cloud infrastructure

Top 5 DevOps trends

With DevOps enabling organizations able to act smarter, collaborate faster, and deliver better quality results, it’s no wonder it has become a top priority for the tech industry.

DevOps delivers a level of speed, efficiency, reliability, and quality in software development that the industry has never seen before.

It also has shown how sales in management without the advice and recommendations of technical experts leads to costly inefficiencies when delivering products to the end-user.

DevOps has changed the cultural paradigm and has made the positive impact of developers on business decision-making that much more apparent.

With developers picking peer-recommended tools to solve challenging problems and pitching them to management, organizations such as Tensure are able to kickstart the growth potential of their clients.

There are several exciting things happening in DevOps, and these are the top trends we think are going to make a difference in 2022:

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Gitops: the #1 way to control your code. Centralization is queen.

GitOps is the practice of storing as much of the configuration in version control (namely Git) by merging code to ‘main’ trigger deployment workflows.

Essentially, GitOps is a continuous deployment pattern that gives developers more control over code by creating a central source of truth that the team is using at all times.

“The availability of continuous deploy systems,” says David Ramsington, expert DevOps engineer at Tensure, “and it being something you do first, rather than later, is great because it’s easy to set up quickly. It feels really good to see code running in production within minutes after writing it. I feel like I’m providing more value to the end-user this way. Also, the new tools start adding in state changes automatically if it detects an unhealthy system, which provides a nice safety net for your prod. config.”

This practice is increasingly more popular in DevOps areas like Infrastructure as Code (IaC).

Having the state of a system located in a central place allows for more control, which allows developers to save time and energy by not needing to search through cloud provider consoles.

It’s a process that gets many developers really excited. James Dreier, another expert DevOps engineer at Tensure, has this to say:

“I love GitOps. It takes so much toil off of my daily work. Whether it’s automating a deployment, or validating a pull request before a merge. It reduces work and human error. The real trick is implementing it in a way that doesn’t hinder the development workflow.”

Mlops and aiops: the #1 way to better analyze the overwhelming amount of data generated by organizations.

These days, most organizations are collecting or creating data ALL the time. Whether this data is business-related or operational, in order for businesses to reap the benefits of data science workflows, they need to be smart about organizing and analyzing this overwhelming amount of data.

Traditional data science solutions aren’t able to keep up with the volume of data being generated, and that’s when machine learning and artificial intelligence comes in to save the day.

MLOps/ AI Ops is bringing CI/CD and automatic infrastructure provisioning to machine learning and other AI model training algorithms. These newer methods provide visibility into huge pools of data that automatically generates insights into problems, their root causes, and any solutions that can fix them.

This is especially exciting in the DevOps landscape because both AIOps and MLOps provide the visibility and automation needed to speed up processes and decrease inefficiencies.

In other words, David, notes:

“Since data scientists typically work outside of version control, training an algorithm with a set of data gets dramatically easier to iterate when you start defining your workflows in code. The amount of operational efficiency increases, because you can see how changes evolve over time. And if you find that your new algorithm is bad, you can revert a commit and be back to where you started.”

Kubernetes operators framework: the #1 way to reduce the number of repetitive tasks and take human error out of the equation.

The Kubernetes Operator framework provides custom resources to Kubernetes that can manage applications and their components.

The goal is for operators to function like humans do when managing application services.

The people who look after applications and their services have in-depth knowledge of how a system is supposed to behave, how to deploy it, and how to react if there are problems.

Their job includes many repetitive tasks that take up significant time and energy such as deploying an application, taking and restoring backups of application states, and simulating failure in all or parts of a cluster to test its resilience.

The Operators framework aims to automate these repetitive tasks so developers can focus on more important work.

Jame’s notes how freeing it is to not have to do these repetitive tasks,

“If it is something I have to do more than once, I generally don’t want to do it again — Kubernetes gives us an easy way to take the toil and automate it. It gives us a way to implement custom resources on our clusters that allow us to offload tasks that would usually be manual.”
David, also had this to say,
“Taking the human element out of Ops is exciting because it’s taking actions that feel risky, and then turning them into repeatable reliable processes with significantly lower chances of making mistakes.”

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Finops: the #1 way to manage costs and implement right-size solutions across an organization.

FinOps is a cultural shift (much like DevOps is) that encourages organizations to better manage their development costs and implement proper solutions across an organization. By establishing a cross-functional team that keeps a close eye on where expenditures are being spent, organizations can increase visibility of their costs and metrics in order to make smarter decisions.

It allows organizations to implement best practices to optimize costs, whether it be through capacity planning, right-sizing, or negotiating Committed Use Discounts.  Ultimately, it encourages measurement, not just of cost, but also of resource utilization, which makes an organization more effective and agile at what they do.

James has this to say,

“The Finops Foundation didn’t even start until 2019. This is really one of the latest trends to hit the DevOps space. It provides organizations a way to structure a team and work with Product Managers and Principal Engineers to find solutions that bring the most value for their investment. If you are ruling your infrastructure by the “almighty dollar”, you will find improvements across the board.”

David, also chimes in:

“When I first heard about FinOps I thought it was another way to promote Serverless: pay for what you use, more or less. I think FinOps goes deeper than that. It’s really about paying attention to what it costs to do what you’re currently doing and trying to move that needle down so you can boost return on investment.”

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Devsecops: the #1 way to incorporate it security into the full lifecycle of applications.

DevSecOps is an approach to culture, automation, and platform design that integrates security as a shared responsibility throughout the entire lifecycle of an app.

In order to take full advantage of the agility and responsibility offered by a DevOps approach, organizations must also pay attention to security. Otherwise, outdated security practices can undo every DevOps initiative that an organization takes. It’s necessary to keep the DevOps workflow from ever slowing down, so organizations can keep being productive and efficient at their work.

David says,

“DevSecOps brings the responsibility of maintaining a secure application closer to the developers, which increases the quality of code resulting in fewer breaches for the end-user. One of the running jokes in the space is, ‘It’s security’s job is to say ‘no’ to developers’. By embedding development in the process, we can lean in and contribute more to the business value.”

James adds,

“Shifting security “left” is my favorite. If you can bring dependency vulnerability management down to the developers that are writing the code, then you have already reduced your attack surface area. Slap some static code analysis on top of that, and now you have a solid core for DevSecOps. The hard part here is finding the balance. Security teams are always going to scream for zero vulnerabilities. but you have to be realistic with the likelihood of attack and, finding other ways to mitigate it other than telling the devs they just can’t use a certain library.”

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