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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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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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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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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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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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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 At Banzai Cloud we deploy large distributed applications to Kubernetes clusters that we also operate. We don’t enjoy waking up to PagerDuty notifications in the middle of the night, so we try to get ahead of problems by operating these clusters as efficiently as possible.
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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 Kafka on Kubernetes the easy way At Banzai Cloud we provision and monitor large Kubernetes clusters deployed to multiple cloud/hybrid environments, using Prometheus. The clusters, applications or frameworks are all managed by our next generation PaaS, Pipeline.
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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 At Banzai Cloud we provision and monitor large Kubernetes clusters deployed to multiple cloud/hybrid environments. These clusters and applications or frameworks are all managed by our next generation PaaS, Pipeline.
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At Banzai Cloud we run multiple Kubernetes clusters deployed with our next generation PaaS, Pipeline, and we deploy these clusters across different cloud providers like AWS, Azure and Google, or on-premise. These clusters are typically launched via the same control plane deployed either to AWS, as a CloudFormation template, or Azure, as an ARM template. And, since we practice what we preach, they run inside Kubernetes as well. One of the added values to deployments via Pipeline is out-of-the-box monitoring and dashboards through default spotguides for the applications we also support out-of-the-box.
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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 Cluster recommender Cloud instance type and price information as a service Last week we open sourced the Hollowtrees project, a framework that manages AWS spot instance clusters - batteries included: Hollowtrees - an alert-react based framework that’s part of the Pipeline PaaS, which coordinates monitoring, applies rules and dispatches action chains to plugins using standard CNCF interfaces AWS spot instance termination Prometheus exporter AWS autoscaling group Prometheus exporter AWS Spot Instance recommender Kubernetes action plugin to execute k8s operations (e.
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