

DevOps Journeys - Guest blog with Dan Holdsworth

Guest Blog with Dan Holdsworth
“Containerisation is the new 'norm,' making deployments more predictable and scalable."
This opinion from Dan Holdsworth lays the foundation for our latest guest blog, where he explores how containerization has revolutionised the DevOps landscape, making deployments more predictable and scalable.
Dan discusses how the widespread adoption of containerization has become a cornerstone of modern DevOps practices, emphasising its role in driving predictable deployments and serving as an essential learning project for new DevOps practitioners.
DevOps has transformed the way organisations build, deploy, and manage software. In your experience, how has the DevOps landscape evolved in recent years, and what do you see as the most significant shifts driving its growth and adoption today?
Containerization becoming the "norm" was the biggest evolution in my opinion and was a huge part of enabling more predictable deployments in companies. There was a big push a couple of years ago for everything being containerised and it's a common portfolio/learning project for those getting into DevOps.
With the growing adoption of AI and machine learning in DevOps, how do you see AIOps transforming traditional practices, and how are you incorporating these technologies into your processes?
The only way I can see AI & ML making a large enough impact on DevOps to transform practices truly is in the logging space. If models were trained on common logs, and we could incorporate AI into pipelines, then we could potentially never have failing builds due to them being fixed either before the run or once an error in the build logs is seen.
With the increasing emphasis on developer productivity and autonomous teams, how do you balance self-service models with governance and security requirements?
It's pretty simple really, you offer the illusion of self-service by only offering apps that are pre-approved and vetted by the platform teams.
As the need for continuous compliance grows, how are companies integrating security into their CI/CD pipelines, and what strategies are they using to ensure compliance in dynamic cloud environments?
In my experience, assuming you've done all you can to shift the compliance to earlier in the development process, you can focus on adding security scans that meet your needs in the CI pipelines, adding Terraform, Ansible, and other IaC/CaC code to version control and treating it the same as product code can tackle any issues with version compliance when using it to build dynamic environments.
In the era of GitOps and Infrastructure as Code (IaC), how do you ensure best practices for version control, automation, and consistency across environments?
If you're using GitOps, one of the most important areas to nail down is in the branching and PR reviews as poor branching strategies and PR reviews are what allow issues to make their way into production.
What are some of the most common reasons DevOps initiatives fail, and what lessons have you learned from these failures that could help others avoid similar pitfalls?
I would say the biggest issues is not in the individuals but in the company itself, some departments or companies don't really understand (still) what DevOps is and this can result in the teams being over burdened with tasks outside of their remit.
What are some of the most common reasons DevOps initiatives fail, and what lessons have you learned from these failures that could help others avoid similar pitfalls?
I would say the biggest issues is not in the individuals but in the company itself, some departments or companies don't really understand (still) what DevOps is and this can result in the teams being over burdened with tasks outside of their remit.
To hear Dan's insights compared with 7 other industry leaders, download DevOps Journeys 4.0 today. DevOps Journeys provides a roadmap to navigate evolving challenges and stay ahead of the curve.
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