Building cloud native applications
What you'll learn, and how you can apply it
After this training, you will understand what makes an application a cloud-native application and get an excellent foundation to get started with designing and building cloud-native applications. Additionally, you will learn how to:
- decide when to use containers vs. functions
- set up the environment for development and debugging
- set up CI/CD pipelines for builds and deployments
- set up monitoring for key application metrics
- decide on communication patterns
- utilize a service mesh to do zero-downtime deployments, A/B tests, and canary deployments
Who is this presentation for?
This training is for software developers and architects who want to get an overview of cloud-native development and principles and start developing cloud-native applications.
Hardware and/or installation requirements:
Make sure you have a computer with installed Docker and Kubernetes—you can either use Minikube or Docker for Mac/Windows or even a managed Kubernetes solution from one of the cloud providers.
Cloud native fundamentals
- Fallacies of distributed computing and why they are still valid in a cloud-native world
- Availability and SLAs in cloud-native applications
- Microservices, containers, and functions
- Meaning of serverless computing
- Application modernization
Architecting cloud-native applications
- Choosing the right compute option
- Choosing the right data option
- Service communication patterns
- Understanding gateways, ingress, and egress
- Defense in depth
Developing cloud-native applications
- Development process – tools and environments
- Local and in-cloud debugging
- Configuration and secret management
Testing cloud-native applications
- Testing in the cloud-native world
- Development, testing, staging environments
- Testing in production
- Mock services
Operating cloud-native applications
- Setting up effective CI/CD pipelines
- Builds, deployments, and releases
- Importance of monitoring and observability
- Centralized logging and visualizing metrics
- Alerting and on-call
- What is it and why is it interesting?
- Traffic management: Zero downtime deployments, A/B testing, Canary
- Ingress and egress
- Testing with the service mesh
- Developing resiliency services
- Security in the mesh
- Portability considerations
- Packaging options
- Special cases: Air gapped environments
About your instructors
Peter Jausovec is a software engineer with more than 10 years of experience in the field of software development and tech. During his career, he spent time in various roles, starting with QA then moving to software engineering and leading tech teams. His early career was mostly focused on developer and cloud tooling, however, in recent years he has been focusing on developing distributed systems and cloud-native solutions.
Boris Scholl is a Product Architect with the Azure Compute engineering team focusing on the next generation of distributed systems platforms and application models. He has been working on Azure Developer tools and platforms in various product engineering roles since late 2011. Boris re-joined the Azure Compute team in 2018 after having spent the 18 months outside Microsoft leading an engineering team to work on a microservices platform based on Kubernetes and Service Meshes. His work on distributed systems platforms has resulted in several patents about cloud computing and distributed systems. Boris is a frequent speaker at industry events, a contributor to many blogs, instructor for distributed computing topics and the lead author of one of the first books about microservices and Docker on Azure (Microservices with Docker on Azure).
Get the Platinum pass or the Training pass to add this course to your package. Early Price ends 20 September.
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