Building a Cloud Culture at Yelp (BDT305) | AWS re:Invent 2013

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Amazon Web Services

Yelp is evolving from a purely hosted infrastructure environment to running many systems in AWS—paving the way for their growth to 108 million monthly visitors (source: Google Analytics). Embracing a cloud culture reduced reliability issues, sped up the pace of innovation, and helped them support dozens of data-intensive Yelp features, including search relevance, usage graphs, review highlights, spam filtering, and advertising optimizations. Today, Yelp runs 7+ TB hosted databases, 250+ GB compressed logs per day in Amazon S3, and hundreds of Amazon Elastic MapReduce jobs per day. In this session, Yelp engineers share the secrets of their success and show how they achieved big wins with Amazon EMR and open source libraries, policies around development, privacy, and testing.

Technologie Business

Building a Cloud Culture at Yelp
Jim Blomo – Engineering Manager, Yelp
November 15, 2013

© 2013 Amazon.com, Inc. and its affiliates. All rights reserved. May not be copied, modified, or distributed in whole or in part without the express consent of Amazon.com, Inc.

Why Cloud?

Yelp!

Yelp Data

Why Cloud?
specificity & optimization
generality & abstraction

Make the Trade-Off!

How Cloud?

Back to the Past

$Logging – an aside {user_id: 5, request_id: "b1946ac92492d2347c6235b4d2611184", search_query: "farm to table", city: "Portland, OR", results: [17289, 8230452, 825429, 184312,...], timestamp: 1384469660 }$

Hadoop Trade-Offs

Riddle: Success?
• How do you know
when your
infrastructure is a
success?
• Starts failing under
heavy load
• "Too many" users
overloading the system

Hadoop Issues

EMR Solutions

S3

• Clusters up for limited
amount of time
• Upgrades handled by
Amazon
• Multiple clusters
means no capacity
coordination

Trade-Offs

Trade-Offs

Trade-Offs
Standard configs
Resource consumption tracking
testing

No Cargo Cults

Standard Configs

mrjob Configs
# standard

# memory intensive

# cpu intensive

Resource Tracking

python -m mrjob.tools.emr.terminate_idle_job_flows
-c mrjob.conf

Testing
--runner emr

mr_canary.py

mrjob is Open Source

Adoption

Cloud Calculations
• 5 days with 10
machines = 1 day
with 50 machines
• (On demand pricing
simplification)

Cost

Cost

Cost Control

Data Availability

• s3mysqldump

Overview
in: logs & DB dumps

in: JSON logs

out: CSV, JSON, MyISAM
in: s3mysqldump
S3 out: LOAD DATA or rsync

Pitfalls

Leaky Abstractions

Closed Source

bootstrap-actions/configure-hadoop
mapred.reduce.tasks.speculative.execution=false

Data Explosion

Tron

Wanted

Next Up: Services

Cloud Strategy
Target
generality & abstraction

easiest way

Tandem

We’re Hiring

yelp.com/careers

Please give us your feedback on this
presentation

BDT305 – Cloud @Yelp
As a thank you, we will select prize
winners daily for completed surveys!

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La varietà e la quantità di dati che si crea ogni giorno accelera sempre più velocemente e rappresenta una opportunità irripetibile per innovare e creare nuove startup. Tuttavia gestire grandi quantità di dati può apparire complesso: creare cluster Big Data su larga scala sembra essere un investimento accessibile solo ad aziende consolidate. Ma l’elasticità del Cloud e, in particolare, i servizi Serverless ci permettono di rompere questi limiti. Vediamo quindi come è possibile sviluppare applicazioni Big Data rapidamente, senza preoccuparci dell’infrastruttura, ma dedicando tutte le risorse allo sviluppo delle nostre le nostre idee per creare prodotti innovativi.

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Ora puoi utilizzare Amazon Elastic Kubernetes Service (EKS) per eseguire pod Kubernetes su AWS Fargate, il motore di elaborazione serverless creato per container su AWS. Questo rende più semplice che mai costruire ed eseguire le tue applicazioni Kubernetes nel cloud AWS.In questa sessione presenteremo le caratteristiche principali del servizio e come distribuire la tua applicazione in pochi passaggi

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Esegui pod serverless con Amazon EKS e AWS Fargate

Amazon Web Services

Vent'anni fa Amazon ha attraversato una trasformazione radicale con l'obiettivo di aumentare il ritmo dell'innovazione. In questo periodo abbiamo imparato come cambiare il nostro approccio allo sviluppo delle applicazioni ci ha permesso di aumentare notevolmente l'agilità, la velocità di rilascio e, in definitiva, ci ha consentito di creare applicazioni più affidabili e scalabili. In questa sessione illustreremo come definiamo le applicazioni moderne e come la creazione di app moderne influisce non solo sull'architettura dell'applicazione, ma sulla struttura organizzativa, sulle pipeline di rilascio dello sviluppo e persino sul modello operativo. Descriveremo anche approcci comuni alla modernizzazione, compreso l'approccio utilizzato dalla stessa Amazon.com.

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L’utilizzo dei container è in continua crescita. Se correttamente disegnate, le applicazioni basate su Container sono molto spesso stateless e flessibili. I servizi AWS ECS, EKS e Kubernetes su EC2 possono sfruttare le istanze Spot, portando ad un risparmio medio del 70% rispetto alle istanze On Demand. In questa sessione scopriremo insieme quali sono le caratteristiche delle istanze Spot e come possono essere utilizzate facilmente su AWS. Impareremo inoltre come Spreaker sfrutta le istanze spot per eseguire applicazioni di diverso tipo, in produzione, ad una frazione del costo on-demand!

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In recent months, many customers have been asking us the question – how to monetise Open APIs, simplify Fintech integrations and accelerate adoption of various Open Banking business models. Therefore, AWS and FinConecta would like to invite you to Open Finance marketplace presentation on October 20th. Event Agenda : Open banking so far (short recap) • PSD2, OB UK, OB Australia, OB LATAM, OB Israel Intro to Open Finance marketplace • Scope • Features • Tech overview and Demo The role of the Cloud The Future of APIs • Complying with regulation • Monetizing data / APIs • Business models • Time to market One platform for all: a Strategic approach Q&A

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Per creare valore e costruire una propria offerta differenziante e riconoscibile, le startup di successo sanno come combinare tecnologie consolidate con componenti innovativi creati ad hoc. AWS fornisce servizi pronti all'utilizzo e, allo stesso tempo, permette di personalizzare e creare gli elementi differenzianti della propria offerta. Concentrandoci sulle tecnologie di Machine Learning, vedremo come selezionare i servizi di intelligenza artificiale offerti da AWS e, anche attraverso una demo, come costruire modelli di Machine Learning personalizzati utilizzando SageMaker Studio.

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Con l'approccio tradizionale al mondo IT per molti anni è stato difficile implementare tecniche di DevOps, che finora spesso hanno previsto attività manuali portando di tanto in tanto a dei downtime degli applicativi interrompendo l'operatività dell'utente. Con l'avvento del cloud, le tecniche di DevOps sono ormai a portata di tutti a basso costo per qualsiasi genere di workload, garantendo maggiore affidabilità del sistema e risultando in dei significativi miglioramenti della business continuity. AWS mette a disposizione AWS OpsWork come strumento di Configuration Management che mira ad automatizzare e semplificare la gestione e i deployment delle istanze EC2 per mezzo di workload Chef e Puppet. Scopri come sfruttare AWS OpsWork a garanzia e affidabilità del tuo applicativo installato su Instanze EC2.

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Vuoi conoscere le opzioni per eseguire Microsoft Active Directory su AWS? Quando si spostano carichi di lavoro Microsoft in AWS, è importante considerare come distribuire Microsoft Active Directory per supportare la gestione, l'autenticazione e l'autorizzazione dei criteri di gruppo. In questa sessione, discuteremo le opzioni per la distribuzione di Microsoft Active Directory su AWS, incluso AWS Directory Service per Microsoft Active Directory e la distribuzione di Active Directory su Windows su Amazon Elastic Compute Cloud (Amazon EC2). Trattiamo argomenti quali l'integrazione del tuo ambiente Microsoft Active Directory locale nel cloud e l'utilizzo di applicazioni SaaS, come Office 365, con AWS Single Sign-On.

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Amazon Web Services e VMware organizzano un evento virtuale gratuito il prossimo mercoledì 14 Ottobre dalle 12:00 alle 13:00 dedicato a VMware Cloud ™ on AWS, il servizio on demand che consente di eseguire applicazioni in ambienti cloud basati su VMware vSphere® e di accedere ad una vasta gamma di servizi AWS, sfruttando a pieno le potenzialità del cloud AWS e tutelando gli investimenti VMware esistenti. Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi. La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.

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Molte aziende oggi, costruiscono applicazioni con funzionalità di tipo ledger ad esempio per verificare lo storico di accrediti o addebiti nelle transazioni bancarie o ancora per tenere traccia del flusso supply chain dei propri prodotti. Alla base di queste soluzioni ci sono i database ledger che permettono di avere un log delle transazioni trasparente, immutabile e crittograficamente verificabile, ma sono strumenti complessi e onerosi da gestire. Amazon QLDB elimina la necessità di costruire sistemi personalizzati e complessi fornendo un database ledger serverless completamente gestito. In questa sessione scopriremo come realizzare un'applicazione serverless completa che utilizzi le funzionalità di QLDB.

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Con l’ascesa delle architetture di microservizi e delle ricche applicazioni mobili e Web, le API sono più importanti che mai per offrire agli utenti finali una user experience eccezionale. In questa sessione impareremo come affrontare le moderne sfide di progettazione delle API con GraphQL, un linguaggio di query API open source utilizzato da Facebook, Amazon e altro e come utilizzare AWS AppSync, un servizio GraphQL serverless gestito su AWS. Approfondiremo diversi scenari, comprendendo come AppSync può aiutare a risolvere questi casi d’uso creando API moderne con funzionalità di aggiornamento dati in tempo reale e offline. Inoltre, impareremo come Sky Italia utilizza AWS AppSync per fornire aggiornamenti sportivi in tempo reale agli utenti del proprio portale web.

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Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi. La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali. In queste slide, gli esperti AWS e VMware presentano semplici e pratici accorgimenti per facilitare e semplificare la migrazione dei carichi di lavoro Oracle accelerando la trasformazione verso il cloud, approfondiranno l’architettura e dimostreranno come sfruttare a pieno le potenzialità di VMware Cloud ™ on AWS.

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Amazon Elastic Container Service (Amazon ECS) è un servizio di gestione dei container altamente scalabile, che semplifica la gestione dei contenitori Docker attraverso un layer di orchestrazione per il controllo del deployment e del relativo lifecycle. In questa sessione presenteremo le principali caratteristiche del servizio, le architetture di riferimento per i differenti carichi di lavoro e i semplici passi necessari per poter velocemente migrare uno o più dei tuo container.

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5. Why Cloud? specificity & optimization generality & abstraction

6. Make the Trade-Off!

8. Back to the Past

9. Logging – an aside {user_id: 5, request_id: "b1946ac92492d2347c6235b4d2611184", search_query: "farm to table", city: "Portland, OR", results: [17289, 8230452, 825429, 184312,...], timestamp: 1384469660 }

10. Hadoop Trade-Offs

11. Riddle: Success? • How do you know when your infrastructure is a success? • Starts failing under heavy load • "Too many" users overloading the system

12. Hadoop Issues

13. EMR Solutions S3 • Clusters up for limited amount of time • Upgrades handled by Amazon • Multiple clusters means no capacity coordination

16. Trade-Offs Standard configs Resource consumption tracking testing

17. No Cargo Cults

18. Standard Configs

19. mrjob Configs # standard # memory intensive # cpu intensive

20. Resource Tracking python -m mrjob.tools.emr.terminate_idle_job_flows -c mrjob.conf

21. Testing --runner emr mr_canary.py

22. mrjob is Open Source

24. Cloud Calculations • 5 days with 10 machines = 1 day with 50 machines • (On demand pricing simplification)

27. Cost Control

28. Data Availability • s3mysqldump

29. Overview in: logs & DB dumps in: JSON logs out: CSV, JSON, MyISAM in: s3mysqldump S3 out: LOAD DATA or rsync

31. Leaky Abstractions

32. Closed Source bootstrap-actions/configure-hadoop mapred.reduce.tasks.speculative.execution=false

33. Data Explosion Tron

35. Next Up: Services

36. Cloud Strategy Target generality & abstraction easiest way

38. We’re Hiring yelp.com/careers

39. Please give us your feedback on this presentation BDT305 – Cloud @Yelp As a thank you, we will select prize winners daily for completed surveys!