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We strongly believe in Rust as a powerful language for building production-grade software, especially for systems like ours that run alongside Kubernetes.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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external-dns
Configure external DNS servers (AWS Route53, Google CloudDNS and others) for Kubernetes Ingresses and Services
The second one is a combination of tools: External DNS, cert-manager, and NGINX ingress. Using these as a stack, you can quickly deploy an application, making it available through a DNS with a TLS without much effort via simple annotations. When I first discovered External DNS, I was amazed at its quality.
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Pierre: The first tool I recommend is K9s. It's not just a time-saver but a productivity booster. With its intuitive interface, you can speed up all the usual kubectl commands, access logs, edit resources and configurations, and more. It's like having a personal assistant for your cluster management tasks.
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The second one is a combination of tools: External DNS, cert-manager, and NGINX ingress. Using these as a stack, you can quickly deploy an application, making it available through a DNS with a TLS without much effort via simple annotations. When I first discovered External DNS, I was amazed at its quality.
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The second one is a combination of tools: External DNS, cert-manager, and NGINX ingress. Using these as a stack, you can quickly deploy an application, making it available through a DNS with a TLS without much effort via simple annotations. When I first discovered External DNS, I was amazed at its quality.
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The last one is mostly an observability stack with Prometheus, Metric server, and Prometheus adapter to have excellent insights into what is happening on the cluster. You can reuse the same stack for autoscaling by repurposing all the data collected for monitoring.
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metrics-server
Scalable and efficient source of container resource metrics for Kubernetes built-in autoscaling pipelines.
The last one is mostly an observability stack with Prometheus, Metric server, and Prometheus adapter to have excellent insights into what is happening on the cluster. You can reuse the same stack for autoscaling by repurposing all the data collected for monitoring.
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The last one is mostly an observability stack with Prometheus, Metric server, and Prometheus adapter to have excellent insights into what is happening on the cluster. You can reuse the same stack for autoscaling by repurposing all the data collected for monitoring.
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When it came to deployment, I had several options, and I chose the hard way: deploying Kubernetes on bare metal nodes using KubeSpray. Troubleshooting bare metal Kubernetes deployments honed my skills in pinpointing issues. This hands-on experience provided a deep understanding of how each component, like the Control Plane, kubelet, Container Runtime, and scheduler, interacts to orchestrate containers.
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Another resource that I found pretty helpful was "Kubernetes the Hard Way" by Kelsey Hightower despite its complexity.
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We use Cluster Autoscaler to automatically adjust the number of nodes (cluster size) based on your actual usage to ensure efficiency. Additionally, we deploy Vertical and Horizontal Pod Autoscalers to scale your applications' resources as their needs change automatically.
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We closely monitor Kubernetes and cloud providers' updates by following official changelogsand using RSS feeds, allowing us to anticipate potential issues and adapt our infrastructure proactively.
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We also leverage tools like Kubent, popeye, kdave, and Pluto to help us manage API deprecations (when Kubernetes deprecates features in updates) and ensure the overall health of our infrastructure.
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We also leverage tools like Kubent, popeye, kdave, and Pluto to help us manage API deprecations (when Kubernetes deprecates features in updates) and ensure the overall health of our infrastructure.
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We also leverage tools like Kubent, popeye, kdave, and Pluto to help us manage API deprecations (when Kubernetes deprecates features in updates) and ensure the overall health of our infrastructure.
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We also leverage tools like Kubent, popeye, kdave, and Pluto to help us manage API deprecations (when Kubernetes deprecates features in updates) and ensure the overall health of our infrastructure.
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We keep a close eye on all the charts we use by storing them in a central repository. This way, we have a clear history of every version we've used. We use a tool called helm-freeze to lock down the specific version of each chart we want to use. We can also track changes between chart and software versions using the git diff command.
