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Service interruptions caused by outages have severe consequences that range from harming a provider’s reputation to frustrating a customer to the point that they move to a competitor, so it’s extremely important to build and run resilient systems. Resiliency must be implemented at multiple levels from the bottom infrastructure layer to the application. For our customers, it’s a necessity that the EKS clusters they deploy their production applications onto be highly available.
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One of the key features of Pipeline, our hybrid cloud container management platform, is its ability to provision Kubernetes clusters across five different cloud providers (Alibaba, Azure, Amazon, Google, Oracle), private datacenters (vmWare, baremetal, etc), or any combination thereof. It does this by using either cloud provider-managed Kubernetes, or our own CNCF certified Kubernetes distribution - PKE. Each cloud provider’s internal LB is different, and so is the way each is integrated with Kubernetes.
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A few weeks ago we discussed the way that we integrated Kubernetes federation v2 into Pipeline, and took a deep dive into how it works. This is the next post in our federation multi cloud/cluster series, in which we’ll dig into some real world use cases involving one of Kubefed’s most interesting features: Replica Scheduling Preference.

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One of the key features of our container management platform, Pipeline, and our CNCF certified Kubernetes distribution, PKE, is their ability to seamlessly form and run federated clusters across multi- and hybrid-cloud environments. While users of the Pipeline platform often have different requirements depending on whether they take a single or multi-cloud approach, they’re usually built around two key features: Multi-cloud application management Backyards, an Istio-based automated service mesh for multi- and hybrid-clouds Today, we’re happy to announce that we’ve added support for Kubernetes federation v2, which is being made available as a beta feature in the Pipeline platform.
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At Banzai Cloud we blog mostly about our container management platform, Pipeline. We frequently gloss over the workhorse underneath Pipeline, our CNCF certified Kubernetes distribution, PKE. That’s because our customers usually install and manage PKE with Pipeline, and thus benefit from all the enterprise-grade features we’ve already made available on that platform. However, PKE is also available on its own, and is one of the simplest ways to kickstart a Kubernetes cluster across multiple supported environments.
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If you’re reading this post, you’re likely already familiar with our container management platform, Pipeline, and our CNCF certified Kubernetes distribution, PKE: you probably already know how we make it possible to spin up clusters across five cloud providers and on-premise, in multi-cloud but also hybrid-cloud environments. But whether these are single or multi-cluster topologies, resilience is key. We at Banzai Cloud believe this is the case not just for infrastructural components but for entire managed application environments, like Apache Kafka.
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A few weeks ago we announced a new version of Pipeline, the hybrid any-cloud platform. This post is part of a series of posts highlighting the multi- and hybrid-cloud features on that platform. Today, we will be focusing specifically on multi-cloud features. Before we take a deep dive into our technical content, let’s go over some of the key expectations an enterprise has when it embraces a multi-cloud strategy:
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There has been a lot of talk about multi- and hybrid-cloud deployments over the past years. Some cloud vendors see these trends as a threat, others look at them as an opportunity. We think that beneath the buzzwords lie some very important use-cases driven by the needs of enterprises and SaaS providers. However, delivering and operating multi- and hybrid-clouds had been too complex for most organizations so far. The use-cases that we’ve seen at customers broadly relate to three main areas: flexibility, cost optimization, and compliance.
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Every major cloud provider offers a managed Kubernetes service that aims to simplify the provisioning of Kubernetes clusters in its respective environment. The Banzai Cloud Pipeline platform has always supported these major providers - AWS, Azure, Google, Oracle, Alibaba Cloud - turning their managed k8s services into a single solution-oriented application platform that allows enterprises to develop, deploy and securely scale container-based applications in multi-cloud environments. While this was very appealing from the outset, we quickly realized there was demand among our enterprise users to implement more sophisticated use cases that were limited by our initial approach.
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In our last post about using Cadence workflows to spin up Kubernetes we outlined the basic concept of Cadence and walked you through how to use the Cadence workflow engine. Let’s dive into the experiences and best practices associated with implementing complex workflows in Go. We will use the deployment of our PKE Kubernetes distribution, from Pipeline to AWS EC2 as an example. Of course, you can deploy PKE independently, but Pipeline takes care of your cluster’s entire life-cycle , starting from nodepool and instance type recommendations, through infrastructure deployment, certificate management, opt-in deployment and configuration of our powerful monitoring, logging, service mesh, security scan, and backup/restore solutions, to the scaling or termination of your cluster.
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