Course : Spring: Big Data and new architectures around Kafka and the Cloud
Practical course - 4d
- 28h00 - Ref. SGG
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 | Understanding the concept of big data |
| Discover Hadoop and Spark |
| Understanding reactive architecture with Kafka |
| Setting up a project in the cloud (AWS) |
| Mastering serverless |
Intended audience
Java/Java EE developers, software architects.
Prerequisites
Knowledge equivalent to that acquired in the course "Spring 5 training, developing enterprise applications" (ref. SPG). Knowledge of Docker and Big Data.
Course schedule
1 Key concepts and tools
- Evolving technologies.
- Docker containers and virtualization.
- The cloud.
- NoSQL.
- The Spring framework.
- Big data.
- Hadoop.
- Kafka.
Hands-on work
2 Pre-design analysis and implementation with Spring
- Analysis of user stories.
- Application modeling.
- Spring in MVC, hexagonal layers.
- Creating Spring microservices from the DDD.
- Ubiquitous language.
- Model and Bounded Context.
- Pitfalls to avoid.
- Best practices.
Hands-on work
Based on a business problem, we're going to use DDD to build a set of micro-services that communicate with each other.
3 Reactive/asynchronous architecture with Kafka
- Message brokers.
- Discover Kafka.
- Push/pull data and producers.
- Consumers and brokers.
- Topics and scores.
- Offset and ZooKeeper.
- Implementation of Kafka in a micro-service architecture.
Hands-on work
Design of a reactive architecture with the Kafka broker linking the microservices.
4 Application and software architecture
- Micro-service architecture.
- CQRS and Event-sourcing.
- Reactive architecture.
- Serverless processing in the cloud.
Hands-on work
Analysis and implementation of previous exercises and improvements by presenting architecture concepts.
5 Big data and the creation of a cloud-based data lake
- Architecture and operation of big data.
- Data lake and data mining concepts.
- Presentation of cloud and non-cloud solutions.
Hands-on work
Implementation of a cloud-based data lake in which a set of data will be deposited for subsequent processing.
6 Big data and data analysis with Hadoop
- Concept and tools.
- Hadoop: introduction to the environment.
- Map Reduce.
- HDFS and HBase.
- Spark: introduction to the environment.
- Comparison with Map Reduce.
- Hadoop integration.
- Data handling.
Hands-on work
Retrieve and analyze data from the data lake using a Spark Hadoop solution. The results can then be represented graphically.
Customer reviews
5 / 5
Customer reviews are based on end-of-course evaluations. The score is calculated from all evaluations within the past year. Only reviews with a textual comment are displayed.
JEROME C.
28/10/25
5 / 5
I really liked the fact that the course was run dynamically using diagrams and with direct interaction with the trainer if we had any questions. The time was devoted to what the technologies did, their advantages and disadvantages and to discussing the technologies with the instructor. There was a good compromise with the practical exercises where the trainer showed us how to implement things without 'wasting time' on that.
Publication date : 03/18/2024
PARTICIPANTS
Java/Java EE developers, software architects.
PREREQUISITES
Knowledge equivalent to that acquired in the course "Spring 5 training, developing enterprise applications" (ref. SPG). Knowledge of Docker and Big Data.
TRAINER QUALIFICATIONS
The experts leading the training are specialists in the covered subjects. They have been approved by our instructional teams for both their professional knowledge and their teaching ability, for each course they teach. They have at least five to ten years of experience in their field and hold (or have held) decision-making positions in companies.
ASSESSMENT TERMS
The trainer evaluates each participant’s academic progress throughout the training using multiple choice, scenarios, hands-on work and more.
Participants also complete a placement test before and after the course to measure the skills they’ve developed.
TERMS AND DEADLINES
Registration must be completed 24 hours before the start of the training.
ACCESSIBILITY FOR PEOPLE WITH DISABILITIES
Do you need special accessibility accommodations? Contact Mrs. Fosse, Disability Manager, at psh-accueil@orsys.fr to review your request and its feasibility.
Java/Java EE developers, software architects.
PREREQUISITES
Knowledge equivalent to that acquired in the course "Spring 5 training, developing enterprise applications" (ref. SPG). Knowledge of Docker and Big Data.
TRAINER QUALIFICATIONS
The experts leading the training are specialists in the covered subjects. They have been approved by our instructional teams for both their professional knowledge and their teaching ability, for each course they teach. They have at least five to ten years of experience in their field and hold (or have held) decision-making positions in companies.
ASSESSMENT TERMS
The trainer evaluates each participant’s academic progress throughout the training using multiple choice, scenarios, hands-on work and more.
Participants also complete a placement test before and after the course to measure the skills they’ve developed.
TEACHING AIDS AND TECHNICAL RESOURCES
• The main teaching aids and instructional methods used in the training are audiovisual aids, documentation and course material, hands-on application exercises and corrected exercises for practical training courses, case studies and coverage of real cases for training seminars.
• At the end of each course or seminar, ORSYS provides participants with a course evaluation questionnaire that is analysed by our instructional teams.
• A check-in sheet for each half-day of attendance is provided at the end of the training, along with a course completion certificate if the trainee attended the entire session.
• The main teaching aids and instructional methods used in the training are audiovisual aids, documentation and course material, hands-on application exercises and corrected exercises for practical training courses, case studies and coverage of real cases for training seminars.
• At the end of each course or seminar, ORSYS provides participants with a course evaluation questionnaire that is analysed by our instructional teams.
• A check-in sheet for each half-day of attendance is provided at the end of the training, along with a course completion certificate if the trainee attended the entire session.
TERMS AND DEADLINES
Registration must be completed 24 hours before the start of the training.
ACCESSIBILITY FOR PEOPLE WITH DISABILITIES
Do you need special accessibility accommodations? Contact Mrs. Fosse, Disability Manager, at psh-accueil@orsys.fr to review your request and its feasibility.
Dates and locations
Last places available
Guaranteed date, in person or remotely
Guaranteed session