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Building a Codeless Log
Pipeline with Confluent
Sink Connector
2021
Pollyanna R. Valente
Site Reliability Engineer at Loggi which, among other things, takes
care of the company’s data pipeline. Holding a Computer Science
Degree with one year of experience working with Kafka and is an
active member of Kafka BR (Brazilians’ community Kafka).
Site Reliability Engineer at Loggi, focused on maintaining the
production environment and building a data pipeline.
Daniel Sousa
Agenda
● Loggi
● Motivation
● Our Pipeline
3
4
We are an unicorn
startup, making
millions of deliveries
throughout Brazil.
Loggi is a logistics company enabled by
technology to connect Brazil.
5
Connecting Brazil means delivering
everything to everyone everywhere.
6
Sources: Ebit (Brazil), NBC (USA), Xinhua (China), Italian Trade Agency (China) , US Department of Commerce (USA)
7
1. Client pickup 2. Cross-docking 3. Mini hub 4. Last-mile
● Loggi One mobile app for senders
● Loggi One web app for senders
● API integration for senders
● Driver mobile app
● XD App mobile app for operators
● Warehouse Management System (WMS)
● Integration with sorters and IOT
● XD App mobile app for operators
● Integration with sorters and IOT
● Driver mobile app
● Loggi One web app for recipients
● Proprietary route optimization algos
● Independent contractor for pickup
● Loggi Leve: franchisees with dedicated
fleets
● Cross-docking warehouses leased on
Loggi’ balance sheet
● Operators are mainly employees
● Some urbans hubs are leased and
operated directly by Loggi
● Loggi Leve: franchisees own and operate
their hubs
● Independent contractors
● Loggi Leve: franchises with dedicated fleet
Building from scratch the next generation delivery network
Harnessing the power of available technologies at every step: mobile, machine learning, automation, IOT and cloud computing
Tech
Stack
Asset
Intensity
HIGH
LOW
3
HIGH
LOW
9
HIGH
LOW
6
HIGH
LOW
2
8
Motivation
Recently, some teams came up with a new
demand to perform analytical explorations
joining structured log messages with business
data, stored in relational databases. This would
allow them to answer questions such as, What
is the percentage of packages with an
unsuccessful first delivery, for example.
So, we need to find a way to put the two
information on the same place to the team be
allowed do consume easily both information
and work with them together.
9
Our Log Pipeline
10
Thank you!

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Building a Codeless Log Pipeline w/ Confluent Sink Connector | Pollyanna Valente and Daniel Sousa, Loggi

  • 1. 1 Building a Codeless Log Pipeline with Confluent Sink Connector 2021
  • 2. Pollyanna R. Valente Site Reliability Engineer at Loggi which, among other things, takes care of the company’s data pipeline. Holding a Computer Science Degree with one year of experience working with Kafka and is an active member of Kafka BR (Brazilians’ community Kafka). Site Reliability Engineer at Loggi, focused on maintaining the production environment and building a data pipeline. Daniel Sousa
  • 4. 4 We are an unicorn startup, making millions of deliveries throughout Brazil.
  • 5. Loggi is a logistics company enabled by technology to connect Brazil. 5
  • 6. Connecting Brazil means delivering everything to everyone everywhere. 6
  • 7. Sources: Ebit (Brazil), NBC (USA), Xinhua (China), Italian Trade Agency (China) , US Department of Commerce (USA) 7 1. Client pickup 2. Cross-docking 3. Mini hub 4. Last-mile ● Loggi One mobile app for senders ● Loggi One web app for senders ● API integration for senders ● Driver mobile app ● XD App mobile app for operators ● Warehouse Management System (WMS) ● Integration with sorters and IOT ● XD App mobile app for operators ● Integration with sorters and IOT ● Driver mobile app ● Loggi One web app for recipients ● Proprietary route optimization algos ● Independent contractor for pickup ● Loggi Leve: franchisees with dedicated fleets ● Cross-docking warehouses leased on Loggi’ balance sheet ● Operators are mainly employees ● Some urbans hubs are leased and operated directly by Loggi ● Loggi Leve: franchisees own and operate their hubs ● Independent contractors ● Loggi Leve: franchises with dedicated fleet Building from scratch the next generation delivery network Harnessing the power of available technologies at every step: mobile, machine learning, automation, IOT and cloud computing Tech Stack Asset Intensity HIGH LOW 3 HIGH LOW 9 HIGH LOW 6 HIGH LOW 2
  • 8. 8 Motivation Recently, some teams came up with a new demand to perform analytical explorations joining structured log messages with business data, stored in relational databases. This would allow them to answer questions such as, What is the percentage of packages with an unsuccessful first delivery, for example. So, we need to find a way to put the two information on the same place to the team be allowed do consume easily both information and work with them together.