helm
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helm | Grafana | |
---|---|---|
205 | 378 | |
25,974 | 60,196 | |
0.9% | 1.3% | |
9.0 | 10.0 | |
6 days ago | 5 days ago | |
Go | TypeScript | |
Apache License 2.0 | GNU Affero General Public License v3.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
helm
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deploying a minio service to kubernetes
helm
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Building a VoIP Network with Routr on DigitalOcean Kubernetes: Part I
Helm (Get from here https://helm.sh/)
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The 2024 Web Hosting Report
It’s also well understood that having a k8s cluster is not enough to make developers able to host their services - you need a devops team to work with them, using tools like delivery pipelines, Helm, kustomize, infra as code, service mesh, ingress, secrets management, key management - the list goes on! Developer Portals like Backstage, Port and Cortex have started to emerge to help manage some of this complexity.
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Deploying a Web Service on a Cloud VPS Using Kubernetes MicroK8s: A Comprehensive Guide
Kubernetes orchestrates deployments and manages resources through yaml configuration files. While Kubernetes supports a wide array of resources and configurations, our aim in this tutorial is to maintain simplicity. For the sake of clarity and ease of understanding, we will use yaml configurations with hardcoded values. This method simplifies the learning process but isn’t ideal for production environments due to the need for manual updates with each new deployment. Although there are methods to streamline and automate this process, such as using Helm charts or bash scripts, we’ll not delve into those techniques to keep the tutorial manageable and avoid fatigue — you might be quite tired by that point!
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Deploy Kubernetes in Minutes: Effortless Infrastructure Creation and Application Deployment with Cluster.dev and Helm Charts
Helm is a package manager that automates Kubernetes applications' creation, packaging, configuration, and deployment by combining your configuration files into a single reusable package. This eliminates the requirement to create the mentioned Kubernetes resources by ourselves since they have been implemented within the Helm chart. All we need to do is configure it as needed to match our requirements. From the public Helm chart repository, we can get the charts for common software packages like Consul, Jenkins SonarQube, etc. We can also create our own Helm charts for our custom applications so that we don’t need to repeat ourselves and simplify deployments.
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Introduction to Helm: Comparison to its less-scary cousin APT
Generally I felt as if I was diving in the deepest of waters without the correct equipement and that was horrifying. Unfortunately to me, I had to dive even deeper before getting equiped with tools like ArgoCD, and k8slens. I had to start working with... HELM.
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🎀 Five tools to make your K8s experience more enjoyable 🎀
Within the architecture of Cyclops, a central component is the Helm engine. Helm is very popular within the Kubernetes community; chances are you have already run into it. The popularity of Helm plays to Cyclops's strength because of its straightforward integration.
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Building a Kubernetes Operator with the Operator Framework
helm: brew install helm
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Kubernetes Made Simple - Introducing Cyclops
Not to go too deep, but Helm is a very popular open-source package manager for Kubernetes. It helps you create configuration files that are needed for applications running in Kubernetes. These charts let Kubernetes know how to handle your application in the cluster.
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10 Ways for Kubernetes Declarative Configuration Management
Helm: The package management tool of Kubernetes resources, which manages the configuration of Kubernetes resources through the configuration template.
Grafana
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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.
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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.
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Teach Yourself Programming in Ten Years (1998)
I completely agree but do feel it needs qualifying. The problems beginners run into aren't usually the same as the problems experienced devs run into when adopting a language new to them, but where I see the two overlap I know something is a serious hazard in a language.
Java as a first language: won't like the boilerplate but won't have any point of comparison anyway, will get a few NPEs, might use threads and get data races but won't experience memory unsafety.
Go as a first language: much less boilerplate, but will still get nil panics, will be encouraged to use goroutines because every tutorial shows off how "easy" they are, will get data races with full blown memory unsafety immediately.
Rust as a first language: `None` // no examples found
I think Go as a beginner language would be better if people were discouraged from using goroutines instead of actively encouraged (the myth of "CSP solves everything"), otherwise I think it needs much better tooling to save people from walking off a cliff with their goroutines. And no, -race clearly isn't it, especially not for a beginner.
And in one respect I've found Go more of a hazard for experienced devs than beginners: the function signature of append() gives you the intuition of a functional programming append that never modifies the original slice. This has literally resulted in CVEs[1] even by experienced devs, especially combined with goroutines. Beginners won't have an intuition for this and will hopefully check the documentation instead of assuming.
[1] https://github.com/grafana/grafana/security/advisories/GHSA-...
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Start your server remotely
I build the Tasmota firmware for the S31's nightly, and expose the Prometheus endpoint so I can also monitor the current used by these devices in real time with the data pushed to Grafana. I have ~30 of them in my home/homelab, and servers, appliances, sump pump, fans, etc. are all monitored by my S31 fleet.
What are some alternatives?
Thingsboard - Open-source IoT Platform - Device management, data collection, processing and visualization.
Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]
Heimdall - An Application dashboard and launcher
Wazuh - Wazuh - The Open Source Security Platform. Unified XDR and SIEM protection for endpoints and cloud workloads.
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.
uptime-kuma - A fancy self-hosted monitoring tool
skywalking - APM, Application Performance Monitoring System
Freeboard - A damn-sexy, open source real-time dashboard builder for IOT and other web mashups. A free open-source alternative to Geckoboard.
Dashing
dashy - 🚀 A self-hostable personal dashboard built for you. Includes status-checking, widgets, themes, icon packs, a UI editor and tons more!
Sentry - Developer-first error tracking and performance monitoring
crossplane - The Cloud Native Control Plane