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Architecting Python Microservices in AWS with ECS and App Mesh

Learn to build, deploy and operatre modern Python based microservice applications in the AWS Cloud!

In this course learners will be taken on a journey to learn the fundamental principles of what a microservice architecture is and how to build, deploy and operate Python based microservices in the the AWS Cloud. This course provides a balance of theory covering the key aspects of each major technology or cloud architecture component then made practical with several code samples, walk-thrus, and demonstrations with working examples deployed to the AWS Cloud.

Apache Kafka Crash Course for Java and Python Developers

Gain valuable skills in Apache Kafka from a 2X Certified Confluent Kafka Engineer!

Java or Python Software Developers are taken on a fast track journey to attaining skills required to harness the amazing power for Apache Kafka. Students gain the practical knowledge to build loosely coupled distributed systems that scale to insane levels of throughput while maintaining unprecedented resiliency.

The Apache Kafka Crash Course for Java and Python Developers is specifically designed for quickly preparing Developers to be prepared for upcoming interviews or make timely yet significant contributions implementing Apache Kafka messaging or event streaming in their current roles. The course provides a balance of fundamental theory on the inner workings of Apache Kafka's storage mechanism along with the know how to tune producer and consumer applications for performance and resiliency. This course is packed full of practical examples with code samples for putting the theoretical content into practice in two of the most popular languages used in industry, Java and Python.

Ultimate Guide to Data Streaming with AWS Kinesis

In this course students learn to harness the power of Kinesis Data Streams (KDS) and Kinesis Data Firehose (KDF) to construct high-throughput, low latency, pipelines of data across a variety of architectural components leading to scalable and loosely coupled systems. Additional focus is placed on how these stream persistence technologies are used in conjunction with Kinesis Data Analytics to perform advanced, real-time, computations which drive informed business actions and insights.

• Scalable real-time big data analytics using fully managed infrastructure
• Dozens of code examples and walk throughs in both Java and Python

Apache Flink Programming using Table API and SQL

In this course students learn to harness the power of Apache Flink, a modern distributed computing framework, providing a unified approach to both batch and streaming data processing workloads. This course focuses on the relational programming paradigm exposed through the Table API and SQL interface with Python offering intuitive yet powerful abstractions to process vast amounts of data from bounded (batch) or unbounded (streaming) sources.

• Learn batch processing through examples of consuming, processing, and producing results from/to the filesystem in CSV format
• Learn stream processing with examples consuming, processing and producing results from/to Apache Kafka running in a local Dockerized Kafka cluster

Building Python CLI Apps with Click

This is a practical, example heavy, course on building Python based Command Line Interface (CLI) apps. Such CLI tools are used to automate a wide range of simple to complex tasks, freeing users from repetitive mundane activities ultimately increasing productivity. The Click library featured in this course empowers Python software developers with the ability to build rich CLI tools while requiring significantly less code than what’s possible with the regular Python standard library or other programming languages.

After participating in this course viewers will have a strong grasp of building CLI programs containing common types of arguments and options like string, numbers, flags and I/O sources as well as collecting user input via plain text and hidden (aka masked) input prompts and even to compose nested programs with sub commands. Emphasis is also placed on how to write automated tests with your CLI applications harnessing some very useful features of the Click library that simplify writing tests and lead to higher quality software.

Ultimate Guide to Deploying Flask to AWS

In this course you will learn how to deploy Python based Flask applications to the AWS Cloud using both traditional EC2 Virtual Private Servers (VPS) along with the ever increasingly popular Serverless method using Fully Managed AWS service offerings.  In the sections on traditional Server based EC2 deployments I present professional grade, open source, and battle tested technologies such as Nginx web server, uWSGI Python application server, and PostgreSQL database.  For server based deployment methods I cover a variety of architectures from monolithic to distributed N-tier approaches. For Serverless deployments I utilize the AWS Serverless Application Model (SAM) with AWS API Gateway, AWS Lambda and AWS DynamoDB managed services to build a microservices like REST API.  This course covers the most common, industry leading, methods of architecting and deploying Python based Flask applications utilizing the AWS Cloud in ways that are fault tolerant, cost effective, and scalable.