There is a lot of the art of the possible between the GitOps Engine, Argo CD, and the Application-as-Code platform, Shipa. In a recent blog post, we outlined the power of a one-line developer experience. Though if you are unfamiliar with ArgoCD, here is a guide to get you started with Argo CD and leveraging Shipa for your first deployment.

I recently started working at SUSE. Before joining SUSE, my Kubernetes experience included vanilla Kubernetes, AKS and EKS but mostly OpenShift and Red Hat Advanced Cluster Management. I worked in technical pre-sales, so I knew about Rancher, K3s and RKE and their key features but I never spent time with them. When I joined SUSE, I started testing Rancher, Rancher Desktop, K3s, k3d and RKE2 and I had a great time with them. First things first, I will

Spot worker nodes on EKS (Elastic Kubernetes Service) are a great way to save costs by allowing customers to take advantage of unused capacity. With Sumo Logic, we have experimented with and adopted spot worker nodes for some of our EKS clusters to see if we can pass along the same benefits. We decided to share some of the learnings, challenges, and caveats with using spot instances along with the monitoring setup.

Our goal has always been to automate and standardize the management of infrastructure and deployment of applications across user infrastructure. Today, we are excited to announce that we've launched support for Google Cloud (GCP), expanding our natively supported providers list and further expanding the choice, flexibility, and reach the platform offers to current and new users. With this new integration, users can deploy, manage, and scale their containerized workloads to GCP compute infrastructure.

Heroku Vs. AWS remains a long and persistent debate among developers. Both platforms have strengths and weaknesses. Over the last 10 years, Heroku and AWS played a huge role in the cloud hosting and software development industry, by significantly unlocking productivity in a way that it has never been reached before. They are the platforms behind most of the successes from the last decade. However, we are in 2022 and it still looks like if we (developers) were in 2010 to deploy our apps in the cloud.

Since the 90s, when you run a company in the Healthcare industry in the US market, you must comply with the Health Insurance Portability and Accountability Act (HIPAA) Security Rule. Some of the security rules are directly linked to how you operate your organization, the others how you manage your application data for your customers. This article will walk you through what to consider on AWS to be HIPAA compliant in 2022.

The process of monitoring servers and applications has undergone many transformations throughout the years. When it began, the main question was whether the server was up or down. Now, monitoring helps answer questions about the internal state of an application and infer its status (also called white box monitoring). Monitoring today's complex infrastructure systems can be just as much an art as a technical skill.

Kubernetes has become a fixture in production for most IT Operations teams. The VMware “State of Kubernetes 2021 Report” shows a distinct shift towards a reliance on Kubernetes, with almost two thirds of respondents now saying they use it in production. Companies with over 500 developers are driving this adoption, with 78% reporting that they run mostly- or all-containerized workloads in production.

As a software engineer, leveraging GitHub is one of those tools that transcend your personal and professional development activities. Bringing open source to the masses, GitHub is a familiar platform for many. A newer addition to the GitHub Platform is GitHub Actions which was originally a workflow engine, now expanding into CI/CD.

While the global spend on artificial intelligence (AI) and machine learning (ML) was $50 billion in 2020 and is expected to increase to $110 billion by 2024 per an IDC report, AI/ML success has been hard to come by—and often slow to arrive when it does. There are four main impediments to successful adoption of AI/ML in the cloud-native enterprise.