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Life of a startup
Sjoerd Mulder
AMSTERDAM 16 - 17 MAY 2017
Crobox uses
consumer psychology
and
machine learning to
find the
“why” behind the “buy”
How does it work?
2. Build persuasion profiles of each individual
visitor using eventsourcing and machine learning
1. Collect click behaviour on the website of
our customers through Javascript
3. Enrich website with predictions on what
to show to the visitor
Server
Let’s build it!
(summer 2015) Spring Boot
Nginx LB
MongoDB
Bigger Server
Let’s scale it up!
(Q4 2015)
Spring Boot
Nginx load balancer
DB Server 1
MongoDB
DB Server 2
MongoDB
Challenges
This “guy” These “people”
Challenges
● No automatic restarting when service OOM’s
● Manual deployments using CLI, e.g. error prone
● MongoDB just locks up on read-heavy operations
● Many logs on multiple servers
● Hard to handle peak traffic
Solution: Many logs on multiple servers
(Q4 2015)
ELK stack
+
Graylog
Solution: Hard to handle peak traffic
(Q1 2016)
1. Separate event
collection to service
outside of monolith
2. Added Kafka
in between of collector
and processing
New challenge
Service discovery
Spring Boot
Nginx Load Balancer
CollCollectorCollector
Kafka
Solution: MongoDB locking problem
(Q1 2016)
Use different datastore for
analytics and statistics queries
New challenge
Elasticsearch
Use different datastore for KV
collections larger than 100k rows
New challenge
Monitoring
Solution: Deployment and restarts
(Q1 2016)
Mesos and Marathon FTW!
Typical deployment
$ http PUT https://mesos-master/marathon/v2/apps/collector < marathon.json
{ "id": "collector",
"instances": 3,
"cpus": 2,
"mem": 2048,
"container": {
"type": "DOCKER",
"docker": {
"image": "crobox/collector:1.234",
...
}
},
"healthChecks": [{
"path": "/health",
"timeoutSeconds": 5
}],
...
}
Solution: Service discovery
(Q1 2016)
Consul
Service Discovery and Configuration Made Easy.
Consul-template
Creates configuration files based on services in Consul
Mesos-consul bridge
Automatically registers marathon jobs as services in Consul
Solution: Monitoring
(Q1 2016)
Prometheus / alertmanager
Open-source metrics and alerting
monitoring solution
Kamon
Open-source metric recording and trace
support JVM library
Grafana
The open platform for beautiful
analytics and monitoring
Future ready
(Q2 2016)
Nginxloadbalancer
Master server quorumMaster server quorum3 master servers
Monitoring / CIMonitoring & Logging
N worker servers
Node reqs
Service Service Service Service
Monitoring & logging
Grafana
Graylog
Now deploy any service with ease!
(Q2 2016 - now)
Platform services
● Collector API
● Public API
● Admin API
● Visitor service
● Product service
● Account service
● Reporting service
● Database replicators
● Prediction service
Auxiliary services
● Apache Zeppelin
● Kibana
● Superset
● Apache Spark
● Secor
● Device detector
● GeoIP lookup
● Webpack compiler
● Referrer parser
Challenge: Elasticsearch
● Really likes resources
● Single queries can down a
whole cluster
● Unreliable response times
● Really likes resources
Solution: Elasticsearch
(Q4 2016)
ClickHouse is an open source
column-oriented database management
system capable of real time generation of
analytical data reports using SQL queries.
https://clickhouse.yandex
SELECT
product_id,
uniq(profile_id) as value
FROM product_events
WHERE date >= '2017-05-01' AND
event_type = 'bought'
GROUP BY product_id
ORDER BY product_id DESC
Conclusion
● Container orchestration
● Aggregated logging
● Monitoring, monitoring, monitoring
● Use the database that fits your use-case
Thank you!
Questions?
Surprise: we are also hiring :-)
sjoerd@crobox.com

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Life of a startup - Sjoerd Mulder - Codemotion Amsterdam 2017

  • 1. Life of a startup Sjoerd Mulder AMSTERDAM 16 - 17 MAY 2017
  • 2.
  • 3. Crobox uses consumer psychology and machine learning to find the “why” behind the “buy”
  • 4. How does it work? 2. Build persuasion profiles of each individual visitor using eventsourcing and machine learning 1. Collect click behaviour on the website of our customers through Javascript 3. Enrich website with predictions on what to show to the visitor
  • 5. Server Let’s build it! (summer 2015) Spring Boot Nginx LB MongoDB
  • 6. Bigger Server Let’s scale it up! (Q4 2015) Spring Boot Nginx load balancer DB Server 1 MongoDB DB Server 2 MongoDB
  • 8. Challenges ● No automatic restarting when service OOM’s ● Manual deployments using CLI, e.g. error prone ● MongoDB just locks up on read-heavy operations ● Many logs on multiple servers ● Hard to handle peak traffic
  • 9. Solution: Many logs on multiple servers (Q4 2015) ELK stack + Graylog
  • 10. Solution: Hard to handle peak traffic (Q1 2016) 1. Separate event collection to service outside of monolith 2. Added Kafka in between of collector and processing New challenge Service discovery Spring Boot Nginx Load Balancer CollCollectorCollector Kafka
  • 11. Solution: MongoDB locking problem (Q1 2016) Use different datastore for analytics and statistics queries New challenge Elasticsearch Use different datastore for KV collections larger than 100k rows New challenge Monitoring
  • 12. Solution: Deployment and restarts (Q1 2016) Mesos and Marathon FTW!
  • 13. Typical deployment $ http PUT https://mesos-master/marathon/v2/apps/collector < marathon.json { "id": "collector", "instances": 3, "cpus": 2, "mem": 2048, "container": { "type": "DOCKER", "docker": { "image": "crobox/collector:1.234", ... } }, "healthChecks": [{ "path": "/health", "timeoutSeconds": 5 }], ... }
  • 14. Solution: Service discovery (Q1 2016) Consul Service Discovery and Configuration Made Easy. Consul-template Creates configuration files based on services in Consul Mesos-consul bridge Automatically registers marathon jobs as services in Consul
  • 15. Solution: Monitoring (Q1 2016) Prometheus / alertmanager Open-source metrics and alerting monitoring solution Kamon Open-source metric recording and trace support JVM library Grafana The open platform for beautiful analytics and monitoring
  • 16. Future ready (Q2 2016) Nginxloadbalancer Master server quorumMaster server quorum3 master servers Monitoring / CIMonitoring & Logging N worker servers Node reqs Service Service Service Service
  • 18. Now deploy any service with ease! (Q2 2016 - now) Platform services ● Collector API ● Public API ● Admin API ● Visitor service ● Product service ● Account service ● Reporting service ● Database replicators ● Prediction service Auxiliary services ● Apache Zeppelin ● Kibana ● Superset ● Apache Spark ● Secor ● Device detector ● GeoIP lookup ● Webpack compiler ● Referrer parser
  • 19. Challenge: Elasticsearch ● Really likes resources ● Single queries can down a whole cluster ● Unreliable response times ● Really likes resources
  • 20. Solution: Elasticsearch (Q4 2016) ClickHouse is an open source column-oriented database management system capable of real time generation of analytical data reports using SQL queries. https://clickhouse.yandex SELECT product_id, uniq(profile_id) as value FROM product_events WHERE date >= '2017-05-01' AND event_type = 'bought' GROUP BY product_id ORDER BY product_id DESC
  • 21. Conclusion ● Container orchestration ● Aggregated logging ● Monitoring, monitoring, monitoring ● Use the database that fits your use-case
  • 22. Thank you! Questions? Surprise: we are also hiring :-) sjoerd@crobox.com