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Creating Kubernetes clusters in the cloud and deploying (or CI/CDing) applications to those clusters is not always simple. There are a few conventional options, but they are either cloud or distribution specific. While we were working on our open source Pipeline Platform, we needed a solution which covered (here follows an inclusive but not exhaustive list of requirements): provisioning of Kubernetes clusters on all major cloud providers (via REST, UI and CLI) using a unified interface application lifecycle management (on-demand deploy, dependency management, etc) preferably over a REST interface support for multi tenancy, and advanced security scenarios (app to app security with dynamic secrets, standards, multi-auth backends, and more) ability to build cross-cloud or hybrid Kubernetes environments This posts highlights the ease of creating Kubernetes clusters using the Pipeline API on the following providers:
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At Banzai Cloud we continue to work hard on the Pipeline platform we’re building on Kubernetes. We’ve open sourced quite a few operators already, and even recently teamed up with Red Hat and CoreOS to begin work on Kubernetes Operators using the new Operator SDK, and to help move human operational knowledge into code. The purpose of this blog will be to take a dive deep into the PVC Operator.
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At Banzai Cloud we’re building a feature rich platform, Pipeline, on top of Kubernetes. With Pipeline we provision large, multi-tenant Kubernetes clusters on all major cloud providers - AWS, GCP, Azure and BYOC - and deploy all kinds of predefined or ad-hoc workloads to these clusters. We wanted to set the industry standard for the way in which our users log in and interact with secure endpoints, and, at the same time, we wanted to provide dynamic secret management for each application we support.
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At Banzai Cloud we run and deploy containerized applications to our PaaS, Pipeline. Java or JVM-based workloads, are among the notable workloads deployed to Pipeline, so getting them right is pretty important for us and our users. Java/JVM based workloads on Kubernetes with Pipeline Why my Java application is OOMKilled Deploying Java Enterprise Edition applications to Kubernetes A complete guide to Kubernetes Operator SDK Spark, Zeppelin, Kafka on Kubernetes
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Note: The Spotguides feature mentioned in this post is outdated and not available anymore. In case you are interested in a similar feature, contact us for details. A good number of years ago, back at beginning of this century, most of us here at Banzai Cloud were in the Java Enterprise business, building application servers (BEA Weblogic and JBoss) and JEE applications. Those days are gone; the technology stack and landscape has dramatically changed; monolithic applications are out of fashion, but we still have lots of them running in production.
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Banzai Cloud announced today that it will collaborate with Red Hat in an effort to help standardize the management of complex stateful applications on Kubernetes. Simultaneously, Red Hat announced the Operator Framework, an open source toolkit designed to manage application instances on Kubernetes in a more effective, automated, and scalable way. Banzai Cloud will work collaboratively with Red Hat on this open source project, which will focus on the creation of a new Software Development Kit (SDK) for the “operators” pattern.
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Note: The Spotguides feature mentioned in this post is outdated and not available anymore. In case you are interested in a similar feature, contact us for details. Our last post about the Banzai Cloud CI/CD flow described how to build/deploy a Spring Boot application on Kuberbetes. This post does the same for a Node.js application. We’ve teamed up with our friends at RisingStack to streamline Node.js application deployments to Kubernetes (pushable to any cloud provider) with Pipeline, which does all the heavylifting and allows developers to focus on writing the code.
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Cloud cost management series: Overspending in the cloud Managing spot instance clusters on Kubernetes with Hollowtrees Monitor AWS spot instance terminations Diversifying AWS auto-scaling groups Draining Kubernetes nodes A few months ago we posted on this blog about overspending in the cloud. We discussed how difficult it is to keep track of the vast array of instance types and pricing options offered by cloud providers, especially on AWS with spot pricing.
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At Banzai Cloud we’re always looking for new and innovative technologies that support our users in their transition to microservices deployed on Kubernetes, using Pipeline. In recent months we’ve partnered with CoreOS and RedHat to work on Kubernetes operators. That project was opensourced today, and is now available on GitHub. If you read through the rest of this blog, you’ll learn what an operator is, and how to use the operator sdk to develop an operator through a concrete example we developed, here, at Banzai Cloud.
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This week KubeCon + CloudNativeCon, Copenhagen will bring together over 4000+ developers, architects and other members of the cloud native and open source communities under one roof. We at BanzaiCloud are part of these communities, as well as the CNCF landscape since we’re certified experts in these technologies and operating under the umbrella of the Cloud Native Computing Foundation, so we can’t wait. Join us to learn about Kubernetes and its related technologies directly from industry experts.
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