#Pull Docker Images for Grafana and Prometheus

[techdirectarchive]

Docker Setup: Monitoring Synology with Prometheus and Grafana

In this article, we will discuss “Docker Setup: Monitoring Synology with Prometheus and Grafana”. We will be utilizing Portainer which is a lightweight/open-source management solution designed to simplify working with Docker containers instead of working with the Container Manager on Synology. Please see How to use Prometheus for Monitoring, how to Install Grafana on Windows and Windows Server,…

[alivah2kinfosys]

DevOps Course Online for Beginners and Professionals

Introduction: Why DevOps Skills Matter Today

In today's fast-paced digital world, businesses rely on faster software delivery and reliable systems. DevOps, short for Development and Operations, offers a practical solution to achieve this. It’s no longer just a trend; it’s a necessity for IT teams across all industries. From startups to enterprise giants, organizations are actively seeking professionals with strong DevOps skills.

Whether you're a beginner exploring career opportunities in IT or a seasoned professional looking to upskill, DevOps training online is your gateway to success. In this blog, we’ll walk you through everything you need to know about enrolling in a DevOps course online, from fundamentals to tools, certifications, and job placements.

What Is DevOps?

Definition and Core Principles

DevOps is a cultural and technical movement that unites software development and IT operations. It aims to shorten the software development lifecycle, ensuring faster delivery and higher-quality applications.

Core principles include:

Automation: Minimizing manual processes through scripting and tools

Continuous Integration/Continuous Deployment (CI/CD): Rapid code integration and release

Collaboration: Breaking down silos between dev, QA, and ops

Monitoring: Constant tracking of application performance and system health

These practices help businesses innovate faster and respond quickly to customer needs.

Why Choose a DevOps Course Online?

Accessibility and Flexibility

With DevOps training online, learners can access material anytime, anywhere. Whether you're working full-time or managing other responsibilities, online learning offers flexibility.

Updated Curriculum

A high-quality DevOps online course includes the latest tools and techniques used in the industry today, such as:

Jenkins

Docker

Kubernetes

Git and GitHub

Terraform

Ansible

Prometheus and Grafana

You get hands-on experience using real-world DevOps automation tools, making your learning practical and job-ready.

Job-Focused Learning

Courses that offer DevOps training with placement often include resume building, mock interviews, and one-on-one mentoring, equipping you with everything you need to land a job.

Who Should Enroll in a DevOps Online Course?

DevOps training is suitable for:

Freshers looking to start a tech career

System admins upgrading their skills

Software developers wanting to automate and deploy faster

IT professionals interested in cloud and infrastructure management

If you're curious about modern IT processes and enjoy problem-solving, DevOps is for you.

What You’ll Learn in a DevOps Training Program

1. Introduction to DevOps Concepts

DevOps lifecycle

Agile and Scrum methodologies

Collaboration between development and operations teams

2. Version Control Using Git

Git basics and repository setup

Branching, merging, and pull requests

Integrating Git with DevOps pipelines

3. CI/CD with Jenkins

Pipeline creation

Integration with Git

Automating builds and test cases

4. Containerization with Docker

Creating Docker images and containers

Docker Compose and registries

Real-time deployment examples

5. Orchestration with Kubernetes

Cluster architecture

Pods, services, and deployments

Scaling and rolling updates

6. Configuration Management with Ansible

Writing playbooks

Managing inventories

Automating infrastructure setup

7. Infrastructure as Code with Terraform

Deploying cloud resources

Writing reusable modules

State management and versioning

8. Monitoring and Logging

Using Prometheus and Grafana

Alerts and dashboards

Log management practices

This hands-on approach ensures learners are not just reading slides but working with real tools.

Real-World Projects You’ll Build

A good DevOps training and certification program includes projects like:

CI/CD pipeline from scratch

Deploying a containerized application on Kubernetes

Infrastructure provisioning on AWS or Azure using Terraform

Monitoring systems with Prometheus and Grafana

These projects simulate real-world problems, boosting both your confidence and your resume.

The Value of DevOps Certification

Why It Matters

Certification adds credibility to your skills and shows employers you're job-ready. A DevOps certification can be a powerful tool when applying for roles such as:

DevOps Engineer

Site Reliability Engineer (SRE)

Build & Release Engineer

Automation Engineer

Cloud DevOps Engineer

Courses that include DevOps training and placement also support your job search with interview preparation and job referrals.

Career Opportunities and Salary Trends

High Demand, High Pay

According to industry reports, DevOps engineers are among the highest-paid roles in IT. Average salaries range from $90,000 to $140,000 annually, depending on experience and region.

Industries hiring DevOps professionals include:

Healthcare

Finance

E-commerce

Telecommunications

Software as a Service (SaaS)

With the right DevOps bootcamp online, you’ll be prepared to meet these opportunities head-on.

Step-by-Step Guide to Getting Started

Step 1: Assess Your Current Skill Level

Understand your background. If you're a beginner, start with fundamentals. Professionals can skip ahead to advanced modules.

Step 2: Choose the Right DevOps Online Course

Look for these features:

Structured curriculum

Hands-on labs

Real-world projects

Mentorship

DevOps training with placement support

Step 3: Build a Portfolio

Document your projects on GitHub to show potential employers your work.

Step 4: Get Certified

Choose a respected DevOps certification to validate your skills.

Step 5: Apply for Jobs

Use placement support services or apply directly. Showcase your portfolio and certifications confidently.

Common DevOps Tools You’ll Master

Tool

Use Case

Git

Source control and version tracking

Jenkins

CI/CD pipeline automation

Docker

Application containerization

Kubernetes

Container orchestration

Terraform

Infrastructure as Code

Ansible

Configuration management

Prometheus

Monitoring and alerting

Grafana

Dashboard creation for system metrics

Mastering these DevOps automation tools equips you to handle end-to-end automation pipelines in real-world environments.

Why H2K Infosys for DevOps Training?

H2K Infosys offers one of the best DevOps training online programs with:

Expert-led sessions

Practical labs and tools

Real-world projects

Resume building and interview support

DevOps training with placement assistance

Their courses are designed to help both beginners and professionals transition into high-paying roles smoothly.

Key Takeaways

DevOps combines development and operations for faster, reliable software delivery

Online courses offer flexible, hands-on learning with real-world tools

A DevOps course online is ideal for career starters and upskillers alike

Real projects, certifications, and placement support boost job readiness

DevOps is one of the most in-demand and well-paying IT domains today

Conclusion

Ready to build a future-proof career in tech? Enroll in H2K Infosys’ DevOps course online for hands-on training, real-world projects, and career-focused support. Learn the tools that top companies use and get placement-ready today.

[computingpostcom]

This article is part of Smart Infrastructure monitoring series, we’ve already covered how to Install Prometheus Server on CentOS 7 and how to Install Grafana and InfluxDB on CentOS 7. We have a Ceph cluster on production that we have been trying to find good tools for monitoring it, lucky enough, we came across Prometheus and Grafana. Ceph Cluster monitoring with Prometheus requires Prometheus exporter that scrapes meta information about a ceph cluster. In this guide, we’ll use DigitalOcean Ceph exporter. Pre-requisites: Installed Prometheus Server. Installed Grafana Server. Docker installed on a Server to run Prometheus Ceph exporter. It should be able to talk to ceph cluster. Working Ceph Cluster Access to Ceph cluster to copy ceph.conf configuration file and the ceph..keyring in order to authenticate to your cluster. Follow below steps for a complete guide on how to set this up. Step 1: Install Prometheus Server and Grafana: Use these links for how to install Prometheus and Grafana. Install Prometheus Server on CentOS 7 and  Install Grafana and InfluxDB on CentOS 7. Install Prometheus Server and Grafana on Ubuntu Install Prometheus Server and Grafana on Debian Step 2: Install Docker on Prometheus Ceph exporter client Please note that Prometheus Ceph exporter client should have access to Ceph cluster network for it to pull Cluster metrics. Install Docker on this server using our official Docker installation guide: Install Docker CE on Ubuntu / Debian / Fedora / Arch / CentOS Also, install docker-compose. Install Docker Compose on Linux Systems Step 3: Build Ceph Exporter Docker image Once you have Docker Engine installed and service running. You should be ready to build docker image from DigitalOcean Ceph exporter project. Consider installing Git if you don’t have it already. sudo yum -y install git If you’re using Ubuntu, run: sudo apt update && sudo apt -y install git Then clone the project from Github: git clone https://github.com/digitalocean/ceph_exporter.git Switch to the ceph_exporter directory and build docker image: cd ceph_exporter docker build -t ceph_exporter . This will build an image named ceph_exporter. It may take a while depending on your internet and disk write speeds. $ docker images REPOSITORY TAG IMAGE ID CREATED SIZE ceph_exporter latest 1e3b0082e6d4 3 minutes ago 379MB Step 4: Start Prometheus ceph exporter client container Copy ceph.conf configuration file and the ceph..keyring to /etc/ceph directory and start docker container host’s network stack. You can use vanilla docker commands, docker-compose or systemd to manage the container. For docker command line tool, run below commands. docker run -it \ -v /etc/ceph:/etc/ceph \ --net=host \ -p=9128:9128 \ digitalocean/ceph_exporter For docker-compose, create the following file: $ vim docker-compose.yml # Example usage of exporter in use version: '2' services: ceph-exporter: image: ceph_exporter restart: always network_mode: "host" volumes: - /etc/ceph:/etc/ceph ports: - '9128:9128' Then start docker container using: $ docker-compose up -d For systemd, create service unit file like below: $ sudo vim /etc/systemd/system/ceph_exporter.service [Unit] Description=Manage Ceph exporter service [Install] WantedBy=multi-user.target [Service] Restart=always TimeoutStartSec=0 ExecStartPre=-/usr/bin/docker kill ceph_exporter ExecStartPre=-/usr/bin/docker rm ceph_exporter ExecStart=/usr/bin/docker run \ --name ceph_exporter \ -v /etc/ceph:/etc/ceph \ --net=host \ -p=9128:9128 \ ceph_exporter ExecStop=-/usr/bin/docker kill ceph_exporter ExecStop=-/usr/bin/docker rm ceph_exporter Reload systemd daemon: sudo systemctl daemon-reload Start and enable the service: sudo systemctl enable ceph_exporter sudo systemctl start ceph_exporter Check container status:

sudo systemctl status ceph_exporter You should get output like below if all went fine. Step 5: Open 9128 on the firewall. I use firewalld since this is a CentOS 7 server, allow access to port 9128 from your trusted network. sudo firewall-cmd --permanent \ --add-rich-rule 'rule family="ipv4" \ source address="192.168.10.0/24" \ port protocol="tcp" port="9128" accept' sudo firewall-cmd --reload Test access with nc or telnet command. $ telnet 127.0.0.1 9128 Trying 127.0.0.1... Connected to 127.0.0.1. Escape character is '^]'. $ nc -v 127.0.0.1 9128 Ncat: Version 6.40 ( http://nmap.org/ncat ) Ncat: Connected to 127.0.0.1:9128. Step 6: Configure Prometheus scrape target with Ceph exporter We need to define the Prometheus static_configs line for created ceph exporter container.  Edit the file /etc/prometheus/prometheus.yml on your Prometheus server to look like below. scrape_configs: - job_name: prometheus static_configs: - targets: ['localhost:9090'] - job_name: 'ceph-exporter' static_configs: - targets: ['ceph-exporter-node-ip:9128'] labels: alias: ceph-exporter Replace localhost with your ceph exporter host IP address. Remember to restart Prometheus service after making the changes: sudo systemctl restart prometheus Step 7: Add Prometheus Data Source to Grafana Login to your Grafana Dashboard and add Prometheus data source. You’ll need to provide the following information: Name: Name given to this data source Type: The type of data source, in our case this is Prometheus URL: IP address and port number of Prometheus server you’re adding. Access: Specify if access through proxy or direct. Proxy means access through Grafana server, direct means access from the web. Save the settings by clicking save & Test button. Step 8: Import Ceph Cluster Grafana Dashboards The last step is to import the Ceph Cluster Grafana Dashboards. From my research, I found the following Dashboards by Cristian Calin. Ceph Cluster Overview: https://grafana.com/dashboards/917 Ceph Pools Overview: https://grafana.com/dashboards/926 Ceph OSD Overview: https://grafana.com/dashboards/923 We will use dashboard IDs 917, 926 and 923 when importing dashboards on Grafana. Click the plus sign (+)> Import to import dashboard. Enter the number that matches the dashboard you wish to import above. To View imported dashboards, go to Dashboards and select the name of the dashboard you want to view. For OSD and Pools dashboard, you need to select the pool name / OSD number to view its usage and status. SUSE guys have similar dashboards available on https://github.com/SUSE/grafana-dashboards-ceph Other Prometheus Monitoring guides: How to Monitor Redis Server with Prometheus and Grafana in 5 minutes How to Monitor Linux Server Performance with Prometheus and Grafana in 5 minutes How to Monitor BIND DNS server with Prometheus and Grafana Monitoring MySQL / MariaDB with Prometheus in five minutes How to Monitor Apache Web Server with Prometheus and Grafana in 5 minutes

[netmetic]

To Collect or Not Collect?

Recently, I posted my blog, “Do You Know What Your Data Center is Up To?,” to jump-start a discussion about making your data center autonomous.  One thing I realized after I posted that first blog is that I didn’t give any technical details. This blog addresses that problem, providing some real “meat” that you can use to start the shift to autonomous data center.

First, let me talk about the reference architecture for telemetry collection. A telemetry architecture includes the following key components:

Learning:  Ingesting the key telemetry data points, defining baselines, and then identifying trends which drive prescriptive controls.

Control:  The scheduler that acts upon the telemetry data to make changes.

Alerting: When collection data is out of norm, the alerting system sends a notification to the DC Ops team.

Visualization: The system that shows the collected data in graph format.

TSDB (time-series database):  The system that captures the inbound telemetry (push) or scrapes (pull) data from collection end points.

Scalable & Expandable Collection Tool:  An agent or application that captures the key telemetry and either pushes or pulls the information in a given time interval.

Each component has a number of options and potential combinations to create the right architecture for your needs.

Now that you know what an end-to-end telemetry collection system looks like, let’s consider a couple real-world solution architectures that showcase a few of these components. These solutions are industry-known and widely available to deploy throughout your data center.

The following solution architecture combines CollectD* with Grafana* and Prometheus*. What makes this compelling is the community support for Grafana, which allows you toeasily download and deploy graphs into your instance. Prometheus will scrape the logs from the local machines, therefore the nodes are not actually reporting out; instead, they are exposing their telemetry info for the pull. Installation is rather simple for both Grafana and Prometheus and the configuration information is easy to add for the nodes to your instance.

As another option, you could use CollectD with the ELK stack (Logstash*, Elasticsearch* and Kibana*).  What I have found very intriguing about this solution is that if you are using Docker*, there are a few containers easily implementable (from an all-in-one container to a three-container model). This solution requires each node to setup their “Network” plug-in in CollectD to push their information for a given time interval to Logstash.

Both of these solution architectures are open source, which means they have great community support and you have more configuration options than you can imagine. Along with CollectD working on the top server OS platforms such as Centos*, Red Hat Enterprise Linux (RHEL), Ubuntu*, and FreeBSD*.

With each of these solution architectures the scale factor is important. Anyone can set up a telemetry system on a single node or even a rack – and this is perfect for testing and to show the business value and TCO of such a system. But when it’s time to scale to thousands of nodes, you need to start thinking of deployment. Do I use a Docker image to deploy via Kubernetes*? Do I use Chef*, Ansible*, or a custom tool to make the telemetry system part of my automated build and deployment process? These are all good questions to think through when considering future telemetry you may need for new use cases and adjacent platform components.

So let’s keep this going… what do I collect? Well, it depends. What is your pain point? Here’s a mapping of pain points to what telemetry you should collect (not an exhaustive list):

Pain Point

What to Collect

Why You Need It

Infrastructure Efficiency (Power Management, Thermal Management and Workload Optimization) System-level Info Gathers the system-level information around power and thermals which is being exposed through the Baseboard Management Controller (BMC) to the OS. Utilization Utilization of the system over time Performance Information Monitoring the performance of the CPU, cache, and memory. Needed to determine the amount of effective headroom on the system. Used to target specific machines for workload co-location Reliability Power & Temperature Spikes Need to know if there are any system issues like power spikes or high temperatures causing the failure or rapid degradation of the device Memory Errors Logging tool for memory errors seen in the system DIMM Performance & Health Shows the wear-out indication of a drive along with various other health-related metrics (for example, unsafe power downs) Raw performance and health for the DIMM Utilization of the system and indicator if the system is highly used during the time of failure Throughput Monitoring high throughput and its relation to the failure or potential failure. Used alongside the MCElog and ipmitools for failure trend detection Performance Performance Metrics System-level performance for each cgroup, which is necessary to understand the resource consumption of each cgroup (that is, workload) Memory Access Measuring the memory accesses of the system, which is used for calculating the effective headroom for resources

I hope this blog has gotten you even further excited about transforming your data center into an autonomous environment. Stay tuned for my next blog, which will delve deeper into what exciting projects Intel is working on that can help you with that transformation.

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