Grafana Tutorial

...deploy-preview-grafana-120659-zb444pucvq-vp.a.run.app/docs/grafana/latest/setup-grafana/configure-access/configure-authentication/....a.run.app/docs/grafana/latest/setup-grafana/configure-access/configure-authentication/....a.run.app/docs/grafana/latest/setup-grafana/configure-access/configure-authentication/...IAM revamp #120383 SAML interactive tutorial interactive-tutorials#117

...://deploy-preview-grafana-120659-zb444pucvq-vp.a.run.app/docs/grafana/latest/setup-grafana/configure-access/configure-authentication/saml...://deploy-preview-grafana-120659-zb444pucvq-vp.a.run.app/docs/grafana/latest/setup-grafana/configure-access/configure-authentication/saml...: IAM revamp #120383 SAML interactive tutorial interactive-tutorials#117

..., The Promtail (default Agent for Grafana Loki ) is now End-Of-Life by ... their existing Promtail configuration to Grafana Alloy. Kind see this post ... - How to start with Grafana Loki and Alloy | Migrate existing ... you are using Docker with Grafana Loki to visualize container log ... to replace Promtail with Grafana Alloy I have created this video tutorial that explains very...

...Promtail with Grafana Alloy I have created this video tutorial that ... files (for your Grafana Loki deployments) to Grafana Alloy in Docker environments...queries. This tutorial is also for those users who are new to Grafana Alloy and... Link to the video: Docker Tutorial: Getting started with Grafana Loki and Alloy | Complete Promtail... going EOL Intro. to Grafana Alloy (advantages, features) Demo Docker ...

... plugin tutorial Why I'm a Great Fit: Extensive experience with grafana ecosystem...

...machine itself going using this tutorial ahttps://grafana.com/docs/alloy/latest/tutorials/...alloy following these instructions, ahttps://grafana.com/docs/alloy/latest/set-up/...metrics using these instructions ahttps://grafana.com/docs/alloy/latest/collect/... using the instructions here ahttps://grafana.com/docs/alloy/latest/reference/... example code here. ahttps://grafana.com/docs/alloy/latest/reference/...

...://www.oracle.com/enterprise-manager/technologies/grafana/ are completely non-functional. All version... Oracle Enterprise Manager App for Grafana" (https://www.youtube.com/watch?... install oracle-emcc-app-5.0.0 for Grafana 11.5.1 and Oracle ... plugin available through the standard Grafana plugin repository The entire setup ... broken links, and the video tutorial assumes you can already download ...

... from #117637 Added video tutorial and also the Grafana Play demo links to... the visibility when viewing https://grafana.com/grafana/plugins/mysql/ and also inside... the Grafana UI (plugin area) Please check ...

... from #117637 Added video tutorial and also the Grafana Play demo links to... the visibility when viewing https://grafana.com/grafana/plugins/mysql/ and also inside... the Grafana UI (plugin area) Please check ...

... from #117637 Added video tutorial and also the Grafana Play demo links to... the visibility when viewing https://grafana.com/grafana/plugins/mysql/ and also inside... the Grafana UI (plugin area) Please check ...

Added video tutorial and also the Grafana Play demo links to MySQL datasource README file. This will update and improve the visibility when viewing https://grafana.com/grafana/plugins/mysql/ and also inside the Grafana UI (plugin area) Please check that: It works as expected from a user's perspective. The docs are updated, and if this is a notable improvement, it's added to our What's New doc.

added the datasource/MySQL label

bot requested a review from lwandz13 as a code owner

Backport 87e7b0d from #117486 Added a video link for learning about the Grafana MySQL data source plugin. Homepage: https://grafana.com/docs/grafana/latest/datasources/mysql/

bot added this to the 12.4.x milestone

... @brandon We have a dedicated tutorial that covers this topic. Hope... multiple contact points. Grafana Labs Get started with Grafana Alerting - Multi-dimensional...

..., The Promtail (default Agent for Grafana Loki ) will be End-Of-Life (EOL... their existing Promtail configuration to Grafana Alloy. Kind see this post ... Promtail (End-Of-Life) to Alloy for Grafana Loki How To Dear Community ...members , Promtail (default agent for Grafana Loki ) will be End-Of-Life by ... to replace Promtail with Grafana Alloy I have created this video tutorial that explain a very...

Hi, I’m following the RedHat tutorial to connect OpenTelemetry Collector and ... when I connected it to Grafana, I only see the cluster ... sending telemetry to OTel. In Grafana, my data source points to: ....version: Str(3.24.2) Grafana labels: (service_name is empty) image1567×...

... quotes , like so: {{ .CommonLabels.grafana_folder }} Grafana Labs KV - Notification template... reference | Grafana documentation By default, Grafana provides predefined templates to... our getting started with Templating tutorial.

submitted by /u/usmanlinux to r/AlmaLinux [link] [comments]

Hi all, The Promtail (default agent for Grafana Loki) is now End-Of-Life by March 2026. Source of Announcement: Official Promtail Page It means that: No releases of any security patches No Bug fixes or new improvements The only way to move forward is to replace Promtail with Grafana Alloy For that, I have created this video tutorial that explains very detailed step-by-step instructions on how to migrate your existing Promtail configuration files (for your Grafana Loki deployments) to Grafana Alloy in Docker environments and be able to keep using Loki without re-creating your dashboards or queries. Link to the video: https://www.youtube.com/watch?v=3W99Go4S39E This tutorial is also for those users who are new to Grafana Alloy and want to get started with Docker Compose deployments with minimal effort. The video contains the following sections: Starting with fundamentals for new users Why Promtail is going EOL Intro. to Grafana Alloy (advantages, features) Demo Docker Compose Setup Migration Setup for your Loki Understanding Configuration Advanced Debugging/Troubleshooting Bonus Exercise Please share, if you have any questions. Hope you will find this helpful. submitted by /u/usmanlinux to r/grafana [link] [comments]

Salutare Reddit, am obosit. Au trecut aproape 6 luni de cautat de munca dupa ce am fost si eu victima unui val de restructurari la o companie unde n-am apucat sa stau foarte mult, ba chiar recent am apucat sa lucrez o luna si la CGS unde am fost, ca multi altii, concediat in training si m-am gandit ca poate imi voi gasi urmatorul job chiar aici. Motivatie? Rate, un copil care parea ca a aparut la momentul potrivit, stres si griji constante ca trebuie sa fac un ban, macar sa-mi pot acoperi cheltuielile prioritare. Experienta mea? Cea mai relevanta este in roluri customer facing, support, monitoring (Grafana, New Relic, Splunk, Cloudwatch), troubleshooting, log analysis, tracing, am lucrat cu AWS si chiar am terminat un curs pentru certificarea Solutions Architect (da, nu am bani sa dau examenul, pot spune ca inca ma pregatesc pentru el), putin Kubernetes, high severity incident management (initial triage si call-out echipelor relevante, timeline si putin RCA), basic Linux knowledge, pot adauga si o oarecare expunere practica la Bash si Python (pot intelege, in linii mari, ce face codul) - mi-as dori sa am sansa sa invat macar unul dintre cele doua limbaje la un nivel proficient. Am capacitatea de a ma adapta si invata foarte repede, imi doresc sa evoluez in urmatorii ani spre DevOps, insa sunt genul de persoana care invata lucruri in timp ce le face, fug ca dracu de tutorial hell. Sunt in cautare de pozitii remote, asta e principala mea grija, fiindca mi-as dori sa petrec cat mai mult timp cu familia. Sunt dispus sa accept si pozitii hybrid pentru Bucuresti (si imprejurimi) dar cu prezenta redusa la birou fiindca locuiesc in Targoviste Daca stiti vreo companie care este in cautarea unui parteneriat de lunga durata, sau poate sunt si printre voi recruiteri, va rog sa ma contactati in privat si putem discuta mai pe larg. Multumesc! submitted by /u/alegz1698 to r/RoMunca [link] [comments]

I'm digging Techno Tim's setup for monitoring a plex setup with exporters + prometheus + grafana. Source: https://www.youtube.com/watch?v=MmBN2Ahbdao Source: https://technotim.live/posts/monitor-your-plex-server-like-a-pro/ The challenge I have is that my media server has an integrated intel GPU, not nvidia... so the dcgm-exporter doesn't work. I've tried oneDr0ps exporter (source) but that's not really providing any meaningful data. Anyone else with a similar setup? Thoughts? Suggestions? submitted by /u/evcgm to r/PleX [link] [comments]

I see a lot of people jumping straight into Docker and Kubernetes and then wondering why they feel lost. DevOps isn’t just “learn these 5 tools” it’s a mix of mindset, fundamentals, and the right tools at the right time. Here’s a breakdown of how I’d start if I was new in 2025. Learn the Fundamentals First Before you even touch fancy automation tools, make sure you actually understand the stuff you’ll be automating. That means: Linux basics (file system, processes, permissions, services) Networking (IP, DNS, HTTP/S, ports, routing, NAT, firewalls) System administration (users, groups, package management, logs) Bash scripting for automating simple tasks Basic Python scripting (log parsing, API calls, automation scripts) If you can’t explain what happens when you curl a URL or why a service isn’t starting, you’ll struggle later. Version Control and CI/CD Are Core Skills Every DevOps pipeline starts with Git. Learn branching, merging, pull requests, and resolving conflicts. Then move into CI/CD (Continuous Integration/Continuous Deployment). Popular tools: Jenkins GitLab CI GitHub Actions CircleCI You don’t just need to “click a deploy button” — understand pipeline stages, automated testing, build artifacts, and how to roll back if something breaks. Containers and Orchestration Containers are a big part of DevOps. Start with Docker: Build images with Dockerfiles Use volumes and networks Work with multi-container apps via Docker Compose Once you’re solid there, learn Kubernetes (K8s). Don’t rush this — it’s a lot. Focus on: Pods, deployments, services ConfigMaps and secrets Scaling and rolling updates Ingress and service discovery You’ll also want to understand managed K8s services like AWS EKS, Azure AKS, or GCP GKE. Cloud Skills Are Non-Negotiable Pick one cloud provider to start: AWS, Azure, or GCP. AWS is the most common, but it’s fine to choose based on job market in your area. Learn: Compute (EC2) Networking (VPC, subnets, security groups) Storage (S3, EBS) IAM (roles, policies, least privilege) Then, learn how to deploy containers or Kubernetes clusters in the cloud. Infrastructure as Code (IaC) This is how you make cloud resources repeatable and version-controlled. Terraform is the most popular and works with all major clouds. Learn how to: Define infrastructure in .tf files Use variables and modules Apply and destroy infrastructure safely Store state securely Monitoring, Logging, and Alerting If you build and deploy something but can’t see when it’s failing, you’re not doing DevOps. Get hands-on with: Prometheus + Grafana for metrics ELK stack (Elasticsearch, Logstash, Kibana) for logging Cloud-native tools like AWS CloudWatch or GCP Stackdriver Security (DevSecOps Basics) Security is now a core part of DevOps, not an afterthought. Learn to: Scan code for vulnerabilities (Snyk, Trivy) Manage secrets (Vault, AWS Secrets Manager) Secure Docker images Apply IAM best practices Build Real Projects Don’t just follow tutorials. Build something end-to-end, like: A microservice app with Docker CI/CD pipeline → Docker → Kubernetes → Cloud deployment Terraform for infra provisioning Monitoring + logging setup Push everything to GitHub with a README that explains your setup. Network With the Community Join DevOps communities: Reddit (r/devops, r/kubernetes, r/aws) CNCF Slack channels DevOps Discord servers Local meetups or conferences Ask questions, share your progress, and help others. Stay Consistent & Keep Learning DevOps tools evolve fast. Even once you land a job, you’ll keep learning. Read blogs, watch KubeCon talks, experiment in your home lab. If you start from zero and commit a few hours per week, you could be job-ready in 6–8 months. The key is not to try and master everything at once — build layer by layer, and make sure each new tool you learn connects to something you already understand. If you want a well-structured course & resource suggestions to follow this roadmap step-by-step, DM me and I’ll share what worked for me and others breaking into DevOps. submitted by /u/Intellipaat_Team to r/devops [link] [comments]

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Hey everyone! I'm a full stack dev but have never really used grafana/prometheus. I wanted to monitor my homelab so I have set up everything and I am getting data consistently, the dashboard looks very nice. However, with the exception of a few things, I really don't know what I am looking at. There are some many plots that I have no idea what they represent or do. So I was wondering if there is a tutorial out there somewhere or a book or something I can look at that will explain everything, the uses of each plot, what to look out for, what alerts are good and why etc. Ideally quite in depth. I understand I can go plot by plot do research and find the information on my own but I'm wondering if there is a resource that has already compiled everything. submitted by /u/Oudwin to r/sysadmin [link] [comments]

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If you stay in an apartment and your neighbour smokes, some of that cigarette smoke may find its way into your house. This is not ideal. To fight this problem, I propose an automatic window closing system triggered by cigarette smoke. In particular, it is triggered by a spike in particulate matter concentration. This works because cigarette smoke is known to contain a large amount of particulate matter and volatile organic compounds. (See: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6352107/#:~:text=They%20found%20that%20the%20most,µm%20sized%20particles%20%5B57%5D.)) Demonstration https://reddit.com/link/1cxciva/video/vdscdqdr6t1d1/player You can see the Arduino, sensor, and motor driver hanging haphazardly on the left side of the video. Does it really work? Yes somewhat. Currently, if you smell cigarette smoke in your apartment, it would be too late to close your windows. If you close your windows, the cigarette smoke would be trapped in the house with you. If you don't, the cigarette smoke gets stronger and stronger. With this new set-up, the window completely closes within 30-45 seconds of the start of the event. This protects your apartment from the bulk of the wave that follows. https://preview.redd.it/2eth9bws6t1d1.png?width=1686&format=png&auto=webp&s=20ab7175f461a1704ae7fc8045586fbe8b4d483a The 30-45 seconds is not a hard limit. It's due to: Poor sensor placement due to the a limit on how long the data cables could be Insufficiently sensitive algorithm to differentiate between noise and an actual smoke event Unoptimal speed of actuator (running at 60-70% of maximum currently) to close the windows due to an inefficient motor driver. With the entire setup optimised, the response time should be as short as 12-15 seconds (from start of event to complete window closure). Nonetheless, at the moment, the proof of concept demonstrates that it should work. The rest of this post would be dedicated to a technical description. High Level idea https://preview.redd.it/hnlos2cu6t1d1.png?width=1630&format=png&auto=webp&s=cd1e14cfbf5575d9d5dd2aeb433018dee83f3f91 The particulate sensor continuously monitors particulate concentrations and feeds it to a microcontroller. The microcontroller receives the data and uses an algorithm to determine when there is a spike. When a spike is detected, the microcontroller sends a signal to the motor driver. The motor driver selects the speed and the direction of the motor in the actuator. The actuator closes the window. Low level implementation An overview of the physical setup is as follows: https://preview.redd.it/kj5e6k1w6t1d1.png?width=2184&format=png&auto=webp&s=8b084d8efad34b799d569229f0a39bc4513e670c Particulate Sensor The particulate sensor is an Adafruit PMSA0003I sensor, mounted on an Adafruit breakout board, that detects particulate matter using an in-built laser. The particles are measured according to binned particulate sizes. For our case, we considered the smallest bin (0.3-1.0μm) because we observed the biggest spike in this interval. The sensor was programmed to take readings every 3 seconds. This is acceptable because the single-response time for the sensor is ≤1 second and it is not too unreasonably slow to detect spikes in readings. These readings were then sent to an Arduino MKR Wifi 1010 Microcontroller. We remark that the particulate sensor requires 5V to be powered. For power and data communications, we connected the breakout board to an Arduino MKR Wifi 1010 via a Stemma QT cable (see: https://www.mouser.sg/ProductDetail/Adafruit/4209?qs=PzGy0jfpSMvCXPIwCvMoFg%3D%3D). The connection details are detailed here https://learn.adafruit.com/pmsa003i/arduino. Microcontroller The Arduino MKR Wifi 1010 microcontroller receives sensor data and translates that to signal data. If we take a look at the incoming data, it is extremely noisy. To smooth out the noise, we applied a Kalman filter. See https://www.cs.unc.edu/~welch/media/pdf/kalman_intro.pdf for more details. Within a short interval, we expect the sensor data to be roughly constant. The Kalman filter was designed under this assumption. Upon applying the Kalman filter, we shall take it as the 'ground truth'. When we observed the data over time, we observe sharp spikes. These spikes correspond to two different pollution sources: incense and cigarette smoke. Incense burns slowly over time so the spike lasts for a few hours. On the other hand, cigarette smoke is characterised by a sharp spike of about 10-15 minutes in duration. Regardless of the source, we want to close the window whenever a spike is detected. To do this, a lagging baseline is taken. We define the baseline at a point in time as the median value of the 'ground truth' values in a five minute window. This corresponds to data that is 5-10 minutes old. If at any moment the positive difference between the 'ground truth' and the baseline is larger than the 98.5th percentile of the distribution, we trigger the actuator. The trigger works by sending a LOW/HIGH signal to the Motor Driver. Why 98.5th percentile? It just seems to work. Choosing a smaller percentile like 97th percentile leads to more false positive window closures (maybe not a bad thing) whereas choosing a larger percentile leads to much slower response times. Actuator and Motor Driver The inexpensive L298N bridge serves as a motor driver. The bridge helps us to control the speed (but it is not important here since we just want it go to at maximum speed) and the direction. The direction is controlled by a LOW/HIGH signal from the Arduino. To swap the direction, we simply flip the signals and send a HIGH/LOW signal instead. The Hakiwo 12V Linear Actuator was purchased off Aliexpress and has a power rating of 20W and a rated speed speed of 100mm/s. This sounds pretty good on paper as the sliding window would close in 7 seconds. However, in practice, the speed when: directly connecting the actuator to a 12V DC Power Supply is about ±85-90mm/s. connected to a 12V DC Power Supply via the L298N bridge is about ±58mm/s. The significant difference in speed could be attributed to the voltage drop incurred by the L298N bridge. It was stated that when 12V is supplied to L298N bridge, only 10V actually reaches the motor. Hence, the massive heatsink to dissipate the heat. See https://howtomechatronics.com/tutorials/arduino/arduino-dc-motor-control-tutorial-l298n-pwm-h-bridge/. Logging We want to log the data and be able to have convenient access to the data. To do so, we connected the Arduino MKR Wifi 1010 to AWS IoT Core service. Subsequently, we routed messages sent from AWS IoT Core to AWS Timestream which is basically a database. To visualise the data, we sent it to AWS-managed Grafana. See https://docs.arduino.cc/tutorials/opta/getting-started-with-aws-iot-core/ on how to set it up. Algorithm Design After logging the data into AWS Timestream, we would like to load the data on my personal computer to design the algorithm. We unloaded it to AWS S3 and downloaded the archive file. We used Julia on an .ipynb instance. Julia because it's faster than Python. Upon designing and verifying the algorithm on past data, it is then translated into C++ for uploading to the Arduino. Algorithm Subplots Check The plot generated above is used for us to visually inspect the effectiveness of the algorithm. Visually, the spikes are all protected (actuators are activated throughout the duration of a cigarette smoke event). Although it's not that effective with the incense pollution but that's not a problem for us at the moment. To take note The Arduino MKR Wifi 1010 Wifi chip is really weak. My empirical observations was if the Wifi signal is less than -60dBm, you would not be able to reliably connect to your router. When the Ardunio is powered by a USB connection and the Adafruit PMSA0003I particulate sensor is powered from the Arduino, there would not be enough power to boot both the Arduino and the sensor when first connected to the power supply. To fix this, the 5V wire of the stemma qt cable is disconnected when the Arduino is powered. Once the CHRG light on the Arduino has stopped blinking, we reconnect the wire. If the Arduino and sensor are powered separately, it does not work either. I don't know why. Total Cost SGD65 - Sensor (Mouser) SGD50 - Arduino (Mouser) SGD70 - Actuator (Aliexpress) SGD2 - L298N bridge (Shopee) SGD10 - Mounting tapes (Hardware shops) SGD1/mth - AWS Future improvements Lower Cost - The current cost is about SGD200. However it can be reduced further by switching to ESP32s. If there is sufficient demand for mass production, unit prices for the electronics would be 5-20% lower and custom PCBs would allow us to avoid the premium associated with breakout boards. Better Motor Driver - The current L298N bridge is too inefficient and too bulky. It retards the actuator too much. Additionally, if the actuator were to upgraded to a higher speed actuator which requires 5A of current, the L298N would be unsuitable. Better spike trigger algorithm - The current algorithm still takes about 10-30 seconds from start of smoking to full window closure. If the algorithm is too sensitive, then it is prone to triggering sometimes by noise. If the algorithm is too insensitive, then too much cigarette smoke would enter the apartment before getting triggered. Cheaper microcontroller - The Arduino MKR Wifi 1010 microcontroller is fairly expensive at about 39 USD. Since ESP32s are inexpensive and they have an efficient protocol (ESP-NOW) for communication between ESP32s, we can assign each device a microcontroller -- one for the sensor, one for each actuator, and one for control. We would no longer be limited by the length of the data cables. We would then be able to have more optimal placement of the sensors and the actuators. Faster actuator - If we need to get more mileage out of this entire setup, a faster actuator that goes at 150mm/s can be considered. submitted by /u/040502702142621 to r/singapore [link] [comments]

submitted by /u/VolkovLabs to r/grafana [link] [comments]

Does anyone has a tutorial on how to configure Grafana in openshift? I am trying and trying, and trying with no sucess. Have tried diferente ones and until know it doesnt work. submitted by /u/ddi32 to r/sysadmin [link] [comments]

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I am wanting to setup Grafana on my unraid box to monitor the host system, and docker containers, id also like to monitor my Synology, and possibly my Untangle firewall if possible. Sadly, I cant seem to find any good tutorials anywhere. I know about the UUD, and the Grafana unraid stack. Ive already checked those out, but I really want to get my hands dirty and make my own. Just don't know where to start. submitted by /u/relink2013 to r/unRAID [link] [comments]

I have put my docker tutorials in this playlist, I hope you are going to enjoy it. Please share your comments. submitted by /u/thetips4u to r/docker [link] [comments]

Hey, In this article/video I'll show you how to create a Docker based Smart Home hub on a Raspberry Pi from scratch. I'm going to install Home Assistant (HASSIO), Node-RED, Mosquitto MQTT, Grafana, InfluxDb, Pi-Hole, Portainer, OpenHAB, Plex media server, Log2Ram & TasmoAdmin, but don't worry it will be easier than you think and everything will be based on Docker containers. https://youtu.be/5JMNHuHv134 How to setup Raspberry Pi as SMART HOME hub - Home Assistant, Node RED, Grafana, InfluxDB etc. Guide From Scratch If you want to read instead of watching then check the full article here - https://peyanski.com/raspberry-pi-as-smart-home-hub-video-tutorial/ After you complete this tutorial you will be able to connect almost every smart device that you have, in one place, and control it from there. Oh and there is even a menu. Stay safe, Kiril submitted by /u/KPeyanski to r/docker [link] [comments]

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