Category: DevOps Culture

Choosing the Right Programming Language

In software engineering, selecting a programming language is a pivotal decision for any organization. The appropriate language contributes to a streamlined development workflow and yields a resilient software solution that facilitates swift and efficient debugging, documentation, enhancement and maintenance. On the other hand, selecting an unsuitable language can set a project on a course for failure from the onset. Given the multitude of available options and the magnitude of this decision, how can programmers ensure they make the most judicious language choice?

A comprehensive and effective decision-making process begins with a thorough understanding of the current landscape, historical context and the evolutionary trajectory of programming languages. It is also imperative to critically appreciate the benchmarks employed by computer scientists and the industry’s best practices in language selection. Programmers who invest time to enhance their expertise in these domains will mitigate the risk of selecting a language deficient in essential features or one poised for obsolescence, thereby safeguarding the resulting product’s longevity, relevance and success.

The evolution of programming languages

Charles Babbage is credited with creating the first computer between 1833 and 1871. He spent nearly 40 years perfecting his invention, which ultimately could perform simple calculations. While Babbage is recognized for building the initial computer, in 1883, Ada Lovelace played a pivotal role by devising the programming language for Babbage’s invention. Today, 140 years later, more than 500 distinct programming languages facilitate human-computer interaction. The continuous adaptation and innovation of programming languages have paralleled the dynamic evolution of technology.

Contemporary programming languages, such as Swift, Kotlin and Go, exhibit more user-friendly syntax and enhanced ease of use than their predecessors, including SQL, MATLAB and C. Recent languages often integrate features that were unavailable just a few years ago. As such, programmers have the ability to select from a diverse array of languages, identifying the most suitable for their project that facilitates the efficient completion of tasks. For example, Swift is used in Mac and iOS platforms, C# is tailored for the .NET Framework and JavaScript, renowned for constructing the internet, is a testament to the varied roles these languages play in diverse technological domains.

Selecting the right programming language

With vast options of programming languages available, one of the greatest challenges is determining which is best suited for a particular project. Comparing the various features and syntaxes of languages can be complicated. Based on recent industry trends, Table 1 details the key programming languages in popular areas/domains.

Area/Domain	Programming Languages
Web development	JavaScript, Java, HTML5, Ruby, TypeScript
Mobile development	Kotlin, Swift, Objective-C, ++, C#
Data science	Python, R, SQL, Scala, Julia, MATLAB
Artificial intelligence and machine learning	Python, R, Java, Lisp, Prolog, JavaScript
Cloud computing	Java, Python, JavaScript, Golang, .Net Core
Cybersecurity	Perl, C++, SQL, Ruby, Rust, Assembly

Table 1: Key programming languages by domain

Scientifically benchmarking programming languages

One of the most efficient and effective ways to differentiate programming languages is through benchmarking, a process through which computer scientists analyze and compare programming languages. For instance, they may compare the performance of different programming languages directly against each other. They may also assess performance differences between different compilers or runtimes of the same language with the same source code. In addition, they may assess real server environments such as hosted cloud VMs or Docker/Podman and their effects on the performance of various programming languages.

Numerous renowned computer scientists have begun benchmarking programming languages, making it easier to tell them apart and select the best language for a particular task. The Computer Language Benchmarks Game is a popular free software project that compares how popular programming languages implement simple algorithms. Programmers can view results and better comprehend each language, its speed and optimal use cases. Additionally, several reputable websites, such as Programming Language and compiler-Benchmarks and Kostya-benchmark, provide computer scientists with side-by-side comparisons of different programming languages, taking into account various performance issues.

Ranking of programming languages by popularity (2023)

When selecting a programming language, some of the factors for programmers to consider include the targeted platform, production time, language elasticity, community/support, the programmer’s experience with the language, and the language’s current popularity. Popularity is an important factor because even though more than 500 programming languages are available, most of the industry relies on just 10, making those the most likely to remain in use. Table 2 highlights the 10 most popular programming languages based on the PYPL Index, which assesses how frequently language tutorials are searched for on Google and Stack Overflow’s Developer Survey 2023.

Ranking	PYPL Ranking September 2023	Stack Overflow’s Developer Survey 2023
#1	Python	JavaScript
#2	Java	HTML/CSS
#3	JavaScript	Python
#4	C#	SQL
#5	C/C++	TypeScript
#6	PHP	Bash/Shell
#7	R	Java
#8	TypeScript	C#
#9	Swift	C++
#10	Objective-C	C

Table 2: 2023 10 most popular programming languages

When making the final programming language selection, it is essential to remember that no programming language will be perfect for any particular project. As such, programmers need to allow for some flexibility in the selection process. Determine what is most important, such as speed, performance or fewer lines of code, and then sacrifice other areas to ensure a solution that best fits the identified priorities.

The future of programming languages

Today’s programming world is centered around artificial intelligence (AI) and machine learning (ML). As such, languages like Python, currently a driving force behind AI, will likely grow in popularity. Moving forward, programmers can expect an increase in the popularity of JavaScript, which dominates web browsers; Java, which is prevalent in the business world; Kotlin, which is widely used in apps and C++, which is used frequently in system-level programming and game development.

As technology evolves, programming languages—both existing and yet-to-be-developed—will play a pivotal role in shaping the future of a digital landscape. Their role in incorporating new tech features, expanding ML, augmenting AI and furthering the internet-of-things (IoT) will become increasingly critical.

As new languages appear and evolve, old languages will fade away. To that end, Analytics Insight recently published a list of 10 programming languages, including currently well-used languages like Visual Basic and COBOL, which it expects to dramatically decrease in popularity and use by 2030. For this reason, it is essential for developers and decision-makers to stay up to date on the ever-evolving world of programming languages. As existing languages are retired and new ones enter the marketplace, it is imperative that professionals learn promising new languages and continually upskill. Those who commit to ongoing training and education will simplify the programming language selection process, increase their chances of running a successful project, and solidify their position in an increasingly competitive marketplace. Those who don’t risk going extinct alongside once-popular programming languages.

January 3, 2024

Skillsoft Survey Sees AI Driving Increased Need to Retrain IT Teams

More organizations than ever will need to invest in IT training as advances in artificial intelligence (AI) transform roles and responsibilities in the coming year.

A survey of 2,740 IT decision-makers conducted by Skillsoft, a provider of an online training platform, finds two-thirds (66%) were already dealing with skills gaps in 2023. As AI becomes more pervasively applied to the management of IT, that skills gap is only going to widen given the limited pool of IT professionals that have any experience using AI to manage IT.

Skillsoft CIO Orla Daly said it’s already apparent AI creates an imperative for training because there are simply not enough IT people with the requisite skills required. In fact, the survey finds nearly half of IT decision-makers (45%) plan to close skills gaps by training their existing teams. That training is crucial because the primary reason IT staff change jobs is a lack of growth and development opportunities, noted Daly.

While there is naturally a lot of consternation over the potential elimination of IT jobs, in the final analysis, AI will add more different types of jobs than it eliminates, adds Daly. Each of those jobs will require new skills that will need to be acquired and honed, she notes. “Training is the price of innovation,” said Daly.

In the meantime, there is much interest in finding ways to automate existing IT processes to create more time for IT teams to experiment with AI technologies, said Daly.

The report also finds well over half of IT decision-makers (56%) expect their IT budgets to increase to help pay for new platforms and tools, compared with only 12% expecting a decrease.

It’s not clear to what degree AI will transform the management of AI, but it’s already apparent that many manual tasks involving, for example, generating reports are about to be automated. The instant summarization capabilities that generative AI enables also promise to dramatically reduce the time required to onboard new members to an incident response team. Rather than having to allocate someone on the team to bring new members up to speed, each new member of the team will use queries framed in natural language to determine for themselves the extent of the crisis at hand.

In addition, many tasks that today require expensive specialists to perform might become more accessible to a wider range of organizations as, for example, more DevOps processes are automated. That doesn’t necessarily mean that DevOps as an IT discipline disappears as much as it leads to the democratization of best DevOps practices.

Each IT organization in the year ahead will need to determine to what degree to rely on AI to manage IT processes. It may take a while before IT teams have enough confidence in AI to rely on it to manage mission-critical applications but many of the tasks that today conspire to make the management of IT tedious will undoubtedly fade away. The challenge and the opportunity now is identify those tasks today with an eye toward revamping how IT might be managed in the age of AI tomorrow.

January 2, 2024
Five Great DevOps Job Opportunities

devopsy.kinsta.cloud is now providing a weekly DevOps jobs report through which opportunities for DevOps professionals will be highlighted to better serve our audience.

Our goal in these challenging economic times is to make it easier for DevOps professionals to advance their careers.

Of course, the pool of available DevOps talent is still relatively constrained, so when one DevOps professional takes on a new role it tends to create an opportunity for others.

The five job postings shared this week are selected based on the company looking to hire, the vertical industry segment and, naturally, the pay scale being offered.

We’re also committed to providing additional insights into the state of the DevOps job market. In the meantime, for your consideration:

CareerBuilder.com

Belcan Federal
Anaheim, California
Lead DevOps Engineer
$140,000 to $170,000

Dice.com

Trinity IT Services
Remote
DevOps Lead
$115,000 to $165,000

SimplyHired.com

EMMES Corp
Rockville, Maryland
DevOps Engineer
$115,000 to $145,000

Indeed.com

VyncaCare
San Francisco, California
DevOps Engineer
$110,000 to $140,000

LinkedIn

L3Harris Technologies
Colorado Springs, Colorado
Senior DevOps/AWS Specialist
$91,500 to $170,500

January 2, 2024
Best of 2023: ‘Scrum == Cancer’ ¦ Plus: Linux 6.5 Ships

As we close out 2023, we at devopsy.kinsta.cloud wanted to highlight the most popular articles of the year. Following is the latest in our series of the Best of 2023.

Welcome to The Long View—where we peruse the news of the week and strip it to the essentials. Let’s work out what really matters.

This week: Scrum sucks, sources say; and here comes the Linux 6.5 kernel. (more…)

December 29, 2023
Best of 2023: Microservices Sucks — Amazon Goes Back to Basics

As we close out 2023, we at devopsy.kinsta.cloud wanted to highlight the most popular articles of the year. Following is the latest in our series of the Best of 2023.

Welcome to The Long View—where we peruse the news of the week and strip it to the essentials. Let’s work out what really matters.

This week: Amazon Prime Video has ditched its use of microservices-cum-serverless, reverting to a traditional, monolithic architecture. It vastly improved the workload’s cost and scalability. (more…)

December 28, 2023
DevOps 2024: DevOps Isn’t Dead; Long Live DevOps

Well, it has been quite the year in general and quite the year as it relates to DevOps. As I sit here on the cusp of the 10th year of publishing devopsy.kinsta.cloud, I look back and recognize how much DevOps has grown, evolved, matured and shifted over time. As was the case 10 years ago, there are those who say DevOps does not work or insist that DevOps is dead. My response:

“They stab it with their steely knives
But they just can’t kill the beast.”
~ Eagles, Hotel California

No, it seems you can’t kill DevOps. Much like Obi-Wan Kenobi being struck down by Darth Vader, DevOps, it seems, is more powerful than ever. It has seeped into the very fabric of IT.

While cloud native has become the dominant form of computing, the fact is you really would not have cloud-native stacks without DevOps fundamentals enabling them. As cloud-native continues to grow, so does DevOps.

One of the interesting things about DevOps is the fact that it really has become an enterprise toolset. While initially scaling DevOps across an organization was challenging (and still is for many), it has become much more common to see large enterprises—or ‘horses,’ as Gene Kim would call them—adopting DevOps methodologies across significant parts of their IT teams.

Speaking of Gene Kim, some have pointed to his recent announcement that he’s changing the name of his DevOps Enterprise Summit (DOES) to Enterprise Technology Leadership Summit as evidence of DevOps’ demise. We will be interviewing Gene on Techstrong.TV the first week in January 2024 and will address this with him, so stay tuned. But without giving out too many spoilers, Gene felt that DOES had expanded beyond just DevOps to encompass a general technology discussion (hey, AI will be in there for sure) aimed at technology leaders (C-suite). But rest assured that Gene Kim does not think DevOps is dead.

Looking ahead to 2024, I see DevOps making broad inroads into the SMB and mid-enterprise market. The DevOps toolset and methodology have matured to the point where it can be adopted and used successfully in IT environments not as resource-rich or process-driven as large enterprises generally are.

Another continuing story in DevOps is DevSecOps. Security and/or quality continues to be a key driver for DevOps pipelines, with the software supply chain and SBOM security still driving lots of adoption and adaptation.

Did I mention AI? You can’t discuss much today without mentioning it, or so it seems. AI is a catalyst for automation. Generally, in software development and deployment, where there is automation, you guessed it—there is DevOps.

But here is one out of left field for you: ITSM. It seems like IT service management is making a big comeback (some say it never left). Today’s ITSM incorporates many DevOps fundamentals to increase scale and agility. On this front, stay tuned; in partnership with PeopleCert, the folks behind ITIL, Prince 2 and the DevOps Institute, we will roll out a series of virtual events in 2024, tying all three of these key technologies together.

So, there’s lots going on in the DevOps world for 2024. You can count on us here at Techstrong Group to keep you in the know.
On that note, this will close out our coverage for 2023. To all of our readers, watchers, listeners, friends, sponsors and contributors, a Merry Christmas, Happy New Year, and here is to a healthy and prosperous 2024.

December 26, 2023
All Your IT Team Wants This Holiday Season is a Break!

The holiday season is all about giving. As organizations increasingly look to IT as they move toward new digital tools and processes, now is the perfect time to give back to IT teams tirelessly working to keep the modern enterprise online. Whether your system performance has been naughty or nice this year, there’s no denying that tech professionals have earned our appreciation, respect—and the tools to set them up for success in 2024.

For IT teams limited in both time and resources, simply maintaining systems can feel as impossible as squeezing themselves down a chimney or delivering gifts to millions of homes in a single night. On top of that, instead of being greeted with milk and cookies, they’re inundated with endless performance issues, support requests and alerts—leaving little time left over for the important work of innovating.

They say the best gifts are the ones you can’t wrap. That holds true for IT teams, too. This year, bring your organization the gift of a simpler, speedier, more rewarding workload. If your team is dreaming of a tech-savvy future, here are some enterprise software solutions to make their lives easier that they won’t want to re-gift:

Enjoy the View With Observability

Everyone loves to cozy up at home during a winter snowstorm, but with the widespread migration to combined remote, on-premises and distributed hybrid environments, the daily monitoring journey for today’s IT teams is more akin to trekking blindly through a blizzard.

Observability tools are metaphorical snowshoes and goggles that can help them not only weather the storm but see clearly from the mountaintop. Observability is the answer to the modern enterprise’s struggle to gain full visibility into their organization’s apps, networks, databases and infrastructure—something nearly half of IT professionals lack, according to SolarWinds research. IT teams will be able to rest easier at night with visions of sugarplums, rather than outages or anomalies, dancing in their heads.

Even better, integrating artificial intelligence (AI) capabilities into observability solutions to collect and provide data on what’s not performing as expected and why will help your teams take a proactive approach to solving issues.

Lend a Helping Hand With AIOps

AI isn’t just the shiny new toy of the tech world. Organizations using AI for IT operations (AIOps) can give the gift of support to their overworked IT teams by automating some of the time-consuming and mundane tasks that stand between them and a focus on innovation.

Adding AIOps to observability can provide IT teams with maximum visibility into the state of their digital ecosystems through automated discovery and dependency mapping. Additionally, your teams can gain the ability to easily track inbound connections linked across the organization’s application stack and storage volumes with auto-instrumented views.

Today, it simply isn’t feasible for humans alone to manage modern IT environments without intelligent automation. Think of AIOps as a workshop of elves operating in the background to ensure workloads and processes are streamlined and moving as efficiently as possible. With AIOps in place to analyze data and streamline workloads and processes, IT teams are relieved of some pressure—and can focus on accelerating your digital transformation rather than just maintaining it.

Give the Gift of Time

Finally, although you can’t outright give the gift of time to your IT team, you can still arm them with tools that save time year-round. In 2024, more organizations will embrace IT service management (ITSM) to improve their IT outcomes, service delivery and employee satisfaction.

SolarWinds research found that enterprises using AI-powered ITSM tools were able to reduce system downtime by 21% and decrease time spent resolving incident and service requests by 23%. In fact, the average SolarWinds customer reported savings of 23 hours weekly due to reduced ticket volume—nearly the equivalent of adding an employee to the team.

This holiday season, the best gifts you can give your IT teams are the actionable, predictive intelligence and tools they need to optimize performance, cut down on complications and quickly resolve issues. (As a bonus, it will certainly make you more popular than the guy from The 12 Days of Christmas who thought it was a good idea to gift his partner geese, milkmaids and leaping lords.)

December 22, 2023
Best of 2023: Are We Witnessing the End of Open Source?

As we close out 2023, we at devopsy.kinsta.cloud wanted to highlight the most popular articles of the year. Following is the latest in our series of the Best of 2023.

Hailed as a groundbreaking movement in software creation, open source software has become an indispensable pillar of modern software development. Often described as democratized technology, it has empowered countless individuals and organizations to collaborate and innovate. However, the community now stands at a critical juncture, and there’s some speculation that we’re seeing a decline in the open source space.

Why is Open Source so Popular in Modern Software Development?

At the heart of open source lies the power of collaboration. Unlike proprietary (closed source) software, open source invites participation from a diverse range of contributors, allowing them to work collectively to create and improve software. This inclusivity fosters shared knowledge and cooperation, leading to the creation of groundbreaking software.

In addition to collaboration, the open source development approach eliminates financial barriers and significantly enhances accessibility in software development. With open source software typically distributed under licenses that allow users to access, use, modify and distribute the software freely, this eliminates the need for costly licenses usually associated with proprietary software. This affordability allows organizations of all sizes to leverage innovative solutions without accruing high upfront costs.

Within the framework of open source software, transparency is ingrained. The accessibility of the source code makes it possible for users and contributors to scrutinize the source code, promoting trust and accountability. By promoting scrutiny and peer review, transparency ensures that flaws are quickly identified and addressed. It also empowers users to have greater control over their choices in technology.

With these benefits coupled with success stories from enormous projects like Linux, Apache and MySQL, open source positioned itself as having the potential to compete with proprietary alternatives, leading to widespread adoption across the technology industry.

More Projects are Jumping Ship

Given these numerous benefits, one might wonder: What challenges could arise with this approach? In recent years, there have been sentiments amongst contributors that the space might be losing steam. Their concerns are fueled by a few key factors that may erode or undermine the collaborative essence of the movement.

A huge factor is the commercialization of open source projects. A popular example of this phenomenon is the GitHub acquisition – GitHub, the home for open source projects for years, was acquired by the tech giant Microsoft in 2018. This news ruffled some feathers in the community, as Microsoft was seen as a proponent of proprietary software. It also raised doubts about whether GitHub would maintain autonomy over its decision-making process.

Regardless of these doubts, the community overcame the bump in the road rather quickly and continued contributing to the platform for years. However, in 2022, GitHub announced that a sub-program called Copilot, which open source developers had been working on, would emerge as a commercial product, with the profits going to GitHub itself. This development infuriated community developers, and they faced a rude awakening that any open source platform could decide to commercialize their projects without contributors sharing in the financial rewards or even gaining recognition for their work. Another open source project that has fallen victim to commercialization is OpenAI.

There have also been increasing concerns about whether open-sourcing core business models will cause more harm than good. Unlike in the past, it’s a lot easier for projects to become popular, creating a high possibility that someone else can steal the idea or offering and quickly create a commercial product based on the project.

These considerations are part of a broader discussion regarding the shifting dynamics and potential departure from the core principles within the community, causing participants to be uneasy.

The Dust Settles: Open Source Remains Strong

Despite the concerns and challenges facing the community, open source has undeniably transformed how we build and deploy software. We must approach the future of the movement with cautious optimism.

Drawing from past experiences like GitHub and OpenAI, it is clear that the community is resilient and adaptive. Contributors who do not agree with the acquisition of GitHub or the commercialization of OpenAI will take their gifts and contribute to projects whose values they agree with.

However, open source is at a crossroads and is grappling with challenges and changes that demand introspection. This introspection, hopefully, will lead to adjustments in the open source space that reaffirm its core principles and address concerns. Open source is not fizzling out, at least not yet; we can think of it as undergoing a transformative phase that will shape its future and ensure that it remains an important pillar in the software development landscape.

To hear more about cloud-native topics, join the Cloud Native Computing Foundation and the cloud-native community at KubeCon+CloudNativeCon North America 2023 – November 6-9, 2023.

December 22, 2023
DevOps 2023: The View From the Rearview Mirror

How can this be? Here we are, right before Christmas, and it will be a new year before we know it. Time to put 2023 in our rearview mirrors. I, for one, say, good riddance. I’m sorry, but 2023 will not go down as a great year for me, and I think it was a tough year for many of our friends in the tech world, too. In fact, to quote Queen Elizabeth (who we lost in 2022), for me, 2023 was in many ways an annus horribilis.

I say that because 2023 saw the sometimes-savage impact of the cycles of the market up close. For the first time in a long time, many of our friends and colleagues were the victims of layoffs. In fact, according to Crunchbase, over 191,000 U.S.-based tech workers were the victims of layoffs. That doesn’t include non-U.S.-based workers, which could easily drive that number to over a quarter of a million. That is on the heels of 2022, when about half that number of workers were laid off. So, in the last two years we have seen 350,000 or so tech workers laid off. For many of these folks, finding their next gig was not as easy as it was in the past. There weren’t recruiters breaking down their doors with interview opportunities. Employers became more selective and demanding. If you are looking for a job that is 100% remote so you can work from wherever, that gets much harder. Employers want employees in the office again. Probably every one of you reading this was either laid off at some point in the last two years or you know someone who was. But it wasn’t just the layoffs. The very foundation of our tech infrastructure suffered seismic shocks, too.

For many of us, the Silicon Valley Bank failure in March was a splash of cold water in the face that signaled business as usual was no longer going to be business as usual. I have been in tech for 30+ years, and for much of that time, SVB was a mainstay of venture-backed startups. Most of the venture-backed companies I helped found were customers. If they could fail, who and what else was suspect? We soon found out what else was not as rock solid as we had led ourselves to believe. The entire VC ecosystem that the tech world relied upon was shaken to its core. With the unprecedented rapid rise in interest rates by the Fed, the underlying business fundamentals of the tech VC market were broken. Who would take a risk investing in non-profitable startups when you could get tax-free bonds that paid as much, guaranteed? We actually saw VC funds close up shop, not raise new funds and cut back. This resulted in over 3,200 venture-backed companies failing in 2023. For those companies who held on, many received the message from their boards that they shouldn’t expect to raise more money at “up valuations” until sometime in 2024 or beyond. They should hold on to their cash. It seems reasonable, but you know, with VCs, there are always two sides (or more) to the coin.

These companies are usually not profitable. They burn money every month. When they cut, they do so first with marketing and sales, and generally, their growth slows. Slow growth makes it difficult to raise funds at an increased valuation. So, it becomes a death spiral. They aren’t growing enough to raise money at a decent valuation, but they are being told to shut down the marketing spend. It’s a Catch-22.

In addition to all the macroeconomic news, 2023 was also a year where war seemed to be breaking out everywhere. I am reminded of the old saying, “War is not healthy for children and other living things.” It isn’t great for tech either, as it turns out. Especially when those war zones are also in places that support thriving tech economies.

So, besides macroeconomic slumps and wars, what else can we say about 2023? In terms of DevOps, we saw a year where DevOps seemed to move from front-and-center to blending in. I think most organizations today are using some sort of CI/CD process in terms of developing and deploying software. Many of the fundamentals of DevOps have seeped into the very fabric of our IT infrastructure. Some may see this as “the death of DevOps;” heck, even Gene Kim is renaming DOES into something else. But as I will explain in my next article, the rumors of DevOps’ demise have been greatly exaggerated. To the contrary, DevOps is beginning to see its promise fulfilled. You will have to read my next blog to get more of my views on this topic.

But 2023 (like all black clouds) also had a silver lining. As Dustin Hoffman in The Graduate said (sort of), I have two words for you: AI. With all due respect to Taylor Swift, my Person of the Year was not really a person at all. I would say it’s AI. You could not swing a golf club around tech people in 2023 without hitting AI in the head. AI has the potential to be a civilization-changing technology. On par with the internet itself, the cellphone and the like, AI could change the lives of everyone. This is as opposed to technologies like the cloud or methodologies like DevOps that were technology-market-changing. AI is attracting literally billions of dollars in investments and is moving forward at warp speed, in spite of those who say it should slow down. It promises to invade and disrupt every corner of IT as well as one business vertical after the next. A perusal of our Techstrong.ai site will give you all you need to know. The impact of AI on DevOps is just starting to be understood. Operationalizing AI for IT will be a major theme for us here at Techstrong in the year ahead, so stay tuned.

While 2023 has been a difficult year in tech, the great thing about cycles is they cycle through. What went down will come up. We are already starting to see signs of an uptick. I am personally optimistic that 2024 will be a great year for the tech world and I pray for the world in general with fewer wars, less death and less sickness. How about more peace, more commerce, more goodwill, better health and, of course, more DevOps?

Happy holidays and happy new year to all of our Techstrong community!

December 22, 2023
Best of 2023: 11 Steps to a Successful DevOps Career
As we close out 2023, we at devopsy.kinsta.cloud wanted to highlight the most popular articles of the year. Following is the latest in our series of the Best of 2023.

The world of technology is evolving at a rapid pace, and the past few years have introduced a new shift in digital transformation and software development. The traditional business model is no longer viable, and to remain relevant in the extremely competitive business landscape, organizations need DevOps.

As more and more companies explore what it takes to implement DevOps practices, the need for highly qualified DevOps engineers has soared. In fact, DevOps engineers are among the most sought-after professions in the IT industry.

So, if you have set your mind on becoming a DevOps engineer, your chances of getting a job are high. Yet, as demand for DevOps increases, so is your competition. Enterprises will absolutely not hire just everyone. Therefore, talent and expertise are a must.

The process of becoming a DevOps engineer requires time and dedication. So, it’s crucial to start off right. We’ve put together a guide to the steps needed to get you on the right track, along with a few resources you can take advantage of.

How to Become a Successful DevOps Engineer

1. Master at Least One Programming Language

To successfully manage DevOps projects, you need to be familiar with programming languages. While you are unlikely to be writing source code, you will need to automate processes, integrate databases, and occasionally debug code. Therefore, working knowledge of programming languages will help you understand code and review it.

So, mastering one or several programming languages is a great place to start your DevOps roadmap. While you can get away with one, we do recommend that you pick at least two or three to be more competitive. Here are some programming languages that you can choose from: Java, JavaScript, Python, Ruby, C, C++, Go and Node.js.

Here are some free resources you can use:
And some paid resources:
2. Learn Different Operating Systems

Operating systems will power the technology the teams will be using to work and communicate, as well as run the servers you’ll deploy applications on. So, you’ll need to know how to configure your servers using the command line terminal.

Operating systems you can get started with are Linux, Windows, MacOs, Ubuntu and Unix.

Some free resources you can use are:
And some paid resources:
3. Know How to Operate in the Terminal

Once you are familiar with operating systems, you should know how to perform systems tasks without the help of GUI or graphical user interface. So, get started on learning how to do bash scripting, text manipulation, process monitoring, system performance, networking, as well as compiling apps from source. PowerShell, Vim, Nano and Emacs are names you should get familiar with.

Here are some free resources for you:
And some paid ones:
4. Understand Networking, Security and Protocols

Cybersecurity is becoming more important by the day, especially if you walk in DevOps shoes. So, you’ll need to understand how protocols support various request types. This will prevent the risks of bad players (and there are plenty of them) intercepting your data during transfers and intercepting your applications.

What should you learn? HTTP, HTTPS, SSL and SSH.

A free resource to get your hands on:
- OSI Model Explained
And some paid ones:
5. Learn Server Administration

As a DevOps engineer, you will have to monitor servers. They will be fulfilling requests when users request the information they need. Common web servers and related services to get familiar with are Apache, IIS, Tomcat, Linkerd, NGINX, Envoy, Istio and Caddy.

A few free resources for you:
And some paid ones:
6. Study Containers and Container Orchestration

Containers gather and organize all application code, libraries and dependencies together in a portable format so code can be written once and run anywhere. Container management is the use of a platform to organize software containers. It is essential to optimize efficiency and streamline container delivery for faster application development and deployment. They combine all libraries in a deployable unit without depleting the host operating system’s CPU and memory resources.

Here are some free resources:
As well as some paid ones:
7. Specialize in Microservices and Learn about Miniservices

To remain competitive in the DevOps space, you need to use the latest architecture patterns. While many still rely on miniservices, microservices architecture is the way of the future. They allow to improve scalability, system resilience and maintainability, offer greater technology stack flexibility, and enable faster deployments.

Keep in mind that miniservices are still relevant, and you should be familiar with both.

Here are some valuable resources to get your hands on:
8. Learn Infrastructure-as-Code (IaC)

Once you master containers and container management, infrastructure-as-code (IaC) is where you should head next. It’s one of the main areas of focus for a skilled DevOps engineer and will be vital for the success of the projects that you work with.

Some tools you’ll need to familiarize yourself with are Puppet, Terraform, Docker Swarm, Ansible, Istio, Chef and more.

Some free resources to get the basics:
As well as paid ones:
9. Understand Continuous Integration and Continuous Deployment (CI/CD) Tools

One of the core DevOps principles is continuous integration and continuous delivery/deployment (CI/CD). So, it’s a no-brainer that you should get familiar with the subject. CI/CD tools support various phases of the pipeline and help automate processes and handoffs that free up your teams’ hands.

The CI/CD tools for you to learn are GitHub, GitLab, Jenkins and Bamboo.

Free tools to get started with:
And paid ones:
10. Learn and Practice How to Monitor Software and Infrastructure

As a DevOps engineer, you will be responsible for monitoring applications and infrastructure to work on improving efficiency and resolving errors. This will require you to observe data from applications, servers, network devices and more and track metrics like hardware capacity, network throughput and uptime.

Some tools to get familiar with are Grafana, Datadog, Zabbix, Prometheus and Nagios.

A few free tools to start with are:
And a few paid resources:
11. Study Cloud Providers and Cloud Design Patterns

Modern applications are hosted in the cloud, with cloud services providing numerous benefits such as scalability and cost reduction. As a result, it’s vital to understand the various cloud services available as well as their design patterns and best practices.

Tools you should get familiar with are AWS, Azure, Google Cloud and Heroku.

Free resources to start with:
And paid ones:
Bonus: Learn DevOps Tools and Stay Up to Date with DevOps Trends

And last but not least, remember that this DevOps roadmap is just the beginning of your DevOps career. In an industry that is continuously evolving, you’ll need to continuously evolve and learn so that you know how to efficiently manage your clients’ projects, regardless of their scope. Be sure to regularly take new courses and follow DevOps development blogs for industry news and insights.

As technology is continuously advancing and evolving, the need for highly skilled and experienced DevOps engineers is on the rise. If you would like to become a DevOps engineer, follow this DevOps roadmap for 2023 and arm yourself with lots of patience (and coffee, lots of coffee).
December 21, 2023