As DevOps professionals gathered at the recent DevOpsCon 2024 in Berlin, Germany John Willis opened the conference with a keynote addressing the pivotal intersection of DevOps and artificial intelligence (AI). Read on to discover Willis' insights and learn why sustainable AI innovation can only be fulfilled with a DevOps mindset.
In the rapidly evolving landscape of software development, the need for efficient and scalable application deployment and management has become a paramount concern. As applications grew more complex, spanning multiple services and components, the traditional monolithic approach became increasingly cumbersome and inflexible. The rise of microservices brought about numerous benefits, such as increased agility, scalability, and resilience.
Even in the cloud-native world, we can’t avoid dealing with infrastructure. What's worse, approaches such as microservices mean that some amount of responsibility for infrastructure is shifting to the project team. In this article, we’ll show that we as developers shouldn’t be afraid of infrastructure. Quite the opposite, with infrastructure as code, we can reuse much of our existing knowledge and put it to good use.
In today's rapidly evolving digital landscape, observability has emerged as a critical aspect of monitoring and maintaining system performance. Yet, misconceptions about its role persist, leading teams to overlook essential metrics and insights necessary for effective DevOps practices. This article explores the observability myth, clarifying what true observability entails and how organizations can leverage it to enhance their monitoring strategies. By understanding the intricacies of observability, teams can improve incident response, optimize system health, and foster a culture of continuous improvement in their software development lifecycle.
If you feel underwhelmed by your Kubernetes implementation, it might be because you're not finished yet. Organizational limitations can stifle your K8s deployment.
Distributed systems are complicated. Any software architecture who has ever built a distributed system rarely denies this. But the question arises: how complicated are these systems? Many programmers and those responsible in companies have an exaggerated fear of them. After all, all computer programs are complicated, or they become so over time, even if fans of low-code ideas might sometimes dispute this. This article is not about whether distributed systems should be avoided in general (certainly not!), but about why they become complicated and how you can avoid this.
DevOps was set in motion in 2008 with the encounter of two people at an Agile conference in Toronto: Andrew Clay Shafer and Patrick Debois came together in a meetup on the topic of "Agile Infrastructure". Later, the term DevOps was coined for the better collaboration between developers and operations teams.
Progressive delivery decouples code deployment and feature release. This is enabled through well-proven techniques to provide product owners, delivery, and system reliability engineering (SRE) teams with significantly more control and flexibility in their value streams. High-performing delivery teams are driven by curiosity and this means ongoing customer experimentation. But how do we achieve this at pace and without destabilizing our systems?
Kubernetes is a container orchestrator that has rapidly gained popularity among developers and IT operations teams alike. While it started out as a tool to manage containerized applications, it has evolved into much more than that — Kubernetes is a microcosmos and it is “eating the world.”
Kubernetes is a container orchestrator that has rapidly gained popularity among developers and IT operations teams alike. While it started out as a tool to manage containerized applications, it has evolved into much more than that — Kubernetes is a microcosmos and it is “eating the world.”