distributed JVM embeddable database built upon Apache ...
Introducing HerdDB - a distributed JVM embeddable database built upon Apache ...Introducing HerdDB - a distributed JVM embeddable database built upon Apache ...
Introducing HerdDB - a distributed JVM embeddable database built upon Apache ...StreamNative
 
Operational Tips for Deploying Spark by Miklos Christine
Operational Tips for Deploying Spark by Miklos ChristineOperational Tips for Deploying Spark by Miklos Christine
Operational Tips for Deploying Spark by Miklos ChristineSpark Summit
 
MySQL Live Migration - Common Scenarios
MySQL Live Migration - Common ScenariosMySQL Live Migration - Common Scenarios
MySQL Live Migration - Common ScenariosMydbops
 

Empfohlen

Cassandra & puppet, scaling data at $15 per month
Cassandra & puppet, scaling data at $15 per monthCassandra & puppet, scaling data at $15 per month
Cassandra & puppet, scaling data at $15 per monthdaveconnors
 
High Concurrency Architecture and Laravel Performance Tuning
High Concurrency Architecture and Laravel Performance TuningHigh Concurrency Architecture and Laravel Performance Tuning
High Concurrency Architecture and Laravel Performance TuningAlbert Chen
 
Real-time Data Pipeline: Kafka Streams / Kafka Connect versus Spark Streaming
Real-time Data Pipeline: Kafka Streams / Kafka Connect versus Spark StreamingReal-time Data Pipeline: Kafka Streams / Kafka Connect versus Spark Streaming
Real-time Data Pipeline: Kafka Streams / Kafka Connect versus Spark StreamingAbdelhamide EL ARIB
 
Kafka Multi-Tenancy - 160 Billion Daily Messages on One Shared Cluster at LINE
Kafka Multi-Tenancy - 160 Billion Daily Messages on One Shared Cluster at LINEKafka Multi-Tenancy - 160 Billion Daily Messages on One Shared Cluster at LINE
Kafka Multi-Tenancy - 160 Billion Daily Messages on One Shared Cluster at LINEkawamuray
 
HBaseConEast2016: Coprocessors – Uses, Abuses and Solutions
HBaseConEast2016: Coprocessors – Uses, Abuses and SolutionsHBaseConEast2016: Coprocessors – Uses, Abuses and Solutions
HBaseConEast2016: Coprocessors – Uses, Abuses and SolutionsMichael Stack
 
Introducing HerdDB - a distributed JVM embeddable database built upon Apache ...
Introducing HerdDB - a distributed JVM embeddable database built upon Apache ...Introducing HerdDB - a distributed JVM embeddable database built upon Apache ...
Introducing HerdDB - a distributed JVM embeddable database built upon Apache ...StreamNative
 
Operational Tips for Deploying Spark by Miklos Christine
Operational Tips for Deploying Spark by Miklos ChristineOperational Tips for Deploying Spark by Miklos Christine
Operational Tips for Deploying Spark by Miklos ChristineSpark Summit
 
MySQL Live Migration - Common Scenarios
MySQL Live Migration - Common ScenariosMySQL Live Migration - Common Scenarios
MySQL Live Migration - Common ScenariosMydbops
 
(ARC204) Architecting Microsoft Workloads on AWS | AWS re:Invent 2014
(ARC204) Architecting Microsoft Workloads on AWS | AWS re:Invent 2014(ARC204) Architecting Microsoft Workloads on AWS | AWS re:Invent 2014
(ARC204) Architecting Microsoft Workloads on AWS | AWS re:Invent 2014Amazon Web Services
 
Kafka meetup JP #3 - Engineering Apache Kafka at LINE
Kafka meetup JP #3 - Engineering Apache Kafka at LINEKafka meetup JP #3 - Engineering Apache Kafka at LINE
Kafka meetup JP #3 - Engineering Apache Kafka at LINEkawamuray
 
How To Scale v2
How To Scale v2How To Scale v2
How To Scale v2Georgio_1999
 
Apache Drill (ver. 0.1, check ver. 0.2)
Apache Drill (ver. 0.1, check ver. 0.2)Apache Drill (ver. 0.1, check ver. 0.2)
Apache Drill (ver. 0.1, check ver. 0.2)Camuel Gilyadov
 
What is apache Kafka?
What is apache Kafka?What is apache Kafka?
What is apache Kafka?Kenny Gorman
 
PostgreSQL Replication High Availability Methods
PostgreSQL Replication High Availability MethodsPostgreSQL Replication High Availability Methods
PostgreSQL Replication High Availability MethodsMydbops
 
Webinar: Deep Dive on Apache Flink State - Seth Wiesman
Webinar: Deep Dive on Apache Flink State - Seth WiesmanWebinar: Deep Dive on Apache Flink State - Seth Wiesman
Webinar: Deep Dive on Apache Flink State - Seth WiesmanVerverica
 
Sun Web Server Brief
Sun Web Server BriefSun Web Server Brief
Sun Web Server BriefMurthy Chintalapati
 
Presto Testing Tools: Benchto & Tempto (Presto Boston Meetup 10062015)
Presto Testing Tools: Benchto & Tempto (Presto Boston Meetup 10062015)Presto Testing Tools: Benchto & Tempto (Presto Boston Meetup 10062015)
Presto Testing Tools: Benchto & Tempto (Presto Boston Meetup 10062015)Matt Fuller
 
Semantic Search Engines
Semantic Search EnginesSemantic Search Engines
Semantic Search EnginesAtul Shridhar
 
What is the State of my Kafka Streams Application? Unleashing Metrics. | Neil...
What is the State of my Kafka Streams Application? Unleashing Metrics. | Neil...What is the State of my Kafka Streams Application? Unleashing Metrics. | Neil...
What is the State of my Kafka Streams Application? Unleashing Metrics. | Neil...HostedbyConfluent
 
Repository performance tuning
Repository performance tuningRepository performance tuning
Repository performance tuningJukka Zitting
 
London Apache Kafka Meetup (Jan 2017)
London Apache Kafka Meetup (Jan 2017)London Apache Kafka Meetup (Jan 2017)
London Apache Kafka Meetup (Jan 2017)Landoop Ltd
 
One Tool to Rule Them All- Seamless SQL on MongoDB, MySQL and Redis with Apac...
One Tool to Rule Them All- Seamless SQL on MongoDB, MySQL and Redis with Apac...One Tool to Rule Them All- Seamless SQL on MongoDB, MySQL and Redis with Apac...
One Tool to Rule Them All- Seamless SQL on MongoDB, MySQL and Redis with Apac...Tim Vaillancourt
 
MySQL shell and It's utilities - Praveen GR (Mydbops Team)
MySQL shell and It's utilities - Praveen GR (Mydbops Team)MySQL shell and It's utilities - Praveen GR (Mydbops Team)
MySQL shell and It's utilities - Praveen GR (Mydbops Team)Mydbops
 
hbaseconasia2017: Large scale data near-line loading method and architecture
hbaseconasia2017: Large scale data near-line loading method and architecturehbaseconasia2017: Large scale data near-line loading method and architecture
hbaseconasia2017: Large scale data near-line loading method and architectureHBaseCon
 
Highlights Of Sqoop2
Highlights Of Sqoop2Highlights Of Sqoop2
Highlights Of Sqoop2Alexander Alten-Lorenz
 
Presto on Apache Spark: A Tale of Two Computation Engines
Presto on Apache Spark: A Tale of Two Computation EnginesPresto on Apache Spark: A Tale of Two Computation Engines
Presto on Apache Spark: A Tale of Two Computation EnginesDatabricks
 
HBaseCon2017 Removable singularity: a story of HBase upgrade in Pinterest
HBaseCon2017 Removable singularity: a story of HBase upgrade in PinterestHBaseCon2017 Removable singularity: a story of HBase upgrade in Pinterest
HBaseCon2017 Removable singularity: a story of HBase upgrade in PinterestHBaseCon
 
Kafka Connect
Kafka ConnectKafka Connect
Kafka ConnectOleg Kuznetsov
 
Методики «Inversion of Control» и «Dependency Injection». Применение в Spring.
Методики «Inversion of Control» и «Dependency Injection». Применение в Spring.Методики «Inversion of Control» и «Dependency Injection». Применение в Spring.
Методики «Inversion of Control» и «Dependency Injection». Применение в Spring.Fedor Malyshkin
 
Принципы Solid на практике
Принципы Solid на практикеПринципы Solid на практике
Принципы Solid на практикеEatDog
 

Weitere ähnliche Inhalte

Was ist angesagt?

(ARC204) Architecting Microsoft Workloads on AWS | AWS re:Invent 2014
(ARC204) Architecting Microsoft Workloads on AWS | AWS re:Invent 2014(ARC204) Architecting Microsoft Workloads on AWS | AWS re:Invent 2014
(ARC204) Architecting Microsoft Workloads on AWS | AWS re:Invent 2014Amazon Web Services
 
Kafka meetup JP #3 - Engineering Apache Kafka at LINE
Kafka meetup JP #3 - Engineering Apache Kafka at LINEKafka meetup JP #3 - Engineering Apache Kafka at LINE
Kafka meetup JP #3 - Engineering Apache Kafka at LINEkawamuray
 
Apache Drill (ver. 0.1, check ver. 0.2)
Apache Drill (ver. 0.1, check ver. 0.2)Apache Drill (ver. 0.1, check ver. 0.2)
Apache Drill (ver. 0.1, check ver. 0.2)Camuel Gilyadov
 
What is apache Kafka?
What is apache Kafka?What is apache Kafka?
What is apache Kafka?Kenny Gorman
 
PostgreSQL Replication High Availability Methods
PostgreSQL Replication High Availability MethodsPostgreSQL Replication High Availability Methods
PostgreSQL Replication High Availability MethodsMydbops
 
Webinar: Deep Dive on Apache Flink State - Seth Wiesman
Webinar: Deep Dive on Apache Flink State - Seth WiesmanWebinar: Deep Dive on Apache Flink State - Seth Wiesman
Webinar: Deep Dive on Apache Flink State - Seth WiesmanVerverica
 
Presto Testing Tools: Benchto & Tempto (Presto Boston Meetup 10062015)
Presto Testing Tools: Benchto & Tempto (Presto Boston Meetup 10062015)Presto Testing Tools: Benchto & Tempto (Presto Boston Meetup 10062015)
Presto Testing Tools: Benchto & Tempto (Presto Boston Meetup 10062015)Matt Fuller
 
Semantic Search Engines
Semantic Search EnginesSemantic Search Engines
Semantic Search EnginesAtul Shridhar
 
What is the State of my Kafka Streams Application? Unleashing Metrics. | Neil...
What is the State of my Kafka Streams Application? Unleashing Metrics. | Neil...What is the State of my Kafka Streams Application? Unleashing Metrics. | Neil...
What is the State of my Kafka Streams Application? Unleashing Metrics. | Neil...HostedbyConfluent
 
Repository performance tuning
Repository performance tuningRepository performance tuning
Repository performance tuningJukka Zitting
 
London Apache Kafka Meetup (Jan 2017)
London Apache Kafka Meetup (Jan 2017)London Apache Kafka Meetup (Jan 2017)
London Apache Kafka Meetup (Jan 2017)Landoop Ltd
 
One Tool to Rule Them All- Seamless SQL on MongoDB, MySQL and Redis with Apac...
One Tool to Rule Them All- Seamless SQL on MongoDB, MySQL and Redis with Apac...One Tool to Rule Them All- Seamless SQL on MongoDB, MySQL and Redis with Apac...
One Tool to Rule Them All- Seamless SQL on MongoDB, MySQL and Redis with Apac...Tim Vaillancourt
 
MySQL shell and It's utilities - Praveen GR (Mydbops Team)
MySQL shell and It's utilities - Praveen GR (Mydbops Team)MySQL shell and It's utilities - Praveen GR (Mydbops Team)
MySQL shell and It's utilities - Praveen GR (Mydbops Team)Mydbops
 
hbaseconasia2017: Large scale data near-line loading method and architecture
hbaseconasia2017: Large scale data near-line loading method and architecturehbaseconasia2017: Large scale data near-line loading method and architecture
hbaseconasia2017: Large scale data near-line loading method and architectureHBaseCon
 
Presto on Apache Spark: A Tale of Two Computation Engines
Presto on Apache Spark: A Tale of Two Computation EnginesPresto on Apache Spark: A Tale of Two Computation Engines
Presto on Apache Spark: A Tale of Two Computation EnginesDatabricks
 
HBaseCon2017 Removable singularity: a story of HBase upgrade in Pinterest
HBaseCon2017 Removable singularity: a story of HBase upgrade in PinterestHBaseCon2017 Removable singularity: a story of HBase upgrade in Pinterest
HBaseCon2017 Removable singularity: a story of HBase upgrade in PinterestHBaseCon
 

Was ist angesagt? (20)

(ARC204) Architecting Microsoft Workloads on AWS | AWS re:Invent 2014
(ARC204) Architecting Microsoft Workloads on AWS | AWS re:Invent 2014(ARC204) Architecting Microsoft Workloads on AWS | AWS re:Invent 2014
(ARC204) Architecting Microsoft Workloads on AWS | AWS re:Invent 2014
 
Kafka meetup JP #3 - Engineering Apache Kafka at LINE
Kafka meetup JP #3 - Engineering Apache Kafka at LINEKafka meetup JP #3 - Engineering Apache Kafka at LINE
Kafka meetup JP #3 - Engineering Apache Kafka at LINE
 
How To Scale v2
How To Scale v2How To Scale v2
How To Scale v2
 
Apache Drill (ver. 0.1, check ver. 0.2)
Apache Drill (ver. 0.1, check ver. 0.2)Apache Drill (ver. 0.1, check ver. 0.2)
Apache Drill (ver. 0.1, check ver. 0.2)
 
What is apache Kafka?
What is apache Kafka?What is apache Kafka?
What is apache Kafka?
 
PostgreSQL Replication High Availability Methods
PostgreSQL Replication High Availability MethodsPostgreSQL Replication High Availability Methods
PostgreSQL Replication High Availability Methods
 
Webinar: Deep Dive on Apache Flink State - Seth Wiesman
Webinar: Deep Dive on Apache Flink State - Seth WiesmanWebinar: Deep Dive on Apache Flink State - Seth Wiesman
Webinar: Deep Dive on Apache Flink State - Seth Wiesman
 
Sun Web Server Brief
Sun Web Server BriefSun Web Server Brief
Sun Web Server Brief
 
Presto Testing Tools: Benchto & Tempto (Presto Boston Meetup 10062015)
Presto Testing Tools: Benchto & Tempto (Presto Boston Meetup 10062015)Presto Testing Tools: Benchto & Tempto (Presto Boston Meetup 10062015)
Presto Testing Tools: Benchto & Tempto (Presto Boston Meetup 10062015)
 
Semantic Search Engines
Semantic Search EnginesSemantic Search Engines
Semantic Search Engines
 
What is the State of my Kafka Streams Application? Unleashing Metrics. | Neil...
What is the State of my Kafka Streams Application? Unleashing Metrics. | Neil...What is the State of my Kafka Streams Application? Unleashing Metrics. | Neil...
What is the State of my Kafka Streams Application? Unleashing Metrics. | Neil...
 
Repository performance tuning
Repository performance tuningRepository performance tuning
Repository performance tuning
 
London Apache Kafka Meetup (Jan 2017)
London Apache Kafka Meetup (Jan 2017)London Apache Kafka Meetup (Jan 2017)
London Apache Kafka Meetup (Jan 2017)
 
One Tool to Rule Them All- Seamless SQL on MongoDB, MySQL and Redis with Apac...
One Tool to Rule Them All- Seamless SQL on MongoDB, MySQL and Redis with Apac...One Tool to Rule Them All- Seamless SQL on MongoDB, MySQL and Redis with Apac...
One Tool to Rule Them All- Seamless SQL on MongoDB, MySQL and Redis with Apac...
 
MySQL shell and It's utilities - Praveen GR (Mydbops Team)
MySQL shell and It's utilities - Praveen GR (Mydbops Team)MySQL shell and It's utilities - Praveen GR (Mydbops Team)
MySQL shell and It's utilities - Praveen GR (Mydbops Team)
 
hbaseconasia2017: Large scale data near-line loading method and architecture
hbaseconasia2017: Large scale data near-line loading method and architecturehbaseconasia2017: Large scale data near-line loading method and architecture
hbaseconasia2017: Large scale data near-line loading method and architecture
 
Highlights Of Sqoop2
Highlights Of Sqoop2Highlights Of Sqoop2
Highlights Of Sqoop2
 
Presto on Apache Spark: A Tale of Two Computation Engines
Presto on Apache Spark: A Tale of Two Computation EnginesPresto on Apache Spark: A Tale of Two Computation Engines
Presto on Apache Spark: A Tale of Two Computation Engines
 
HBaseCon2017 Removable singularity: a story of HBase upgrade in Pinterest
HBaseCon2017 Removable singularity: a story of HBase upgrade in PinterestHBaseCon2017 Removable singularity: a story of HBase upgrade in Pinterest
HBaseCon2017 Removable singularity: a story of HBase upgrade in Pinterest
 
Kafka Connect
Kafka ConnectKafka Connect
Kafka Connect
 

Andere mochten auch

Методики «Inversion of Control» и «Dependency Injection». Применение в Spring.
Методики «Inversion of Control» и «Dependency Injection». Применение в Spring.Методики «Inversion of Control» и «Dependency Injection». Применение в Spring.
Методики «Inversion of Control» и «Dependency Injection». Применение в Spring.Fedor Malyshkin
 
Принципы Solid на практике
Принципы Solid на практикеПринципы Solid на практике
Принципы Solid на практикеEatDog
 
Best Practices Scaling Web Application Up to Your First 10 Million Users
Best Practices Scaling Web Application Up to Your First 10 Million UsersBest Practices Scaling Web Application Up to Your First 10 Million Users
Best Practices Scaling Web Application Up to Your First 10 Million UsersAmazon Web Services
 
Принципы объектно-ориентированного дизайна
Принципы объектно-ориентированного дизайнаПринципы объектно-ориентированного дизайна
Принципы объектно-ориентированного дизайнаСергей Шебанин
 
Принципы проектирования S.O.L.I.D
Принципы проектирования S.O.L.I.DПринципы проектирования S.O.L.I.D
Принципы проектирования S.O.L.I.DAndreyGeonya
 
Deep Dive: Scaling Up to Your First 10 Million Users
Deep Dive: Scaling Up to Your First 10 Million UsersDeep Dive: Scaling Up to Your First 10 Million Users
Deep Dive: Scaling Up to Your First 10 Million UsersAmazon Web Services
 
(DVO201) Scaling Your Web Applications with AWS Elastic Beanstalk
(DVO201) Scaling Your Web Applications with AWS Elastic Beanstalk(DVO201) Scaling Your Web Applications with AWS Elastic Beanstalk
(DVO201) Scaling Your Web Applications with AWS Elastic BeanstalkAmazon Web Services
 
7 Stages of Scaling Web Applications
7 Stages of Scaling Web Applications7 Stages of Scaling Web Applications
7 Stages of Scaling Web ApplicationsDavid Mitzenmacher
 
Diagnosing Technical Issues With Search Engine Optimization
Diagnosing Technical Issues With Search Engine OptimizationDiagnosing Technical Issues With Search Engine Optimization
Diagnosing Technical Issues With Search Engine OptimizationNine By Blue
 
Web scale IT - Nutanix
Web scale IT - NutanixWeb scale IT - Nutanix
Web scale IT - NutanixUnitiv
 
Introduction to Web Architecture
Introduction to Web ArchitectureIntroduction to Web Architecture
Introduction to Web ArchitectureChamnap Chhorn
 
Architecture of a Modern Web App
Architecture of a Modern Web AppArchitecture of a Modern Web App
Architecture of a Modern Web Appscothis
 

Andere mochten auch (12)

Методики «Inversion of Control» и «Dependency Injection». Применение в Spring.
Методики «Inversion of Control» и «Dependency Injection». Применение в Spring.Методики «Inversion of Control» и «Dependency Injection». Применение в Spring.
Методики «Inversion of Control» и «Dependency Injection». Применение в Spring.
 
Принципы Solid на практике
Принципы Solid на практикеПринципы Solid на практике
Принципы Solid на практике
 
Best Practices Scaling Web Application Up to Your First 10 Million Users
Best Practices Scaling Web Application Up to Your First 10 Million UsersBest Practices Scaling Web Application Up to Your First 10 Million Users
Best Practices Scaling Web Application Up to Your First 10 Million Users
 
Принципы объектно-ориентированного дизайна
Принципы объектно-ориентированного дизайнаПринципы объектно-ориентированного дизайна
Принципы объектно-ориентированного дизайна
 
Принципы проектирования S.O.L.I.D
Принципы проектирования S.O.L.I.DПринципы проектирования S.O.L.I.D
Принципы проектирования S.O.L.I.D
 
Deep Dive: Scaling Up to Your First 10 Million Users
Deep Dive: Scaling Up to Your First 10 Million UsersDeep Dive: Scaling Up to Your First 10 Million Users
Deep Dive: Scaling Up to Your First 10 Million Users
 
(DVO201) Scaling Your Web Applications with AWS Elastic Beanstalk
(DVO201) Scaling Your Web Applications with AWS Elastic Beanstalk(DVO201) Scaling Your Web Applications with AWS Elastic Beanstalk
(DVO201) Scaling Your Web Applications with AWS Elastic Beanstalk
 
7 Stages of Scaling Web Applications
7 Stages of Scaling Web Applications7 Stages of Scaling Web Applications
7 Stages of Scaling Web Applications
 
Diagnosing Technical Issues With Search Engine Optimization
Diagnosing Technical Issues With Search Engine OptimizationDiagnosing Technical Issues With Search Engine Optimization
Diagnosing Technical Issues With Search Engine Optimization
 
Web scale IT - Nutanix
Web scale IT - NutanixWeb scale IT - Nutanix
Web scale IT - Nutanix
 
Introduction to Web Architecture
Introduction to Web ArchitectureIntroduction to Web Architecture
Introduction to Web Architecture
 
Architecture of a Modern Web App
Architecture of a Modern Web AppArchitecture of a Modern Web App
Architecture of a Modern Web App
 

Ähnlich wie How to scale your web app

Handling Data in Mega Scale Systems
Handling Data in Mega Scale SystemsHandling Data in Mega Scale Systems
Handling Data in Mega Scale SystemsDirecti Group
 
NZSPC 2013 - Ultimate SharePoint Infrastructure Best Practices Session
NZSPC 2013 - Ultimate SharePoint Infrastructure Best Practices SessionNZSPC 2013 - Ultimate SharePoint Infrastructure Best Practices Session
NZSPC 2013 - Ultimate SharePoint Infrastructure Best Practices SessionMichael Noel
 
Optimize DR and Cloning with Logical Hostnames in Oracle E-Business Suite (OA...
Optimize DR and Cloning with Logical Hostnames in Oracle E-Business Suite (OA...Optimize DR and Cloning with Logical Hostnames in Oracle E-Business Suite (OA...
Optimize DR and Cloning with Logical Hostnames in Oracle E-Business Suite (OA...Andrejs Prokopjevs
 
Troubleshooting SQL Server
Troubleshooting SQL ServerTroubleshooting SQL Server
Troubleshooting SQL ServerStephen Rose
 
[よくわかるAmazon Redshift in 大阪]Amazon Redshift最新情報と導入事例のご紹介
[よくわかるAmazon Redshift in 大阪]Amazon Redshift最新情報と導入事例のご紹介[よくわかるAmazon Redshift in 大阪]Amazon Redshift最新情報と導入事例のご紹介
[よくわかるAmazon Redshift in 大阪]Amazon Redshift最新情報と導入事例のご紹介Amazon Web Services Japan
 
Membase Meetup 2010
Membase Meetup 2010Membase Meetup 2010
Membase Meetup 2010Membase
 
Spring 2007 SharePoint Connections Oleson Advanced Administration and Plannin...
Spring 2007 SharePoint Connections Oleson Advanced Administration and Plannin...Spring 2007 SharePoint Connections Oleson Advanced Administration and Plannin...
Spring 2007 SharePoint Connections Oleson Advanced Administration and Plannin...Joel Oleson
 
Front Range PHP NoSQL Databases
Front Range PHP NoSQL DatabasesFront Range PHP NoSQL Databases
Front Range PHP NoSQL DatabasesJon Meredith
 
Building a Scalable Architecture for web apps
Building a Scalable Architecture for web appsBuilding a Scalable Architecture for web apps
Building a Scalable Architecture for web appsDirecti Group
 
Sql 2012 always on
Sql 2012 always onSql 2012 always on
Sql 2012 always ondilip nayak
 
Shared Personalization Service - How To Scale to 15K RPS, Patrice Pelland
Shared Personalization Service - How To Scale to 15K RPS, Patrice PellandShared Personalization Service - How To Scale to 15K RPS, Patrice Pelland
Shared Personalization Service - How To Scale to 15K RPS, Patrice PellandFuenteovejuna
 
[よくわかるAmazon Redshift]Amazon Redshift最新情報と導入事例のご紹介
[よくわかるAmazon Redshift]Amazon Redshift最新情報と導入事例のご紹介[よくわかるAmazon Redshift]Amazon Redshift最新情報と導入事例のご紹介
[よくわかるAmazon Redshift]Amazon Redshift最新情報と導入事例のご紹介Amazon Web Services Japan
 
Presentation on Large Scale Data Management
Presentation on Large Scale Data ManagementPresentation on Large Scale Data Management
Presentation on Large Scale Data ManagementChris Bunch
 
CUBRID Developer's Course
CUBRID Developer's CourseCUBRID Developer's Course
CUBRID Developer's CourseCUBRID
 
Altoros using no sql databases for interactive_applications
Altoros using no sql databases for interactive_applicationsAltoros using no sql databases for interactive_applications
Altoros using no sql databases for interactive_applicationsJeff Harris
 
Getting Maximum Performance from Amazon Redshift (DAT305) | AWS re:Invent 2013
Getting Maximum Performance from Amazon Redshift (DAT305) | AWS re:Invent 2013Getting Maximum Performance from Amazon Redshift (DAT305) | AWS re:Invent 2013
Getting Maximum Performance from Amazon Redshift (DAT305) | AWS re:Invent 2013Amazon Web Services
 

Ähnlich wie How to scale your web app (20)

Client server
Client serverClient server
Client server
 
Handling Data in Mega Scale Systems
Handling Data in Mega Scale SystemsHandling Data in Mega Scale Systems
Handling Data in Mega Scale Systems
 
Mdb dn 2016_11_ops_mgr
Mdb dn 2016_11_ops_mgrMdb dn 2016_11_ops_mgr
Mdb dn 2016_11_ops_mgr
 
NZSPC 2013 - Ultimate SharePoint Infrastructure Best Practices Session
NZSPC 2013 - Ultimate SharePoint Infrastructure Best Practices SessionNZSPC 2013 - Ultimate SharePoint Infrastructure Best Practices Session
NZSPC 2013 - Ultimate SharePoint Infrastructure Best Practices Session
 
Sql Server
Sql ServerSql Server
Sql Server
 
Optimize DR and Cloning with Logical Hostnames in Oracle E-Business Suite (OA...
Optimize DR and Cloning with Logical Hostnames in Oracle E-Business Suite (OA...Optimize DR and Cloning with Logical Hostnames in Oracle E-Business Suite (OA...
Optimize DR and Cloning with Logical Hostnames in Oracle E-Business Suite (OA...
 
No sql exploration keyvaluestore
No sql exploration keyvaluestoreNo sql exploration keyvaluestore
No sql exploration keyvaluestore
 
Troubleshooting SQL Server
Troubleshooting SQL ServerTroubleshooting SQL Server
Troubleshooting SQL Server
 
[よくわかるAmazon Redshift in 大阪]Amazon Redshift最新情報と導入事例のご紹介
[よくわかるAmazon Redshift in 大阪]Amazon Redshift最新情報と導入事例のご紹介[よくわかるAmazon Redshift in 大阪]Amazon Redshift最新情報と導入事例のご紹介
[よくわかるAmazon Redshift in 大阪]Amazon Redshift最新情報と導入事例のご紹介
 
Membase Meetup 2010
Membase Meetup 2010Membase Meetup 2010
Membase Meetup 2010
 
Spring 2007 SharePoint Connections Oleson Advanced Administration and Plannin...
Spring 2007 SharePoint Connections Oleson Advanced Administration and Plannin...Spring 2007 SharePoint Connections Oleson Advanced Administration and Plannin...
Spring 2007 SharePoint Connections Oleson Advanced Administration and Plannin...
 
Front Range PHP NoSQL Databases
Front Range PHP NoSQL DatabasesFront Range PHP NoSQL Databases
Front Range PHP NoSQL Databases
 
Building a Scalable Architecture for web apps
Building a Scalable Architecture for web appsBuilding a Scalable Architecture for web apps
Building a Scalable Architecture for web apps
 
Sql 2012 always on
Sql 2012 always onSql 2012 always on
Sql 2012 always on
 
Shared Personalization Service - How To Scale to 15K RPS, Patrice Pelland
Shared Personalization Service - How To Scale to 15K RPS, Patrice PellandShared Personalization Service - How To Scale to 15K RPS, Patrice Pelland
Shared Personalization Service - How To Scale to 15K RPS, Patrice Pelland
 
[よくわかるAmazon Redshift]Amazon Redshift最新情報と導入事例のご紹介
[よくわかるAmazon Redshift]Amazon Redshift最新情報と導入事例のご紹介[よくわかるAmazon Redshift]Amazon Redshift最新情報と導入事例のご紹介
[よくわかるAmazon Redshift]Amazon Redshift最新情報と導入事例のご紹介
 
Presentation on Large Scale Data Management
Presentation on Large Scale Data ManagementPresentation on Large Scale Data Management
Presentation on Large Scale Data Management
 
CUBRID Developer's Course
CUBRID Developer's CourseCUBRID Developer's Course
CUBRID Developer's Course
 
Altoros using no sql databases for interactive_applications
Altoros using no sql databases for interactive_applicationsAltoros using no sql databases for interactive_applications
Altoros using no sql databases for interactive_applications
 
Getting Maximum Performance from Amazon Redshift (DAT305) | AWS re:Invent 2013
Getting Maximum Performance from Amazon Redshift (DAT305) | AWS re:Invent 2013Getting Maximum Performance from Amazon Redshift (DAT305) | AWS re:Invent 2013
Getting Maximum Performance from Amazon Redshift (DAT305) | AWS re:Invent 2013
 

Kürzlich hochgeladen

Powerpoint exploring the locations used in television show Time Clash
Powerpoint exploring the locations used in television show Time ClashPowerpoint exploring the locations used in television show Time Clash
Powerpoint exploring the locations used in television show Time Clashcharlottematthew16
 
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationSafe Software
 
WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brandgvaughan
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsMark Billinghurst
 
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Mark Simos
 
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)Wonjun Hwang
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationRidwan Fadjar
 
"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii SoldatenkoFwdays
 
Vector Databases 101 - An introduction to the world of Vector Databases
Vector Databases 101 - An introduction to the world of Vector DatabasesVector Databases 101 - An introduction to the world of Vector Databases
Vector Databases 101 - An introduction to the world of Vector DatabasesZilliz
 
Connect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationConnect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationSlibray Presentation
 
The Future of Software Development - Devin AI Innovative Approach.pdf
The Future of Software Development - Devin AI Innovative Approach.pdfThe Future of Software Development - Devin AI Innovative Approach.pdf
The Future of Software Development - Devin AI Innovative Approach.pdfSeasiaInfotech2
 
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Patryk Bandurski
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLScyllaDB
 
What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024Stephanie Beckett
 
Training state-of-the-art general text embedding
Training state-of-the-art general text embeddingTraining state-of-the-art general text embedding
Training state-of-the-art general text embeddingZilliz
 
Commit 2024 - Secret Management made easy
Commit 2024 - Secret Management made easyCommit 2024 - Secret Management made easy
Commit 2024 - Secret Management made easyAlfredo García Lavilla
 
"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr BaganFwdays
 
Search Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdfSearch Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdfRankYa
 

Kürzlich hochgeladen (20)

Powerpoint exploring the locations used in television show Time Clash
Powerpoint exploring the locations used in television show Time ClashPowerpoint exploring the locations used in television show Time Clash
Powerpoint exploring the locations used in television show Time Clash
 
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptxE-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
 
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
 
WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brand
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR Systems
 
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
 
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 Presentation
 
DMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special EditionDMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special Edition
 
"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko
 
Vector Databases 101 - An introduction to the world of Vector Databases
Vector Databases 101 - An introduction to the world of Vector DatabasesVector Databases 101 - An introduction to the world of Vector Databases
Vector Databases 101 - An introduction to the world of Vector Databases
 
Connect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationConnect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck Presentation
 
The Future of Software Development - Devin AI Innovative Approach.pdf
The Future of Software Development - Devin AI Innovative Approach.pdfThe Future of Software Development - Devin AI Innovative Approach.pdf
The Future of Software Development - Devin AI Innovative Approach.pdf
 
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQL
 
What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024
 
Training state-of-the-art general text embedding
Training state-of-the-art general text embeddingTraining state-of-the-art general text embedding
Training state-of-the-art general text embedding
 
Commit 2024 - Secret Management made easy
Commit 2024 - Secret Management made easyCommit 2024 - Secret Management made easy
Commit 2024 - Secret Management made easy
 
"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan
 
Search Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdfSearch Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdf
 

How to scale your web app

  • 1. How to scale (with ruby on rails) George Palmer [email_address] 3dogsbark.com
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11. User Clusters (2) App Server Master DB User Cluster 1 User Cluster 2 User clusters are themselves one of the two database setups outlined earlier SELECT * FROM users WHERE username=‘Bob’ AND … user_id=91732db_cluster=2
  • 12.
  • 13.
  • 14. The final architecture (2) Load balancer Master DB App Server 1 App Server 2 App Server 50 … DB Connection Manager Master DB Session DB Search DB NLS DB Master Slave Slave Slave Master Slave Slave Slave User Cluster 2 User Cluster 1 NFS/SAN
  • 15.
  • 16.
  • 17.
  • 18.
  • 19.
  • 20. Cached architecture Squid Master DB App Server 1 App Server 2 App Server 50 … DB Connection Manager Master DB Session DB Search DB NLS DB Master Slave Slave Slave Master Slave Slave Slave User Cluster 2 User Cluster 1 NFS/SAN M C M C M C MC=memcached
  • 21.
  • 22. Cached architecture – 1 machine Squid Master DB App Server 1 App Server 2 App Server 5 … DB Connection Manager Master DB Session DB Search DB NLS DB Master Slave Slave Slave User Cluster 1 NFS/SAN Memcached Physical Machine
  • 23.
  • 24.

Hinweis der Redaktion

  1. First barcamp Rails but principles applied elsewhere blog