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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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Check out Backyards in action on your own clusters: curl https://getbackyards.sh | sh && backyards install -a --run-demo What to know more? Get in touch with us, or delve into the details of the latest release. 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.
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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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A few weeks ago we announced a new version of Pipeline, the hybrid any-cloud platform. This post is part of a series of posts highlighting the multi- and hybrid-cloud features on that platform. Today, we will be focusing specifically on multi-cloud features. Before we take a deep dive into our technical content, let’s go over some of the key expectations an enterprise has when it embraces a multi-cloud strategy:
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Amid a growing number of increasingly sophisticated cyber attacks, enterprises are searching for ways to enable security wherever possible, in order to protect their data in transit and at rest. Big data processing is no exception; security is a very broad topic and to cover it in its entirety would be beyond the scope of this post. Instead, we will focus exclusively on those security capabilities that Spark on Kubernetes provides (by Spark on Kubernetes, we mean when Spark uses Kubernetes as an external cluster manager for creating and running executors).
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Check out Backyards in action on your own clusters: curl https://getbackyards.sh | sh && backyards install -a --run-demo What to know more? Get in touch with us, or delve into the details of the latest release. Service mesh probably needs no introduction. But, just to recap, let’s define it as a highly configurable, dedicated and low‑latency infrastructure layer designed to handle and provide reliable service-to-service communication, implemented as lightweight network proxies deployed alongside application code.
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