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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. For the past two years, we have been running a freely available, hosted and managed Pipeline environment at beta.banzaicloud.io (called the Banzai Cloud Pipeline Developer Preview), which over 2000 users are using to manage clusters across 5 public cloud providers. The platform is mainly used for testing and evaluation purposes, but we also know several hundreds of users who decided to deploy production workloads on Pipeline-managed clusters to benefit from the features of the platform without the burden of managing it themselves.
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Government organizations and institutions have similar requirements and goals regarding their IT infrastructure as commercial enterprises: it must be flexible enough to adapt to the changing needs of the organization, easy to maintain and monitor, scalable to meet the changing workload requirements, highly available and resistent to errors, and of course secure to protect the various sensitive data such organizations must process. In addition, they must meet the requirements of various national and state-level regulations, like the Federal Risk and Authorization Management Program (FedRAMP), the Department of Defense (DoD) Cloud Computing Security Requirements Guide (SRG), the Federal Information Security Management Act (FISMA), and other legislation.
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A generation of system engineers has grown up who’ve never had to go to a data center as part of their job. It’s easy to forget that while cloud computing offers an abstraction over physical servers, they do still exist behind the scenes — more of them than ever before. There are hardly any companies anymore that host all of their IT infrastructure on premises, but many enterprises have reasons to continue managing physical servers as part of their infrastructure.
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One of the many best-practices for operating Kubernetes clusters is to frequently perform Kubernetes version upgrades in those clusters. This insures that you’ll be running your workload with a version of Kubernetes that contains the latest security fixes, stability improvements, and features. There are two ways of doing this: manually with, for example, kubeadm when you’re running on bare-metal and, if you’re using one of the many cloud-provider Kubernetes solutions, the assisted way They all have their benefits and downsides.
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At Banzai Cloud we always strive to make things simpler and to make complex services available to our customers. We try to reduce the complexity of setting up components and services by automating as much setup as possible - to expose these for users in a transparent, easy to understand manner. This effort led us to introduce integrated services to the Banzai Cloud Pipeline platform. We have already written about what integrated services are, and we also have described a few of them, like automated public DNS management for Kubernetes clusters and cluster expiration.
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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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