The document provides an agenda for a MuleSoft meetup in Baltimore on converting data between AVRO and JSON formats. The summary is: 1. The meetup agenda includes an introduction to AVRO and JSON data formats, demos of converting between the formats using Mule and Confluent Schema Registry, and a Q&A session. 2. The speaker, Shruthi R, will provide an overview of AVRO and JSON, demonstrate converting between the formats using Mule transformations, and introduce Confluent Schema Registry for storing schemas. 3. Additional demos will show converting AVRO to JSON and JSON to AVRO using Confluent Schema Registry to retrieve schemas instead of embedding them.

1. 1
Baltimore Meetup will start
shortly...meanwhile
@Attendees: Kindly introduce yourself in Chat
● Name
● Company
● Location
● Mule Experience

2. BALTIMORE MuleSoft
Meetup
AVRO to JSON/JSON to AVRO
Conversion using Confluent
Schema Registry – Use Case and
Demo
6th August 2022
Start
Recording...

3. ● Introduction
● Overview on AVRO and JSON
● Convert AVRO to Json and Json
to AVRO through Mule - DEMO
● Introduction to Confluent
Schema Registry
● Convert AVRO to Json and Json
to AVRO using confluent
schema registry - DEMO
● Q&A
● Trivia
● Meetup: Feedback & Upcoming
Events
Agenda
3

4. Meet your Baltimore Meetup
Leaders
5

5. Today’s Meetup
Speaker
Shruthi R
Application Development Analyst at Accenture
● Mulesoft Certified Developer(Mule 3 & 4) with 3.5 years of experience
working in Mule 3 & Mule 4 Live Projects.
● Have good technical experience in designing & implementing various
integration solutions for Retail and Health Care Domains.
● Worked as a key resources for many projects integrating Salesforce CRM,
Workday, MDM etc.
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6. ● Both the speaker and host are organizing this meet up in individual capacity only. We are not
representing our companies here.
● This presentation is strictly for learning purpose only. Organizer/Presenter do not hold any
responsibility that same solution will work for your business requirements also.
● This presentation is not meant for any promotional activities.
● This meeting will be recorded and shared.
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Safe Harbour
Statement

7. Overview on AVRO and JSON

8. 9
● Avro is used to define the data schema/structure for a record's value.
● An AVRO schema is created using JSON format and can have single or multiple
fields.
{
"type": "record",
"namespace": "com.example",
"name": "FullName",
"fields": [
{ "name": "first", "type": "string" },
{ "name": "last", "type": "string" }
]
}
What is AVRO?
Type: For Avro schemas, type is
always record. This means that there will be
multiple fields defined.
Namespace: It is used to differentiate one
schema type from another
Name: This is the schema name which when
combined with the namespace, uniquely
identifies the schema
Field: A simple data type, such as an integer or
a string, or it can be complex data

9. 9
Why AVRO?
● Embedding documentation in the schema reduces data interpretation
misunderstandings, allows other team members to know about your data
without asking you for clarification.
● It has a very compact format. The bulk of JSON, repeating every field name
with every single record, is what makes JSON inefficient for high-volume usage.
● It is very fast.
Advantages
● Helps producers or consumers of data streams know the right fields that are
needed in an event and what type each field is.
● Keeps data clean, and make everyone more agile
● They protect downstream data consumers from malformed data, as only valid
data will be permitted in the topic.
● Schemas also help solve one of the hardest problems in organization-wide data
flow modeling and handling change in data format

10. 9
● JSON is basically a combination of key/value pair and arrays.
● The data types supported by JSON are string, number, object, array, boolean and
null.
{
"id" : 100,
"name" : "John",
"subject" : [ "Maths",
"address" : {
"city" : "faridabad",
What is JSON?

11. 9
● To prevent data loss or corruption by maintaining the integrity of the data and
embedded structures.
● End Systems supports or requires data in the format
Why Data Conversion Required?

12. AVRO to JSON and JSON to AVRO
Conversion through Mule

13. 9
● Each Binary message should be embedded with AVRO schema to process via mule.
● Is feasible when the payload received from external system is in embedded
format(Binary + AVRO schema).
JSON to AVRO Conversion
● Json payload is converted into binary data embedded with AVRO schema.
● Is feasible when the external system accepts the data in embedded format(Binary
+ AVRO schema).
AVRO to JSON Conversion

14. Conversion Via Mule - DEMO

15. Introduction to Confluent Schema Registry

16. 9
Pre-Requisites:
1. Anypoint Studio Version 7.12.1
2. Mule Runtime Version 4.4.0
3. Confluent Cloud Account
● Anypoint Connector for Confluent Schema Registry provides a mechanism to store
and retrieve AVRO and JSON Schema.
Advantages of Confluent Schema Registry
● It reduces the size of the message because the entire schema does not need to be
embedded and sent or received from the external system/APIs
● Not all systems support embedded data.
Confluent Schema Registry Connector

17. 9
Creating Confluent Cloud Account
Confluent Cloud is a resilient, scalable streaming data service based on Apache Kafka,
which is an event streaming platform used to collect, process, store, and integrate data.
Create a free account at https://www.confluent.io/get-started/

18. 9
Creating Schema Registry
● Select the Region to create the schema registry.
● Click on Add Schema.
● Copy paste you AVRO Schema and add the schema name.

19. 9
Confluent Schema Registry Connector
● Download the connector from Exchange.

20. 9
● Required AVRO Schema to be registered in Confluent Cloud.
● During conversion corresponding Avro schema is retrieved using schema ID to
convert the binary data to JSON.
JSON to AVRO Conversion
● Retrieve the AVRO schema from confluent and replace with ID to convert JSON to
Binary.
AVRO to JSON Conversion

21. Conversion Via Confluent Schema
Registry – Use Case and DEMO

22. Q & A

23. 9
● Medium Blog on Confluent Schema Registry in Mule 4:
https://medium.com/@shruthi_r/confluent-schema-registry-in-mule-4-
9e4b55f495e0
● Github link to code:
https://github.com/Shruthiii960/confluentSchemaRegistry
Resources

24. Trivia Round

25. 31
1. Which is the other connector using which we
can connect to confluent cloud in mulesoft ?
(A) NetSuite
(B) Kafka
(C) AS2

26. 2. What is the default streaming strategy used by
confluent cloud registry connector operations?
(A) Repeatable
(B) Non Repeatable
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27. 3. AVRO schemas describe the format of the
message and are defined using
(A) JSON
(B) XML
(C) JavaScript
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28. Meetup
Feedback

29. ● Share:
○ Tweet using the hashtag #MuleSoftMeetups #MuleMeetup
○ Invite your network to join: https://meetups.mulesoft.com/baltimore/
● Feedback:
○ Fill out the survey feedback and suggest topics for upcoming events
○ Contact MuleSoft at meetups@mulesoft.com for ways to improve the program
● Nominate Yourself as Meetup Speaker:
○ Amazing opportunity to public speaking, broadening skills and expanding
network
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Knowledge Shared is Knowledge
Squared!

30. Meetup
Photo

31. Thank You !!!