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High Performance Architecture Patterns
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Celso Crivelaro
May 12, 2016
Technology
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High Performance Architecture Patterns
Celso Crivelaro
May 12, 2016
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Transcript
High Performance Architecture Patterns Celso Crivelaro @celsocrivelaro
$ whoami > Celso Crivelaro - Engineer and MSc in
Computer Engineering - Dev Ruby / Python / Java @celsocrivelaro http://crivelaro.me
None
None
SMTP Locaweb - Transaction email platform - Fast and high
quality email sending - Live reports - Integration by SMTP Protocol and HTTP API - 2,5 Millions of messages per day - + 2 years
None
Platforms
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High Availability
Resource Consumption
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Disk Memory Band- width Processor time Logs GC Open Connections
Deadlocks Stop all disk activities Swap Slowness Services stop responding Queues Amount Workers Slowness
Integrations
Integrations always fails!
Integration Fails always Internal External DB API Storage Network API
ISP Hop Cloud
Map hidden integrations E.g. DNS
Fail Fast
Failing Fast reduces transient errors
Timeouts
Never trust in default timeouts
Threads Timeouts to get rid of deadlocls Internal Little timeout
External Depends: The least possible
Retry
1 2 3 5 8 n Fibonacci Proportion ...
Isolate Critical Components
Panel / API Painel Web Internal API - HTTP Resources
Connection Pool App Server Business Rules Integrations
App Internal API App Panel Painel Web API - HTTP
Resources Conn. Pool App Server Business Rules Integrations Resources Conn. Pool App Server Business Rules Integrations
Less Components == Less Problems
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Redundancy
Health Check
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Scalability
CAP Theorem
Availability Consistency Tolerance to network partition
Availability Consistency Partition Tolerance to network partition whether system is
available or not
Availability Consistency Tolerance to network partition Same data in all
nodes
Availability Consistency Tolerance to network partition Tolerante when a network
fails
Availability Consistency Partition Tolerance Postgres
Availability Consistency Partition Tolerance DNS
Availability Consistency Partition Tolerance Protocols
Evaluate which one is acceptable to your platform
Pool of Resources
App Connection Resource Connection Connection Connection Connection
Controlled Timeouts Controlled Resource Consumption Avoid opening/closing connections overhead
Cache
Make your data closer to your app
When use cache App API DB
Default Cache Strategy App Cache Source 1 2 3
Hot Cache Strategy App Cache Source 2 1
Load Balacing
LB App App App App
Load Balance Strategy matters!
Decoupled Architecture
Slow Processing Fast processing Asynchronous Processing Authentication Message Transformation MTA
Providers User Message Persistence Consolidation
Background jobs Messaging frameworks
How to discover bottlenecks?
Test your limits... Load Test Stress Test Peak Test
Telemetry
None
Grafana + InfluxDB
Other scalabity patterns
Indexes
Sharding
References
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http://use-the-index-luke.com
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Thank you! Celso Crivelaro @celsocrivelaro
[email protected]