Cloud-native architecture
Cloud-native architecture is an approach to designing and operating applications to exploit cloud infrastructure and services, including distributed operation, elasticity, and automated management.
Platform Engineering on Kubernetes
A cloud-native application is software designed to run using cloud-oriented infrastructure and operational practices, commonly with independently deployable services.
- How it is used
- Uses a cloud-native walking skeleton to test service architecture, integrations, delivery practices, and platform needs.
- How deep it goes
- Develops the pattern through a multi-service example, monolith comparison, and runtime experiments; treats the challenge list as non-exhaustive.
- Examples
- Follows a Conference application with frontend and backend services, a Call for Proposals use case, and Kubernetes configuration changes.
- What you can do after
- Operate/configure it by deploying services to Kubernetes, inspecting data flows and scaling, and changing configurations to observe failure behavior.
Read how Platform Engineering on Kubernetes explains cloud-native architecture →
Think Like a CTO
A cloud-native project is a software project architected to exploit the elasticity and managed capabilities of cloud computing platforms.
- How it is used
- Frames cloud-native architecture as a modernization goal and a way to use cloud elasticity rather than merely relocate servers.
- How deep it goes
- Defines automatic scaling and offers decision criteria and warning signs, but stops short of an implementation procedure.
- Examples
- Uses an electricity analogy, a staged server migration, seasonal demand, monthly bills, and release downtime.
- What you can do after
- Evaluate/understand whether a cloud deployment gains elasticity and whether a staged move would reduce modernization risk.
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Effective Platform Engineering
Cloud-native technology is software designed to exploit elastic, distributed, and automated cloud computing capabilities.
- How it is used
- Uses cloud capabilities to build engineering platforms that accelerate software delivery while reducing infrastructure operating work.
- How deep it goes
- Explains API-first consumption, vendor delegation, experimentation, and Kubernetes standardization without detailing complete cluster internals.
- Examples
- Uses cloud-vendor APIs and Kubernetes as concrete examples of on-demand infrastructure and standardized distributed-service orchestration.
- What you can do after
- Apply it via cloud-vendor APIs and Kubernetes to experiment quickly, standardize orchestration, and preserve strategic engineering capacity.
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Go in Practice, Second Edition
A cloud-native application is software designed to exploit programmatic cloud infrastructure for on-demand scaling, failure recovery, and composition from distributed services.
- How it is used
- Deploys containerized applications that scale, recover from failures, and compose microservices on programmatic cloud infrastructure.
- How deep it goes
- Explains container and virtual-machine differences and demonstrates a multistage build, while deferring clustered multi-container interactions.
- Examples
- Uses a container-versus-VM comparison and a Go multistage Dockerfile targeting separate build and runtime images.
- What you can do after
- Build it from scratch by compiling Go inside a multistage Docker image and prepare applications for variable cloud environments.
Read how Go in Practice, Second Edition explains cloud-native architecture →
Amazon Web Services in Action, Third Edition: An in-depth guide to AWS
A cloud-native architecture is a system design that builds on cloud services, elastic resource management, and independently deployable application components.
- How it is used
- Deploys modern web applications by combining load balancing, container orchestration, serverless compute capacity, and object storage.
- How deep it goes
- Explains component roles and demonstrates CloudFormation deployment, task configuration, permissions, service scaling, and rollback.
- Examples
- Uses the Notea note-taking application, CloudFormation templates, ECS task definitions, service configuration, and AWS CLI commands.
- What you can do after
- Operate and configure a containerized web application through CloudFormation, ECS, Fargate, S3, and AWS CLI commands.
gRPC Microservices in Go
A cloud-native application is an application designed to run using distributed, elastic, and container-oriented cloud infrastructure.
- How it is used
- Deploys independently scalable microservices as containerized workloads managed through Kubernetes and CI/CD pipelines.
- How deep it goes
- Explains containers, service discovery, resource configuration, certificates, and release strategies, but stops short of low-level runtime internals.
- Examples
- Uses Product service scaling, Docker images, Kubernetes deployments, CronJobs, TLS certificates, and RollingUpdate, Blue-Green, and canary releases.
- What you can do after
- Build and deploy containerized Go gRPC services to Kubernetes with per-service scaling and selected release strategies.
Read how gRPC Microservices in Go explains cloud-native architecture →
Related concepts
- cloud-native network functionincludes · A cloud-native network function (CNF) is a telecommunications network function designed to run as modular, containerized software on cloud-native infrastructure.
- distributed systemkind of · A distributed system is a computing system whose components run across multiple networked processes or machines and coordinate through communication.
- eventual consistencyuses · Eventual consistency is a distributed-data consistency model that allows replicas to differ temporarily but guarantees they converge to a consistent state after updates propagate, typically when no further updates occur.
- monolithic architecturecontrasts with · Monolithic architecture is a software architecture in which an application's major functionality is organized and deployed as a single integrated unit.
- observabilityuses · Observability is the ability to infer a system’s internal state and behavior from its externally available outputs, such as logs, metrics, and traces.
These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.