zfs-localpv
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zfs-localpv | Grafana | |
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12 | 378 | |
363 | 60,196 | |
4.4% | 1.3% | |
7.1 | 10.0 | |
7 days ago | 5 days ago | |
Go | TypeScript | |
Apache License 2.0 | GNU Affero General Public License v3.0 |
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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.
zfs-localpv
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ZFS 2.2.0 (RC): Block Cloning merged
I use it in Kubernetes via https://github.com/openebs/zfs-localpv
The PersistentVolume API is a nice way to divvy up a shared resource across different teams, and using ZFS for that gives us the snapshotting, deduplication, and compression for free. For our workloads, it benchmarked faster than XFS so it was a no-brainer.
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OpenEBS on MicroK8S on Hetzner
Last few months I experimented more and more with all OpenEBS solutions that fit small Kubernetes cluster, using MicroK8S and Hetzner Cloud for a real experience.
- Openebs ?? Or equivalent
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Network Storage on On-Prem Barebones Machine
I would investigate https://openebs.io/ https://portworx.com/ https://longhorn.io/ if you are forced to you can mount ISCSI on the kublet and feed it to one of those solutions. Keep in mind most of the big guys buy some sort of managed solution that you can point a CSI like trident https://netapp-trident.readthedocs.io
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Ask HN: What are some fun projects to run on a home K8s cluster?
What are some cool projects to self hosted on a home Raspberry Pi (64 bit) Kubernetes cluster (Helm charts). arm64 support is a must. A lot of projects only build amd64 Docker containers which don't run on my cluster.
I currently run:
- obenebs (provides abstraction for using local k8s worker disks as PVC mounts when running on-prem) -- https://openebs.io/
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My self-hosting infrastructure, fully automated
What do you use to provision Kubernetes persistent volumes on bare metal? I’m looking at open-ebs (https://openebs.io/).
Also, when you bump the image tag in a git commit for a given helm chart, how does that get deployed? Is it automatic, or do you manually run helm upgrade commands?
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Jinja2 not formatting my text correctly. Any advice?
ListItem( 'Kubernetes', 'https://kubernetes.io/', 'Container Engines and Orchestration', """Kubernetes is an open-source container-orchestration system for automating computer application deployment, scaling, and management.""" ), ListItem( 'Podman', 'https://podman.io/', 'Container Engines and Orchestration', """Podman is a daemonless, open source, Linux native tool designed to make it easy to find, run, build, share and deploy applications using Open Containers Initiative (OCI) Containers and Container Images.""" ), # Data Storage :: Block Storage ListItem( 'Amazon EBS', 'https://aws.amazon.com/ebs/', 'Data Storage :: Block Storage', """Amazon Elastic Block Store (Amazon EBS) is an easy-to-use, scalable, high-performance block-storage service designed for Amazon Elastic Compute Cloud (Amazon EC2).""" ), ListItem( 'OpenEBS', 'https://openebs.io/', 'Data Storage :: Block Storage', """OpenESB is a Java-based open-source enterprise service bus. It allows you to integrate legacy systems, external and internal partners and new development in your Business Process.""" ), # Data Storage :: Cluster Storage ListItem( 'Ceph', 'https://ceph.io/en/', 'Data Storage :: Cluster Storage', """Ceph is an open-source software storage platform, implements object storage on a single distributed computer cluster, and provides 3-in-1 interfaces for object-, block- and file-level storage.""" ), ListItem( 'Hadoop Distributed File System', 'https://hadoop.apache.org/docs/r1.2.1/hdfs_design.html', 'Data Storage :: Cluster Storage', """The Hadoop Distributed File System ( HDFS ) is a distributed file system designed to run on commodity hardware.""" ), # Data Storage :: Object Storage ListItem( 'Amazon S3', 'https://aws.amazon.com/s3/', 'Data Storage :: Object Storage', """Amazon S3 or Amazon Simple Storage Service is a service offered by Amazon Web Services that provides scalable object storage through a web service interface.""" )
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Building a "complete" cluster locally
Ideas from my kubernetes experience: * Cert-Manager is very popular and almost a must-have if you terminate SSL inside the cluster * Backups using velero * A dashboard/UI is actually very helpful to quickly browse resources, client tools like k9s are fine too * Secret: Management: Bitnami Sealed Secrets is the second big project in that space * I would add Loki to aggregate Logs * Never heard of ory. Usually I see (dex)[https://dexidp.io/] or keycloak used for Authentication * I like to run OpenEBS as in-cluster storage. * Istio isn't compatible with the upcomming ServiceMeshInterface (i think), so the trend seem to go toward Linkerd * Some Operator to deploy your favorite Database, is also a nice learning exercise.
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Why OpenEBS 3.0 for Kubernetes and Storage?
OpenEBS ZFS LocalPV (declared stable), used widely for production workloads that need direct and resilient storage has added new capabilities like:
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ZFS and Ceph
So I'm in the process of converting every node in my cluster to ZFS (RAID1 - a single mirror zpool) (powered by OpenEBS's ZFS LocalPV for the k8s heads out there). I'm going to try running Ceph w/ bluestore but doing something that would normally make absolutely no sense -- disabling the checksumming features of Ceph.
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
longhorn - Cloud-Native distributed storage built on and for Kubernetes
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