SlideShare une entreprise Scribd logo
Deploying Kafka at Dropbox
Alternately: how to handle 10,000,000 QPS in one cluster (but don't)
The Plan
• Welcome
• Use Case
• Initial Design
• Iterations of Woe
• Current Setup
• Future Plans
Your Speakers
• Mark Smith <zorkian@dropbox.com>

formerly of Google, Bump, StumbleUpon, etc

likes small airplanes and not getting paged

• Sean Fellows <fellows@dropbox.com>

formerly of Google

likes corgis and distributed systems
The Plan
• Welcome
• Use Case
• Initial Design
• Iterations of Woe
• Current Setup
• Future Plans
Dropbox
• Over 500 million signups
• Exabyte scale storage system
• Multiple hardware locations + AWS
Log Events
• Wide distribution (1,000 categories)
• Several do >1M QPS each + long tail
• About 200TB/day (raw)
• Payloads range from empty to 15MB JSON blobs
Current System
• Existing system based on Scribe + HDFS
• Aggregate to single destination for analytics
• Powers Hive and standard map-reduce type analytics

Want: real-time stream processing!
The Plan
• Welcome
• Use Case
• Initial Design
• Iterations of Woe
• Current Setup
• Future Plans
Initial Design
• One big cluster
• 20 brokers: 96GB RAM, 16x2TB disk, JBOD config
• ZK ensemble run separately (5 members)
• Kafka 0.8.2 from Github
• LinkedIn configuration recommendations
The Plan
• Welcome
• Use Case
• Initial Design
• Iterations of Woe
• Current Setup
• Future Plans
Unexpected Catastrophes
• Disks failure or reaching 100%
• Repair is manual, won't expire unless caught up
• Crash looping, controller load
• Simultaneous restarts
• Even graceful, recovery is sometimes very bad (even 0.9!)
• Rebalancing is dangerous
• Saturates disks, partitions fall out of ISRs, offline, etc
System Errors
• Controller issues
• Sometimes goes AWOL with e.g. big rebalances
• Can have multiple controllers (during serial operations)
• Cascading OOMs
• Too many connections
Lack of Tooling
• Usually left to the reader
• Few best practices
• But we love Kafka Manager
• More to come later!
Newer Clients
• State of Go/Python clients
• Bad behavior at scale
• Laserbeam, retries, backoff
• Too many connections == OOM
• Good clients take time
Bad Configs
• Many, many tunables -- lots of rope
• Unclean leader election
• Preferred leader automation
• Disk threads (thanks Gwen!)
• Little modern documentation on running at scale
• Todd Palino helped us out early, tho, so thank you!
The Plan
• Welcome
• Use Case
• Initial Design
• Iterations of Woe
• Current Setup
• Future Plans
Hardware
• Hardware RAID 10
• ~25TB usable/box (spinning rust)
• During broker replacement
• 200ms p99 commit latency down to 10ms!
• Failure tolerance, full disk protection
• Canary cluster
Monitoring
• MPS vs QPS (metadata reqs!)
• Bad Stuff graph
• Disk utilization/latency
• Heap usage
• Number of controllers
Tooling
• Rolling restarter (health checks!)
• Rate limited partition rebalancer (MPS)
• Config verifier/enforcer
• Coordinated consumption (pre-0.9)
• Auditing framework
Customer Culture
• Topics : organization :: partitions : scale
• Do not hash to partitions
• No ordering requirements
• Namespaces and ownership are required
Success! x
• Kafka goes fast (18M+ MPS on 20 brokers)
• Multiple parallel consumption
• Low latency (at high produce rates)
• 0.9 is leaps ahead of 0.8.2 (upgrade!)
• Supportable by a small team (at our scale)
The Plan
• Welcome
• Use Case
• Initial Design
• Iterations of Woe
• Current Setup
• Future Plans
The Future
• Big is fun but has problems
• Open source our tooling
• Moving towards replication
• Automatic up-partitioning and rebalancing
• Expanding auditing to clients
• Low volume latencies
Deploying Kafka at Dropbox
• Mark Smith <zorkian@dropbox.com>
• Sean Fellows <fellows@dropbox.com>
We would love to talk with other people who are running Kafka at similar
scales. Email us!
And... questions! (If we have time.)

Contenu connexe

Tendances

Infrastructure at Scale: Apache Kafka, Twitter Storm & Elastic Search (ARC303...
Infrastructure at Scale: Apache Kafka, Twitter Storm & Elastic Search (ARC303...Infrastructure at Scale: Apache Kafka, Twitter Storm & Elastic Search (ARC303...
Infrastructure at Scale: Apache Kafka, Twitter Storm & Elastic Search (ARC303...
Amazon Web Services
 
Kafka Summit NYC 2017 - Apache Kafka in the Enterprise: What if it Fails?
Kafka Summit NYC 2017 - Apache Kafka in the Enterprise: What if it Fails? Kafka Summit NYC 2017 - Apache Kafka in the Enterprise: What if it Fails?
Kafka Summit NYC 2017 - Apache Kafka in the Enterprise: What if it Fails?
confluent
 
Kafka Summit NYC 2017 - Introducing Exactly Once Semantics in Apache Kafka
Kafka Summit NYC 2017 - Introducing Exactly Once Semantics in Apache KafkaKafka Summit NYC 2017 - Introducing Exactly Once Semantics in Apache Kafka
Kafka Summit NYC 2017 - Introducing Exactly Once Semantics in Apache Kafka
confluent
 
Data pipeline with kafka
Data pipeline with kafkaData pipeline with kafka
Data pipeline with kafka
Mole Wong
 
Exactly-once Stream Processing with Kafka Streams
Exactly-once Stream Processing with Kafka StreamsExactly-once Stream Processing with Kafka Streams
Exactly-once Stream Processing with Kafka Streams
Guozhang Wang
 
Netflix Keystone Pipeline at Samza Meetup 10-13-2015
Netflix Keystone Pipeline at Samza Meetup 10-13-2015Netflix Keystone Pipeline at Samza Meetup 10-13-2015
Netflix Keystone Pipeline at Samza Meetup 10-13-2015
Monal Daxini
 
Architecture of a Kafka camus infrastructure
Architecture of a Kafka camus infrastructureArchitecture of a Kafka camus infrastructure
Architecture of a Kafka camus infrastructure
mattlieber
 
Bridging the Gap: Connecting AWS and Kafka
Bridging the Gap: Connecting AWS and KafkaBridging the Gap: Connecting AWS and Kafka
Bridging the Gap: Connecting AWS and Kafka
Pengfei (Jason) Li
 
Apache Kafka at LinkedIn
Apache Kafka at LinkedInApache Kafka at LinkedIn
Apache Kafka at LinkedIn
Discover Pinterest
 
Deploying Confluent Platform for Production
Deploying Confluent Platform for ProductionDeploying Confluent Platform for Production
Deploying Confluent Platform for Production
confluent
 
(BDT318) How Netflix Handles Up To 8 Million Events Per Second
(BDT318) How Netflix Handles Up To 8 Million Events Per Second(BDT318) How Netflix Handles Up To 8 Million Events Per Second
(BDT318) How Netflix Handles Up To 8 Million Events Per Second
Amazon Web Services
 
Apache Storm In Retail Context
Apache Storm In Retail ContextApache Storm In Retail Context
Apache Storm In Retail Context
Karthik Deivasigamani
 
How to Lock Down Apache Kafka and Keep Your Streams Safe
How to Lock Down Apache Kafka and Keep Your Streams SafeHow to Lock Down Apache Kafka and Keep Your Streams Safe
How to Lock Down Apache Kafka and Keep Your Streams Safe
confluent
 
ApacheCon2019 Talk: Kafka, Cassandra and Kubernetes at Scale – Real-time Ano...
ApacheCon2019 Talk: Kafka, Cassandra and Kubernetesat Scale – Real-time Ano...ApacheCon2019 Talk: Kafka, Cassandra and Kubernetesat Scale – Real-time Ano...
ApacheCon2019 Talk: Kafka, Cassandra and Kubernetes at Scale – Real-time Ano...
Paul Brebner
 
Building Large-Scale Stream Infrastructures Across Multiple Data Centers with...
Building Large-Scale Stream Infrastructures Across Multiple Data Centers with...Building Large-Scale Stream Infrastructures Across Multiple Data Centers with...
Building Large-Scale Stream Infrastructures Across Multiple Data Centers with...
confluent
 
Multi cluster, multitenant and hierarchical kafka messaging service slideshare
Multi cluster, multitenant and hierarchical kafka messaging service   slideshareMulti cluster, multitenant and hierarchical kafka messaging service   slideshare
Multi cluster, multitenant and hierarchical kafka messaging service slideshare
Allen (Xiaozhong) Wang
 
Kafka Summit NYC 2017 - Scalable Real-Time Complex Event Processing @ Uber
Kafka Summit NYC 2017 - Scalable Real-Time Complex Event Processing @ UberKafka Summit NYC 2017 - Scalable Real-Time Complex Event Processing @ Uber
Kafka Summit NYC 2017 - Scalable Real-Time Complex Event Processing @ Uber
confluent
 
Kafka at scale facebook israel
Kafka at scale   facebook israelKafka at scale   facebook israel
Kafka at scale facebook israel
Gwen (Chen) Shapira
 
High cardinality time series search: A new level of scale - Data Day Texas 2016
High cardinality time series search: A new level of scale - Data Day Texas 2016High cardinality time series search: A new level of scale - Data Day Texas 2016
High cardinality time series search: A new level of scale - Data Day Texas 2016
Eric Sammer
 
Stream Me Up, Scotty: Transitioning to the Cloud Using a Streaming Data Platform
Stream Me Up, Scotty: Transitioning to the Cloud Using a Streaming Data PlatformStream Me Up, Scotty: Transitioning to the Cloud Using a Streaming Data Platform
Stream Me Up, Scotty: Transitioning to the Cloud Using a Streaming Data Platform
confluent
 

Tendances (20)

Infrastructure at Scale: Apache Kafka, Twitter Storm & Elastic Search (ARC303...
Infrastructure at Scale: Apache Kafka, Twitter Storm & Elastic Search (ARC303...Infrastructure at Scale: Apache Kafka, Twitter Storm & Elastic Search (ARC303...
Infrastructure at Scale: Apache Kafka, Twitter Storm & Elastic Search (ARC303...
 
Kafka Summit NYC 2017 - Apache Kafka in the Enterprise: What if it Fails?
Kafka Summit NYC 2017 - Apache Kafka in the Enterprise: What if it Fails? Kafka Summit NYC 2017 - Apache Kafka in the Enterprise: What if it Fails?
Kafka Summit NYC 2017 - Apache Kafka in the Enterprise: What if it Fails?
 
Kafka Summit NYC 2017 - Introducing Exactly Once Semantics in Apache Kafka
Kafka Summit NYC 2017 - Introducing Exactly Once Semantics in Apache KafkaKafka Summit NYC 2017 - Introducing Exactly Once Semantics in Apache Kafka
Kafka Summit NYC 2017 - Introducing Exactly Once Semantics in Apache Kafka
 
Data pipeline with kafka
Data pipeline with kafkaData pipeline with kafka
Data pipeline with kafka
 
Exactly-once Stream Processing with Kafka Streams
Exactly-once Stream Processing with Kafka StreamsExactly-once Stream Processing with Kafka Streams
Exactly-once Stream Processing with Kafka Streams
 
Netflix Keystone Pipeline at Samza Meetup 10-13-2015
Netflix Keystone Pipeline at Samza Meetup 10-13-2015Netflix Keystone Pipeline at Samza Meetup 10-13-2015
Netflix Keystone Pipeline at Samza Meetup 10-13-2015
 
Architecture of a Kafka camus infrastructure
Architecture of a Kafka camus infrastructureArchitecture of a Kafka camus infrastructure
Architecture of a Kafka camus infrastructure
 
Bridging the Gap: Connecting AWS and Kafka
Bridging the Gap: Connecting AWS and KafkaBridging the Gap: Connecting AWS and Kafka
Bridging the Gap: Connecting AWS and Kafka
 
Apache Kafka at LinkedIn
Apache Kafka at LinkedInApache Kafka at LinkedIn
Apache Kafka at LinkedIn
 
Deploying Confluent Platform for Production
Deploying Confluent Platform for ProductionDeploying Confluent Platform for Production
Deploying Confluent Platform for Production
 
(BDT318) How Netflix Handles Up To 8 Million Events Per Second
(BDT318) How Netflix Handles Up To 8 Million Events Per Second(BDT318) How Netflix Handles Up To 8 Million Events Per Second
(BDT318) How Netflix Handles Up To 8 Million Events Per Second
 
Apache Storm In Retail Context
Apache Storm In Retail ContextApache Storm In Retail Context
Apache Storm In Retail Context
 
How to Lock Down Apache Kafka and Keep Your Streams Safe
How to Lock Down Apache Kafka and Keep Your Streams SafeHow to Lock Down Apache Kafka and Keep Your Streams Safe
How to Lock Down Apache Kafka and Keep Your Streams Safe
 
ApacheCon2019 Talk: Kafka, Cassandra and Kubernetes at Scale – Real-time Ano...
ApacheCon2019 Talk: Kafka, Cassandra and Kubernetesat Scale – Real-time Ano...ApacheCon2019 Talk: Kafka, Cassandra and Kubernetesat Scale – Real-time Ano...
ApacheCon2019 Talk: Kafka, Cassandra and Kubernetes at Scale – Real-time Ano...
 
Building Large-Scale Stream Infrastructures Across Multiple Data Centers with...
Building Large-Scale Stream Infrastructures Across Multiple Data Centers with...Building Large-Scale Stream Infrastructures Across Multiple Data Centers with...
Building Large-Scale Stream Infrastructures Across Multiple Data Centers with...
 
Multi cluster, multitenant and hierarchical kafka messaging service slideshare
Multi cluster, multitenant and hierarchical kafka messaging service   slideshareMulti cluster, multitenant and hierarchical kafka messaging service   slideshare
Multi cluster, multitenant and hierarchical kafka messaging service slideshare
 
Kafka Summit NYC 2017 - Scalable Real-Time Complex Event Processing @ Uber
Kafka Summit NYC 2017 - Scalable Real-Time Complex Event Processing @ UberKafka Summit NYC 2017 - Scalable Real-Time Complex Event Processing @ Uber
Kafka Summit NYC 2017 - Scalable Real-Time Complex Event Processing @ Uber
 
Kafka at scale facebook israel
Kafka at scale   facebook israelKafka at scale   facebook israel
Kafka at scale facebook israel
 
High cardinality time series search: A new level of scale - Data Day Texas 2016
High cardinality time series search: A new level of scale - Data Day Texas 2016High cardinality time series search: A new level of scale - Data Day Texas 2016
High cardinality time series search: A new level of scale - Data Day Texas 2016
 
Stream Me Up, Scotty: Transitioning to the Cloud Using a Streaming Data Platform
Stream Me Up, Scotty: Transitioning to the Cloud Using a Streaming Data PlatformStream Me Up, Scotty: Transitioning to the Cloud Using a Streaming Data Platform
Stream Me Up, Scotty: Transitioning to the Cloud Using a Streaming Data Platform
 

En vedette

Kafka At Scale in the Cloud
Kafka At Scale in the CloudKafka At Scale in the Cloud
Kafka At Scale in the Cloud
confluent
 
Kafka + Uber- The World’s Realtime Transit Infrastructure, Aaron Schildkrout
Kafka + Uber- The World’s Realtime Transit Infrastructure, Aaron SchildkroutKafka + Uber- The World’s Realtime Transit Infrastructure, Aaron Schildkrout
Kafka + Uber- The World’s Realtime Transit Infrastructure, Aaron Schildkrout
confluent
 
The Enterprise Service Bus is Dead! Long live the Enterprise Service Bus, Rim...
The Enterprise Service Bus is Dead! Long live the Enterprise Service Bus, Rim...The Enterprise Service Bus is Dead! Long live the Enterprise Service Bus, Rim...
The Enterprise Service Bus is Dead! Long live the Enterprise Service Bus, Rim...
confluent
 
Stream Processing with Kafka in Uber, Danny Yuan
Stream Processing with Kafka in Uber, Danny Yuan Stream Processing with Kafka in Uber, Danny Yuan
Stream Processing with Kafka in Uber, Danny Yuan
confluent
 
101 ways to configure kafka - badly (Kafka Summit)
101 ways to configure kafka - badly (Kafka Summit)101 ways to configure kafka - badly (Kafka Summit)
101 ways to configure kafka - badly (Kafka Summit)
Henning Spjelkavik
 
When it Absolutely, Positively, Has to be There: Reliability Guarantees in Ka...
When it Absolutely, Positively, Has to be There: Reliability Guarantees in Ka...When it Absolutely, Positively, Has to be There: Reliability Guarantees in Ka...
When it Absolutely, Positively, Has to be There: Reliability Guarantees in Ka...
confluent
 
Real-Time Analytics Visualized w/ Kafka + Streamliner + MemSQL + ZoomData, An...
Real-Time Analytics Visualized w/ Kafka + Streamliner + MemSQL + ZoomData, An...Real-Time Analytics Visualized w/ Kafka + Streamliner + MemSQL + ZoomData, An...
Real-Time Analytics Visualized w/ Kafka + Streamliner + MemSQL + ZoomData, An...
confluent
 
The Rise of Real Time
The Rise of Real TimeThe Rise of Real Time
The Rise of Real Time
confluent
 
Simplifying Event Streaming: Tools for Location Transparency and Data Evoluti...
Simplifying Event Streaming: Tools for Location Transparency and Data Evoluti...Simplifying Event Streaming: Tools for Location Transparency and Data Evoluti...
Simplifying Event Streaming: Tools for Location Transparency and Data Evoluti...
confluent
 
Kafka, Killer of Point-to-Point Integrations, Lucian Lita
Kafka, Killer of Point-to-Point Integrations, Lucian LitaKafka, Killer of Point-to-Point Integrations, Lucian Lita
Kafka, Killer of Point-to-Point Integrations, Lucian Lita
confluent
 
More Datacenters, More Problems
More Datacenters, More ProblemsMore Datacenters, More Problems
More Datacenters, More Problems
Todd Palino
 
Introducing Kafka Streams: Large-scale Stream Processing with Kafka, Neha Nar...
Introducing Kafka Streams: Large-scale Stream Processing with Kafka, Neha Nar...Introducing Kafka Streams: Large-scale Stream Processing with Kafka, Neha Nar...
Introducing Kafka Streams: Large-scale Stream Processing with Kafka, Neha Nar...
confluent
 
Siphon - Near Real Time Databus Using Kafka, Eric Boyd, Nitin Kumar
Siphon - Near Real Time Databus Using Kafka, Eric Boyd, Nitin KumarSiphon - Near Real Time Databus Using Kafka, Eric Boyd, Nitin Kumar
Siphon - Near Real Time Databus Using Kafka, Eric Boyd, Nitin Kumar
confluent
 
Fundamentals of Stream Processing with Apache Beam, Tyler Akidau, Frances Perry
Fundamentals of Stream Processing with Apache Beam, Tyler Akidau, Frances Perry Fundamentals of Stream Processing with Apache Beam, Tyler Akidau, Frances Perry
Fundamentals of Stream Processing with Apache Beam, Tyler Akidau, Frances Perry
confluent
 
Protecting your data at rest with Apache Kafka by Confluent and Vormetric
Protecting your data at rest with Apache Kafka by Confluent and VormetricProtecting your data at rest with Apache Kafka by Confluent and Vormetric
Protecting your data at rest with Apache Kafka by Confluent and Vormetric
confluent
 
Kafka Summit SF Apr 26 2016 - Generating Real-time Recommendations with NiFi,...
Kafka Summit SF Apr 26 2016 - Generating Real-time Recommendations with NiFi,...Kafka Summit SF Apr 26 2016 - Generating Real-time Recommendations with NiFi,...
Kafka Summit SF Apr 26 2016 - Generating Real-time Recommendations with NiFi,...
Chris Fregly
 
Deep Dive into Apache Kafka
Deep Dive into Apache KafkaDeep Dive into Apache Kafka
Deep Dive into Apache Kafka
confluent
 
Leveraging Kafka for Big Data in Real Time Bidding, Analytics, ML & Campaign ...
Leveraging Kafka for Big Data in Real Time Bidding, Analytics, ML & Campaign ...Leveraging Kafka for Big Data in Real Time Bidding, Analytics, ML & Campaign ...
Leveraging Kafka for Big Data in Real Time Bidding, Analytics, ML & Campaign ...
Helena Edelson
 
Kafka at Scale: Multi-Tier Architectures
Kafka at Scale: Multi-Tier ArchitecturesKafka at Scale: Multi-Tier Architectures
Kafka at Scale: Multi-Tier Architectures
Todd Palino
 
What's new in Confluent 3.2 and Apache Kafka 0.10.2
What's new in Confluent 3.2 and Apache Kafka 0.10.2 What's new in Confluent 3.2 and Apache Kafka 0.10.2
What's new in Confluent 3.2 and Apache Kafka 0.10.2
confluent
 

En vedette (20)

Kafka At Scale in the Cloud
Kafka At Scale in the CloudKafka At Scale in the Cloud
Kafka At Scale in the Cloud
 
Kafka + Uber- The World’s Realtime Transit Infrastructure, Aaron Schildkrout
Kafka + Uber- The World’s Realtime Transit Infrastructure, Aaron SchildkroutKafka + Uber- The World’s Realtime Transit Infrastructure, Aaron Schildkrout
Kafka + Uber- The World’s Realtime Transit Infrastructure, Aaron Schildkrout
 
The Enterprise Service Bus is Dead! Long live the Enterprise Service Bus, Rim...
The Enterprise Service Bus is Dead! Long live the Enterprise Service Bus, Rim...The Enterprise Service Bus is Dead! Long live the Enterprise Service Bus, Rim...
The Enterprise Service Bus is Dead! Long live the Enterprise Service Bus, Rim...
 
Stream Processing with Kafka in Uber, Danny Yuan
Stream Processing with Kafka in Uber, Danny Yuan Stream Processing with Kafka in Uber, Danny Yuan
Stream Processing with Kafka in Uber, Danny Yuan
 
101 ways to configure kafka - badly (Kafka Summit)
101 ways to configure kafka - badly (Kafka Summit)101 ways to configure kafka - badly (Kafka Summit)
101 ways to configure kafka - badly (Kafka Summit)
 
When it Absolutely, Positively, Has to be There: Reliability Guarantees in Ka...
When it Absolutely, Positively, Has to be There: Reliability Guarantees in Ka...When it Absolutely, Positively, Has to be There: Reliability Guarantees in Ka...
When it Absolutely, Positively, Has to be There: Reliability Guarantees in Ka...
 
Real-Time Analytics Visualized w/ Kafka + Streamliner + MemSQL + ZoomData, An...
Real-Time Analytics Visualized w/ Kafka + Streamliner + MemSQL + ZoomData, An...Real-Time Analytics Visualized w/ Kafka + Streamliner + MemSQL + ZoomData, An...
Real-Time Analytics Visualized w/ Kafka + Streamliner + MemSQL + ZoomData, An...
 
The Rise of Real Time
The Rise of Real TimeThe Rise of Real Time
The Rise of Real Time
 
Simplifying Event Streaming: Tools for Location Transparency and Data Evoluti...
Simplifying Event Streaming: Tools for Location Transparency and Data Evoluti...Simplifying Event Streaming: Tools for Location Transparency and Data Evoluti...
Simplifying Event Streaming: Tools for Location Transparency and Data Evoluti...
 
Kafka, Killer of Point-to-Point Integrations, Lucian Lita
Kafka, Killer of Point-to-Point Integrations, Lucian LitaKafka, Killer of Point-to-Point Integrations, Lucian Lita
Kafka, Killer of Point-to-Point Integrations, Lucian Lita
 
More Datacenters, More Problems
More Datacenters, More ProblemsMore Datacenters, More Problems
More Datacenters, More Problems
 
Introducing Kafka Streams: Large-scale Stream Processing with Kafka, Neha Nar...
Introducing Kafka Streams: Large-scale Stream Processing with Kafka, Neha Nar...Introducing Kafka Streams: Large-scale Stream Processing with Kafka, Neha Nar...
Introducing Kafka Streams: Large-scale Stream Processing with Kafka, Neha Nar...
 
Siphon - Near Real Time Databus Using Kafka, Eric Boyd, Nitin Kumar
Siphon - Near Real Time Databus Using Kafka, Eric Boyd, Nitin KumarSiphon - Near Real Time Databus Using Kafka, Eric Boyd, Nitin Kumar
Siphon - Near Real Time Databus Using Kafka, Eric Boyd, Nitin Kumar
 
Fundamentals of Stream Processing with Apache Beam, Tyler Akidau, Frances Perry
Fundamentals of Stream Processing with Apache Beam, Tyler Akidau, Frances Perry Fundamentals of Stream Processing with Apache Beam, Tyler Akidau, Frances Perry
Fundamentals of Stream Processing with Apache Beam, Tyler Akidau, Frances Perry
 
Protecting your data at rest with Apache Kafka by Confluent and Vormetric
Protecting your data at rest with Apache Kafka by Confluent and VormetricProtecting your data at rest with Apache Kafka by Confluent and Vormetric
Protecting your data at rest with Apache Kafka by Confluent and Vormetric
 
Kafka Summit SF Apr 26 2016 - Generating Real-time Recommendations with NiFi,...
Kafka Summit SF Apr 26 2016 - Generating Real-time Recommendations with NiFi,...Kafka Summit SF Apr 26 2016 - Generating Real-time Recommendations with NiFi,...
Kafka Summit SF Apr 26 2016 - Generating Real-time Recommendations with NiFi,...
 
Deep Dive into Apache Kafka
Deep Dive into Apache KafkaDeep Dive into Apache Kafka
Deep Dive into Apache Kafka
 
Leveraging Kafka for Big Data in Real Time Bidding, Analytics, ML & Campaign ...
Leveraging Kafka for Big Data in Real Time Bidding, Analytics, ML & Campaign ...Leveraging Kafka for Big Data in Real Time Bidding, Analytics, ML & Campaign ...
Leveraging Kafka for Big Data in Real Time Bidding, Analytics, ML & Campaign ...
 
Kafka at Scale: Multi-Tier Architectures
Kafka at Scale: Multi-Tier ArchitecturesKafka at Scale: Multi-Tier Architectures
Kafka at Scale: Multi-Tier Architectures
 
What's new in Confluent 3.2 and Apache Kafka 0.10.2
What's new in Confluent 3.2 and Apache Kafka 0.10.2 What's new in Confluent 3.2 and Apache Kafka 0.10.2
What's new in Confluent 3.2 and Apache Kafka 0.10.2
 

Similaire à Deploying Kafka at Dropbox, Mark Smith, Sean Fellows

Tuning kafka pipelines
Tuning kafka pipelinesTuning kafka pipelines
Tuning kafka pipelines
Sumant Tambe
 
Java one2015 - Work With Hundreds of Hot Terabytes in JVMs
Java one2015 - Work With Hundreds of Hot Terabytes in JVMsJava one2015 - Work With Hundreds of Hot Terabytes in JVMs
Java one2015 - Work With Hundreds of Hot Terabytes in JVMs
Speedment, Inc.
 
Diagnosing Problems in Production - Cassandra
Diagnosing Problems in Production - CassandraDiagnosing Problems in Production - Cassandra
Diagnosing Problems in Production - Cassandra
Jon Haddad
 
Dissecting Scalable Database Architectures
Dissecting Scalable Database ArchitecturesDissecting Scalable Database Architectures
Dissecting Scalable Database Architectures
hypertable
 
HBase Low Latency, StrataNYC 2014
HBase Low Latency, StrataNYC 2014HBase Low Latency, StrataNYC 2014
HBase Low Latency, StrataNYC 2014
Nick Dimiduk
 
Apache Performance Tuning: Scaling Out
Apache Performance Tuning: Scaling OutApache Performance Tuning: Scaling Out
Apache Performance Tuning: Scaling Out
Sander Temme
 
How does Apache Pegasus (incubating) community develop at SensorsData
How does Apache Pegasus (incubating) community develop at SensorsDataHow does Apache Pegasus (incubating) community develop at SensorsData
How does Apache Pegasus (incubating) community develop at SensorsData
acelyc1112009
 
Best practices for highly available and large scale SolrCloud
Best practices for highly available and large scale SolrCloudBest practices for highly available and large scale SolrCloud
Best practices for highly available and large scale SolrCloud
Anshum Gupta
 
Drupal performance
Drupal performanceDrupal performance
Drupal performance
Piyuesh Kumar
 
Cassandra Day Atlanta 2015: Diagnosing Problems in Production
Cassandra Day Atlanta 2015: Diagnosing Problems in ProductionCassandra Day Atlanta 2015: Diagnosing Problems in Production
Cassandra Day Atlanta 2015: Diagnosing Problems in Production
DataStax Academy
 
Cassandra Day Chicago 2015: Diagnosing Problems in Production
Cassandra Day Chicago 2015: Diagnosing Problems in ProductionCassandra Day Chicago 2015: Diagnosing Problems in Production
Cassandra Day Chicago 2015: Diagnosing Problems in Production
DataStax Academy
 
Cassandra Day London 2015: Diagnosing Problems in Production
Cassandra Day London 2015: Diagnosing Problems in ProductionCassandra Day London 2015: Diagnosing Problems in Production
Cassandra Day London 2015: Diagnosing Problems in Production
DataStax Academy
 
Webinar - DreamObjects/Ceph Case Study
Webinar - DreamObjects/Ceph Case StudyWebinar - DreamObjects/Ceph Case Study
Webinar - DreamObjects/Ceph Case Study
Ceph Community
 
Performance out
Performance outPerformance out
Performance out
Andrea Martinez
 
Diagnosing Problems in Production (Nov 2015)
Diagnosing Problems in Production (Nov 2015)Diagnosing Problems in Production (Nov 2015)
Diagnosing Problems in Production (Nov 2015)
Jon Haddad
 
Advanced Operations
Advanced OperationsAdvanced Operations
Advanced Operations
DataStax Academy
 
Webinar: Diagnosing Apache Cassandra Problems in Production
Webinar: Diagnosing Apache Cassandra Problems in ProductionWebinar: Diagnosing Apache Cassandra Problems in Production
Webinar: Diagnosing Apache Cassandra Problems in Production
DataStax Academy
 
Webinar: Diagnosing Apache Cassandra Problems in Production
Webinar: Diagnosing Apache Cassandra Problems in ProductionWebinar: Diagnosing Apache Cassandra Problems in Production
Webinar: Diagnosing Apache Cassandra Problems in Production
DataStax Academy
 
Performance_Out.pptx
Performance_Out.pptxPerformance_Out.pptx
Performance_Out.pptx
sanjanabal
 
2 7
2 72 7

Similaire à Deploying Kafka at Dropbox, Mark Smith, Sean Fellows (20)

Tuning kafka pipelines
Tuning kafka pipelinesTuning kafka pipelines
Tuning kafka pipelines
 
Java one2015 - Work With Hundreds of Hot Terabytes in JVMs
Java one2015 - Work With Hundreds of Hot Terabytes in JVMsJava one2015 - Work With Hundreds of Hot Terabytes in JVMs
Java one2015 - Work With Hundreds of Hot Terabytes in JVMs
 
Diagnosing Problems in Production - Cassandra
Diagnosing Problems in Production - CassandraDiagnosing Problems in Production - Cassandra
Diagnosing Problems in Production - Cassandra
 
Dissecting Scalable Database Architectures
Dissecting Scalable Database ArchitecturesDissecting Scalable Database Architectures
Dissecting Scalable Database Architectures
 
HBase Low Latency, StrataNYC 2014
HBase Low Latency, StrataNYC 2014HBase Low Latency, StrataNYC 2014
HBase Low Latency, StrataNYC 2014
 
Apache Performance Tuning: Scaling Out
Apache Performance Tuning: Scaling OutApache Performance Tuning: Scaling Out
Apache Performance Tuning: Scaling Out
 
How does Apache Pegasus (incubating) community develop at SensorsData
How does Apache Pegasus (incubating) community develop at SensorsDataHow does Apache Pegasus (incubating) community develop at SensorsData
How does Apache Pegasus (incubating) community develop at SensorsData
 
Best practices for highly available and large scale SolrCloud
Best practices for highly available and large scale SolrCloudBest practices for highly available and large scale SolrCloud
Best practices for highly available and large scale SolrCloud
 
Drupal performance
Drupal performanceDrupal performance
Drupal performance
 
Cassandra Day Atlanta 2015: Diagnosing Problems in Production
Cassandra Day Atlanta 2015: Diagnosing Problems in ProductionCassandra Day Atlanta 2015: Diagnosing Problems in Production
Cassandra Day Atlanta 2015: Diagnosing Problems in Production
 
Cassandra Day Chicago 2015: Diagnosing Problems in Production
Cassandra Day Chicago 2015: Diagnosing Problems in ProductionCassandra Day Chicago 2015: Diagnosing Problems in Production
Cassandra Day Chicago 2015: Diagnosing Problems in Production
 
Cassandra Day London 2015: Diagnosing Problems in Production
Cassandra Day London 2015: Diagnosing Problems in ProductionCassandra Day London 2015: Diagnosing Problems in Production
Cassandra Day London 2015: Diagnosing Problems in Production
 
Webinar - DreamObjects/Ceph Case Study
Webinar - DreamObjects/Ceph Case StudyWebinar - DreamObjects/Ceph Case Study
Webinar - DreamObjects/Ceph Case Study
 
Performance out
Performance outPerformance out
Performance out
 
Diagnosing Problems in Production (Nov 2015)
Diagnosing Problems in Production (Nov 2015)Diagnosing Problems in Production (Nov 2015)
Diagnosing Problems in Production (Nov 2015)
 
Advanced Operations
Advanced OperationsAdvanced Operations
Advanced Operations
 
Webinar: Diagnosing Apache Cassandra Problems in Production
Webinar: Diagnosing Apache Cassandra Problems in ProductionWebinar: Diagnosing Apache Cassandra Problems in Production
Webinar: Diagnosing Apache Cassandra Problems in Production
 
Webinar: Diagnosing Apache Cassandra Problems in Production
Webinar: Diagnosing Apache Cassandra Problems in ProductionWebinar: Diagnosing Apache Cassandra Problems in Production
Webinar: Diagnosing Apache Cassandra Problems in Production
 
Performance_Out.pptx
Performance_Out.pptxPerformance_Out.pptx
Performance_Out.pptx
 
2 7
2 72 7
2 7
 

Plus de confluent

Speed Wins: From Kafka to APIs in Minutes
Speed Wins: From Kafka to APIs in MinutesSpeed Wins: From Kafka to APIs in Minutes
Speed Wins: From Kafka to APIs in Minutes
confluent
 
Evolving Data Governance for the Real-time Streaming and AI Era
Evolving Data Governance for the Real-time Streaming and AI EraEvolving Data Governance for the Real-time Streaming and AI Era
Evolving Data Governance for the Real-time Streaming and AI Era
confluent
 
Catch the Wave: SAP Event-Driven and Data Streaming for the Intelligence Ente...
Catch the Wave: SAP Event-Driven and Data Streaming for the Intelligence Ente...Catch the Wave: SAP Event-Driven and Data Streaming for the Intelligence Ente...
Catch the Wave: SAP Event-Driven and Data Streaming for the Intelligence Ente...
confluent
 
Santander Stream Processing with Apache Flink
Santander Stream Processing with Apache FlinkSantander Stream Processing with Apache Flink
Santander Stream Processing with Apache Flink
confluent
 
Unlocking the Power of IoT: A comprehensive approach to real-time insights
Unlocking the Power of IoT: A comprehensive approach to real-time insightsUnlocking the Power of IoT: A comprehensive approach to real-time insights
Unlocking the Power of IoT: A comprehensive approach to real-time insights
confluent
 
Workshop híbrido: Stream Processing con Flink
Workshop híbrido: Stream Processing con FlinkWorkshop híbrido: Stream Processing con Flink
Workshop híbrido: Stream Processing con Flink
confluent
 
Industry 4.0: Building the Unified Namespace with Confluent, HiveMQ and Spark...
Industry 4.0: Building the Unified Namespace with Confluent, HiveMQ and Spark...Industry 4.0: Building the Unified Namespace with Confluent, HiveMQ and Spark...
Industry 4.0: Building the Unified Namespace with Confluent, HiveMQ and Spark...
confluent
 
AWS Immersion Day Mapfre - Confluent
AWS Immersion Day Mapfre   -   ConfluentAWS Immersion Day Mapfre   -   Confluent
AWS Immersion Day Mapfre - Confluent
confluent
 
Eventos y Microservicios - Santander TechTalk
Eventos y Microservicios - Santander TechTalkEventos y Microservicios - Santander TechTalk
Eventos y Microservicios - Santander TechTalk
confluent
 
Q&A with Confluent Experts: Navigating Networking in Confluent Cloud
Q&A with Confluent Experts: Navigating Networking in Confluent CloudQ&A with Confluent Experts: Navigating Networking in Confluent Cloud
Q&A with Confluent Experts: Navigating Networking in Confluent Cloud
confluent
 
Citi TechTalk Session 2: Kafka Deep Dive
Citi TechTalk Session 2: Kafka Deep DiveCiti TechTalk Session 2: Kafka Deep Dive
Citi TechTalk Session 2: Kafka Deep Dive
confluent
 
Build real-time streaming data pipelines to AWS with Confluent
Build real-time streaming data pipelines to AWS with ConfluentBuild real-time streaming data pipelines to AWS with Confluent
Build real-time streaming data pipelines to AWS with Confluent
confluent
 
Q&A with Confluent Professional Services: Confluent Service Mesh
Q&A with Confluent Professional Services: Confluent Service MeshQ&A with Confluent Professional Services: Confluent Service Mesh
Q&A with Confluent Professional Services: Confluent Service Mesh
confluent
 
Citi Tech Talk: Event Driven Kafka Microservices
Citi Tech Talk: Event Driven Kafka MicroservicesCiti Tech Talk: Event Driven Kafka Microservices
Citi Tech Talk: Event Driven Kafka Microservices
confluent
 
Confluent & GSI Webinars series - Session 3
Confluent & GSI Webinars series - Session 3Confluent & GSI Webinars series - Session 3
Confluent & GSI Webinars series - Session 3
confluent
 
Citi Tech Talk: Messaging Modernization
Citi Tech Talk: Messaging ModernizationCiti Tech Talk: Messaging Modernization
Citi Tech Talk: Messaging Modernization
confluent
 
Citi Tech Talk: Data Governance for streaming and real time data
Citi Tech Talk: Data Governance for streaming and real time dataCiti Tech Talk: Data Governance for streaming and real time data
Citi Tech Talk: Data Governance for streaming and real time data
confluent
 
Confluent & GSI Webinars series: Session 2
Confluent & GSI Webinars series: Session 2Confluent & GSI Webinars series: Session 2
Confluent & GSI Webinars series: Session 2
confluent
 
Data In Motion Paris 2023
Data In Motion Paris 2023Data In Motion Paris 2023
Data In Motion Paris 2023
confluent
 
Confluent Partner Tech Talk with Synthesis
Confluent Partner Tech Talk with SynthesisConfluent Partner Tech Talk with Synthesis
Confluent Partner Tech Talk with Synthesis
confluent
 

Plus de confluent (20)

Speed Wins: From Kafka to APIs in Minutes
Speed Wins: From Kafka to APIs in MinutesSpeed Wins: From Kafka to APIs in Minutes
Speed Wins: From Kafka to APIs in Minutes
 
Evolving Data Governance for the Real-time Streaming and AI Era
Evolving Data Governance for the Real-time Streaming and AI EraEvolving Data Governance for the Real-time Streaming and AI Era
Evolving Data Governance for the Real-time Streaming and AI Era
 
Catch the Wave: SAP Event-Driven and Data Streaming for the Intelligence Ente...
Catch the Wave: SAP Event-Driven and Data Streaming for the Intelligence Ente...Catch the Wave: SAP Event-Driven and Data Streaming for the Intelligence Ente...
Catch the Wave: SAP Event-Driven and Data Streaming for the Intelligence Ente...
 
Santander Stream Processing with Apache Flink
Santander Stream Processing with Apache FlinkSantander Stream Processing with Apache Flink
Santander Stream Processing with Apache Flink
 
Unlocking the Power of IoT: A comprehensive approach to real-time insights
Unlocking the Power of IoT: A comprehensive approach to real-time insightsUnlocking the Power of IoT: A comprehensive approach to real-time insights
Unlocking the Power of IoT: A comprehensive approach to real-time insights
 
Workshop híbrido: Stream Processing con Flink
Workshop híbrido: Stream Processing con FlinkWorkshop híbrido: Stream Processing con Flink
Workshop híbrido: Stream Processing con Flink
 
Industry 4.0: Building the Unified Namespace with Confluent, HiveMQ and Spark...
Industry 4.0: Building the Unified Namespace with Confluent, HiveMQ and Spark...Industry 4.0: Building the Unified Namespace with Confluent, HiveMQ and Spark...
Industry 4.0: Building the Unified Namespace with Confluent, HiveMQ and Spark...
 
AWS Immersion Day Mapfre - Confluent
AWS Immersion Day Mapfre   -   ConfluentAWS Immersion Day Mapfre   -   Confluent
AWS Immersion Day Mapfre - Confluent
 
Eventos y Microservicios - Santander TechTalk
Eventos y Microservicios - Santander TechTalkEventos y Microservicios - Santander TechTalk
Eventos y Microservicios - Santander TechTalk
 
Q&A with Confluent Experts: Navigating Networking in Confluent Cloud
Q&A with Confluent Experts: Navigating Networking in Confluent CloudQ&A with Confluent Experts: Navigating Networking in Confluent Cloud
Q&A with Confluent Experts: Navigating Networking in Confluent Cloud
 
Citi TechTalk Session 2: Kafka Deep Dive
Citi TechTalk Session 2: Kafka Deep DiveCiti TechTalk Session 2: Kafka Deep Dive
Citi TechTalk Session 2: Kafka Deep Dive
 
Build real-time streaming data pipelines to AWS with Confluent
Build real-time streaming data pipelines to AWS with ConfluentBuild real-time streaming data pipelines to AWS with Confluent
Build real-time streaming data pipelines to AWS with Confluent
 
Q&A with Confluent Professional Services: Confluent Service Mesh
Q&A with Confluent Professional Services: Confluent Service MeshQ&A with Confluent Professional Services: Confluent Service Mesh
Q&A with Confluent Professional Services: Confluent Service Mesh
 
Citi Tech Talk: Event Driven Kafka Microservices
Citi Tech Talk: Event Driven Kafka MicroservicesCiti Tech Talk: Event Driven Kafka Microservices
Citi Tech Talk: Event Driven Kafka Microservices
 
Confluent & GSI Webinars series - Session 3
Confluent & GSI Webinars series - Session 3Confluent & GSI Webinars series - Session 3
Confluent & GSI Webinars series - Session 3
 
Citi Tech Talk: Messaging Modernization
Citi Tech Talk: Messaging ModernizationCiti Tech Talk: Messaging Modernization
Citi Tech Talk: Messaging Modernization
 
Citi Tech Talk: Data Governance for streaming and real time data
Citi Tech Talk: Data Governance for streaming and real time dataCiti Tech Talk: Data Governance for streaming and real time data
Citi Tech Talk: Data Governance for streaming and real time data
 
Confluent & GSI Webinars series: Session 2
Confluent & GSI Webinars series: Session 2Confluent & GSI Webinars series: Session 2
Confluent & GSI Webinars series: Session 2
 
Data In Motion Paris 2023
Data In Motion Paris 2023Data In Motion Paris 2023
Data In Motion Paris 2023
 
Confluent Partner Tech Talk with Synthesis
Confluent Partner Tech Talk with SynthesisConfluent Partner Tech Talk with Synthesis
Confluent Partner Tech Talk with Synthesis
 

Dernier

哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样
哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样
哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样
insn4465
 
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
ecqow
 
Computational Engineering IITH Presentation
Computational Engineering IITH PresentationComputational Engineering IITH Presentation
Computational Engineering IITH Presentation
co23btech11018
 
Advanced control scheme of doubly fed induction generator for wind turbine us...
Advanced control scheme of doubly fed induction generator for wind turbine us...Advanced control scheme of doubly fed induction generator for wind turbine us...
Advanced control scheme of doubly fed induction generator for wind turbine us...
IJECEIAES
 
官方认证美国密歇根州立大学毕业证学位证书原版一模一样
官方认证美国密歇根州立大学毕业证学位证书原版一模一样官方认证美国密歇根州立大学毕业证学位证书原版一模一样
官方认证美国密歇根州立大学毕业证学位证书原版一模一样
171ticu
 
LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by AnantLLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
Anant Corporation
 
Manufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptxManufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptx
Madan Karki
 
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdfBPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
MIGUELANGEL966976
 
Properties Railway Sleepers and Test.pptx
Properties Railway Sleepers and Test.pptxProperties Railway Sleepers and Test.pptx
Properties Railway Sleepers and Test.pptx
MDSABBIROJJAMANPAYEL
 
International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning an...International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning an...
gerogepatton
 
CompEx~Manual~1210 (2).pdf COMPEX GAS AND VAPOURS
CompEx~Manual~1210 (2).pdf COMPEX GAS AND VAPOURSCompEx~Manual~1210 (2).pdf COMPEX GAS AND VAPOURS
CompEx~Manual~1210 (2).pdf COMPEX GAS AND VAPOURS
RamonNovais6
 
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
IJECEIAES
 
spirit beverages ppt without graphics.pptx
spirit beverages ppt without graphics.pptxspirit beverages ppt without graphics.pptx
spirit beverages ppt without graphics.pptx
Madan Karki
 
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
IEEE Aerospace and Electronic Systems Society as a Graduate Student MemberIEEE Aerospace and Electronic Systems Society as a Graduate Student Member
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
VICTOR MAESTRE RAMIREZ
 
BRAIN TUMOR DETECTION for seminar ppt.pdf
BRAIN TUMOR DETECTION for seminar ppt.pdfBRAIN TUMOR DETECTION for seminar ppt.pdf
BRAIN TUMOR DETECTION for seminar ppt.pdf
LAXMAREDDY22
 
Harnessing WebAssembly for Real-time Stateless Streaming Pipelines
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesHarnessing WebAssembly for Real-time Stateless Streaming Pipelines
Harnessing WebAssembly for Real-time Stateless Streaming Pipelines
Christina Lin
 
Certificates - Mahmoud Mohamed Moursi Ahmed
Certificates - Mahmoud Mohamed Moursi AhmedCertificates - Mahmoud Mohamed Moursi Ahmed
Certificates - Mahmoud Mohamed Moursi Ahmed
Mahmoud Morsy
 
Unit-III-ELECTROCHEMICAL STORAGE DEVICES.ppt
Unit-III-ELECTROCHEMICAL STORAGE DEVICES.pptUnit-III-ELECTROCHEMICAL STORAGE DEVICES.ppt
Unit-III-ELECTROCHEMICAL STORAGE DEVICES.ppt
KrishnaveniKrishnara1
 
Embedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoringEmbedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoring
IJECEIAES
 
Textile Chemical Processing and Dyeing.pdf
Textile Chemical Processing and Dyeing.pdfTextile Chemical Processing and Dyeing.pdf
Textile Chemical Processing and Dyeing.pdf
NazakatAliKhoso2
 

Dernier (20)

哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样
哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样
哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样
 
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
 
Computational Engineering IITH Presentation
Computational Engineering IITH PresentationComputational Engineering IITH Presentation
Computational Engineering IITH Presentation
 
Advanced control scheme of doubly fed induction generator for wind turbine us...
Advanced control scheme of doubly fed induction generator for wind turbine us...Advanced control scheme of doubly fed induction generator for wind turbine us...
Advanced control scheme of doubly fed induction generator for wind turbine us...
 
官方认证美国密歇根州立大学毕业证学位证书原版一模一样
官方认证美国密歇根州立大学毕业证学位证书原版一模一样官方认证美国密歇根州立大学毕业证学位证书原版一模一样
官方认证美国密歇根州立大学毕业证学位证书原版一模一样
 
LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by AnantLLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
 
Manufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptxManufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptx
 
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdfBPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
 
Properties Railway Sleepers and Test.pptx
Properties Railway Sleepers and Test.pptxProperties Railway Sleepers and Test.pptx
Properties Railway Sleepers and Test.pptx
 
International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning an...International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning an...
 
CompEx~Manual~1210 (2).pdf COMPEX GAS AND VAPOURS
CompEx~Manual~1210 (2).pdf COMPEX GAS AND VAPOURSCompEx~Manual~1210 (2).pdf COMPEX GAS AND VAPOURS
CompEx~Manual~1210 (2).pdf COMPEX GAS AND VAPOURS
 
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
 
spirit beverages ppt without graphics.pptx
spirit beverages ppt without graphics.pptxspirit beverages ppt without graphics.pptx
spirit beverages ppt without graphics.pptx
 
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
IEEE Aerospace and Electronic Systems Society as a Graduate Student MemberIEEE Aerospace and Electronic Systems Society as a Graduate Student Member
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
 
BRAIN TUMOR DETECTION for seminar ppt.pdf
BRAIN TUMOR DETECTION for seminar ppt.pdfBRAIN TUMOR DETECTION for seminar ppt.pdf
BRAIN TUMOR DETECTION for seminar ppt.pdf
 
Harnessing WebAssembly for Real-time Stateless Streaming Pipelines
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesHarnessing WebAssembly for Real-time Stateless Streaming Pipelines
Harnessing WebAssembly for Real-time Stateless Streaming Pipelines
 
Certificates - Mahmoud Mohamed Moursi Ahmed
Certificates - Mahmoud Mohamed Moursi AhmedCertificates - Mahmoud Mohamed Moursi Ahmed
Certificates - Mahmoud Mohamed Moursi Ahmed
 
Unit-III-ELECTROCHEMICAL STORAGE DEVICES.ppt
Unit-III-ELECTROCHEMICAL STORAGE DEVICES.pptUnit-III-ELECTROCHEMICAL STORAGE DEVICES.ppt
Unit-III-ELECTROCHEMICAL STORAGE DEVICES.ppt
 
Embedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoringEmbedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoring
 
Textile Chemical Processing and Dyeing.pdf
Textile Chemical Processing and Dyeing.pdfTextile Chemical Processing and Dyeing.pdf
Textile Chemical Processing and Dyeing.pdf
 

Deploying Kafka at Dropbox, Mark Smith, Sean Fellows

  • 1. Deploying Kafka at Dropbox Alternately: how to handle 10,000,000 QPS in one cluster (but don't)
  • 2. The Plan • Welcome • Use Case • Initial Design • Iterations of Woe • Current Setup • Future Plans
  • 3. Your Speakers • Mark Smith <zorkian@dropbox.com>
 formerly of Google, Bump, StumbleUpon, etc
 likes small airplanes and not getting paged
 • Sean Fellows <fellows@dropbox.com>
 formerly of Google
 likes corgis and distributed systems
  • 4. The Plan • Welcome • Use Case • Initial Design • Iterations of Woe • Current Setup • Future Plans
  • 5. Dropbox • Over 500 million signups • Exabyte scale storage system • Multiple hardware locations + AWS
  • 6. Log Events • Wide distribution (1,000 categories) • Several do >1M QPS each + long tail • About 200TB/day (raw) • Payloads range from empty to 15MB JSON blobs
  • 7. Current System • Existing system based on Scribe + HDFS • Aggregate to single destination for analytics • Powers Hive and standard map-reduce type analytics
 Want: real-time stream processing!
  • 8. The Plan • Welcome • Use Case • Initial Design • Iterations of Woe • Current Setup • Future Plans
  • 9. Initial Design • One big cluster • 20 brokers: 96GB RAM, 16x2TB disk, JBOD config • ZK ensemble run separately (5 members) • Kafka 0.8.2 from Github • LinkedIn configuration recommendations
  • 10. The Plan • Welcome • Use Case • Initial Design • Iterations of Woe • Current Setup • Future Plans
  • 11. Unexpected Catastrophes • Disks failure or reaching 100% • Repair is manual, won't expire unless caught up • Crash looping, controller load • Simultaneous restarts • Even graceful, recovery is sometimes very bad (even 0.9!) • Rebalancing is dangerous • Saturates disks, partitions fall out of ISRs, offline, etc
  • 12. System Errors • Controller issues • Sometimes goes AWOL with e.g. big rebalances • Can have multiple controllers (during serial operations) • Cascading OOMs • Too many connections
  • 13. Lack of Tooling • Usually left to the reader • Few best practices • But we love Kafka Manager • More to come later!
  • 14. Newer Clients • State of Go/Python clients • Bad behavior at scale • Laserbeam, retries, backoff • Too many connections == OOM • Good clients take time
  • 15. Bad Configs • Many, many tunables -- lots of rope • Unclean leader election • Preferred leader automation • Disk threads (thanks Gwen!) • Little modern documentation on running at scale • Todd Palino helped us out early, tho, so thank you!
  • 16. The Plan • Welcome • Use Case • Initial Design • Iterations of Woe • Current Setup • Future Plans
  • 17. Hardware • Hardware RAID 10 • ~25TB usable/box (spinning rust) • During broker replacement • 200ms p99 commit latency down to 10ms! • Failure tolerance, full disk protection • Canary cluster
  • 18. Monitoring • MPS vs QPS (metadata reqs!) • Bad Stuff graph • Disk utilization/latency • Heap usage • Number of controllers
  • 19.
  • 20. Tooling • Rolling restarter (health checks!) • Rate limited partition rebalancer (MPS) • Config verifier/enforcer • Coordinated consumption (pre-0.9) • Auditing framework
  • 21.
  • 22. Customer Culture • Topics : organization :: partitions : scale • Do not hash to partitions • No ordering requirements • Namespaces and ownership are required
  • 23. Success! x • Kafka goes fast (18M+ MPS on 20 brokers) • Multiple parallel consumption • Low latency (at high produce rates) • 0.9 is leaps ahead of 0.8.2 (upgrade!) • Supportable by a small team (at our scale)
  • 24. The Plan • Welcome • Use Case • Initial Design • Iterations of Woe • Current Setup • Future Plans
  • 25. The Future • Big is fun but has problems • Open source our tooling • Moving towards replication • Automatic up-partitioning and rebalancing • Expanding auditing to clients • Low volume latencies
  • 26. Deploying Kafka at Dropbox • Mark Smith <zorkian@dropbox.com> • Sean Fellows <fellows@dropbox.com> We would love to talk with other people who are running Kafka at similar scales. Email us! And... questions! (If we have time.)