Gtk-Message: 21:23:41.751: Not loading module

 Error message: he message you're seeing:

Gtk-Message: 21:23:41.751: Not loading module "atk-bridge": The functionality is provided by GTK natively. Please try to not load it.

FIX:- 

indicates that the atk-bridge module is no longer necessary for your version of GTK, as the functionality it provides is now built into GTK itself. This is more of an informational or warning message rather than an error, and your application should still run fine without any issues.

However, if you'd like to suppress this message or resolve it for a cleaner output, here are some approaches:

1. Ensure Dependencies Are Up-to-Date

Make sure you have the latest versions of GTK and its related packages:

 sudo apt update
sudo apt upgrade

You can also specifically update GTK and ATK packages (on Ubuntu/Debian):

sudo apt install --reinstall libgtk-3-0 at-spi2-core libatk-adaptor
 

2. Unset GTK Modules Environment Variable (Suppress Message)

The message might be triggered because the GTK_MODULES environment variable includes atk-bridge. You can suppress this by unsetting the variable.

Run the following command in your terminal before launching your application:

unset GTK_MODULES
 

To make this change permanent, you can add the command to your .bashrc or .bash_profile:

echo "unset GTK_MODULES" >> ~/.bashrc
source ~/.bashrc
 

3. Check for Old Configurations

Some applications or configurations may explicitly load unnecessary modules. Look for any GTK or atk-bridge settings that might be outdated in the following locations:

• ~/.config/gtk-3.0/settings.ini
• /etc/gtk-3.0/settings.ini

You may not find this file, but if you do, ensure there’s no manual loading of atk-bridge.

4. Install Accessibility Bridge (Optional)

If you still want to install the atk-bridge module (even though it's not necessary), you can do so with:

sudo apt install at-spi2-core
 

5. Suppress the Warning in Output (Advanced)

If you're running a script or an application that logs GTK messages and you want to suppress this specific message, you can redirect the output using grep or sed.

Example:

your-application 2>&1 | grep -v "Not loading module 'atk-bridge'"
 

These steps should help either resolve or suppress the atk-bridge message depending on your preference. If the message is just cosmetic and not affecting functionality, you can safely ignore it.

 

 

 

Install Prometheus in Minikube using Helm

To install Prometheus in Minikube using Helm, follow these step-by-step instructions. This process assumes that you already have Minikube and Helm installed.

Prerequisites:

1. Minikube installed on your machine. Minikube Installation Guide
2. kubectl installed and configured. kubectl Installation Guide
3. Helm installed on your machine. Helm Installation Guide

Step-by-Step Installation

Step 1: Start Minikube

Start your Minikube cluster:

 minikube start

Wait for Minikube to start, and check the status:

 minikube status

Step 2: Add Helm Repository for Prometheus

Helm provides a stable repository that contains Prometheus charts. First, add the prometheus-community repository:

 helm repo add prometheus-community https://prometheus-community.github.io/helm-charts

Update your Helm repository to make sure everything is up-to-date:

 helm repo update

Step 3: Create a Namespace for Monitoring

Create a dedicated namespace for Prometheus (e.g., monitoring):

 kubectl create namespace monitoring

Step 4: Install Prometheus Using Helm

Now, use Helm to install Prometheus. You will use the Prometheus chart from the prometheus-community repository.

helm install prometheus prometheus-community/prometheus --namespace monitoring
 

This command will:

• Install the Prometheus chart from the prometheus-community Helm repo.
• Use the namespace monitoring for the Prometheus components.

Step 5: Verify the Installation

Check the resources created in the monitoring namespace:

kubectl get all -n monitoring
 

You should see several resources such as pods, services, deployments, statefulsets, etc.

Step 6: Access the Prometheus UI

To access the Prometheus UI, we will use Minikube’s service tunneling feature. Run the following command to get the service URL:

minikube service prometheus-server -n monitoring
 

This will launch a browser window to access Prometheus.

If you want to expose the Prometheus UI via port forwarding, you can run:

helm uninstall prometheus --namespace monitoring
 

You can also delete the monitoring namespace if you no longer need it:

kubectl delete namespace monitoring
 

 

 

 

About Prometheus

 GitHub Link : https://github.com/Naveenjayachandran/Kubernetes_Prometheus

What is Prometheus?

Prometheus is an open-source systems monitoring and alerting toolkit originally built at SoundCloud. Since its inception in 2012, many companies and organizations have adopted Prometheus, and the project has a very active developer and user community. It is now a standalone open source project and maintained independently of any company. To emphasize this, and to clarify the project's governance structure, Prometheus joined the Cloud Native Computing Foundation in 2016 as the second hosted project, after Kubernetes.

Prometheus collects and stores its metrics as time series data, i.e. metrics information is stored with the timestamp at which it was recorded, alongside optional key-value pairs called labels.

For more elaborate overviews of Prometheus, see the resources linked from the media section.

Features

Prometheus's main features are:

• a multi-dimensional data model with time series data identified by metric name and key/value pairs
• PromQL, a flexible query language to leverage this dimensionality
• no reliance on distributed storage; single server nodes are autonomous
• time series collection happens via a pull model over HTTP
• pushing time series is supported via an intermediary gateway
• targets are discovered via service discovery or static configuration
• multiple modes of graphing and dashboarding support

What are metrics?

Metrics are numerical measurements in layperson terms. The term time series refers to the recording of changes over time. What users want to measure differs from application to application. For a web server, it could be request times; for a database, it could be the number of active connections or active queries, and so on.

Metrics play an important role in understanding why your application is working in a certain way. Let's assume you are running a web application and discover that it is slow. To learn what is happening with your application, you will need some information. For example, when the number of requests is high, the application may become slow. If you have the request count metric, you can determine the cause and increase the number of servers to handle the load.

Components

The Prometheus ecosystem consists of multiple components, many of which are optional:

• the main Prometheus server which scrapes and stores time series data
• client libraries for instrumenting application code
• a push gateway for supporting short-lived jobs
• special-purpose exporters for services like HAProxy, StatsD, Graphite, etc.
• an alertmanager to handle alerts
• various support tools

Most Prometheus components are written in Go, making them easy to build and deploy as static binaries.

Architecture

This diagram illustrates the architecture of Prometheus and some of its ecosystem components:

Prometheus scrapes metrics from instrumented jobs, either directly or via an intermediary push gateway for short-lived jobs. It stores all scraped samples locally and runs rules over this data to either aggregate and record new time series from existing data or generate alerts. Grafana or other API consumers can be used to visualize the collected data.

When does it fit?

Prometheus works well for recording any purely numeric time series. It fits both machine-centric monitoring as well as monitoring of highly dynamic service-oriented architectures. In a world of microservices, its support for multi-dimensional data collection and querying is a particular strength.

Prometheus is designed for reliability, to be the system you go to during an outage to allow you to quickly diagnose problems. Each Prometheus server is standalone, not depending on network storage or other remote services. You can rely on it when other parts of your infrastructure are broken, and you do not need to setup extensive infrastructure to use it.

When does it not fit?

Prometheus values reliability. You can always view what statistics are available about your system, even under failure conditions. If you need 100% accuracy, such as for per-request billing, Prometheus is not a good choice as the collected data will likely not be detailed and complete enough. In such a case you would be best off using some other system to collect and analyze the data for billing, and Prometheus for the rest of your monitoring.