Microservices Training in Patras

Confluent Apache Kafka is an enterprise-grade distributed event streaming platform built on Apache Kafka. It supports high-throughput, fault-tolerant data pipelines and real-time streaming applications.

This instructor-led, live training (online or onsite) is aimed at intermediate-level engineers and administrators who wish to deploy, configure, and optimize Confluent Kafka clusters in production environments.

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

• Install, configure, and operate Confluent Kafka clusters with multiple brokers.
• Design high-availability setups using Zookeeper and replication techniques.
• Tune performance, monitor metrics, and apply recovery strategies.
• Secure, scale, and integrate Kafka with enterprise environments.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

Confluent Apache Kafka is a distributed event streaming platform designed for high-throughput, fault-tolerant data pipelines and real-time analytics.

This instructor-led, live training (online or onsite) is aimed at intermediate-level system administrators and DevOps professionals who wish to install, configure, monitor, and troubleshoot Confluent Apache Kafka clusters.

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

• Understand the components and architecture of Confluent Kafka.
• Deploy and manage Kafka brokers, Zookeeper quorums, and key services.
• Configure advanced features including security, replication, and performance tuning.
• Use management tools to monitor and maintain Kafka clusters.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

This instructor-led, live training in Patras (online or onsite) is aimed at intermediate-level Java developers who wish to integrate Apache Kafka into their applications for reliable, scalable, and high-throughput messaging.

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

• Understand the architecture and core components of Kafka.
• Set up and configure a Kafka cluster.
• Produce and consume messages using Java.
• Implement Kafka Streams for real-time data processing.
• Ensure fault tolerance and scalability in Kafka applications.

This instructor-led, live training in Patras (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 Patras (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 Patras (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 Patras (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 Patras (online or onsite) is aimed at intermediate-level Java developers who wish to design, develop, deploy, and maintain microservices-based applications using Java frameworks like Spring Boot and Spring Cloud.

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

• Understand the principles and benefits of microservices architecture.
• Build and deploy microservices using Java and Spring Boot.
• Implement service discovery, configuration management, and API gateways.
• Secure, monitor, and scale microservices effectively.
• Deploy microservices using Docker and Kubernetes.

This instructor-led, live training in Patras (online or onsite) is aimed at intermediate-level developers who wish to learn the fundamentals of Kafka and integrate it with Spring Boot.

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

• Understand Kafka and its architecture.
• Learn how to install, configure, and set up a basic Kafka environment.
• Integrate Kafka with Spring Boot.

This instructor-led, live training in Patras (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 Patras (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 Patras (online or onsite) is aimed at intermediate-level developers who wish to develop big data applications with Apache Kafka.

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

• Develop Kafka producers and consumers to send and read data from Kafka.
• Integrate Kafka with external systems using Kafka Connect.
• Write streaming applications with Kafka Streams & ksqlDB.
• Integrate a Kafka client application with Confluent Cloud for cloud-based Kafka deployments.
• Gain practical experience through hands-on exercises and real-world use cases.

This instructor-led, live training in Patras (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 Patras (online or onsite) is aimed at intermediate-level developers and DevOps engineers who wish to build, deploy, and manage microservices using Spring Cloud and Docker.

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

• Develop microservices using Spring Boot and Spring Cloud.
• Containerize applications with Docker and Docker Compose.
• Implement service discovery, API gateways, and inter-service communication.
• Monitor and secure microservices in production environments.
• Deploy and orchestrate microservices using Kubernetes.

This instructor-led, live training in Patras (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.

The course is intended for IT specialists that want to set up a solution based on RabbitMQ, the highly reliable enterprise messaging system that implements the Advanced Message Queuing Protocol (AMQP).

This instructor-led, live training in Patras (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 Patras, 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 Patras (online or onsite) is aimed at developers and software engineers who wish to use RabbitMQ to communicate between microservices through messaging and perform advanced implementation and troubleshooting.

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

• Set up the necessary environment to start developing advanced messaging solutions with RabbitMQ.
• Understand how to design a distributed microservices architecture with RabbitMQ.
• Learn how to implement advanced configuration, security, networking, high availability, and replication.
• Know the common issues encountered in RabbitMQ installations and how to resolve them.
• Learn about memory optimization, flow control, and advanced performance tuning.
• Apply some advanced troubleshooting techniques.

Istio is an open-source service mesh that runs on Kubernetes to provide secure, observable, and manageable connectivity between microservices. By leveraging Istio’s Envoy-based sidecar proxies, teams can enforce policies, secure communications with mTLS, gain deep observability into traffic, and improve reliability at scale.

This instructor-led, live training (online or onsite) is aimed at intermediate-level engineers who wish to deploy, secure, and manage microservices applications using Istio on Kubernetes.

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

• Install and configure Istio on Kubernetes clusters.
• Understand and apply service mesh concepts including traffic management, security, and observability.
• Deploy microservices applications within an Istio service mesh.
• Secure service-to-service communications with mutual TLS (mTLS) and Zero Trust principles.
• Monitor, trace, and troubleshoot microservices with Prometheus, Grafana, and Jaeger.
• Integrate Istio with Calico for advanced network policies and security.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

In this instructor-led, live training in Patras (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.

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

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

• Use Kafka Connect to ingest large amounts of data from a database into Kafka topics.
• Ingest log data generated by an application servers into Kafka topics.
• Make any collected data available for stream processing.
• Export data from Kafka topics into secondary systems for storage and analysis.

This instructor-led, live training in Patras (online or onsite) is aimed at developers who wish to learn how to build, test, debug and deploy an API on top of Google Cloud's Apigee API Platform.

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

• Set up a development environment that includes all needed resources to start developing an API.
• Understand and implement the tools available within Apigee Edge.
• Build and deploy an API to Google Cloud.
• Monitor and debug API errors.
• Leverage Google Cloud's analytics and machine learning solutions to make APIs more intelligent.

This instructor-led, live training in Patras (online or onsite) is aimed at developers who wish to learn how to build, test, debug and deploy an API on top of Google Cloud's Apigee API Platform.

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

• Set up a development environment that includes all needed resources to start developing an API.
• Understand and implement the tools available within Apigee Edge.
• Build and deploy an API to Google Cloud.
• Monitor and debug API errors.
• Leverage Google Cloud's analytics and machine learning solutions to make APIs more intelligent.

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 Patras (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 Patras (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.

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 their applications.

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

• Install and configure Confluent Platform.
• Use Confluent's management tools and services to run Kafka more easily.
• Store and process incoming stream data.
• Optimize and manage Kafka clusters.
• Secure data streams.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

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.

Envoy Proxy is a high-performance edge and service proxy, originally created at Lyft, and now a CNCF project widely adopted in cloud-native infrastructures. Envoy acts as a universal data plane in service mesh architectures, enabling dynamic routing, observability, and Zero Trust security across microservices.

This instructor-led, live training (online or onsite) is aimed at intermediate-level engineers who wish to deploy, configure, and operate Envoy Proxy for modern microservices and service mesh environments.

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

• Install and configure Envoy Proxy in standalone and Kubernetes environments.
• Understand Envoy’s architecture, including filters, clusters, and listeners.
• Configure traffic management policies such as retries, circuit breaking, and load balancing.
• Secure communication with TLS/mTLS and enforce Zero Trust principles.
• Extend Envoy functionality with WebAssembly (WASM) filters.
• Integrate Envoy with service meshes such as Istio and Consul.
• Monitor, trace, and troubleshoot microservice traffic using Envoy’s observability features.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

In this instructor-led, live training in Patras (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.

This course is for enterprise architects, developers, system administrators and anyone who wants to understand and use a high-throughput distributed messaging system. If you have more specific requirements (e.g. only system administration side), this course can be tailored to better suit your needs.

This instructor-led, live training in Patras (online or onsite) is aimed at beginner-level / intermediate-level / advanced-level system administrators and operations engineers who wish to use Apache Kafka to deploy, secure, monitor, and troubleshoot Kafka clusters.

By the end of this training, participants will be able to: explain Kafka architecture and KRaft mode, operate and secure Kafka clusters, monitor performance and reliability, and resolve common production issues.

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

By the end of this training, participants will be able to use Apache Kafka to monitor and manage conditions in continuous data streams using Python programming.

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

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

• Deploy Apache Kafka onto a cloud based server.
• Implement SSL encryption to prevent attacks.
• Add ACL authentication to track and control user access.
• Ensure credible clients have access to Kafka clusters with SSL and SASL authentication.

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

Upon completion of this professional course, participants will have acquired the knowledge and skills necessary to effectively implement, manage, and scale Kuma's service mesh within Kubernetes environments. They will be able to implement advanced traffic routing, observability, and security features to optimize the performance and reliability of their microservices-based applications.

This instructor-led, live training in Patras (online or onsite) is aimed at developers who wish to use Lumen to build Laravel-based microservices and applications.

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

• Set up the necessary development environment to start developing microservices with Lumen.
• Understand the benefits of implementing microservices using Lumen and PHP.
• Perform and implement the microservices functions and operations using the Lumen framework.
• Protect and control access to the microservices architectures by building security layers.

In this instructor-led, live training in Patras, participants will learn how to evaluate different technologies and approaches for the design of a services-based system architecture. The training begins with a discussion and comparison of monolithic systems and service architectures, then digs into the details of microservice architecture.

Participants are given a chance to put their knowledge into practice as they step through the creation and deployment of a set of proof-of-concept microservices built with Spring Cloud, Spring Boot and Docker.
Finally, the relevant infrastructure building blocks are examined to help participants determine the most suitable tools and approaches to use for different organizational requirements.
By the end of this training, participants will have a solid understanding of Service-Oriented Architecture (SOA) and Microservice Architecture as well practical experience using Spring Cloud and related Spring technologies for rapidly developing their own cloud-scale, cloud-ready microservices.

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

This instructor-led, live training in Patras 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.

This instructor-led, live training in Patras (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.

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

In this instructor-led, live training in Patras, participants will learn the fundamentals of building microservices using Spring Cloud and Docker. Participant knowledge is put to the test through exercises and the step-by-step development of sample microservices.

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

• Understand the fundamentals of microservices.
• Use Docker to build containers for microservice applications.
• Build and deploy containerized microservices using Spring Cloud and Docker.
• Integrate microservices with discovery services and the Spring Cloud API Gateway.
• Use Docker Compose for end-to-end integration testing.

This instructor-led, live training in Patras (online or onsite) is aimed at data scientists who wish to use the SMACK stack to build data processing platforms for big data solutions.

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

• Implement a data pipeline architecture for processing big data.
• Develop a cluster infrastructure with Apache Mesos and Docker.
• Analyze data with Spark and Scala.
• Manage unstructured data with Apache Cassandra.

In this instructor-led, live training in Patras, we start with a discussion of microservice architecture. Participant knowledge is put to the test through exercises and the step-by-step development of sample microservices.

By the end of this training, participants will have a solid understanding of how to use Spring Cloud and related Spring technologies to rapidly develop their own cloud-scale, cloud-ready microservices.

This instructor-led, live training in Patras (online or onsite) is aimed at developers who wish to transform traditional architecture into a highly concurrent microservices-based architecture using Spring Cloud, Kafka, Docker, Kubernetes and Redis.

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

• Set up the necessary development environment for building microservices.
• Design and implement a highly concurrent microservices ecosystem using Spring Cloud, Kafka, Redis, Docker and Kubernetes.
• Transform monolithic and SOA services to microservice based architecture.
• Adopt a DevOps approach to developing, testing and releasing software.
• Ensure high concurrency among microservices in production.
• Monitor microservices and implement recovery strategies.
• Carry out performance tuning.
• Learn about future trends in microservices architecture.

Spring Cloud is an open-source lightweight microservices framework for building Java applications for the cloud. Netflix OSS is a set of frameworks and libraries for developing microservices. Spring Cloud integrates nicely with Netflix components using auto configuration and convention over configuration.

In this instructor-led, live training, participants will learn the fundamental concepts of building microservices using Spring Cloud and Netflix OSS. Participant knowledge is put to the test through exercises and the step-by-step development of sample microservices.

By the end of this training participants will have a solid understanding of how to use Spring Cloud and related Spring technologies together with Netflix OSS to rapidly develop their own cloud-scale, cloud-ready microservices.

Audience

• Java Developers

Format of the course

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

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).

This instructor-led, live training in Patras (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.

In this instructor-led, live training in Patras, 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.