kubebuilder
Grafana
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kubebuilder | Grafana | |
---|---|---|
45 | 376 | |
7,311 | 59,887 | |
1.8% | 1.5% | |
9.2 | 10.0 | |
10 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.
kubebuilder
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SpinKube: Orchestrating light, fast and efficient WebAssembly (Wasm) workloads in Kubernetes (k8s)
The Spin operator uses the Kubebuilder framework and contains a Spin App Custom Resource Definition (CRD) and controller. It watches Spin App Custom Resources and realizes the desired state in the K8s cluster. Aside from the immediate benefits gained by running Wasm workloads in k8s, additional optimizations such as Horizontal Pod Scaling (HPA) and k8s Event-driven Autoscaling (KEDA) can be achieved in a pinch.
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Building a Kubernetes Operator with the Operator Framework
kubebuilder: brew install kubebuilder
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Annotations in Kubernetes Operator Design
The operator that I've been working on is designed to manage the full lifecycle of a QuestDB database instance, including version and hardware upgrades, config changes, backups, and (eventually) recovery from node failure. I used the Operator SDK and kubebuilder frameworks to provide scaffolding and API support.
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Kubebuilder Tips and Tricks
Recently, I've been spending a lot of time writing a Kubernetes operator using the go operator-sdk, which is built on top of the Kubebuilder framework. This is a list of a few tips and tricks that I've compiled over the past few months working with these frameworks.
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We moved our Cloud operations to a Kubernetes Operator
Since we built our operator using the Kubebuilder framework, most standard monitoring tasks were handled for us out-of-the-box. Our operator automatically exposes a rich set of Prometheus metrics that measure reconciliation performance, the number of k8s API calls, workqueue statistics, and memory-related metrics. We we were able to ingest these metrics into pre-built dashboards by leveraging the grafana/v1-alpha plugin, which scaffolds two Grafana dashboards to monitor Operator resource usage and performance. All we had to do was add these to our existing Grafana manifests and we were good to go!
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Has anyone ever tried to learn how k8s works?
I wrote a CSI driver and some operators. I admire K8s, because you can find solution to almost any problem in the source code - API versioning, load balancing, request throttling, optimistic concurrency, security, and much much more. I recommend https://book.kubebuilder.io/ It is similar to Operator SDK, but without Openshift-specific stuff. It gradually introduces you to many k8s concepts, and follows design patterns that k8s uses internally.
- What Is A Kubernetes Operator?
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Writing a Kubernetes Operator
A better way to write an operator these days is to use kubebuilder [1].
My complaint is that I have seen orgs write operators for random stuff, often reinventing the wheel. Lot of operators in orgs are result of resume driven development. Having said that it often comes handy for complex orchestration.
- Question: Resources to learn K8s operator programming
- Which subreddit for questions about developing Kubernetes controllers?
Grafana
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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.
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List of your reverse proxied services
Grafana - for dashboards and log monitoring
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PM2 module to monitoring node.js application with export to Prometheus and Grafana
In most cases, applications use the combination of Prometheus + Grafana, which allows collect data and display it in the form of graphs and also to set up alerts for changes in any metrics.
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
helm-operator - Successor: https://github.com/fluxcd/helm-controller — The Flux Helm Operator, once upon a time a solution for declarative Helming.