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Introduction to GitLab Kubernetes

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What is GitLab Kubernetes?

The GitLab Kubernetes Agent gives a safe association between a GitLab occurrence and a Kubernetes bunch and permits pull-based organizations to get cautions dependent on the organization’s approach. We can perform SaaS on GitLab, chúng tôi and have a lot more components not far off.

The Agent gives a protected association between the group and GitLab. We can control access by using Kubernetes features and GitLab features as per our requirements. The Agent gives a highly durable association utilizing WebSockets or gRPC between a Kubernetes group and a GitLab example. Since we need to keep the bunch side part insignificant and lightweight, we envision numerous Agents being introduced into a similar group with various access levels. In any case, this joining is perplexing. To see how the Agent functions, let me initially present its significant parts. GitLab and Kubernetes basically have two parts: GitLab and Kubernetes agent, or we can say that Kubernetes server. Agents are the bunch side part that must be conveyed in the group, while kas is the GitLab server-side part that is overseen closely by GitLab. Since we need to keep the bunch side part as thin as could really be expected, kas is answerable for a large part of the hard work.

Get Started GitLab Kubernetes

This is the reason, right now, kas is just accessible for select clients and activities. However, in the event that you might want to give it a shot, contact me by email or by referencing me in an issue with your undertaking ID, and we will approve your venture.

Create GitLab Kubernetes

Given below shows how we can create GitLab Kubernetes as follows:

We need to follow the different steps to create it:

1. First, we must have an account on GitLab.

2. After that, we need to create a project, as shown in the following screenshot as follows.

Now we can say see in the above screenshot there are two options; the first is we can create a new cluster as per our requirement, and the second is that we can connect an already created cluster. So as per requirement, we can select any option that we want.

The following screenshot shows what is the field we are required to fill as follows:

Running GitLab Kubernetes

GitLab Runner can utilize Kubernetes to run expands on a Kubernetes group. This is conceivable with the utilization of the Kubernetes agent.

The Kubernetes agent, when utilized with GitLab CI, associates with the Kubernetes API in the bunch, making a Pod for each GitLab CI Job. This Pod is comprised of, at any rate, a form holder, a partner compartment, and an extra holder for each help characterized in the .gitlab-ci.yml.

GitLab Kubernetes Workflow

Get ready: Create the Pod against the Kubernetes Cluster. This makes the compartments needed for the form and administrations to run.

Pre-form: Clone, reestablish reserve, and download ancient rarities from past stages. This is run on an exceptional holder as a feature of the Pod.

Fabricate: User assemble.

Post-form: Create.


From the above article, we have taken in the essential idea of the GitLab Kubernetes, and we also see the representation. From this article, we learned how and when we use it.

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Complete Guide On Zbrush Zremesher

Introduction to ZBrush ZRemesher

Zbrush ZRemesher can understand as arranging as well as calculating polygons for doing retopology of the visible portions of the chosen sub tool in this software. With ZRemesher, one can do retopology very quickly instead of doing it manually. Retopology is necessary for having a good number of polygons on the sub tool so that it can easily animate during the animation process. In Zbrush, we also have a ZRemesher brush that helps us locate sub-tool portions according to which we want to do retopology with the ZRemesher option.

How to Use ZRemesher?

We use ZRemesher to minimize polygons on the selected sub tool of our model. So how you can use ZRemesher, let us have a model. We will go to the Light box of this software and choose this Female head from the list. You can use your own model for learning about this topic.

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Now we will go to the transform menu of the menu bar, which is at the top of the working screen, and enable the Polyframe option so that we can see polygons on our selected sub tool, or you can press the Shift + F button of the keyboard as its short cut key.

If we increase the DynaMesh value from the Dynamesh option of the Geometry panel for this model, you can see there are lots of polygons that are not good for animation purposes.

Before you start working with ZRemesher, make a duplicate copy of your subtool because ZRemesher will change the retopology of your sub tool completely but maintain shapes as much as possible.

By default, its value is 5, but you can decrease it as per your requirement. Such as we will take its value as 1 by entering 1 in this option.

And you will have less polygons with the same shape.

Methods of ZRemesher

Using ZRemesher, you can go with some methods; the first one is you can go with symmetry mode, which gives you symmetrical polygons on your selected sub tool. So if your sub tool has symmetry, then make sure you have symmetry mode is on. So, for example, we had taken this sub tool through the ZRemesher process when my symmetry mode was on, and you can see there are equal polygons on both sides of the face.

And the next method is non-symmetry mode so that we will press the X button on the keyboard.

And now, when you press the ZRemesher button of the ZRemesher panel, then you can see it will give you a result that has no symmetry for your sub tool. So you can use it with a non-symmetrical sub tool.

The other method which you can use for not disturbing your desired area. So for that, we make poly groups of our desired area. You can make more than two poly groups of your model, and for making poly groups, we will on Mask brush by holding the Ctrl button of the keyboard.

And we will mask this mouth area.

And press the Ctrl + W button of the keyboard to make this masked area a poly group.

Now enable the “KeepGroups” option of the ZRemesher panel.

And you can see after retopology; it maintains the edges of the mouth very accurately.

If you want, you can press the ZRemesher button again to have smooth polygons.

There is a ZRemesher brush also in the brushes panel, and you can use it for the same purpose as we use Mask brush. With ZRemesher brush, we can specify the area to ZRemesher option for having accurate results.

Now just move the cursor of the mouse around the area which you want to mark. For example, we will mark this eye area. My symmetry mode is On, so it will automatically mark the opposite eye.

You can use any of the methods according to your requirement for having your desired result. You just have to maintain parameters accurately.

Conclusion – ZBrush ZRemesher

We have good information about the ZRemesher option of this software, and now we have an understanding about almost every aspect of this option. You can also use ZRemesher brushes for smooth retopology of the visible sub tool of your model. Now we will suggest you start practicing this method to have more and more command on it.

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A Complete Guide On Feature Extraction Techniques

This article was published as a part of the Data Science Blogathon.

Introduction on Feature Extraction

In Natural Language Processing, Feature Extraction is one of the most important steps to be followed for a better understanding of the context of what we are dealing with. After the initial text is cleaned, we need to transform it into its features to be used for modeling. Document data is not computable so it must be transformed into numerical data such as a vector spac Text Extraction, or Text Vectorization.

In this article, we will explore different types of Feature Extraction Techniques like Bag of words, Tf-Idf, n-gram, word2vec, etc. Without wasting our time let’s start our article.

4. What are the techniques?

1. What is Feature Extraction from the text?

It understands only numerical data. The process of converting text data into numbers is called Feature Extraction from the text. It is also called text vectorization.

So we know that machines can only understand numbers and to make machines able to identify language we need to convert it into numeric form.

But when we have a sentence and we want to predict its sentiment, How will you represent it in numbers? In this article, we are going to study these techniques.

6. Word2Vec(Word Embedding)

Common Terms Used

Word (w) — Words that are used in a document are known as Word.

Techniques for Feature Extraction 1. One Hot Encoding

Let’s say we have documents “We are learning Natural Language Processing”, “We are learning Data Science”, and “Natural Language Processing comes under Data Science”.

corpus – We are learning Natural Language Processing, We are learning Data Science, Natural Language Processing comes under Data Science

Vocabulary(Unique words)  – We are learning Natural Language Processing Data Science comes under – V – 10

Document1 — We are learning Natural Language Processing


2. Easy to implement

One hot encoding is not used in the industry because it has flaws.

4. No capturing of semantic meaning.

2. Bag of Words

Specially used in the Text Classification task.

We can directly use CountVectorizer class by Scikit-learn.

code example


3. Out of Vocabulary (OOV) problem does not occur, which means the model does not give an error.

3. Not consider sentence ordering issues.

3. Bag of n-grams

A bag-of-n -grams model represents a text document as an unordered collection of its n-grams.

n-gram — using n number of words of the document

code example


2. Able to capture the semantic meaning of the sentence.

2. OOV, Ignoring the new word.

4. Tf-Idf — Term Frequency and Inverse Document Frequency

The number of times a word appears in a document is divided by the total number of words in that document. 0 < Tf< 1

The logarithm of the number of documents in the corpus is divided by the number of documents where the specific term appears. In Scikit-learn use log(N/ni) + 1 formula.

code example

Q. Why do we take a log to calculate IDF?


1. This technique is widely used in Information retrieval like a search engine.

4. Semantic meaning does not capture.

5. Custom Features

Creating new custom features using domain knowledge.

5. Character count.

6. Word2vec 

Word Embeddings

Wikipedia says “In natural language processing, word embedding is a term used for the representation of words for text analysis, typically in the form of a real-valued vector that encodes the meaning of the word such that the words that are closer in the vector space are expected to be similar in meaning.”

let’s consider one example boy-man vs boy-table, Can you tell which of the pair has more similar words to each other?

For a human, it’s easy to understand the associations between words in a language. We know that boy and man have more similar meanings than boy and table but what if we want machines to understand this kind of relation automatically in our languages as well? That is what word embeddings come into the picture.

Types of Word Embedding

1. Frequency-based – Count frequency of word



Glove(based on Matric Factorization)

2. Prediction based


What is Word2Vec?

Word2Vec is somewhat different than other techniques which we discussed earlier because it is a Deep learning-based technique.

Word2Vec is a word embedding technique, that converts a given word into a vector as a collection of numbers.

As we have other techniques then why do we need word2vec?

Word2vec capture semantic meaning like happiness and jo

Word2vec create low dimension vector(each word is a collection of a range of 200 to 300.

Word2vec creates a Dense vector(non-zeros)

How to Use It?

2. Self-Trained model


In this article, we learned about different types of feature extraction techniques. The key takeaways from the article are,

We learned different types of feature extraction techniques such as one-hot encoding, bag of words, TF-IDF, word2vec, etc.

One Hot Encoding is a simple technique giving each unique word zero or one.

A bag-of-words is a representation of text that describes the occurrence of words within a document.

TF-IDF is a statistical measure that evaluates how relevant a word is to a document in a collection of documents.

and at the last we have seenWord2Vec. Word2Vec is a word embedding technique, that converts a given word into a vector as a collection of numbers.

Each technique has its pros and cons.

So, this was all about feature extraction techniques. Hope you liked the article.

The media shown in this article is not owned by Analytics Vidhya and is used at the Author’s discretion.


Complete Guide To Powershell Administrator

Introduction to PowerShell Administrator

PowerShell administrator is a person who is responsible for maintaining the overall windows-based servers of an organization. They are also responsible for maintaining the integrity of the data of the organization. They also play a pivotal role in maintaining the on-boarding and off-boarding of employees as they are the ones responsible for maintaining the active directory of the organization. PowerShell administrators are also known as windows administrators.

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Different ways of Running as PowerShell Administrator

There is a major difference between running a cmdlet or a script in PowerShell in a normal mode from that of an administrator mode. It is because most of the operations require admin access and only a PowerShell administrator has the privilege to perform those operations.

Open PowerShell using the run command. Once the PowerShell window is opened, type as Start-Process PowerShell -verb run as and press the enter key.

By using task manager, create a new task. In the name, type PowerShell and check the “Create this task with administrative privileges” and press enter.

Roles and Responsibilities of PowerShell Administrator

Given below are the roles and responsibilities :

1. Check for patches

One of the main responsibilities of a PowerShell administrator is to check for the latest patches that are available and install them. This is a crucial part for any organization to prevent the resources from vulnerabilities attacks and other security related issues. Most of the organization’s patches are installed on a monthly basis to avoid any threats. Get-Hotfix cmdlet is used to find the patches. If we know the id of the patch, then that KB article value should be passed.





It will display the list of all patches that are installed in the local computer.

2. Monitoring the disk space availability

The other important task of the PowerShell administrator is to monitor the available disk space in the system. This process will be tedious in case if there are multiple servers in the system and can’t be done manually. This job is automated by most of the admins with the help of a script which regularly checks for the disk space and sends a trigger based on the condition. These scripts are run using a task scheduler, which will run during non-business hours.




3. Adding users from csv to an AD Group





4. Check if patch is installed in a server or not



In the above example, a list of servers is maintained in one csv and the list of patch ids to be checked for installation in maintained in another csv. For each of the servers mentioned in the csv, all the patch ids are checked if it is installed or not. The server details and patch id’s can be mentioned in the same csv but it would be convenient to have them in different csv’s.

5. Deleting IIS logs older than 10 days




In the above script, a list of log locations is mentioned in the text file. Then in each of the paths, the files that are greater than 7 days are deleted. This can also be scheduled in a task scheduler and can be run daily during non-business hours.


Thus, the article covered in detail who is a PowerShell administrator and what are his roles and responsibilities. The mentioned roles are only a few but there are more tasks than a PowerShell administrator does on his day-to-day activities. The roles are explained with appropriate examples. In some cases, the PowerShell administrator is also responsible for the overall infrastructure of an organization.

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Complete Guide To Logstash Version

Introduction to Logstash

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Various Logstash Version 1. Logstash 6.3.0 Version

All the versions before 6.3.0 supports for 6.2.x versions or earlier versions including 5.x versions which are considered as PQ versions prior to Logstash 6.3.0 therefore making persistent queue enabled therefore recommending deleting all the persistent queue and its associated activities before upgradation.

2. Logstash 6.0 Version

There are some core and major changes in Logstash 6.0 version which are as follows:

Changes in Logstash Core: These changes can affect any of the instance for Logstash which further impacts lot of features. All changes related to Logstash is mainly related to plugins associated with it.

Application settings segment with config.reload.interval parameter has been changed to use all the time related values and convert this to millisecond values for themselves in their desired units of time.

There are certain changes in terms of rpm and deb packages which in turn makes the overall config files match the required configuration with conf.d pattern matching the glob pattern for transformation.

Command line interface behavior also got changed providing options to -e and -f for mutual exclusion and configurations appending the stdin input and stdin output respectively.

There were many plugins which were deprecated from the default bundle based on the usage of data and still those plugins can be used before these versions.


3. Logstash 7.0.0-alpha1

Changes in Logstash Core: In this version the execution of java has been made as default.

There are major changes in core java specifications and all the associated activities.

Referencing to field is also made strict by default.

Bugfix: There is also a bugfix which is related to data type conversions including byte, short as in RabbitMQ input plugin.

Logstash-filter-aggregate is one of the plugins which has an ability to add new feature consisting of custom timeout or inactivity timeout in the block of entire code.

There are many logstash metrics specific to aggregate plugin having aggregate_maps, error_codes, pushed_events to track for.

Another Plugin Added is logstash-filter-jdbc_static: This plugin is used for adding additional information that emphasize on the documentation and signifies ordering in the table ordered.

Logstash-filter-xml: Plugin to add xpath to the failed empty set of arrays, it also fixes the forced_array behavior with nested elements.

4. Logstash 7.0.0-alpha2 Version

It also has some more improvised Plugins which are supported in this release version which are as follows:


Also, it supports one more plugin like logstash-flash-memcached for making cache of stuffs.

Logstash input beats is another plugin which consists of loosen jar-dependencies to allow plugins to work with JRubies including later version.

5. Logstash 7.0.0-beta1 Version

Removal of Removed obsolete lru_cachesize field from the logstash-filter-geoip.

Removal of logstash-filter_jdbc streaming which help in swap out of postgresql for testing and streaming.

Minor documentation fixes and enhancements as well.

Logstash input-beats changed vault of add_hostname with some security aspects to be maintained.

The plugin consists of some kafka dependency that is also being removed.

6. Logstash 7.0.0-rc1 Version

Issues to be fixed for unqualified domains where it will fail for resolving the running instances with Logstash 5.x versions.

It included logstash-filter-kv which acts as a timeout parameter in this version.

7. Logstash 7.0.0-rc2 Version

It has a change related to plugins where the logstash-input-snmp plugin is updated and has a support for SNMP tables which can be queried religiously.

Enhancements related to get more cleared form of logs where three error messages in the client gets saved via target address related.

8. Logstash 7.0.0 Version

Logstash 7.0.0 version includes features from most of the already supported versions from 7.0.0-alpha1, alpha2, beta1, rc1 and rc2 versions.

Supports for most of the other plugins as well where it includes logstash-codec-cef, logstash-codec-netflow and many more.

9. Logstash 7.0.1 Version

It didn’t include much of the changes but majorly focused on bug fixing aspects of all the related 7.0.0 related versions.

10. Logstash 7.1.0 Version – Logstash 7.1.1 Version

In 7.1.0 version majorly updates for the changes to licensing of security features is emphasized on such as encrypted communications, files, and native authentication.

In this 7.1.1 version release majorly focused on bug fixing no user facing changes in the release.

11. Logstash 7.2.0 Version – Logstash 7.2.1 Version

Fixed that Java supports for Java 11 and Joni regexp is enabled.

Jinja2 docker dependency needs to be resolved.

12. Logstash 7.3.0 Version – Logstash 7.3.2 Version

There are major bug fixing related to ability to give multiple pipelines for all the settings.

13. Logstash 7.4.0 Version – Logstash 7.4.2 Version

Not much user-facing changes upto 7.4.2 version.

14. Logstash 7.5.0 Version – Logstash 7.5.2 Version

In 7.5.2 version the major emphasis is kept on improving the logstash start-time by moving class caching from compute steps to compiled pipeline.

Updated all jackson related dependencies.

15. Logstash 7.6.0 Version – Logstash 7.6.2 Version

Some fixes were made related to quoted plugin option key having many regression keys to stop pipeline from starting.

16. Logstash 7.7.0 – Logstash 7.13.4 Version

Have almost same fixes and changes related to plugins and manipulation in pipelines and its related components like GeoIP.

17. Logstash 7.14.0

This is the stable and latest version of Logstash which is currently into release segment.

Conclusion – Logstash Version

The Logstash Elastic Agent input plugin is available and is used with Elastic agents normal availability and elastic workplace search that has really aided in enhancing all the logs. Logging mechanism gets improvised and simplifies the job of maintaining logs in an efficient manner seamlessly. Logstash latest version has come a long way starting from its alpha release with lots of bug fixing and improvements.

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A Complete Guide To Joomla Version

Introduction to Joomla Version

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Different Joomla Versions

As we know, Joomla was a result of the dispute of Mambo, which was formed as a non-profit organization with the intention of protecting the project from lawsuits. It is used widely to create both simple and complex web applications. Joomla is a spelling of Swahili “jumla”, which means “all together”. In September 2023, the first official version of Joomla was released with some major bug fixes. It was basically a rebranding version. Over 3 years, many new versions with so many updates and new changes were released.

1. Joomla 1.x Series

Joomla 1.0: It was the first-ever release of Joomla on 22 September 2005. It is basically for the rebranding release of Mambo. The basic motive of this release is rebranding with major bug fixes. By voting in the community members, the company decided on the logo of Joomla on 29 September 2005.

Joomla 1.5: It was the first major version of Joomla, which was released on 22nd January 2008. This version has got new features and new power levels in the world of CMS (Content Management Systems). It has got full support and enthusiasm from the public. In this version, Joomla has got APIs as well, which helped it to become international CMS. This is the version of Joomla, which has got long term support from the public. Joomla 1.5 was officially ended in April 2012 with the release of Joomla 3.0. The last version of Joomla 1.5v was 1.5.26, which was released on 27th March 2012.

Joomla 1.7.0: This version of Joomla was released in July 2011. This version added some new and important features related to the security and improved migration tools. Features added in this version were very quite important from the user perspective.

2. Joomla 2.x Series

Joomla’s 2.x version was released in 2012 and was one of the major revisions announced after the version 1.x release.

It has got some necessary improvements like:

Making new APIs making it easier for the users to use the application.

One of the major features of multi-language was added in this release.

Bug fixes like registration form on the login page, display of currencies, light box for product images, etc.

SSL features for different pages like login, register, title, etc., were added.

Image resizing and adding new events for plugins were added.

This version of Joomla is an LTS (Long Term Support) release.

3. Joomla 3.x Series

This version focuses on some of the important features like:

The more intuitive backend of the website.

Mobile-friendly websites for the users.

Fixing some major bugs of the 2.x release.

After six months of the release of Joomla 3.0, Joomla 3.1 was released for the users. It included one of the important features of tagging for the users. With the release of Joomla 3.2 and 3.3, which released in November 2013 and April 2014, respectively, it became one of the most popular versions of Joomla making. Other versions obsolete as it helps in the ease of access of websites for the users.

Some features given below were introduced in this version of Joomla:

Ease of navigation in the website.

Editing the content of the website.

A search was added for the various website pages.

Checking the products in stock before ordering.

Ability to unlock an unfinished item on the website.

4. Joomla 4.x Series

With all the chaos that happened in the Joomla 3.x series, the team decided to develop a stable build to improve the relationship between the members. After long discussions on the current situations and the changes that needed to be done, the team was more productive and made many changes in the project.

Some of the features that were added in this release were:

Focused on the usability of the backend interface of Joomla 4.

Support for PHP5 was removed.

Support for SQL server has been removed.

The team members made a new strategy for the development.

Active engagement of team member in testing rather than criticizing the previous releases.

Admin code refactoring was done, along with some major bug fixes.

Conclusion – Joomla Version

The above description clearly explains the full version history of Joomla. It is one of the most popular and widely used systems for content management and designing of software. It is used worldwide and is considered one of the most reliable, easy to use and secure applications to use. It has got wide support and a lot of enthusiasm from the people in such a short period of time.

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