Banzai Cloud Logo Close
Home Products Benefits Blog Company Contact
Get Started
In the last few months we wrote a lot of different blog posts about the Istio service mesh. We started with a simple Istio operator, then went on with different multi-cluster service mesh topologies, Istio CNI and a telemetry deep dive. The contents of the posts were built around our open source Istio operator that helps installing and managing an Istio service mesh in a single or multi and hybrid-cluster setup.
Read more...
One of the core features of the Istio service mesh is the observability of network traffic. Because all service-to-service communication is going through Envoy proxies, and Istio’s control plane is able to gather logs and metrics from these proxies, the service mesh can give you deep insights about your network. While a basic Istio installation is able to set up all the components needed to collect telemetry from the mesh, it’s not easy to understand how these components fit together and how to configure them in a production environment.
Read more...
Two weeks ago we announced the first release of our Istio operator. Since then we’ve added support for Istio’s preliminary 1.1 release. This post will detail how and why you should try it. In creating the operator, our main goal was to simplify the deployment and management of Istio’s components. This release is still in alpha, and its main goal is still to replace Helm charts as a preferred means of installing Istio, but it provides a few additional features we think you’ll find convenient.
Read more...
Service mesh has, without question, been one of the most vigorously debated and obsessed over topics of discussion in recent memory. It seems like, whichever way you turn, you run into heated arguments between those developers that are convinced that service mesh will outgrow even Kubernetes, and the naysayers convinced that, outside of use in a few large companies, service mesh is impractical to the point of uselessness. As always, the truth probably lies somewhere in between, but that doesn’t mean you can avoid developing an opinion, especially if you’re a Kubernetes distribution and platform provider like us.
Read more...
Our last two blog posts about the Kubernetes scheduler explained how taints and tolerations and different types of affinities are working. In today’s post we are going one layer deeper and we’ll discuss how to implement and deploy a custom Kubernetes scheduler. Writing a scheduler may sound intimidating at first, but if you’ll follow this article you’ll realise that creating something that works and schedules pods based on some simple rules is quite easy.
Read more...
The Kubernetes scheduler can be constrained to place a pod on particular nodes using a few different options. One of these options is node and pod affinities. In a smaller homogeneous cluster they probably don’t make too much sense, because the scheduler is doing a good job spreading pods on different nodes, - well, that’s its job - but when you have a larger cluster with different types of nodes, maybe even spreading across availability zones, or multiple racks, then affinities may come in handy.
Read more...
The Banzai Cloud Pipeline platform allows enterprises to develop, deploy and scale container-based applications. It leverages best-of-breed cloud components, such as Kubernetes, to create a highly productive, yet flexible environment for developers and operation teams alike. One of the main features of the Pipeline platform is that it allows enterprises to run workloads cost effectively by mixing spot instances with regular ones, without sacrificing overall reliability. This requires quite a lot of behind the scenes magic to be built on top of core Kubernetes building blocks.
Read more...
Banzai Cloud’s Pipeline platform is an operating system which allows enterprises to develop, deploy and scale container-based applications. It leverages best-of-breed cloud components, such as Kubernetes, to create a highly productive, yet flexible environment for developers and operation teams alike. One of the main features of the Pipeline platform is that it allows enterprises to run workloads cost effectively by mixing spot instances with regular ones, without sacrificing overall reliability.
Read more...
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.
Read more...
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.
Read more...