Master Cloud Native Applications Architecture Best Practices

Explore cloud native architecture and its components. Identify building blocks of cloud native apps and systems, review cloud services, and understand the Cloud Native Computing Foundation definition for course alignment.

Explore 2023 cloud computing trends, including hybrid and edge computing, cloud native platforms, and automation with Aiops, highlighting the growing role of containers, Kubernetes, and serverless in accelerating digital initiatives.

Learn the four-layer cloud architecture—business applications, database, networking, and infrastructure—and how compute, storage, container, ai and ml, analytics, and vpn and sd-wan services integrate to build cloud solutions.

Discover cloud native concepts and components—containers, service meshes, microservices, immutable infrastructure, and declarative APIs—focusing on resilient, manageable, observable, and automated architectures.

Explore the key building blocks of cloud native systems, including microservices, containers, and orchestration, along with DevOps practices, declarative APIs, service meshes, immutable infrastructure, data engineering, and hybrid cloud.

Explore cloud services for architecting cloud native apps, including compute, storage, serverless, databases, migration, integration, content delivery, security, analytics, and developer tools.

Explore containerization and cloud native architecture, covering 2023 trends, container life cycle, development and operation best practices, orchestration with Kubernetes, and container security.

Explore 2023 container trends driving cloud native architectures, including migration of apps to containers and Kubernetes adoption by hyperscalers. Examine container registries, serverless trends, and hybrid multi-cloud adoption.

Compare bare metal, virtual machines, and container configurations for running microservices applications. Explore how containers offer lightweight process isolation, portability, and orchestration in cloud native deployments.

Identify key container concepts including dockerfile, container image, file system layers, container configuration, and OCI formats; explain engines, runtimes, manifests, repositories, and orchestrators that deploy and manage containers.

Develop containers in a DevOps pipeline by keeping images light, one microservice per container, avoiding hard-coded configs, enabling logging, automating builds, and scanning for vulnerabilities.

Trace the container life cycle from creation and image storage to production deployment, then running, pausing, stopping (memory cleared), leaving the environment, or kill for immediate termination.

Keep containers small to improve loading times and cost efficiency. Track health, enable log access, define metrics, run as non-root, set resource limits, and use persistent data stores in production.

Explore how container orchestration and management tools scale production deployments, from basic container services to managed Kubernetes, self-managed clusters, and multi-cloud options.

Understand how Kubernetes orchestrates containerized microservices with pods, nodes, and clusters. Learn how the control plane schedules workloads, balances load, and enables rolling updates for high availability.

Explore container orchestration best practices with a focus on auto scaling, fault tolerance across nodes, Kubernetes references, security through least privilege, version-controlled configurations, and ci cd integration.

Strengthen cloud native security by applying the four C's: code, container, cluster, and cloud, across development, run, and orchestration, with shift-left security, image signing, least privilege, and continuous scanning.

Explore inter-service communications techniques and technologies powering cloud native applications, review 2023 trends, and learn the basics and best practices for APIs, gRPC, message queues, and service mesh in microservices.

Explore 2023 microservices trends, including rising adoption, legacy cloud-native migrations, service mesh, and enhanced monitoring with Aiops and low-code tools in a headless Mach architecture.

Explore best practices for microservices development in cloud native architectures, including containerization, single responsibility, independent databases, asynchronous communications, gateways, health monitoring, and orchestrated scalability.

Explore database strategies for cloud native microservices, including polyglot persistence, private data stores, and patterns like saga and API composition to ensure data consistency.

Explore the twelve-factor methodology for cloud native, containerized microservices. Apply its principles: codebase, dependencies, configurations, backing services, build/release/run, stateless processes, port numbers, concurrency, disposability, dev/prod parity, and admin processes.

Explore inter-service communications techniques for cloud native applications, review 2023 industry trends, and learn best practices for APIs, gRPC, message queues, and service mesh in microservices.

Study cloud native inter service communications trends, including APIs, service mesh, gRPC, and asynchronous methods, with emphasis on API gateways in hybrid multi-cloud environments.

Explore synchronous and asynchronous microservice communications, including http APIs and gRPC, and amqp messaging; compare Kafka and RabbitMQ for scalable data exchange, while considering latency, security, and data formats.

Explore APIs as a foundational inter-program communication method in cloud native environments. Learn how API gateways reduce traffic and latency, enable authentication, and support REST and JSON client interactions.

Explore gRPC, a binary protocol over HTTP/2 for fast, low-latency inter-service communication with protocol buffers, enabling cross-language microservices, streaming, health checks, and API gateway translation.

Learn asynchronous communications with message queues such as AMQP, Kafka, and RabbitMQ. Use 1-to-1 and 1-to-many patterns to build decoupled microservices that process in parallel.

Discover how a service mesh acts as a shadow infrastructure for cloud native microservices, using sidecar proxies to separate communications from business logic and enable secure, observable inter-service traffic.

Explore cloud migration of legacy applications to cloud native architectures, review 2023 industry trends, and outline the business case and strategic considerations for successful cloud migration.

Examine legacy application migrations, market growth from 20 billion to 50 billion by 2028, and cloud-based modernization drivers. See how COBOL, ADA, PL/1, RPG and assembler heritage shapes modernization efforts.

Explore the challenges of migrating legacy applications to cloud-native platforms, including long release cycles, monolith complexity, and limited logging and skills.

Explore DevOps for cloud native applications, review 2023 industry trends, and cover CI/CD pipelines, tools, DevSecOps practices, and curated resources to deepen your understanding.

Discover 2023 devops trends shaping cloud native delivery, from devsecops and security integrated life cycles to GitOps, Kubernetes, low-code, AI ops, and infrastructure as code.

Explore the DevOps life cycle and DevSecOps aligned CI/CD pipelines for cloud native applications, detailing continuous integration, continuous delivery, secure deployment, and automated release practices.

Explore devops tool sets across the lifecycle, including Git and TFS for version control, Jenkins for building, and AWS, Azure, and Terraform for provisioning and CI/CD pipelines.

Discover DevOps best practices, including commit early and often, continuous integration, automated pipelines, environment agnostic builds, canary and blue-green deployments, and DevSecOps security, with a focus on culture and collaboration.

Implement devsecops by embedding security across development, testing, and deployment. Enforce secure coding, scan open source for vulnerabilities, protect secrets, automate, and monitor the full ci/cd pipeline.

Explore data engineering architecture and best practices, including ETL and ELT pipelines and related use cases. Learn architectural building blocks and cloud services powering organizational data pipelines.

Explore current data engineering trends, including data ops, data mesh, data as a service, edge analytics, and hybrid and sovereign cloud strategies, and learn scalable pipeline design.

Develop automated data pipelines that ingest, process, and store data. Explore data engineering use cases such as legacy migration, AI/ML model training, and IoT streaming.

Explore data engineering processes from ingestion to loading, comparing batch and real-time pipelines, ETL and ELT, and data storage in data lakes and warehouses with tools like Flink and Spark.

Explore the ETL pipeline, from extract and cleansing to transform and load into a data warehouse, and see how staging, pre-processing, and business rules support analytics and data insights.

Extract and load data first, then transform it later to speed ingestion and leverage cloud resources, with data stored in a data lake before transformation.

Discover architectural building blocks for data engineering pipelines, including automation with AWS Step Functions and Cloud Composer, scalability, latency, storage options, monitoring, and end-to-end security and cost considerations.

Explore cloud services for building data engineering pipelines across ingestion, transformation, storage, and analytics. Identify tools like Apache Kafka, Spark, Amazon S3, Airflow, Athena, and Redshift to support end-to-end workflows.

Explore hybrid cloud architecture and best practices for building cloud native applications, reviewing 2023 industry trends, business use cases, key technologies and services, and practical steps to implement hybrid clouds.

Explore how hybrid cloud combines on premises and public clouds, multi-cloud adoption, cloud bursting, edge clouds, and aiops to support development and distributed, integrated applications across environments.

Explore the hybrid cloud concept, its growth potential, and how to set up virtual networks, connectivity, monitoring, availability zones, security, and slas for on-premises and public cloud environments.

Explore how hybrid cloud delivers flexibility and cost savings via experimentation, prototyping, and workload distribution. Enable cloud bursting and high availability across on premises and public cloud.

Explore the key components of a typical hybrid cloud network, including VPC, subnets, routing tables, gateways, VPN options, dedicated connections, and security and monitoring strategies.

Define your organization's cloud strategy, identify business use cases and application workloads, assess cloud provider capabilities, and implement monitoring, governance, and SLAs to execute a hybrid cloud strategy.

Explore AWS and Azure architecture guidelines and CNCF recommendations to transform legacy apps into cloud native architectures, with resources to master these guidelines.

Explore how major cloud provider guidelines, including AWS Well-Architected, Azure Well-Architected, and CNCF's recommended journey to cloud native, inform generic best practices for designing high-performing, secure, reliable cloud applications.

Explore the AWS Well-Architected Framework with six pillars—operational excellence, performance efficiency, cost optimization, security, reliability, and sustainability—plus design principles, best practices, lenses, and an assessment tool.

Explore Microsoft Azure's well-architected framework with five pillars: operational excellence, performance efficiency, cost optimization, security, and reliability, and learn how Azure Advisor, design principles, and reference architectures guide cloud architectures.

Explore CNCF's ten-stage cloud native trail map to define a digital transformation roadmap, from containerization to software distribution with Kubernetes, Prometheus, Linkerd, Envoy, and Notary.