Quick Summary

Over the past decade, the concept of “the cloud” has evolved dramatically. What began as a way to replace on-premise servers with rented infrastructure has now grown into a specialized field of its own — cloud engineering. This evolution is defined by the emergence of the cloud computing model, which provides frameworks for how cloud services are delivered and managed. At its core, cloud engineering is about applying engineering principles to cloud systems so that they are not only functional, but also reliable, scalable, secure, and cost-effective.

Today, it is not enough to simply migrate workloads into the cloud. The real value comes from designing with the cloud in mind, enabling organizations to build and deploy cloud applications that are scalable, cost-effective, and easy to manage. It is about building systems that make use of automation, and cloud-native services. Enterprises are embracing hybrid and multi-cloud approaches as part of their cloud adoption strategies, strategically integrating multiple cloud computing models to meet workload predictability, regulatory compliance, and scalability needs. They no longer want to be tied to a single platform, nor can they afford to compromise compliance or regional performance. Hence, the adoption of hybrid and multi-cloud infrastructure is on the rise. Dive deeper in this article to explore the cloud engineering landscape and the engineering practices that make cloud systems robust and efficient.

Introduction

Cloud engineering refers to designing, building, and managing cloud infrastructure. The core engineering principles are applied to build resilient, scalable, secure, and cost-effective systems that can be adapted to business needs. When cloud technology came into being, it started as a place to host servers to replace on-premise infrastructure, shifting the management of comprehensive computing infrastructure—including hardware and data center resources—into the cloud. The foundational components of cloud engineering rely on robust IT infrastructure, which is critical for enabling scalable and efficient cloud solutions. The onset of automation replaced manual setups with Infrastructure as Code (IaC), and it made repeatable and code-driven deployments possible. The scalability and rapid growth of cloud engineering are driven by the vast computing power and computing capacity available in modern cloud environments, supporting advanced applications and diverse enterprise needs. A report published by GlobeNewswire also suggests that the global cloud computing market is forecasted to grow from $766 billion in 2025 to $3.5 trillion by 2035.

Why Cloud Engineering Matters?

Cloud Infrastructure can manage scalability on demand, offering scalability benefits that allow businesses to flexibly grow without investing in new servers. The engineering frameworks help in cost optimization by using automation, serverless designs, and right-sizing for enterprises, with cost savings being a primary benefit of cloud engineering.

Cloud systems have built-in security features that make them a reliable solution for critical industries such as finance, healthcare, and automotive. The cloud engineering field focuses on building reliable and resilient systems with fault-tolerant mechanisms to tackle outages or server failures, with disaster recovery playing a crucial role in ensuring business continuity and data protection. Managed services, such as managed storage and databases, further simplify system administration and enhance operational efficiency. It also powers adoption of AI/ML, IoT, and edge computing at scale. In addition, it enables global reach as applications can be deployed closer to customers worldwide using cloud regions and edge networks.

Core Components of Cloud Architecture

1. Compute : It is the brain of the cloud and the processing power behind the applications. There are various types of computers – Virtual Machines (VMs), containers, and serverless functions. In VMs, the complete server environment is on the cloud and is recommended for legacy applications. The operating system in VMs and containers manages the hardware resources and provides a foundation for application deployment. On the other hand, containers are lightweight, portable, faster to deploy than VMs, and ideal for microservices. In serverless functions (AWS Lambda, Azure Functions), the code runs only when triggered, allowing developers to focus on application code and not on managing hardware or software resources. Serverless computing abstracts away the need to manage traditional software resources, letting users concentrate on their application code. Self service provisioning enables users to access and manage compute resources on demand without manual intervention. The choice of compute model directly impacts scalability, performance, and cost-efficiency, with cloud platforms providing scalable resources that can expand, or contract based on workload needs. Cloud providers also manage other computing resources such as storage, processing power, and network solutions, allowing organizations to utilize these without maintaining their own physical infrastructure.
2. Storage : Data is stored and organized here. Based on the application, different storage types can be selected. Object storage stores unstructured data such as videos, logs, and images. Block storage is used for databases and transactional systems. File storage is best suited for shared access and collaboration. Cloud providers manage other computing resources, including storage and network solutions, to ensure efficient and reliable data management.
3. Networking : A robust network ensures seamless and secure data flow between apps, users, and systems. Virtual networks, such as Virtual Private Clouds (VPCs), are isolated private sub-networks designed to enhance security and control. On the contrary, load balancers distribute traffic to prevent crashes during demand spikes. Firewalls and security groups aim to protect systems by controlling inbound and outbound traffic
4. Platform Services : Platform services are pre-built cloud services that help to accelerate the development time of platforms without the need to reinvent the wheel. It eliminates the need to rebuild the core technology from scratch. A cloud is the underlying infrastructure and environment that supports cloud services, such as IaaS, PaaS, and SaaS offerings. Cloud platforms are comprehensive environments that provide pre-configured tools, scalable resources, and managed services for deploying applications and managing data. There are various platform services available, such as AI/ML APIs, Kubernetes services, and analytics platforms. Platform as a service (PaaS) is a managed development environment that abstracts the underlying infrastructure, enabling developers to focus on application development without managing hardware or software layers. Data analytics is also available as a managed service or platform feature in the cloud, allowing organizations to gain insights and support decision-making. Cloud service offerings encompass a wide range of solutions provided by cloud providers, including infrastructure, platforms, and software as a service.
5. Cloud Deployment Models : There are various kinds of cloud deployment models. A public cloud is a fully managed infrastructure from providers such as AWS, Azure, or Google Cloud. While a private cloud has a dedicated infrastructure with strict security, performance, or compliance features. It is a preferred solution for highly regulated sectors such as banking and defense.

Nowadays, enterprises are looking for a reliable system where all stakes are not put solely on a single system. Hence, hybrid cloud and multi-cloud infrastructure are being actively adopted. Hybrid cloud is a mix of private and public cloud, where the sensitive workloads stay private while analytics or customer-facing services run on the public side. In multi-cloud, there are multiple providers to avoid vendor lock-in and increase resilience.

Engineering Practices in the Cloud

These principles apply software engineering discipline to cloud computing and help scale the cloud using automated and systematic processes. The primary goal is to manage the cloud environment efficiently and securely.

1. Infrastructure as Code (IaC) : IaC is the blueprint of the entire cloud setup where codes for servers, databases, networks, and more are written in a text file. Tools such as Terraform and AWS CloudFormation take this code and automatically create the cloud infrastructure. This practice eliminates configuration drifts and ensures that every environment (development, staging, production) is identical. The entire infrastructure can be easily recreated using a single command. The infrastructure code can be stored in a version control system such as Git, thus allowing teams to track changes, review, and roll back if needed.
2. CI/CD Pipelines (Continuous Integration/Continuous Delivery) : It is an automated process that takes code changes and automatically builds, tests, and deploys them to a production environment. In CI, software developers merge their code changes into a central repository. A built-in server automatically runs tests to catch integration errors early. Once the code passes CI, it is automatically prepared for a release. This means it can be deployed to a production environment with the push of a button. By implementing the CI/CD pipeline, software developers can quickly fix and deploy the code. It allows the development teams to release new features, making it easier to fix any issues promptly. CI/CD pipelines play a crucial role in streamlining the software development lifecycle by automating testing and deployment, which improves the efficiency and reliability of software development in modern cloud environments.
3. Security Engineering : In security engineering, security controls are directly integrated into the design and implementation of cloud infrastructure and applications. It is essential to authenticate and authorize every user or device, whether within or outside the network. Data is encrypted during transit and storage.
4. Reliability Engineering : A reliable system can withstand failure and recover automatically. Reliability engineering ensures that cloud systems are designed with failover mechanisms that automatically take over if the primary system fails, maintaining continuous operation. These systems are configured to detect and fix issues automatically. One of the core features of such a system is auto-healing. To identify weak points, chaos testing is done. In this testing, failures are introduced intentionally to see how the system responds. Following such practices minimizes downtime and service interruptions, which is crucial for customer satisfaction and business continuity.
5. Cost Optimization : Cost optimization techniques involve continuously monitoring and managing cloud usage to maximize business value and minimize unnecessary spending. Various tools are used to track and monitor the cloud resources used, their users, and cost. This data helps deploy the right cloud resources and avoid overprovisioning. Organizations can do more with less by optimizing cloud resources, and that is indeed one of the key benefits of cloud computing. Additionally, cloud-based solutions, especially SaaS, reduce the need for software maintenance by shifting responsibility for installation, updates, and ongoing support to the provider, simplifying operations, and lowering costs for businesses.

Conclusion: Why Cloud Engineering is the Future

In today’s world, every industry is adopting digital transformation, be it banking applications or smart factories. Technologies such as edge computing and 5G also rely on cloud infrastructure for real-time data processing. A reliable internet connection is essential for accessing cloud services, enabling seamless global collaboration, and ensuring uninterrupted data flow between users and cloud infrastructure. Hence, the cloud is emerging as the default backbone driving this transformation. Cloud engineering also plays a major role in the adoption of AI. With the AI model being trained and deployed primarily on cloud, the cloud infrastructure requirements are set to grow.

It is important to stay resilient in this competitive landscape, hence adopting and embracing cloud engineering will benefit companies. It can help to innovate faster and operate efficiently.

eInfochips is a trusted partner for all cloud engineering solutions. Our expertise spans from cloud migration and architecture design to DevOps automation and cloud-native application development. We help enterprises across diverse sectors to set up their cloud infrastructure and ensure seamless integration and enhanced performance. Our team of cloud experts have successfully developed a cloud-based IoT platform for a smart home company. It enabled real-time device monitoring, predictive analytics, and seamless integration with third-party services. Another testament to our expertise is the work we have done for a healthcare provider. The team at eInfochips migrated legacy systems to AWS, ensuring compliance with HIPAA regulations and reducing operational costs by 30%.