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Cloud Expenditure - A Storm is Brewing

Expenditure on cloud computing services reached a mammoth 225 billion dollars in 2022. Companies start their cloud-native journeys with the best intentions and consume the many benefits including: But current cloud expenditure growth levels are unsustainable for many organizations and with 82% of organizations investing in FinOps staff it shows that cloud expenditure is top of mind in the c-suite.

Understanding k3s: Architecture, setup, and uses

If you are looking into the cloud-native world, then the chances of coming across the term “Kubernetes” is high. Kubernetes, also known as K8s, is an open-source system that has the primary responsibility of being a container orchestrator. This has quickly become a lifeline for managing our containerized applications through creating automated deployments.

What is DevOps? Practices, impacts, and challenges

Bridging the gap between development and operations has become essential for the cultural shifts seen in organizations today. DevOps allows these concepts to be brought together, creating an influential blend of cultural philosophies, practices, and technological instruments, facilitating a quicker delivery of products and services. Throughout this blog, I will explore how we should all be embracing DevOps to allow our organizations to compete in an ever-changing digital world.

DevOps Evolution and the Rise of Platform Engineering

As we continue to see rapid technological advancements, organizations must evolve and adapt to maintain a competitive edge. The principles of DevOps - collaboration, automation, continuous integration, and delivery - have emerged as critical success factors in this landscape, enabling organizations to navigate the ever-changing environment.

Mastering Kubernetes Networking with Cilium

In a recent meetup I hosted alongside Kunal Kushwaha, we discussed Cilium, an eBPF-powered open-source cloud-native networking solution that offers security, observability, scalability, and superior performance. Throughout this blog I will explore how the increased usage of Kubernetes has led to the need for advanced networking, security, and observability solutions. This will allow us to take a closer look at how Cilium can benefit Kubernetes users.

Chaos Engineering 2023 with Chaos Mesh

We've seen a tremendous transition in the architecture of our systems over the years, from basic, linear systems to increasingly sophisticated, non-linear systems. We've moved away from monolithic programs, where a single person could comprehend the entire operation of a system, and toward a distributed world dominated by a microservices design.

Reducing the cost of cloud: Tips for reducing your spend at any cloud provider

Spiraling costs are causing organizations to look for ways to reduce their monthly spend – hidden charges and unexpected bills are surprises that CFOs can no longer afford. With current costs from hyperscaler cloud providers skyrocketing, many are now asking whether going cloud-native is the right move for them. There are, however, a number of tips and tricks that you can action today that will help you reduce your cloud bill at any provider.

How Civo has contributed to open source

Over the years, open source has become a way of working that allows people to modify and share designs to inspect, alter, and enhance source code. This has led to a range of benefits for users of open source, such as having more control over software, better security, more stability, and an inspired community. Last year, Mark Boost, CEO at Civo, spoke with OpenUK as part of their yearly report to discover the UK’s journey with open source.

How Cloud Native Can Reduce the Cost of Machine Learning

As engineers, we tend to pride ourselves on building a production-first mindset and operational excellence. According to a recent survey, 74% of executives believe that AI will deliver more efficient business processes, while 55% think that AI will help develop new business models and create new products and services. However, the reality is that 85% of ML projects fail to deliver, and 53% of machine learning prototypes don't make it to production.