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Cloud Engineer vs DevOps Engineer - Differences and Overlaps of tasks and responsibilities


Cloud Engineer vs DevOps engineer

This is the written version of my youtube video ✍️ 🙂


Introduction


This blog article is about two popular roles in software engineering:


DevOps Engineer and Cloud Engineer role

"DevOps Engineer" and "Cloud Engineer"


Now there is a lot of mix up of these two roles and many people, many companies often use them interchangeably. They mix the tasks and responsibilities of these two very often. There are for example plenty of job descriptions for "DevOps Cloud Engineer" or "Cloud DevOps Engineer" 🙈, which would naturally make you think that they are the same role. But then why would you have two names for the same role? 🤔


And that's exactly what I'm going to discuss and clarify in this article.


Why people mix up those 2 roles

So first of all, let's start by saying that DevOps in Cloud Engineer are actually two different roles with different purposes and objectives. But the reason why people mix them up and even use them interchangeably is, because they often have many overlapping responsibilities and skills and also because for relatively new roles, companies sometimes have hard time defining the boundaries between roles.


Like when a software developer should program full stack web application, do operations, monitoring, build the whole CI/CD pipeline, fix the company's Wi-Fi and change the light bulbs in the office. So basically just putting anything and everything on one person or one job description. 😓

So in this article we're gonna define those boundaries.


✔ Topics of this blog article

  • Objectives of DevOps and Cloud Engineer

  • What a DevOps engineer does

  • What a Cloud engineer does

  • What are the tasks they both do, so the similarities and overlaps between these roles

  • What is that really differentiates them and draws a clear line between the two

And of course since we are on TechWorld with Nana, we're gonna see all of that with actual practical examples, not just some generic explanations. 🙃


DevOps Engineer Role


First let me get one thing out of the way, which is that DevOps engineer was actually not meant as a separate role originally. DevOps is a concept and a set of principles and different engineer roles like software developer, IT operation, server administrator and so on were supposed to implement those DevOps practices and principles. So that was the original idea of DevOps. 💡


However, the reality now looks different with hundreds of thousands of DevOps engineer jobs, which means it actually evolved into its own engineering role, which I personally think makes total sense.


Now that we've established that DevOps engineer is its own role, let's compare the two and let's start with the objectives.


Different Objectives of DevOps and Cloud Engineer


DevOps Engineer Objective 🎯

DevOps Engineer's main objective is to make the process of releasing software fast, efficient, without bugs or issues and they achieve that by automating this whole process. So instead of manual steps of approving the release, testing the application changes, validating that everything works or making sure the security is configured etc.


So the DevOps engineers automate this whole process so that it's faster without manual human interaction points.

DevOps engineer automating release pipeline

And I have a detailed video on that if you want to see exactly what DevOps Engineers tasks and responsibilities are. But in a nutshell that's the objective of a DevOps Engineer.


Cloud Engineer Objective 🎯

Create and manage cloud infrastructure
Create and manage cloud infrastructure

On the other hand, the cloud engineer's main objective is to create and manage infrastructure on cloud, so that applications that companies develop can run on it.


Now you're probably thinking: "create and manage cloud infrastructure? That sounds very vague and not really clear and specific". 🤨


So let's start from the very beginning.



The need for Cloud Engineers


Cloud platforms ☁

First of all, we have hundreds of cloud platforms, which are basically companies who went and bought a whole bunch of computers, server machines, wired up the whole thing, configured the networking etc., built the data centers with all those machines in different locations. And other companies can now rent those servers for the fraction of the cost.


At least that's how it started, with a simple use case to be able to rent a server without having to do the whole infrastructure setup yourself, which is a huge overhead if you only need just a few servers. But over time that evolved into something much more powerful and much more complex.


Now we have cloud platforms that offer way more than just compute resources, like renting a server. You can now get not only your whole infrastructure on cloud, but also a bunch of services on top of that like:

cloud platforms offering many services on top of computing resources
  • your application needs database services

  • cache

  • storage backup

  • maybe you want to run the whole application setup in a Kubernetes cluster

  • you want to store the Docker images on cloud

  • build the whole CI/CD pipeline even

  • and you want to do it in multiple geographic regions

  • And when you have hundreds of employees you also want to manage access to your cloud resources users and permissions

  • and so on


Cloud platforms now offer all that through their cloud services and we have tons of small local cloud platforms with maybe one, two data centers, who only operate in one country or region, then we have some larger ones and the gigantic ones like AWS, Google Cloud, Azure. These three are currently the biggest cloud platforms, with AWS being by far the most highly used one.


So now whether you are a small startup or a large company, you can create your entire setup on a cloud platform, without having to own any infrastructure and often without having to install and configure things from scratch, like set up a Docker image registry or installing a Kubernetes cluster on servers, because this type of things are often provided as managed ready services for you to use by those cloud providers.

AWS services
Many AWS services

So let's take AWS as an example. So with AWS you get tons of services that are already configured on top of the actual underlying physical infrastructure. AWS has services not only for software development, but also for machine learning, big data processing, mobile development. It has many types of storage services based on speed, size, durability.


So you have literally everything on there. But not only that, you also have an option to create and manage your own virtual servers and install things on that yourself or you can let AWS manage the underlying infrastructure completely for you, by using their higher level managed services. Or even the combination of both. 🚀


Complexity to set up and manage 👀

So you have all these options, which is very powerful. But with so many options and so many services also comes the complexity, which means, sure, now you don't have to know how to set up an entire registry and set up database with backups from scratch or manager storage yourself, you can use the cloud services directly for those things.


But now you need to learn how to use those services and integrate them or plug them in into your applications. And those services are specific to the cloud platform that provides them.


You need to learn cloud services

So you need to learn how to use Kubernetes cluster service on AWS, which is called "EKS". Or you have to learn how to use and manage an image registry on AWS, called "ECR".


If you instead go for Azure or Google cloud or you move away from AWS to one of those platforms, now you have to learn how to use the equivalent service on Azure or Google Cloud, because they work a little bit differently.

Cloud specific knowledge needed
Cloud specific knowledge needed

And these platforms provide the same services, but they work differently and have different configuration options. So you have to learn all that specific to the platform. The same way you need to set up the underlying infrastructure, servers, firewall configuration, proxies for your application, security within your network, etc. So you need to learn AWS services, that allow all this configuration.



Cloud Engineer Tasks and Responsibilities


1) Configuration with Best Practices 🛠

And when you use those services, you don't just configure them so that your application runs on it, everything works and that's it. That's actually not enough. You need to configure it reliably and securely.


Because everything may be working fine, but you get millions of users visiting your application and now your whole setup crashes, because your application setup was not designed for such a high load. Or even more important, someone hacks into your setup, wiping out your data or completely messing up your whole setup. Or a new developer accidentally misconfigures something and ruins your AWS infrastructure setup.

Build reliable and secure cloud infrastructure
Build reliable and secure cloud infrastructure

So knowing this cloud specific services and how to configure them reliably, securely, in a proper way for your applications to run smoothly, these are exactly the tasks and responsibilities of a Cloud Engineer.




2) Cloud Platform specific knowledge 💡

I mentioned that cloud platforms are different and their services need to be configured differently. So you need a specific knowledge of that specific cloud provider to properly configure your infrastructure setup there.


This means as a Cloud Engineer, you usually specialize in one cloud platform and learn how to use their services. So you're kind of an expert in that cloud platform. That's why we usually have "AWS Cloud Engineer", "Azure Cloud Engineer" specializations.


Now going back to the initial definition of creating and managing cloud infrastructure, what would be some example tasks of an AWS Cloud Engineer, as part of creating and managing AWS cloud infrastructure? 🤔


Well let's say a company is developing an application or multiple applications, which should run on cloud. So AWS Cloud Engineer's job is to decide, how to create an AWS infrastructure to run those applications, which AWS services to use, should they rent servers and directly configure stuff on them or use managed services instead, which cost more but are easier to configure and manage. Like install and configure cluster database on servers or use the RDS service from AWS where all of that is already configured.


Then we have questions like, which storage to use and how to configure that? Maybe your application needs different types of storages, so how to map those needs to AWS storage types. How to do data backups, so in case of disaster data can be restored. Make sure the applications and access to the whole AWS infrastructure is secure.


Because of the complexity of such large cloud platforms and so many options, it's powerful, but complex. So there are lots of ways of misconfiguring things, so it's not that straightforward. That's why good Cloud Engineers who are able to configure things correctly with best practices, security, etc. are so valuable.


And since Cloud Engineer has knowledge of all AWS Services, they know how to configure what company needs with those services. So they can directly map the company's business needs and requirements to the cloud setup:

Map company needs and requirements into cloud setup
Map company needs and requirements into cloud setup

Like if a company needs geographical distribution all over the world, because they have users all over the globe, Cloud Engineer would help configure that by using the right services and configuring them correctly.


Another example would be, if a company has a microservices application to deploy on cloud. Of course you need expertise in how to configure the cloud infrastructure to make sure a complex microservices application can run on it with production best practices, like redundancy, reliability security, data backup and restore mechanism. Again that's where the Cloud Engineering skills and expertise is needed. 💪


3) Cloud Migrations

Moving to cloud can be especially challenging
Moving to cloud can be especially challenging

Another interesting use case is as we all know, more and more companies are moving to cloud, but many of them aren't starting from scratch, but rather they have an existing on-premise infrastructure and services so they want to migrate that to cloud. And building something from scratch on cloud is often way easier, than migrating an existing infrastructure to it.



Many companies are also using hybrid cloud. So they want to migrate only parts of their local infrastructure to cloud, which means they need integrations between local and the cloud infrastructure. Many companies also do multi-cloud, which means they want to use AWS and Azure, maybe for redundancy like if something happens to one AWS data center you have a fallback. Or just in order to take advantage of strength of different cloud providers and what they are good at, like they want to use AWS computing resources, but company has lots of internal Microsoft applications, so they want to leverage Azure Cloud for that. So with multi-cloud again services and applications need to be connected across cloud platforms and those are all very challenging tasks.


So in those cases, Cloud Engineer would develop the strategy for migrating and help successfully migrate to cloud and create integrations in hybrid or multi-cloud environments, where services need to communicate securely and reliably across those environments. 😎


4) Cost Tracking and Optimization 💰

Monitor and optimize cloud costs
Monitor and optimize cloud costs

Another example is cost tracking, because when you use many resources, many cloud services, combine them in various ways, you need to watch out for the cost or at least be able to predict, how much it will cost. And when you have complex setup with geographic distributions using many cloud provided services for convenience, it can get pretty expensive. And that's again where Cloud Engineers tasks and responsibilities are, to make sure that company doesn't have huge cost overruns on their cloud infrastructure.


Cloud Engineers would also monitor the configured infrastructure, to detect any attempts of hacking into the systems. Maybe the cost is spiking because some resources were misconfigured.


Are service running fine, do they have enough resources to handle the traffic and so on.


5) Automation using Infrastructure as Code 🚀

And finally cloud services and infrastructure can get very complex very fast. Which means you don't want to be managing and configuring or creating things in a complex cloud setup manually. You don't want people joining your company or your cloud team wondering, how the whole infrastructure was created, how it's configured, what's configured, where and why. So you need some transparency of your infrastructure setups as well. And also making sure when someone joins in the cloud engineering team, they can easily get on board and not accidentally misconfigure stuff or ruin the existing setup and so on.


And in case things break, in a cloud setup you want to be able to replicate the same cloud configuration again and recover the setup quickly without having to remember exactly what you did to configure the current setup and what exactly needs to be done.


Cloud engineers use IaC for automation
Cloud engineers use IaC for automation

And that's where infrastructure as code or in short "IaC" comes in.

So Cloud Engineers would automate a lot of their own tasks for infrastructure creation and maintenance using infrastructure as code. Because when you have really complex setups, after some point you can't possibly manually manage that anymore. So you will 100 percent need to have some automation.



Differences and Overlaps between DevOps and Cloud Engineer 👀


Differences between DevOps and Cloud Engineer

Now going back to the original comparison between DevOps Engineer and Cloud Engineer to summarize the differences.


DevOps Engineers automate software release process to make it faster, while Cloud Engineers automate cloud infrastructure and management to make companies cloud infrastructure reliable, fast and secure easily recoverable and so on.

Two very different objectives
Two very different objectives

So obviously two very different objectives. 😌 But here is the overlap. ⬇️


Overlaps between Cloud and DevOps Engineer

Part of software release is its deployment on servers, on infrastructure. So if companies deploying its applications to cloud, DevOps Engineers responsibility naturally becomes to make sure the cloud infrastructure is configured and managed properly to allow for fast deployment, for automated testing, validating whether deployment works with blue green or canary deployment strategies and so on.

Overlapping parts of DevOps and Cloud Engineering
Overlapping parts of DevOps and Cloud Engineering

So DevOps Engineer's job would extend to managing the underlying infrastructure, monitoring that is working fine so the applications can be deployed and run successfully, making sure that it's secure, it's not running out of resources, that it's geographically distributed and so on If application is running in Kubernetes cluster managed by AWS, DevOps engineer would make sure the cluster is running fine, it's correctly configured with security in place and so on.


And again DevOps is about automating things to be fast and efficient, so DevOps Engineers would also use infrastructures code tools to automate infrastructure management monitoring etc., but only the parts that directly affect the release process of the application.


So as you see the cloud infrastructure management that directly affects how fast the application can be released, deployed, recovered and so on is also part of DevOps Engineers tasks. And that's where the main overlap happens. So from this perspective it seems like DevOps kind of includes some of the Cloud Engineers tasks.


So companies usually just hire "DevOps Cloud Engineer", who does everything. 😏

But logically it's not possible for one role to do everything from release management, to infrastructure management, to backup and restore management, cost oversight and so on.


DevOps and Cloud Engineer working together
DevOps and Cloud Engineer working together

So we have additional Cloud Engineer role, that is dedicated to cloud services and managing them and should actually be a help for DevOps Engineer to help each other in their own objectives.


Working together 👏

So the objective of Cloud Engineer, which is reliable secure infrastructure also affects the DevOps Engineer's objective of releasing applications fast, because they have to run on that infrastructure.


Which means Cloud Engineer takes care of managing infrastructure and makes sure it runs reliably, so DevOps engineer can build automated processes on top of that to release the applications and run them on that reliable properly configured cloud infrastructure. And you can even use the controls that Cloud Engineer configured to monitor the application to do the automated validation, implement deployment strategies and so on.


So that's basically the comparison between the two. ✅ I hope I was able to give you some clarity around these two roles and was able to answer your questions around them. 😊



 

Want to become a highly demanded DevOps Engineer? 😎

DevOps engineers are in high demand. If you want to become a highly paid DevOps engineer, be sure to check out our 6-month DevOps bootcamp, which is a complete educational program. You will be able to work as a DevOps engineer from day 1 💪


 

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5 Comments


The roles of Cloud Engineer and DevOps Engineer, while distinct, often overlap in tasks and responsibilities. A Cloud Engineer focuses primarily on designing, implementing, and managing cloud infrastructure, ensuring scalability and reliability. In contrast, a DevOps Engineer bridges the gap between development and operations, streamlining software development and deployment processes through continuous integration and continuous delivery (CI/CD) practices. Both roles require collaboration and proficiency in automation tools. This synergy is akin to the approach of Docutrend, a leading company in modern office and workforce technologies on the Northeast. Docutrend provides products and services that help enterprises maximize growth by leveraging innovative technologies to enhance organizational efficiency and productivity, much like how Cloud and DevOps Engineers enhance operational workflows.

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