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ALL ABOUT ELASTIC STACK 6

All About Elastic Stack 6

ELK Stack or Elastic Stack 6 commonly known as (Elasticsearch, Logstash, Kibana) is a powerful tool not only for driving search on big websites, but also for analyzing big data sets in a matter of milliseconds! It is a progressively popular technology, and a valuable skill to have in today’s job market.

Elastic Stack 6 was released last November, and now it is a good time to assess whether to upgrade. To help you folks make that call, we are going to take a look at some of the key changes included in the different components in the stack and review the main breaking changes.

The main changes to Elastic Stack are intended to boost performance, improve consistency, and make retrieval easier. The most significant changes in Logstash are focused on allowing the users to run multiple self-contained pipelines on the same JVM. There are no main changes to Kibana, but a comparatively large amount of minor usability improvements was added.

What You Need to Know
Elasticsearch 6

Changes to Elasticsearch are typically internal and should not require most organizations to tailor how they configure the Elasticsearch, with the big exception being the change to mapping types.

Sparse Doc Values

A sparse values situation results in the use of a huge amount of disk space and file-system cache. The revolution to Lucene 7 lets Elasticsearch support sparse doc values, a new encoding format that minimizes the disk space and improves query throughput.

Upgrades

Updating to the new Elasticsearch version is made easier with a series of upgrade improvements that target at tackling some of the traditional sprints facing upgrade procedures.

A new restart feature denies the need for a full cluster restart and thus reduces downtime. Elasticsearch 5.x indices will be able to be searched using cross-cluster searching: a new approach to cross-cluster operations that change the traditional tribe-node based approach. Deprecation logs have been reinforced with important information on breaking changes.

Logstash 6

Logstash was initially proposed to handle one type of event per instance, and previous to this version, each Logstash instance supported only a single event pipeline. Users can avoid this restriction using conditional statements in the configuration, which often leads to a new set of problems.

Logstash now supports native support for multiple pipelines. These pipelines are defined in a pipeline.yml file, which is loaded by default.

A new pipeline viewer now lets users monitor and analyze Logstash pipelines in Kibana. Pipelines are displayed on a graph where each component is accompanied by relevant metrics. I explored the pipeline viewer in this article.

Kibana 6

The major changes to the UI include a new CSV export option, new colors for better contrast, and enhanced screen reading and keyboard navigation.

Dashboarding in Kibana has two new features. A new full-screen mode was added when viewing dashboards to the users. In addition, the new dashboard also allows administrators to share dashboards securely.

We are going to end this part with a summary that needs to be considered before upgrading. Keep in mind this is a partial list of breaking changes only.

Elasticsearch

The main breaking change in this version is the slow removal of mapping types from indices, so Elasticsearch 6.0 will be able to read indices created in version 5.0 or above only. Elasticsearch 6.0 requires a re-indexing afore full functionality can be achieved; this is because of a number of changes to the Elasticsearch indices. These are accompanied by changes to the CAT, Document, and Java APIs and the Search and Query DSL, as well as REST changes. A result is a number of key changes that affect Elasticsearch deeply, tailoring everything from the structure of queries and scripts to how internal components communicate.

Logstash

Changes in Logstash 6 include several breaking changes, with a number of changes to the input and output options. There are also several plugin changes and a change to the config.reload.interval configuration option, which now uses time value strings instead of millisecond time values.

Kibana

To transfer existing Kibana installations to Kibana 6.0, the Kibana index needs to be re-indexed.

The Verdict

There are pretty a large number of changes in Elastic Stack 6.0. Many of these changes stem from the upgrade to the Lucene 7 database engine, but just as many are part of a general push towards increased proficiency and performance.

Elastic Stack 6.0 also brings significant security changes and improvements. This follows the needs of users deploying Elastic Stack in production environments, where complex security requirements are increasingly the standard.

The major version of the stack comes with a need to re-index, changes to the index structure and a number of configuration modifications to various plugins should come as no surprise. Migration from former versions will need to be planned carefully and, above all, tested.

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WHAT IS AWS CLOUD HSM, HOW IT WORKS AND WHAT ARE THE BENEFITS?

What is AWS Cloud HSM, how it works and what are the benefits?

AWS CloudHSM is a cloud-based hardware security module (HSM) that enables you to easily generate and use your own encryption keys on the AWS Cloud. With CloudHSM, you can manage your own encryption keys using FIPS 140-2 Level 3 validated HSMs. CloudHSM offers you the flexibility to integrate with your applications using industry-standard APIs, such as PKCS#11, Java Cryptography Extensions (JCE), and Microsoft CryptoNG (CNG) libraries. CloudHSM is also standards-compliant and enables you to export all of your keys to most other commercially-available HSMs. It is a fully-managed service that automates time-consuming administrative tasks for you, such as hardware provisioning, software patching, high-availability, and backups. CloudHSM also enables you to scale quickly by adding and removing HSM capacity on-demand, with no up-front costs.

2

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WHY DO WE USE WEBSOCKETS WHEN AJAX CAN DO THE WORK?

Why do we use WebSockets when AJAX can do the work?

There are a few reasons:

Bi-directional communication.If your service is real-time you will typically not want to make a request and wait for a response; you want a response whenever the server is ready to send one. This isn’t possible with AJAX.

Less server overhead. The alternative to WebSockets are HTTP polling techniques (short- or long-polling) or Server Sent Events. Polling techniques are often inefficient or have a larger server burden than WebSockets. Server Sent Events aren’t standardized across browsers.

Smaller request frames. While less of a problem if you’re using HTTP/2, a lot of HTTP requests come with a lot of overhead that you likely don’t want/need for standard requests. Websockets use much smaller frames for communication, resulting in slightly faster communication.

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WHAT IS DYNAMIC WEB DESIGN?

What is dynamic web design?

Dynamic Web page is a web page that changes as per the requirements provided by the user or the computer program.

It displays varied contents each time the page is viewed. The page may change with time or as per the user who uses the site.

There are two types of dynamic web pages viz. Client side scripting, that generates client side content at the user end .Server side scripting are those web pages that vary when the web page is loaded or visited like that of shopping carts, submission forms etc. Dynamic web site enables to update the information frequently.

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WHY DO WE NEED A DOM? WHY CAN’T WE JUST MANIPULATE THE HTML? I WOULD LIKE TO KNOW THE REASONING BEHIND IT, AND WHY THE CONCEPT OF A DOM WAS BORN.

Why do we need a DOM? Why can’t we just manipulate the HTML? I would like to know the reasoning behind it, and why the concept of a DOM was born.

The purpose of the document object model is to manipulate a document with javascript. Without that, no front end scripting involving the document is possible. (Note that you can alter HTML elements in real time with CSS as well, but you’re limited to CSS properties indeed).

As for HTML, it’s a markup language, not meant for scripting. Just as styling is delegated to CSS, front end scripting is delegated to JS.

The use of HTML/CSS and JS is consensual because all major browsers implement them, following specifications (W3C specifications for HTML/CSS and ECMAScript specification for JS). (Note that while there are official sources to tell how they must behave, there are minor implementation differences for all three between browsers).

Simply put, HTML is to describe what is in a document, CSS is to describe how is what HTML describes, JS is to script anything with all that, based on an event driven fashion.

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WHY IS REACT JS MORE POPULAR THAN ANGULARJS?

Why is React JS more popular than AngularJS?

There are two reasons for the shift from AngularJS over to React. First, and the one that triggered interest, is speed. React was much faster and more memory efficient than Angular.

The second reason is more expansive and is what carried React into the stratosphere. Basically, the conception of React is more in-line with where the modern web is going.

AngularJS was born from the first era of web application development. To with, it was an era focused on the DOM. Coders wrote HTML and CSS then attached functionality to it with JavaScript. JQuery is nothing more than a DOM manipulation library, and AngularJS’s raison d’etre was literally to be what HTML would have been like if it had been created with applications in mind. The DOM was paramount.

React rejects the DOM as a thing. Instead, all that exists is the JavaScript application. The state of the application that outputs the DOM. The DOM is a result, not a thing. That is a massive paradigm shift. Suddenly, web pages are genuine applications.

React’s architectural concept was also more elegant and easier to understand. AngularJS relied on dirty-checking, where every component in the application was checked for changes ten times. It was a huge kluge (rhyming unintentional) and was slow as molasses with large DOMs.

React instead maintains a DOM state that is just a big JavaScript object. When the user does something, React creates a new DOM object and compares it to the old one. Any differences are then rendered to the UI. This is very easy to understand and very elegant.

This new philosophy now dominates and AngularJS has been completely obviated. Vue, Ember, Angular 2+, Bobril, and Aurelia all rely on some sort of virtual DOM or another, even though their change detection schemes are different. This new era has pushed frameworks to speeds that were unimaginable just two years ago, and much of this transition is thanks to React.

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WHAT IS GRAPHQL

What is GraphQL

GRAPHQL

GraphQL is an application layer query language that construes a string by a server, which then returns the required data in a detailed format. Open sourced by Facebook in 2015, GraphQL was developed internally during the evolution from Facebook’s HTML5-powered mobile apps to native apps. Today it is the principle graph data query language driving the majority of interactions within iOS and Facebook Android applications. The makers of GraphQL plan to open-source an instruction program on how to implement the server. The goal is to increase GraphQL capabilities to adapt to a wide range of back-end’s. This will let the coders to use the technology in projects of any size to access their own data more competently. The product developers will be able to structure servers and provides powerful frameworks, abstractions, and tools.

HOW TO USE IT

GraphQL is a different way of structuring the contract between client and server. The servers publish a set of rules specific to an application. GraphQL then supplies the language to query the developer’s data for the correct answer, within the constraints of rules. This way product developers are able to execute data requirements in a natural form, such as a declarative one and a hierarchical one. To understand how to use GraphQL, better first look at what it is trying to achieve.

Give client-side developers a well-organized way to query data they want to retrieve.
Give server-side developers a well-organized way to get their data out to their users.
Give everyone an easy and efficient way of retrieving data.

HOW IS IT DIFFERENT

The GraphQL query language is sited between client applications and the actual data sources. It works independently from data sources and other platforms. A GraphQL server can be made in PHP, Node or any other platform of the user’s choice. The users should be able to connect to GraphQL server with web apps, mobile apps or any other type of apps they may be using. They can then query and alter the data they are looking for. The major difference is that GraphQL does not come with a transport layer. That end of the operation is handled by a high-level framework, such as Relay. However, GraphQL have an excellent type system. The system is basically constructed on top of a layer of graphs with a set of rules defined by you. The users may not feel the need to display their data groups as a graph, but if the users really thinks about it, most of the time the user can structure his/her data schema in the form of graphs.

To envision what we are talking about, let’s have a look at some code. For this instance, we will look at creating a query for Product Hunt and want to retrieve data for a typical page:

{ product (id: “react-native-for-android”) { name, link, votes, comments
{ text } } }

The result would be:
{ ”
data”:
{ ”
product”:
{ ”
name”:

“React Native for Android”
, ”
link”:
“https://facebook.github.io/react-native/”
, ”
votes”:

“167”
, ”
comments”:
[ { ”
text”:

“Huuuuge for cross-platform progress.”
}, { ”
text”:

“Exciting stuff.”
} ]
}
}
}

Now the user is working with an upgraded version of Product Hunt and want to display the name of the author next to the comment. Then the user has to simply change the query like this:

{ product (id: “react-native-for-android”) { name, link, votes, comments
{ text, author { avatar } } } }

WHAT THE USER CAN DO WITH GRAPHQL

GraphQL is a very liberating platform. GraphQL, product developers no longer need to cope with ad hoc endpoints or worry about accessing data with multiple roundtrip object retrievals. Instead, the developer can easily create a sophisticated, declarative-hierarchical query dispatched to one single endpoint. Now all the experimentation and newly created views are built exclusively in the client development environment. The hassle of moving unstructured data from ad hoc endpoints into business objects is excluded. Instead, the user will get a powerful, intuitive type system you can use as a tool-building platform. The developer, will have the freedom to put more focus on client software and requirements without having to leave the development environment. As the system changes, the developer will be able to support shipped clients with confidence while staying well within the limits of mobile apps.

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FLASK VS DJANGO

Flask Vs Django

Flask Vs Django

Flask and Django are two of the most popular web frameworks for Python. In this article, we will be discussing some of the points you should consider while choosing between Flask and Django.

WHAT IS DJANGO AND WHAT DOES IT DO?

Django is a well-sophisticated framework aimed at rapid deployment and development of numerous web apps written in Python. This framework is distributed as an open-source. The framework itself is actually a code library, which helps the developers in building reliable, scalable, and workable web apps. Django is one of the most popular frameworks from a wide variety, available to Python developers. There is one limitation though: some things are envisioned to be done in one and the only way.

You can replace certain modules yet some core functionality should remain untouched. This is totally fine in 95% of the projects, and it saves a ton of time, money, and effort during development, as the users will have all the solutions they need straight out of the box.

WHAT IS FLASK?

Flask is another widely used web framework. Differing to Django, it is focused on at providing an out-of-the-box product with complete solutions for each task, Flask works more like a LEGO set, where the user can construct anything he/she wish, using an enormous set of external libraries and add-ons. Flask philosophy is “web development, one drop at a time”. Python developers with huge experience say that Flask enables adding new modules when the time comes, instead of overwhelming the users with the details from the very beginning.

LET’S TAKE A CLOSER LOOK AT WHAT POSSIBILITIES DJANGO HAS TO OFFER

  • Object Relational Mapping allows working with several types of databases such as SQLite, Post greSQL, Oracle and MySQL.
  • Celery allows doing asynchronous tasks and replacing unix crontab for cron jobs.
    The user can use Gunicorn instead of Apache; it’s easy and fun (if the user has no trouble with using NGINX).
  • If the developers are more skilled enough, then the user can use MongoDB as a primary database; this solves quite a lot of problems later on.
  • Using named URLs, reverse function, and the URL template tag allows creating a logically structured system, where one URL update will not inflict confusion.
  • Using supervisor for process monitoring lets restart the framework processes automatically; it is truly a rescuer during development stage.
  • Redis is a valued in-memory data structure store, which can be used for queuing celery jobs, as a cache, as a store for sessions, even for auto-completion and much more.
  • Munin and statds are another great pair of apps, allowing control and monitoring of the users Django app processes.
  • As we can see from the list of websites using this framework, it is planned for creating apps with high scalability; websites that grow from thousands to millions of visitors quickly. This framework works straight out of the box and provides all the major functionalities needed to build an app with Python.

LET US TAKE A LOOK AT FLASK ARCHITECTURE AND FUNCTIONALITY

  • Flask is all about simplicity and ease. There are no limitations and the user can implement anything they want it.
  • No database access layer and ORM. Other apps like SQLAlchemy or pure SQL queries do this job without any restrictions.
  • Routing with decorators is really simple; app structure is also totally adjustable.
    Blueprints are like modules for the application. The user can have lots of them suited for any task and construct to their app like a LEGO toy, using the blueprints best suited for this particular task and the extensions are incredibly helpful and are integrated into the framework easily.
  • Web server and debugging tools: Flask comes with in-built web server and multiple debugging tools, including the in-browser, so the user do not even need NGINX or Apache to test and debug the app.
  • Flask appeared as a substitute to Django, as developers chosen to have a micro framework that would allow them using varying components, and neither of previous frameworks allowed alteration of their modules to some extent. Flask is simple and straightforward thus working in it allows an experienced Python developer in creating projects within short timeframes.

THE VERDICT

Flask works like a sandbox for developers, where they can improve their skills and quickly test solutions using different modules and libraries. We prefer using it for testing and working on less-structured objects, while using Django to deliver a solid product, meeting and exceeding customer’s expectations.

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