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Pipeline is Banzai Cloud’s Kubernetes container management platform, which allows enterprises to develop, deploy and securely scale container-based applications in multi- and hybrid-cloud environments. While one of Pipeline's core features is to automate the provisioning of Kubernetes clusters across major cloud providers, including Amazon, Azure, Google, Oracle, Alibaba Cloud and on-premise environments (VMware and bare metal), we strongly believe that Kubernetes as a Service should be capable of much more.
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In a perfect world, resources are infinite and readily available. But as we all know, things in the real world are never quite so simple. The struggle for resources is much the same in the world of computer programs, where CPU cycles, memory and storage space, or network bandwidth can easily become scarcities even when using the latest generation of devices and technology. Time-sharing, virtual memory and paging, logical volumes… These techniques are used by most operating systems today without the average user or software developer having to think about them, working hard to make the limitations of hardware disappear.
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There has been a lot of talk about multi- and hybrid-clouds 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 has been too complex for most organizations so far. One major area of focus for Banzai Cloud has been hybrid clouds, to create and automate a seamless and consistent operational experience for a concept that has a lot of underlying complexities.
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If you spend any of your time dealing with the cloud native world, you've probably already heard about Kubeflow. It's something we've been playing with since we first began to explore the possibility of running Tensorflow in a distributed way. That was quite some time ago. Since then, Kubeflow has rapidly evolved, so that it now includes dozens of machine learning (ML) frameworks. The frameworks allow for the training and serving of all kinds of machine learning models.
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Over the past few years, Kubernetes has become the de facto standard platform on which the world runs its cloud native applications. Although it has a great value proposition for use in all kinds of cases, its ecosystem is immensely complex and it requires a lot of expertise to operate. This is where the Banzai Cloud Pipeline platform comes in. Our mission is to help integrate Kubernetes into existing organizations, and to make the Kubernetes experience better for everyone:
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Two weeks ago we announced, the tech preview for Banzai Cloud Pipeline 2.0, the hybrid any-cloud platform. That new platform allows customers to build hybrid Kubernetes clusters in four different ways, across 5 cloud providers and on-premise datacenters and introduces a new acronym: BYOK, Bring your own Kubernetes! Day 2 operations Kubernetes has changed how workloads are run by providing a convenient abstraction layer over infrastructure. While many of our customers use Pipeline to create all their clusters, and want to kickstart their Day 0 and Day 1 experiences, others want to reuse the clusters that they have already deployed.
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We are delighted to announce our tech preview of Banzai Cloud Pipeline 2.0, the hybrid any-cloud platform. A little under a year ago we released the first commercial version of Banzai Cloud Pipeline and made it available for development and PoCs by launching our Try Pipeline initiative. Banzai Cloud Pipeline 1.0 was the first incarnation of our vision for a productive and flexible multi-cloud container management platform (now supporting five public clouds and on-prem datacenters).
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One of the earliest features of our hybrid cloud container management platform, Pipeline, was to standardize the running of applications on Kubernetes with a framework we called Spotguides. Spotguides allowed us to build domain specific knowledge into apps, avoid writing boilerplate code, and go from commit to a production ready deployment in minutes. All of this while meeting enterprise-grade requirements such as federated monitoring, centralized log collection, security scans, cluster lifecycle management and lots more.
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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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