Universal-Kubernetes-Helm-Charts
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Universal-Kubernetes-Helm-Charts | Grafana | |
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17 | 379 | |
101 | 60,395 | |
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6.7 | 10.0 | |
20 days ago | 1 day ago | |
Smarty | TypeScript | |
MIT License | GNU Affero General Public License v3.0 |
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Universal-Kubernetes-Helm-Charts
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Dedpulication standards of Helm Charts values file for a global chart with subcharts for our app. What's the right way to only need to specify a value once?
I would point you to what I call the "Universal Helm Charts" and some examples of how to use them.
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Monitoring many cluster k8s
Shameless Plug: Here's one of my dashboards I made for Ingress-Nginx, which is my recommended border router/gateway into all the services. It adds deep robust metrics and configurability, and if you've got years of experience with Nginx also, it allows you rich complex customization via nginx's configuration structure via kubernetes annotations. Besides that I have open-source helm charts which are easy to use, boilerplates showing how to use them, a volume autoscaler to automatically resize your disks as they get full, and a blog where I share various of my experience which is a companion blog to my upcoming book of the same name. Hope this helps! Feel free to ask if you have any further questions.
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Best way of managing Helm?
You may want to check out some other of my Helm Boilerplates to explain and highlight how using subcharts works. This is a companion repo to my upcoming DevOps + Kubernetes book. You also might like to check out my set of open-source universal helm charts which are published in a helm registry right now that you can leverage and has many industry best-practices built into it, such as anti-affinity rules, pod disruption budgets, horizontal pod autoscaling, ingress, service support, etc.
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How do you guys on Mac M1's get around the annoying port forwarding issues with k8s + docker?
References: I use docker and Kubernetes daily. I currently manage numerous clusters and maintain pipelines for hundreds of microservices as I type this. I've been converting microservices into Docker images for companies hundreds if not thousands of times by now over the last bunches of years. I am also an avid and passionate open-source evangelist and Kubernetes/DevOps consultant. I author some Kubernetes controllers such as the Volume Autoscaler and have a set of Open Source Helm Charts and I love to contribute code/fixes wherever I run into issues.
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StatelessSet Resource Type ?
If it helps at all I have some universal helm charts that have a template for easily deploying your application as a deployment or statefulset. You will notice I don’t even have a daemonset chart because it doesn’t make sense to. https://github.com/DevOps-Nirvana/Universal-Kubernetes-Helm-Charts
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Helm makes it overly complex, or is it just me?
See: Open-Source Universal Helm Charts See: Boilerplates of using Open-Source Helm Charts (as a sub-chart)
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The Helmet is a Helm Library Chart that defines many chart templates like Deployment, Service, Ingress, etc which can used in other application charts.
Helm charts - https://github.com/DevOps-Nirvana/Universal-Kubernetes-Helm-Charts Example using helm charts as sub charts - https://github.com/DevOps-Nirvana/Helm-Chart-Boilerplates/tree/master/boilerplate-echoserver
- How do you guys manage your deployment pipelines?
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Monthly 'Shameless Self Promotion' thread - 2023/01
A open-source set of Universal Helm Charts with tons of best-practices baked into it such as autoscaling, PDBs, labeling, and an standardized set of "universal" templates that allows you to pivot between templates easily (meaning, you can easily make a deployment into a Statefulset or a Cronjob). Yes, I need to add more documentation, I know. I'm busy :P
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Creating Kubernetes Templates
Universal Kubernetes Helm Charts
Grafana
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Docker Log Observability: Analyzing Container Logs in HashiCorp Nomad with Vector, Loki, and Grafana
Monitoring application logs is a crucial aspect of the software development and deployment lifecycle. In this post, we'll delve into the process of observing logs generated by Docker container applications operating within HashiCorp Nomad. With the aid of Grafana, Vector, and Loki, we'll explore effective strategies for log analysis and visualization, enhancing visibility and troubleshooting capabilities within your Nomad environment.
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Golang: out-of-box backpressure handling with gRPC, proven by a Grafana dashboard
To help us visualize these scenarios, we'll build a Grafana Dashboard so we can follow along.
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Monitoring, Observability, and Telemetry Explained
Visualization and Analysis: Choose a tool with intuitive and customizable dashboards, charts, and visualizations. A question to ask is, "Are the visualization features of this tool user-friendly and adaptable to our team's specific needs?" Tools like Grafana and Kibana provide powerful visualization capabilities.
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4 facets of API monitoring you should implement
Prometheus: Open-source monitoring system. Often used together with Grafana.
- Grafana: Open and composable observability and data visualization platform
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The Mechanics of Silicon Valley Pump and Dump Schemes
Grafana
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Reverse engineering the Grafana API to get the data from a dashboard
Yes I'm aware that Grafana is open source but the method I used to find the API endpoints is far quicker than digging through hundreds of files in a codebase I'm not familiar with.
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Building an Observability Stack with Docker
So, you will add one last container to allow us to visualize this data: Grafana, an open-source analytics and visualization platform that allows us to see traces and metrics simply. You can set Grafana to read data from both Tempo and Prometheus by setting them as datastores with the following grafana.datasource.yaml config file:
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How to collect metrics from node.js applications in PM2 with exporting to Prometheus
In example above, we use 2 additional parameters: code (HTTP response code) and page (page identifier), which provide detailed statistics. For example, you can build such graphs in Grafana:
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Root Cause Chronicles: Quivering Queue
Robin switched to the Grafana dashboard tab, and sure enough, the 5xx volume on web service was rising. It had not hit the critical alert thresholds yet, but customers had already started noticing.
What are some alternatives?
Helm-Chart-Boilerplates - Example implementations of the universal helm charts
Thingsboard - Open-source IoT Platform - Device management, data collection, processing and visualization.
charts - TrueNAS SCALE Apps Catalogs & Charts
Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]
Packer - Packer is a tool for creating identical machine images for multiple platforms from a single source configuration.
Heimdall - An Application dashboard and launcher
eksctl - The official CLI for Amazon EKS
Wazuh - Wazuh - The Open Source Security Platform. Unified XDR and SIEM protection for endpoints and cloud workloads.
helm-promotion-sample-app - Sample application that is promoted from QA to Staging to Production
Thingspeak - ThingSpeak is an open source “Internet of Things” application and API to store and retrieve data from things using HTTP over the Internet or via a Local Area Network. With ThingSpeak, you can create sensor logging applications, location tracking applications, and a social network of things with status updates.
Chalice-PynamoDB-Docker-Starter-Kit - A starter kit with some boilerplate code for getting started making low-cost serverless applications in Python on AWS with a great local development setup via Docker Compose
uptime-kuma - A fancy self-hosted monitoring tool