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Satellite is a Golang library and RESTful API that determines a host's cloud provider with a simple HTTP call. Behind the scenes, it uses file systems and provider metadata to properly identify cloud providers. When we started to work on Pipeline and the Banzai Cloud Pipeline Platform Operators, we soon realized how frequently we would need to find out which cloud provider the service was actually running on. Note that Pipeline supports 6 different cloud providers
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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 Hands on Thanos Monitoring Vault on Kubernetes using Cloud Native technologies At Banzai Cloud we are building a feature rich enterprise-grade application platform, built for containers on top of Kubernetes, called Pipeline.
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The Banzai Cloud Cloudinfo service retrieves product and pricing information from cloud providers and exposes it through a RESTful API, and UI. Our Kubernetes based Pipeline platform and Telescopes recommendation engine make use of this information when they advise users on cluster layout and resourcing. Here's a quick primer of how and why we utilize the Cloudinfo service: Pipeline platform users have the option of launching clusters or deploying applications based only on resource- and SLA-requirements (price, IO, memory, CPU, GPU, etc.
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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 Hands on Thanos Monitoring Vault on Kubernetes using Cloud Native technologies In depth application observability is a must-have feature for us; we put significant effort into monitoring all our customers’ Kubernetes deployments on the Pipeline platform, as well as the platform itself.
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One of the main advantages of the Pipeline platform is that it allows users to use their infrastructure cost effectively; Telescopes helps with cluster and machine instance recommendations, Hollowtrees enables SLA-aware cost reduction using spot instances, and autoscalers allow for multi-dimensional autoscaling based on custom metrics. This post will highlight some new features of the Banzai Cloud Horizontal Pod Autoscaler Kubernetes Operator and the advanced automation supported by Pipeline - a new, forward-thinking way to operate Kubernetes clusters and autoscale deployments.
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Two core features of the Pipeline platform are advanced security and observability for all Kubernetes deployments. We make sure that all secrets are securely stored, transported, images scanned, deployments monitored, and logs centrally collected. As you might expect from us, we use the industry standard in security components, such as Vault, Prometheus, Grafana, Fluent and more. This post is about monitoring Vault with Prometheus (on Kubernetes) and displaying metrics on Grafana.
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Enterprises often use multi-tenant and heterogenous clusters to deploy their applications to Kubernetes. These applications usually have needs which require special scheduling constraints. Pods may require nodes with special hardware, isolation, or colocation with other pods running in the system. The Pipeline platform allows users to express their constraints in terms of resources (CPU, memory, network, IO, etc.). These requirements are turned into infrastructure specifications using Telescopes. Once the cluster nodes are created and properly labeled by Pipeline, deployments are run with the specified constraints automatically on top of Kubernetes.
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Banzai Cloud announced today that it is collaborating with Oracle to bring its feature-rich application platform to Oracle Kubernetes Engine users. Banzai Cloud’s Pipeline deployment automation and execution engine enables developers to go from commit to scale in minutes by automating all the underlying tasks that provide convenient CI/CD flows, robust security, analytics and the ability to scale. The technology not only provides significant productivity gains to developers, but also increases operational efficiencies by aiding instance selection and automated introspection of large-scale workloads.
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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. The platform itself consists of many building blocks - over 30 components - but they share one commonality: they are all developed in Golang. Obviously we are very fond of Go and like it quite a bit, so in this post we'd like to share the error handling practices that our team of 20+ developers adheres to while building the Pipeline platform.
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Last year Alibaba joined CNCF and announced plans to create their own Kubernetes service - Alibaba ACK. The service was luanched more than a year ago, with its stated objective to make it easy to run Kubernetes on Alibaba Cloud without needing to install, operate, and maintain a Kubernetes control plane. At Banzai Cloud we are committed to providing support for Kubernetes on all major cloud providers, thus one of our priorities was to enable Alibaba Cloud's Container Service for Kubernetes in Pipeline and take the DevOps experience to the next level by turning ACK into a feature-rich enterprise-grade application platform.
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