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Since releasing our open-source Istio operator, we’ve been doing our best to add support for the latest Istio versions as rapidly as possible. Today, we’re happy to announce that we have added Istio 1.2 support for the Banzai Cloud Istio operator. When we added Istio 1.1 support for the operator, we wrote a detailed blog post about how to employ a seamless Istio control plane upgrade in a single-mesh, single-cluster setup.

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At Banzai Cloud we are passionate about observability, and we expend a great amount of effort to make sure we always know what’s happening inside our Kubernetes clusters. All clusters provisioned with Pipeline - our multi- and hybrid-cloud container management platform - are provided with, and rely upon, each of the three pillars of observability: federated monitoring, centralized log collection and traces. In order to automate log collection on Kubernetes, we opensourced a logging-operator built on the Fluent ecosystem.

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A few weeks ago we announced Backyards, Banzai Cloud’s automated service mesh built on top of our Istio operator, which greatly simplifies the complex management of service meshes across multi and hybrid-cloud environments. Backyards is integrated into Banzai Cloud’s container management platform, Pipeline. However, it also works, and is available, as a standalone product. Naturally, using Backyards with Pipeline provides users with a variety of specific benefits (like managing applications in a multi-cloud world) but Backyards works on any Kubernetes installation.

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If you’re reading this post, you’re likely already familiar with our container management platform, Pipeline, and our CNCF certified Kubernetes distribution, PKE: you probably already know how we make it possible to spin up clusters across five cloud providers and on-premise, in multi-cloud but also hybrid-cloud environments. But whether these are single or multi-cluster topologies, resilience is key. We at Banzai Cloud believe this is the case not just for infrastructural components but for entire managed application environments, like Apache Kafka.

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At Banzai Cloud we work on a multi- and hybrid-cloud container management platform, Pipeline. As a result, we’ve opensourced quite a few Kubernetes operators. While writing some of the more complex operators, such as those for Istio, Vault or Kafka, we were faced with lots of unnecessary Kubernetes object updates. These updates are a byproduct of the fact that operators are typically used to manage a large number of resources.

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A strong focus on security has always been a key part of the Banzai Cloud’s Pipeline platform. We incorporated security into our architecture early in the design process, and developed a number of supporting components to be used easily and natively on Kubernetes. From secrets, certificates generated and stored in Vault, secrets dynamically injected in pods, through provider agnostic authentication and authorization using Dex, to container vulnerability scans and lots more: the Pipeline platform handles all these as a default tier-zero feature.

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If you are a frequent reader of this blog or familiar with our products, you may already be aware that the control plane of our multi- and hybrid-cloud container management platform, Pipeline, is available not just as a free/developer service but can be run in any number of preferred envionments, whether cloud or on-prem. The control-plane’s only requirement is Kubernetes, its installation wholely automated by the banzai CLI tool alongside our own CNCF certified Kubernetes distribution, PKE.

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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.

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This is the second part of a very popular post, Helm from basics to advanced. In the previous post (we highly suggest you read it, if you haven’t done so already) we covered Helm’s basics, and finished with an examination of design principles. In this post, we’d like to continue our discussion of Helm by exploring best practices and taking a look at some common mistakes. If you are looking for a place to securely store your Helm charts, remember that Banzai Cloud runs a free Helm Charts repository as a service: charts.

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A few weeks ago we opensourced our Kafka operator, the engine behind our Kafka Spotguide - the easiest way to run Kafka on Kubernetes when it’s deployed to multiple clouds or on-prem, with out-of-the-box monitoring, security, centralized log collection, external access and more. One of our customers’ preferred features is the ability of our Kafka operator to react to custom alerts, in combination with the default options we provide: options like cluster upscaling, adding new Brokers, cluster downscaling, removing Brokers or adding additional disks to a Broker.

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