Microservices Training in Maia

This instructor-led, live training in Maia (online or onsite) is aimed at intermediate-level system administrators who wish to harness Kafka's message queuing features effectively.

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

• Understand Kafka's message queuing capabilities and architecture.
• Configure Kafka topics for message queuing scenarios.
• Produce and consume messages using Kafka.
• Monitor and manage Kafka as a message queue.

This instructor-led, live training in Maia (online or onsite) is aimed at intermediate-level to advanced-level developers, DevOps professionals, and architects who wish to design, deploy, and manage resilient applications using microservices, containers, and continuous integration/continuous deployment (CI/CD) pipelines.

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

• Understand and implement microservices architecture.
• Deploy and manage containerized applications with Docker and Kubernetes.
• Set up and optimize CI/CD pipelines for automated deployments.
• Apply best practices for security, monitoring, and observability.

This instructor-led, live training in Maia (online or onsite) is aimed at beginner-level to intermediate-level system administrators who wish to learn how to effectively manage Kafka topics for efficient data streaming and processing.

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

• Understand Kafka topic fundamentals and architecture.
• Create, configure, and manage Kafka topics.
• Monitor Kafka topics for health, performance, and availability.
• Implement security measures for Kafka topics.

This instructor-led, live training in Maia (online or onsite) is aimed at advanced-level platform engineers and DevOps professionals who wish to master scaling applications using microservices and Kubernetes.

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

• Design and implement scalable microservices architectures.
• Deploy and manage applications on Kubernetes clusters.
• Utilize Helm charts for efficient service deployment.
• Monitor and maintain the health of microservices in production.
• Apply best practices for security and compliance in a Kubernetes environment.

This instructor-led, live training in Maia (online or onsite) is aimed at experienced developers who wish to build, deploy, and scale applications using microservices built with NodeJS and React.

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

• Develop, deploy, and scale applications using different microservices.
• Build a server-side rendered React application.
• Deploy multi-service apps to the cloud using Docker and Kubernetes.
• Perform application testing on microservices.

This instructor-led, live training in Maia (online or onsite) is aimed at developers, integration architects, and system administrators who wish to master the art of advanced integration patterns and techniques using Apache Camel.

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

• Understand advanced integration patterns and techniques.
• Implement complex routing and transformations.
• Optimize performance and scalability.
• Handle errors and exceptions in complex integration scenarios.
• Integrate Apache Camel with various technologies and platforms.

This instructor-led, live training in Maia (online or onsite) is aimed at intermediate to advanced-level developers who wish to develop microservices using Spring Boot, Docker, and Kubernetes.

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

• Understand the microservices architecture.
• Build production-ready microservices using Spring Boot.
• Understand the role of Docker in microservices.
• Set up Kubernetes cluster to deploy microservices.

This instructor-led, live training in Maia (online or onsite) is aimed at intermediate-level to advanced-level developers and architects who wish to develop Java native applications and microservices using Quarkus with optimized memory usage and startup time.

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

• Develop high-performance, lightweight Java native applications using Quarkus.
• Build and deploy RESTful services and microservices architectures.
• Use GraalVM for native compilation and optimize startup and memory efficiency.
• Package and containerize applications for Kubernetes and OpenShift environments.

This instructor-led, live training in Maia (online or onsite) is aimed at software architects and web developers who wish to use RabbitMQ as a messaging middle-ware and program in Java using Spring to build applications.

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

• Use Java and Spring with RabbitMQ to build applications.
• Design asynchronous message driven systems using RabbitMQ.
• Create and apply queues, topics, exchanges, and bindings in RabbitMQ

In this instructor-led, live training in Maia, participants will learn how to install, configure and administer RabbitMQ, then integrate RabbitMQ messaging into a number of sample .NET applications.

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

• Setup, configure and manage RabbitMQ.
• Understand RabbitQ's role in the design and implementation of a microservices architecture.
• Understand how RabbitMQ compares to other Message Queuing Architectures.
• Set up and use RabbitMQ as a broker for handling asynchronous and synchronous messages for real-world enterprise .Net applications.

This instructor-led, live training in Maia (online or onsite) is aimed at engineers who wish to connect, secure, and manage cloud-based applications (e.g., microservices) using an Istio-based service mesh.

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

• Install and configure Istio on Kubernetes.
• Understand service meshes and to implement one with Istio.
• Deploy an Istio service mesh on top of Kubernetes.
• Use a service mesh to run, manage and monitor microservices in the cloud.

In this instructor-led, live training in Maia (online or onsite), participants will learn how to decouple a Python application, then integrate it with the RabbitMQ messaging system to create distributed cloud applications or microservices.

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

• Setup, configure and manage RabbitMQ.
• Understand RabbitMQ's role in the design and implementation of a microservice's architecture.
• Understand how RabbitMQ compares to other Message Queuing Architectures.
• Set up and use RabbitMQ as a broker for handling asynchronous and synchronous messages for real-world Python applications.

The course is intended for system integrators who want to learn about Apache Camel as a rule-based routing and mediation engine that provides a Java object-based implementation of the Enterprise Integration Patterns.

Apigee Edge, which is built on Java, enables you to provide secure access to your services with a well-defined API that is consistent across all of your services, regardless of service implementation. A consistent API:

• Makes it easy for app developers to consume your services.
• Enables you to change the backend service implementation without affecting the public API.
• Enables you to take advantage of the analytics, monetization, developer portal, and other features built into Edge.

Audience

This course is directed at engineers, architects and developers seeking to utilize Apigee Edge in their projects.

This instructor-led, live training in Maia (online or onsite) is aimed at intermediate-level software developers, system architects, and DevOps professionals who wish to build scalable and maintainable applications using a microservices architecture.

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

• Understand the core principles of microservices architecture.
• Design and implement scalable microservice-based systems.
• Apply design patterns and best practices for microservices.
• Implement event-driven approaches such as CQRS and event sourcing.
• Address challenges in system operations and microservices adoption.

Building complex enterprise applications is very challenging in an ever-changing environment.

Changes in the integration between services or systems will trigger changes in the design of the system. This course covers how to design maintainable, fit to the size and purpose of your organisation service and systems architecture and practical infrastructure.

This course covers common problems with building the landscape of distributed apps, starting from integration problem, infrastructure and modern approaches, to solving complexity issues.

This course explains the pros and cons of each solution (e.g. traditional SOA vs Microservice architecture), available tools (mostly open-source) supporting the development and maintenance, etc..

Course Format

It is mostly discussion (with limited presentations).

In this instructor-led, live training in Maia, participants will learn the features, concepts and standards behind WS02 API Manager. Theory will be coupled with live hands-on practice and implementation throughout the training. By the end of the course participants will have the knowledge and practice to deploy their own APIs using the core features of WS02 API Manager.

This instructor-led, live training in Maia is aimed at enterprise developers and architects. It introduces microservice architecture, presents migration strategies from a monolithic system, and walks participants through the creation and deployment of a sample microservice-based application.

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

• Understand when to use and when not to use microservice architecture.
• Create and implement a testing strategy for microservices.
• Deploy a sample microservice-based application into a production environment.
• Refactor a monolithic application into services.

In this instructor-led, live training in Maia, participants will learn how to build microservices using Go (Golang) and Spring Cloud.

Kafka Streams is a client-side library for building applications and microservices whose data is passed to and from a Kafka messaging system. Traditionally, Apache Kafka has relied on Apache Spark or Apache Storm to process data between message producers and consumers. By calling the Kafka Streams API from within an application, data can be processed directly within Kafka, bypassing the need for sending the data 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 pass data to and from Apache Kafka for stream processing.

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

• Understand Kafka Streams features and advantages over other stream processing frameworks
• Process stream data directly within a Kafka cluster
• Write a Java or Scala application or microservice that integrates with Kafka and Kafka Streams
• Write concise 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 heavy hands-on practice

Notes

• To request a customized training for this course, please contact us to arrange

In this instructor-led, live training in Maia (onsite or remote), participants will learn how to set up and integrate different Stream Processing frameworks with existing big data storage systems and related software applications and microservices.

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

• Install and configure different Stream Processing frameworks, such as Spark Streaming and Kafka Streaming.
• Understand and select the most appropriate framework for the job.
• Process of data continuously, concurrently, and in a record-by-record fashion.
• Integrate Stream Processing solutions with existing databases, data warehouses, data lakes, etc.
• Integrate the most appropriate stream processing library with enterprise applications and microservices.

Microservice architecture is an approach to developing a software application as a suite of small, independent services, each running in its own process and communicating with lightweight mechanisms such as an HTTP resource API. These services can be efficiently deployed using continuous automation systems and bypass the need for centralized management. Microservices can be written in different programming languages and integrate with different data storage systems.

This instructor-led, live training is aimed at enterprise developers and architects. It introduces microservice architecture from a .Net perspective, presents migration strategies from a monolithic system, and walks participants through the creation and deployment of a sample microservice-based application.

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

• Understand when to use and when not to use microservice architecture
• Create and implement a testing strategy for microservices
• Deploy a sample microservice-based application into a production environment
• Refactor a monolithic application into services

Audience

• Developers
• Architects

Format of the course

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

This instructor-led, live training in Maia (online or onsite) is aimed at developers who wish to learn how to build microservices on Microsoft Azure Service Fabric (ASF).

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

• Use ASF as a platform for building and managing microservices.
• Understand key microservices programming concepts and models.
• Create a cluster in Azure.
• Deploy microservices on premises or in the cloud.
• Debug and troubleshoot a live microservice application.

Apache Kafka is a distributed streaming platform. It is de facto a standard for building data pipelines and it solves a lot of different use-cases around data processing: it can be used as a message queue, distributed log, stream processor, etc.

We'll start with some theory behind data pipelines in general, then continue with fundamental concepts behind Kafka. We'll also discover important components like Kafka Streams and Kafka Connect.

This instructor-led, live training in Maia (online or onsite) is aimed at developers who wish to use Axon to build well structured enterprise applications that leverage the power of CQRS and Event Sourcing.

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

• Set up the development environment needed to create an Axon Framework application.
• Implement the CQRS (Command Query Responsibility Segregation) and Event Sourcing architectural patterns to develop complex applications.
• Apply the concepts of Domain Driven Design to their application design.
• Build applications that focus on the business problem instead of the infrastructure.

This instructor-led, live training in Maia (online or onsite) is aimed at developers who wish to implement Apache Kafka stream processing without writing code.

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

• Install and configure Confluent KSQL.
• Set up a stream processing pipeline using only SQL commands (no Java or Python coding).
• Carry out data filtering, transformations, aggregations, joins, windowing, and sessionization entirely in SQL.
• Design and deploy interactive, continuous queries for streaming ETL and real-time analytics.

This instructor-led, live training in Maia (online or onsite) is aimed at sysadmins who wish to set up, deploy, manage and optimize an enterprise-grade Kafka cluster.

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

• Set up and administer a Kafka Cluster.
• Evaluate the benefits and disadvantages of deploying Kafka on-premise vs in the cloud.
• Deploy and monitor Kafka in using various on-premise and cloud environment tools.

This instructor-led, live training in Maia (online or onsite) is aimed at system administrators and developers who wish to deploy, manage, monitor, and operate microservices using Traefik.

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

• Configure and launch Traefik through a Docker provider.
• Enable secure and encrypted connections using Let's Encrypt.
• Deploy and connect middleware to a router to transform service requests.
• Monitor Traefik operations using the dashboard.

This instructor-led, live training in Maia (online or onsite) is aimed at data engineers, data scientists, and programmers who wish to use Spark Streaming features in processing and analyzing real-time data.

By the end of this training, participants will be able to use Spark Streaming to process live data streams for use in databases, filesystems, and live dashboards.