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# Containers in the cloud - State of the Art in 2022

Chasing the multi-cloud myth only drowns engineering teams in unnecessary Kubernetes overhead. Simplify your architecture and reduce cognitive load with this structured four-tier framework for modern cloud containers.

- **Speakers:** Federico Fregosi
- **Event:** World Congress 2022
- **Published:** June 15, 2022
- **Duration:** 28:03
- **URL:** https://www.wearedevelopers.com/videos/410-containers-in-the-cloud-state-of-the-art-in-2022

## Summary

The rapid evolution of cloud computing has driven the containerization ecosystem into a state of severe fragmentation, resulting in an overwhelming CNCF software landscape that imposes a high "cognitive load" on engineering teams. Modern system architecture demands a structured methodology rather than a reactive adoption of isolated tools. Compute resources across modern environments can effectively be mapped into four distinct tiers: web application services, managed Kubernetes environments, serverless containers, and raw container primitives. Spanning the major cloud platforms (AWS, Azure, and GCP), this simplified framework utilizes a shared responsibility model to dictate infrastructure strategy based on the organization's desired platform abstraction and engineering capacity.

Across the major cloud providers, unique philosophies distinctively shape these tiers. AWS leads primitive execution with Fargate and handles intricate cluster orchestration via EKS, utilizing native AWS controllers to provision external dependencies like RDS directly through unified YAML configurations. Azure caters heavily to microservices via Azure Container Apps—an opinionated, serverless Kubernetes construct leveraging KEDA and Dapper sidecars to seamlessly simplify external messaging queue integration without custom SDK overhead. Meanwhile, GCP dominates the mature orchestrator space with GKE and Anthos for hybrid infrastructure, complemented by Cloud Run's highly scalable, scale-to-zero application execution layer.

Organizations frequently embrace complex container orchestration driven purely by the "myth of multi-cloud," hoping to achieve absolute vendor-agnostic portability. However, relying strictly on vanilla orchestrators ignores how deeply enterprise microservices physically intertwine with cloud-specific databases, IAM policies, and proprietary event buses. Engineering leadership must recognize that teams are always "choosing an ecosystem" rather than an isolated technology. A pragmatic architectural approach dictates that engineering squads should prioritize serverless containers to reduce API complexity, thereby avoiding the immense operational overhead required to manage Kubernetes the hard way.

**Keywords:** managed kubernetes services, serverless container platforms, container cognitive load, kubernetes multi-cloud myth, cloud ecosystem vendor lock-in, aws fargate primitives, azure container apps, gcp cloud run scaling, dapper sidecar integrations, keda event scaling, cncf landscape fragmentation, infrastructure shared responsibility, microservices orchestration, gcp native binary authentication, hybrid cloud scale-to-zero deployments

## Chapters

1. **Enterprise container migration and historical technology evolution** (00:05) — The evolution of container technology from early Unix system calls to widespread enterprise migration and Docker.
1. **Managing the cognitive load of container ecosystems** (03:00) — Navigating the complex Cloud Native Computing Foundation landscape without a generational approach to container tooling.
1. **Four primary options for running cloud containers** (06:23) — A high-level categorization of cloud container solutions into web, Kubernetes, serverless, and raw containers.
1. **Shared responsibility model for cloud container services** (07:51) — How management tasks shift between cloud providers and developer teams across different container hosting options.
1. **Container hosting options available on Amazon Web Services** (08:53) — Exploring Amazon Web Services solutions including Fargate, Elastic Container Service, EKS, and App Runner.
1. **Container hosting options available on Microsoft Azure** (12:42) — An overview of Microsoft Azure container offerings like Azure Container Instances, AKS, App Service, and Container Apps.
1. **Container hosting options available on Google Cloud Platform** (17:44) — Reviewing Google Cloud container services including GKE with Anthos, Cloud Run serverless execution, and App Engine.
1. **Navigating container orchestration complexity with managed services** (22:27) — Strategies to handle orchestration overhead by leveraging managed services and opinionated Kubernetes subsets.
1. **The realities of multi-cloud portability and vendor lock-in** (25:23) — Why true multi-cloud portability remains a myth due to reliance on provider-specific environments and integrated ecosystems.

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