How to Become an DevOps Engineer in 2020
By: Shane Shown
Tags: Cloud Computing, DevOps, Software Development, Programming, Engineering

DevOps Practices

Now that we’ve gone over what DevOps stands for and what some of its related benefits are, let’s discuss some DevOps practices. A thorough understanding of DevOps methodologies will help clear any lingering queries you may have. That’s not to mention that it will add to your knowledge and come in handy in interviews (which we’ll talk about later).

Continuous integration

One of the biggest problems resulting from teams working in isolation is that merging code when work is completed. It’s not only challenging but also time-consuming. That’s where continuous integration (CI) can help big time.

Developers generally make use of a shared repository (using a version control system such as Git.) with continuous integration. The fact that a continuous integration service simultaneously builds and runs tests on code changes makes it easier to recognize and handle errors. In the long run, continuous integration can help boost developer productivity, address bugs and errors faster, and it can help speed up updates.

Continuous delivery

Evolution forged the entirety of sentient life on this planet using only one tool: the mistake. — Westworld

Robert Ford may have made some critical errors in Westworld, but the man does have some great lines. And he makes a great point about evolution.

Speaking of evolution, many people consider continuous delivery (CD) as the next evolutionary step of CI because it pushes further the development of lifecycle automation.

CD is all about compilation, testing, and the staging environment. This stage of the development lifecycle expands on CI by extending code changes to a testing environment (or a production environment) after the build stage.

If employed correctly, CD can help developers finetune updates by thorough testing across multiple dimensions before the production stage. Continuous Delivery allows developers to run tests such as UI testing, integration testing, and load testing, etc.

Microservices

Microservices are to software design what production lines are to manufacturing. Or, to put it more verbosely, microservices is a software design architecture that takes a hammer to monolithic systems.

Microservices allows applications to be built altogether in one big code repository. Each application consists of multiple microservices and every service is tweaked to excel at one specific function.

For example, let’s look at how Amazon decided to move to microservices. Once upon a time, when Amazon wasn’t the behemoth it is today, their API served them just fine. But as their popularity grew so did their need for a better application program interface.

Amazon decided to get into microservices. Now, instead of a problematic two-tiered architecture, Amazon has multiple services — one that deals with orders, one service that generates their recommended buys list, a payment service, etc. All these services are actually mini-applications with a single business capability.

Infrastructure as code

Thanks to technological innovations, servers and critical infrastructure no longer function the way they did a decade ago. Now, you have cloud providers like Google, that manage business infrastructure for thousands upon thousands of customers in huge data warehouses.

Unsurprisingly, the way engineers manage infrastructure today is way different than what went on previously. And, Infrastructure as Code (IaC) is one of the practices that a DevOps environment may apply to handle a shift in scale.

Under IaC, infrastructure is managed using software development techniques and code (such as version control, etc). Developers can interact with infrastructure programmatically thanks to the cloud’s API-driven model. This allows engineers to handle infrastructure the way they’d tackle application code.

This is important because it allows you to test your infrastructure the same way you would test your code. With IaC at the helm, your system administrators don’t have to stress about issues like the webserver not connecting to the database, etc.

What’s more, IaC can help businesses auto-provision and shape abstraction layers so that developers can go on building services without needing to know the specific hardware, GPU, firmware, and so on, if they have a DevOps team that’s developing infrastructure to push automation forward.

Picture this: Big-time car manufacturers like Mercedes Benz, BMW, and Audi all want to get their hands on the latest in-car experience technologies, right? But if these companies want to ship new services and products they’re going to struggle with the fact everyone on the road has different hardware.

Unless one fine day, the powers that be decide to have universal hardware, edge case devices will continue to act as roadblocks when it comes to development. However, this is where a solid DevOps team can help because they can auto-provision abstraction layers to automate infrastructure services. By solving edge-case challenges in the cloud, a DevOps team can help auto-manufacturers by cutting down costs, and help lessen the burden and strain on developers.

Configuration management

Configuration Management (CM) is important in a DevOps model to encourage continuous integration. It doesn’t matter if you’re hosted in the cloud or managing our systems on-premises, implementing configuration properly can secure accuracy, traceability, and consistency.

When system administrators use code to automate the operating system this leads to the standardization of configuration changes. This kind of regularity saves developers from wasting time manually configuring systems or system applications.

Policy as code

Organizations that have the benefit of infrastructure and configuration codified with the cloud also have the added advantage of monitoring and enforcing compliance at scale.

This type of automation allows organizations to oversee changes in resources efficiently, and it allows security measures to be enforced in a disseminated manner.

Monitoring and logging

Monitoring metrics can help businesses understand the impact of application and infrastructure performance on end-user experience. Analyzing and categorizing data and logs can lead to valuable insights regarding the core causes of problems.

Look at it like this — if services are to be made available 24/7, active monitoring becomes exceedingly important as far as update frequency is concerned.

If you’re scrambling towards code release, you know that it isn’t humanly possible to check all your blind spots. Why? Because not every problem pops up in the user interface. Some bugs work like Ethan Hunt to open security holes, others reduce performance, and then there are the wastrel-type bugs that squander resources.

On the other hand, the generation of containers and instances can make log management feel like finding a needle in a haystack of needles — unpleasant. The sheer amount of raw data to wade through can make finding meaningful information very difficult.

But if you have monitoring systems, you can depend on the metrics to alert the team about any type of anomaly rearing its head across cloud services or applications.

Also, monitoring metrics can help businesses understand the impact of application and infrastructure performance on end-user experience.

Logging can help DevOps teams create user-friendly products or services, or to push continuous integration/delivery forward. Applied together — monitoring and logging can not only help a business get closer to its customers, but they can also help a business understand its own capacity and scale.

For instance, almost all businesses rent out a certain amount of cloud space from cloud providers like AWS, Azure, or even Google Cloud throughout the year. But, if a company isn’t aware of the fact that its capacity can fluctuate due to peak seasons or holidays, or if its team isn’t prepared to handle the ups and downs by creating provisioning layers then things can get pretty ugly — like a website crash.

Communication and collaboration

One of the fundamental cultural aspects of DevOps is communication and collaboration. DevOps tooling and automation (of the software delivery process) focuses on creating collaboration by combining the processes and efficiencies of development and operations.

In a DevOps environment, all teams involved work to build cultural norms relating to information sharing and facilitating communication via project tracking systems, chat applications, and so on. This allows quicker communication between developers and helps bring together all parts of an organization to accomplish set goals and projects.