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One of our goals at BanzaiCloud is to make our customers’ lives easier by providing low barrier to entry, easy to use solutions for running applications on Kubernetes. To achieve this, we often rely on Kubernetes Operators to provide comprehensive solutions over the course of an application's lifecycle. Here is a list of our operators, which we have already open sourced: Vault Operator Prometheus JMX Exporter Operator Wildfly Operator
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At Banzai Cloud we are building a feature rich enterprise-grade application platform, built for containers on top of Kubernetes, called Pipeline. Security is one of our main areas of focus, and we strive to automate and enable those security patterns we consider essential, including tier zero features for all enterprises using the Pipeline Platform. We've blogged about how to handle security scenarios on several of our previous posts. This time we'd like to focus on a different aspect of securing Kubernetes deployments:
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We are excited to announce that Banzai Cloud has joined the Cloud Native Computing Foundation! The CNCF and The Linux Foundation are expending extraordinary effort in helping to standardize open source technologies that enable the development, deployment, management and operation of next generation Cloud Native software stacks. Our mission is to bring Cloud Native to enterprises and with this announcement, we strive to help push container and cloud native technology standardization and interoperability forward.
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At Banzai Cloud we are building a feature-rich enterprise-grade application platform, built for containers on top of Kubernetes, called Pipeline. For an enterprise-grade application platform security is a must and it has many building blocks. Please read through the Security series on our blog to learn how we deal with a variety of security-related issues. Security series: Authentication and authorization of Pipeline users with OAuth2 and Vault Dynamic credentials with Vault using Kubernetes Service Accounts Dynamic SSH with Vault and Pipeline Secure Kubernetes Deployments with Vault and Pipeline Policy enforcement on K8s with Pipeline The Vault swiss-army knife The Banzai Cloud Vault Operator Vault unseal flow with KMS
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At Banzai Cloud we are building a feature rich enterprise-grade application platform, built for containers on top of Kubernetes, called Pipeline. With Pipeline we provision large, multi-tenant Kubernetes clusters on all major cloud providers such as AWS, GCP, Azure, Oracle, Alibaba and BYOC, on-premise and hybrid, and deploy all kinds of predefined or ad-hoc workloads to these clusters. For us and our enterprise users, Kubernetes secret management (base 64) was not sufficient, so we chose Vault and added Kubernetes support to manage our secrets.
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If you followed our blog series on Autoscaling on Kubernetes, you should already be familiar with Kubernetes’ Cluster autoscaler and the Vertical Pod Autoscaler used with Java 10 applications. This post will show you how to use the Horizontal Pod Autoscaler to autoscale your deployments based on custom metrics obtained from Prometheus. As a deployment example we've chosen our JEE Petstore example application on Wildfly to show that, beside metrics like cpu and memory, which are provided by default on Kubernetes, using our Wildfly Operator, all Java and Java Enterprise Edition / Wildfly specific metrics are automatically placed at your fingertips, available in Prometheus, allowing you to easily autoscale deployments.
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Jun 25 2018

Hands on Thanos

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Here at Banzai Cloud we blog a lot about Prometheus and how to use it. One of the problems we have so far neglected to discuss is the inadequate long term storage capability of Prometheus. Luckily a new project called Thanos seeks to address this. If you are not familiar with Prometheus, or are interested in other monitoring related articles, check out our monitoring series, here: Monitoring series: Monitoring Apache Spark with Prometheus Monitoring multiple federated clusters with Prometheus - the secure way Application monitoring with Prometheus and Pipeline Building a cloud cost management system on top of Prometheus Monitoring Spark with Prometheus, reloaded
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When we started to work on our cluster infrastructure recommender, Telescopes, we soon realized how difficult it was to get instance type attributes and pricing information from cloud providers programatically. While EC2, Google Cloud, and Azure all provide some kind of API from which to query this information, in some cases these APIs respond with partially inconsistent data, or their responses are large chunks of JSON files that are very cumbersome to parse.
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At Banzai Cloud we are building a feature rich enterprise-grade application platform, built for containers on top of Kubernetes, called Pipeline. With Pipeline we provision large, multi-tenant Kubernetes clusters on all major cloud providers such as AWS, GCP, Azure and BYOC, on-premise and hybrid, and deploy all kinds of predefined or ad-hoc workloads to these clusters. For us and our enterprise users, Kubernetes secret management (Base64) was woefully inadequate, so we chose Vault with native Kubernetes support to manage our secrets.
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This post highlights how the Pipeline Platform enables Managed Service Identity (MSI) and assigns the Storage Account Contributor role to AKS cluster Virtual Machines. But wait, why? At Banzai Cloud we have a PVC Operator, which makes using Kubernetes Persistent Volumes easier on cloud providers by dynamically creating the required accounts and storage classes. That operator allows us to use the same Helm chart on all supported providers, thus there is no need to create cloud specific Helm charts.
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