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One of the key features of the Pipeline platform is its ability to automatically provision, manage, and operate different application frameworks through what we call spotguides. Among the many spotguides we support on Kubernetes (Spark, Zeppelin, NodeJS, Golang, even custom frameworks - to name a few) Apache Kafka is among the most popular. We are heavily invested in making it as easy and straightforward as possible to operate Apache Kafka automatically on Kubernetes, and we believe that our current Apache Kafka Spotguide does just that.

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Last week we released our open source Istio operator designed to help ease the sometimes difficult task of managing Istio. One of the main feature of the operator is its ability to manage a single mesh multi-cluster Istio. Multi cluster scenarios Typical multi-cluster-based patterns are single mesh - combining multiple clusters into one unit managed by one Istio control plane - and mesh federation, wherein multiple clusters act as individual management domains and the service exposure between those domains is done selectively.

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At Banzai Cloud we try to provide our users with a unified, cloud and on-premise-agnostic authentication and authorization mechanism. Note that our Pipeline platform supports cloud provider-managed Kubernetes and, as of recently, our own Kubernetes distribution - the Pipeline Kubernetes Engine, PKE. We also recently introduced an open source project, JWT-to-RBAC (you can read more about that project, here), designed to solve authentication and authorization challenges within the Pipeline platform in a cloud provider-agnostic way.

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Service mesh has, without question, been one of the most vigorously debated and obsessed over topics of discussion in recent memory. It seems like, whichever way you turn, you run into heated arguments between those developers that are convinced that service mesh will outgrow even Kubernetes, and the naysayers convinced that, outside of use in a few large companies, service mesh is impractical to the point of uselessness. As always, the truth probably lies somewhere in between, but that doesn’t mean you can avoid developing an opinion, especially if you’re a Kubernetes distribution and platform provider like us.

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If you’re a Node.js developer, it’s very likely that you are building microservices and have already come across Kubernetes. Kubernetes is a solid foundation for scalable container deployments but is also infamous for it’s steep learning curve. This post will explain how to containerize your Node.js applications and what it will take to make them production-ready on Kubernetes. While this post can be used as a tutorial for DIY jobs, we have also automated this entire process, allowing developers to kickstart their code to production experience with a few clicks.

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At Banzai Cloud we are building a managed Cloud Native application and devops platform called Pipeline. Pipeline supercharges the development, deployment and scaling of container-based applications with native support for multi and hybrid-cloud environments. The Pipeline platform provides support for advanced scheduling that enables enterprises to run their workflows in an efficient way by scheduling workflows to nodes that meet the needs of the workflow (e.g.: CPU, memory, network, IO, spot price, etc).

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Banzai Cloud’s Pipeline platform allows enterprises to develop, deploy and scale container-based applications on six cloud providers, using multiple Kubernetes distributions. One significant difference between the cloud providers that support Kubernetes (we support ACSK, EKS, AKS, GKE, DO and OKE) and our own Banzai Cloud Pipeline Kubernetes Engine is our ability to access the Kubernetes API server, and to configure it. Whether our enterprise customers are using Banzai Cloud’s PKE distribution in a hybrid environment, or cloud provider-managed Kubernetes, they demand we meet the same high standards - the ability to authenticate and authorize (e.

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One of the Banzai Cloud Pipeline platform’s key open-source projects is Bank-Vaults - the Vault swiss-army knife (and more) for Kubernetes. Feature requirements are part of the Pipeline platform, and the relatively large community around Bank-Vaults also has its own use cases and requirements. We’ve received lots of external contributions (thank you!), and we continue to find time to work on our community-driven features. While there have been many besides, these are the most sought-after features of the last few weeks.

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As a tech startup our main focus is on delivering value to our users and customers which means that the Developer Experience often comes second. Since we launched our beta platform Pipeline, we received an enormous amount of attention not just from users and customers, but from developers as well. Based on your feedback we’ve started to formalize our development processes. This post contains instructions for setting up a basic development environment and explains our development workflow through a simple pull request as an example.

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At Banzai Cloud we’re building a managed Cloud Native application and devops platform, called Pipeline. Pipeline supercharges the development, deployment and scaling of container-based applications with native support for multi- and hybrid-cloud environments. Pipeline’s built-in CI/CD solution is capable of creating Kubernetes clusters, running and testing builds, packaging and deploying applications as Helm charts, and lots more—all while its secrets are stored and managed by Vault. If you’d like to read more about the CI/CD system’s other features, such as native Kubernetes support, unprivileged builds and more, please read this post.

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