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Istio, and in general the service mesh has changed the way of service to service communication (from dumb pipes and smart endpoints to sidecar-to-sidecar). While this has lots of benefits, it can increase the complexity of troubleshooting microservice to microservice communication. One of the typical places developers are checking when comes to troubleshoot is the Envoy sidecar proxy container's access logs, both on the source and destination side. With the increased number of microservices deployed to distributed environments, this process can be tedious, and it's very inconvenient trying to pair source and destination access log pairs.
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There has been a lot of talk about multi- and hybrid-clouds over the past years. Some cloud vendors see these trends as a threat, others look at them as an opportunity. We think that beneath the buzzwords lie some very important use-cases driven by the needs of enterprises and SaaS providers. However, delivering and operating multi- and hybrid-clouds has been too complex for most organizations so far. One major area of focus for Banzai Cloud has been hybrid clouds, to create and automate a seamless and consistent operational experience for a concept that has a lot of underlying complexities.
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One of the most popular feature of Bank-Vaults, the Vault swiss-army knife for Kubernetes is the secret injection webhook. With the growing popularity of Istio, recently the most requested feature was to support for running Bank-Vaults alongside Istio. We are big fans of Istio (a year ago we open sourced an Istio operator) and we have built an automated and operationalized service mesh, Banzai Cloud Backyards. As both components (Bank-Vaults and Backyards) are part of our hybrid cloud container management plaform, Pipeline, we went ahead and made them work together smoothly.
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Apache Kafka was designed with a heavy emphasis on fault-tolerance and high-availability in mind, and thus provides different methods of ensuring enterprise-grade resiliency such as: replication factor - which defines how many partition replicas of a topic should be kept, each one being stored on a different broker. A replication factor of N allows for the loss of N-1 brokers. The new brokers will replace the lost brokers until the number of remaining broker(s) reaches the replication factor, or the number of copies of the partitions of a topic.
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If you spend any of your time dealing with the cloud native world, you've probably already heard about Kubeflow. It's something we've been playing with since we first began to explore the possibility of running Tensorflow in a distributed way. That was quite some time ago. Since then, Kubeflow has rapidly evolved, so that it now includes dozens of machine learning (ML) frameworks. The frameworks allow for the training and serving of all kinds of machine learning models.
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Almost every blog post or lecture explaining how Istio service meshes route traffic takes the time to go over how sidecar containers capture outgoing traffic - how that traffic is routed to another service with another sidecar. However, in the real world, a large amount of network traffic passes through the boundaries of the service mesh itself. That traffic might be from a public facing app that receives traffic from the internet, an internal service that needs to connect to a legacy application running outside the mesh, or a workload that consumes an external, third party API.
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Over the past few years, Kubernetes has become the de facto standard platform on which the world runs its cloud native applications. Although it has a great value proposition for use in all kinds of cases, its ecosystem is immensely complex and it requires a lot of expertise to operate. This is where the Banzai Cloud Pipeline platform comes in. Our mission is to help integrate Kubernetes into existing organizations, and to make the Kubernetes experience better for everyone:
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In today's blogpost we're going to be discussing ingress and egress gateways. First, we'll cover the basics, then we'll go into detail and explore how they work through a series of practical examples. Ingress and egress gateways are load balancers that operate at the edges of any network receiving incoming or outgoing HTTP/TCP connections. Ingress gateways make it possible to define an entry points into an Istio mesh for all incoming traffic to flow through.
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At Banzai Cloud we support and manage hybrid Kubernetes clusters for our customers across five clouds and on-prem (bare metal, VMware). Therefore, the ability and fluency required to observe these clusters is an absolute must. Very frequently, the Pipeline control plane is tasked with managing multiple Kubernetes clusters, which it does through our own CNCF certified Kubernetes distribution, PKE, or a cloud provider-managed distribution. When that happens, it's important that we federate metrics, collect them into a single place for querying, analysis and long term storage.
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Update: While the Kubernetes sidecar feature described in this post did not make it into the 1.18 Kubernetes release, the (sidecar) pattern and the container lifecycle changes are here the stay and can be expected in the 1.19 release. The sidecar concept in Kubernetes is getting more and more popular, and for a good reason. In the container world, it's a common principle that a container should address a single concern only, but do it well.
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