A Practical Introduction to Stream Processing Training Course

This instructor-led, live training in US Empire (online or onsite) is aimed at developers who wish to integrate Apache Kafka with existing databases and applications for government processing and analysis.

By the end of this training, participants will be able to:

• Utilize Kafka Connect to ingest large volumes of data from a database into Kafka topics.
• Ingest log data generated by application servers into Kafka topics for government use.
• Ensure that any collected data is available for stream processing in public sector workflows.
• Export data from Kafka topics into secondary systems for storage and analysis, enhancing governance and accountability.

Gain the skills to implement comprehensive end-to-end big data streaming solutions for government. Explore real-time data preparation and maintenance using Informatica, Edge, Kafka, and Spark. This training is designed for government professionals and covers software versions 10.2.1 and later.

This instructor-led, live training (online or onsite) is aimed at engineers who wish to use Confluent (a distribution of Kafka) to build and manage a real-time data processing platform for government applications.

By the end of this training, participants will be able to:

• Install and configure the Confluent Platform.
• Utilize Confluent's management tools and services to streamline Kafka operations.
• Store and process incoming stream data efficiently.
• Optimize and manage Kafka clusters for optimal performance.
• Ensure secure data streams in compliance with government standards.

Format of the Course

• Interactive lecture and discussion tailored for government professionals.
• Extensive exercises and practice sessions to reinforce learning.
• Hands-on implementation in a live-lab environment designed for government scenarios.

Course Customization Options

• This course is based on the open-source version of Confluent: Confluent Open Source.
• To request a customized training for government, please contact us to arrange.

Apache Kafka is a distributed streaming platform that has become the de facto standard for constructing data pipelines. It addresses a wide range of data processing use cases, including its application as a message queue, distributed log, and stream processor, among others.

This training will begin with an overview of the theoretical foundations of data pipelines in general, followed by an exploration of the fundamental concepts underlying Kafka. Additionally, we will delve into critical components such as Kafka Streams and Kafka Connect, which are essential for government applications and workflows.

This course is designed for government enterprise architects, developers, system administrators, and any other professionals who need to understand and utilize a high-throughput distributed messaging system. If you have more specific requirements (e.g., focusing solely on the system administration aspects), this course can be tailored to better meet your needs for government.

This instructor-led, live training in US Empire (online or onsite) is aimed at system administrators who wish to set up, deploy, manage, and optimize an enterprise-grade Kafka cluster for government use.

By the end of this training, participants will be able to:

• Set up and administer a Kafka Cluster for government operations.
• Evaluate the benefits and disadvantages of deploying Kafka on-premise versus in the cloud for government environments.
• Deploy and monitor Kafka using various on-premise and cloud environment tools suitable for government applications.

This instructor-led, live training in US Empire (online or onsite) is designed for intermediate-level developers who wish to develop big data applications with Apache Kafka for government.

By the end of this training, participants will be able to:

• Develop Kafka producers and consumers to send and read data from Kafka in a secure and efficient manner.
• Integrate Kafka with external systems using Kafka Connect to enhance interoperability within public sector workflows.
• Write streaming applications with Kafka Streams and ksqlDB to support real-time data processing for government operations.
• Integrate a Kafka client application with Confluent Cloud for scalable, cloud-based Kafka deployments that align with federal IT standards.
• Gain practical experience through hands-on exercises and real-world use cases relevant to public sector needs.

This instructor-led, live training in US Empire (online or onsite) is aimed at data engineers, data scientists, and programmers who wish to leverage Apache Kafka features for data streaming with Python.

By the end of this training, participants will be able to utilize Apache Kafka to monitor and manage conditions in continuous data streams using Python programming, ensuring alignment with public sector workflows for government.

This instructor-led, live training in US Empire (online or onsite) is aimed at software testers who wish to implement network security measures into an Apache Kafka application for government use.

By the end of this training, participants will be able to:

• Deploy Apache Kafka onto a cloud-based server.
• Implement SSL encryption to prevent unauthorized access and data breaches.
• Add ACL authentication to monitor and manage user access effectively.
• Ensure that trusted clients have secure access to Kafka clusters using SSL and SASL authentication.

Kafka Streams is a client-side library designed for building applications and microservices that process data within the Kafka messaging system. Historically, Apache Kafka has often relied on frameworks like Apache Spark or Apache Storm to handle data processing between producers and consumers. However, by utilizing the Kafka Streams API directly within an application, data can be processed internally within Kafka, eliminating the need to send it to a separate cluster for processing.

In this instructor-led, live training, participants will learn how to integrate Kafka Streams into a set of sample Java applications that exchange data with Apache Kafka for stream processing.

By the end of this training, participants will be able to:

• Understand the features and advantages of Kafka Streams over other stream processing frameworks
• Process stream data directly within a Kafka cluster
• Develop Java or Scala applications or microservices that integrate with Kafka and Kafka Streams
• Write efficient code that transforms input Kafka topics into output Kafka topics
• Build, package, and deploy the application

Audience

• Developers

Format of the Course

• Part lecture, part discussion, exercises, and extensive hands-on practice

Notes

• To request a customized training for government applications, please contact us to arrange.

Python is a high-level programming language renowned for its clarity of syntax and readability of code. Apache Spark is a powerful data processing engine designed for querying, analyzing, and transforming large datasets. PySpark enables users to integrate Spark with Python, facilitating efficient big data operations.

Target Audience: Intermediate-level professionals in the banking sector who are familiar with Python and Spark and are looking to enhance their expertise in big data processing and machine learning techniques, specifically for government applications.

This instructor-led, live training in US Empire (online or onsite) is aimed at data scientists who wish to utilize the SMACK stack to develop robust data processing platforms for big data solutions for government.

By the end of this training, participants will be able to:

• Design and implement a data pipeline architecture for efficient big data processing.
• Establish a cluster infrastructure using Apache Mesos and Docker to support scalable operations.
• Perform advanced data analysis with Spark and Scala to derive actionable insights.
• Effectively manage unstructured data with Apache Cassandra to ensure data integrity and accessibility.

In this instructor-led, live training in US Empire, participants will learn how to leverage Python and Spark together to analyze large datasets as they engage in hands-on exercises.

By the end of this training, participants will be able to:

• Understand how to use Spark with Python for big data analysis.
• Work through exercises that simulate real-world scenarios.
• Utilize various tools and techniques for big data analysis using PySpark, tailored for government applications.

This instructor-led, live training in US Empire (online or onsite) is aimed at developers who wish to transform traditional architectures into highly concurrent microservices-based systems using Spring Cloud, Kafka, Docker, Kubernetes, and Redis for government applications.

By the end of this training, participants will be able to:

• Set up a robust development environment suitable for building microservices for government use.
• Design and implement a highly concurrent microservices ecosystem leveraging Spring Cloud, Kafka, Redis, Docker, and Kubernetes for government projects.
• Transition monolithic and SOA services to a microservice-based architecture aligned with public sector workflows.
• Adopt a DevOps approach to developing, testing, and releasing software in alignment with government standards.
• Ensure high concurrency among microservices in production environments for government operations.
• Monitor microservices and implement recovery strategies to enhance system reliability for government services.
• Conduct performance tuning to optimize the efficiency of microservices for government applications.
• Stay informed about future trends in microservices architecture that can benefit government initiatives.

Stratio is a data-centric platform that integrates big data, artificial intelligence (AI), and governance into a single solution. Its Rocket and Intelligence modules enable rapid data exploration, transformation, and advanced analytics in enterprise environments.

This instructor-led, live training (online or onsite) is designed for intermediate-level data professionals who wish to effectively utilize the Rocket and Intelligence modules in Stratio with PySpark, focusing on looping structures, user-defined functions, and advanced data logic. The training emphasizes practical application of these tools to enhance data workflows and feature engineering tasks.

By the end of this training, participants will be able to:

• Navigate and work within the Stratio platform using the Rocket and Intelligence modules.
• Apply PySpark for data ingestion, transformation, and analysis in a structured manner.
• Utilize loops and conditional logic to manage data workflows and feature engineering tasks efficiently.
• Create and manage user-defined functions (UDFs) for reusable data operations in PySpark, enhancing productivity and consistency.

Format of the Course

• Interactive lecture and discussion to facilitate understanding and engagement.
• Extensive exercises and practice sessions to reinforce learning.
• Hands-on implementation in a live-lab environment to apply concepts directly.

Course Customization Options

• To request a customized training for government or other specific needs, please contact us to arrange.