One of the main features of the Banzai Cloud Pipeline platform is that it allows enterprises to run workloads cost effectively by mixing spot or preemptible instances with regular ones, without sacrificing overall reliability. The platform allows enterprises to develop, deploy and scale container-based applications and it leverages best-of-breed cloud components, such as Kubernetes, to create a highly productive yet flexible environment for developers and operation teams alike. tl;dr The Banzai Cloud Pipeline platform switched to a unified, cloud-aware spot instance termination handler to properly drain the cluster node and provide information to the monitoring system if an instance is going to be preempted from a cluster nodepool.

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.

A few weeks back we released Telescopes, our Kubernetes cluster layout recommender application. That application has evolved quite a bit, and in this post we’ll provide insight into some its new features and recent changes. 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 tl;dr: We added new features to Telescopes to provide support for blacklisting or whitelisting instance types Recommendation accuracies can now be checked There is now support that allows asking cloud instance types for CPU, memory and network performance.

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.

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 Kubernetes was designed in such a way as to be fault tolerant of worker node failures. If a node goes missing because of a hardware problem, a cloud infrastructure problem, or if Kubernetes simply ceases to receive heartbeat messages from a node for any reason, the Kubernetes control plane is clever enough to handle it.

The adoption of serverless technologies is quickly progressing. According to this survey, it’s on par with the adoption of containers. And, even though ‘serverless’ is a very vague term (it can be argued that it’s rarely used in production, especially in complex applications), it seems set to be one of the most dominant trends in the near future in the cloud computing space. While, once, serverless referred specifically to early stage AWS Lambda, the category has matured rapidly.

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 You may remember the Hollowtrees project we open sourced a few weeks ago: a framework for the management of 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.

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.

Hollowtrees is a wave of highest pedigree, the pin-up centerfold of the Mentawai islands’ surf break which brings new machine-like connotations to the word perfection. Watch out for the aptly named ‘Surgeon’s Table’, a brutal reef famous for taking bits and pieces of Hollowtrees’ surfers as trophies. Hollowtrees, a ruleset based watch-guard keeps spot instance-based clusters safe and allows for them to be used in production. It handles spot price surges within a given region or availability zone and reschedules applications before instances are taken down.

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 One of the primary advantages always discussed in the context of deciding whether to move a deployment to the cloud is cost. There are no upfront costs in moving to the cloud because you don’t have to buy any hardware, and you only pay for what you really use because you can scale your infrastructure according to your workloads.