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登録日: 9月 7, 2020
2 推薦

Badr-Eddine E.

@elbatouriB

 5.0 (11 レビュー)
4.4
4.4
100%
100%
$15 USD / 時間
MOROCCOのフラグ
youssoufia, morocco
$15 USD / 時間
100%
完了したプロジェクト
92%
予算内
92%
期限内
33%
再採用率

Software engineer || SDE @AWS.

Software engineer || AWS SDE Intern. => Programming languages: Java - GoLang - Python - Typescript - Javascript. => Front-end: React - Next - Angular - Tailwind - Chakra UI - Material UI - HTML - CSS - SCSS => Databases: NoSQL( MongoDB - Redis - Elasticsearch ) - SQL - Hibernate - Mongoose - Prisma => Back-end => Spring - JEE - NodeJS - NestJS - ExpressJs. => Microservices => Spring Cloud - Grpc - Kafka => DevOps : Jenkins - Kubernetes - Docker => Cloud Providers : AWS - GCP - Digital ocean => Networking : TCP/UDP, VoIP, WebRTTC, HTTP, RPC, Sockets. My services are: -Building full stack web applications(PWA and SPA included). -Building microservices architecture-based applications. -Building REST APIs and web services. -Building scrapping bots -Building data pipelines -Building Client/Server based application
Freelancer Java Developers Morocco
全て見る Java Developers 、 Morocco

仕事についてBadr-Eddine E.に連絡する

ログインしてチャットで詳細を相談しましょう、

ポートフォリオ

9916748
One of my clients that organizes gaming competitions had an idea where there are pretalks before the matches where players make fun of each other and are hyped about the next game. But the client was a sponsor-based business, so he either used his solution or his sponsor's solution; he needed something like discord that could broadcast live to their Facebook/Instagram/youtube pages and also their application. The application was built using ElectronJS, angular, Typescript, and socket.IO for the front ends and Spring, WebRTC, TCP/UDP, Kafka, Kubernetes, Docker, MongoDB, and Keycloack for the back end. Also, the application was a microservices-based application.
Discord clone.
One of my clients that organizes gaming competitions had an idea where there are pretalks before the matches where players make fun of each other and are hyped about the next game. But the client was a sponsor-based business, so he either used his solution or his sponsor's solution; he needed something like discord that could broadcast live to their Facebook/Instagram/youtube pages and also their application. The application was built using ElectronJS, angular, Typescript, and socket.IO for the front ends and Spring, WebRTC, TCP/UDP, Kafka, Kubernetes, Docker, MongoDB, and Keycloack for the back end. Also, the application was a microservices-based application.
Discord clone.
9916717
A slack clone application whit the same functionalities plugins can be built using either python or javascript. but the dev should always consume the spring boot API for making new functionalities based on existing functionalities the application is microservices-based.
Slack clone, whit angular and spring.
9916701
A Netflix clone with the functionality of streaming videos from the servers dedicated to storage using webRTC for streaming. User and film information is stored in firebase, the business logic layer, and it's built whit spring boot. The application uses spring cloud and Kubernetes to guarantee cloud-native application features. And the application is microservice-based.
Netflix clone using angular,spring boot, firebase and webRTC
A Netflix clone with the functionality of streaming videos from the servers dedicated to storage using webRTC for streaming. User and film information is stored in firebase, the business logic layer, and it's built whit spring boot. The application uses spring cloud and Kubernetes to guarantee cloud-native application features. And the application is microservice-based.
Netflix clone using angular,spring boot, firebase and webRTC
9916696
This application was a microservices-based application since I was forced to use some libraries in python that does both some NLP treatment and also web scraping. This application works as a Search engine that searches e-commerce websites based on the user text input and the configuration for the filter(bestseller, location, etc), when the result is scrapped they should be cached(based on how many times they appear as result. so the search operation will be faster (rather than researching using scrapping again) the caching cluster adapts to the size of its container. Since the application was built using different technologies in order for web services to communicate whit each other and the application to be qualified for a cloud-native application the use of docker and Kubernetes along whit spring cloud was a must, and the application has modern features like infinite scrolling (each time the user reaches the end of page new product will appear), and it has the openID connect.
TechGadget recommendation.
This application was a microservices-based application since I was forced to use some libraries in python that does both some NLP treatment and also web scraping. This application works as a Search engine that searches e-commerce websites based on the user text input and the configuration for the filter(bestseller, location, etc), when the result is scrapped they should be cached(based on how many times they appear as result. so the search operation will be faster (rather than researching using scrapping again) the caching cluster adapts to the size of its container. Since the application was built using different technologies in order for web services to communicate whit each other and the application to be qualified for a cloud-native application the use of docker and Kubernetes along whit spring cloud was a must, and the application has modern features like infinite scrolling (each time the user reaches the end of page new product will appear), and it has the openID connect.
TechGadget recommendation.
This application was a microservices-based application since I was forced to use some libraries in python that does both some NLP treatment and also web scraping. This application works as a Search engine that searches e-commerce websites based on the user text input and the configuration for the filter(bestseller, location, etc), when the result is scrapped they should be cached(based on how many times they appear as result. so the search operation will be faster (rather than researching using scrapping again) the caching cluster adapts to the size of its container. Since the application was built using different technologies in order for web services to communicate whit each other and the application to be qualified for a cloud-native application the use of docker and Kubernetes along whit spring cloud was a must, and the application has modern features like infinite scrolling (each time the user reaches the end of page new product will appear), and it has the openID connect.
TechGadget recommendation.
This application was a microservices-based application since I was forced to use some libraries in python that does both some NLP treatment and also web scraping. This application works as a Search engine that searches e-commerce websites based on the user text input and the configuration for the filter(bestseller, location, etc), when the result is scrapped they should be cached(based on how many times they appear as result. so the search operation will be faster (rather than researching using scrapping again) the caching cluster adapts to the size of its container. Since the application was built using different technologies in order for web services to communicate whit each other and the application to be qualified for a cloud-native application the use of docker and Kubernetes along whit spring cloud was a must, and the application has modern features like infinite scrolling (each time the user reaches the end of page new product will appear), and it has the openID connect.
TechGadget recommendation.
This application was a microservices-based application since I was forced to use some libraries in python that does both some NLP treatment and also web scraping. This application works as a Search engine that searches e-commerce websites based on the user text input and the configuration for the filter(bestseller, location, etc), when the result is scrapped they should be cached(based on how many times they appear as result. so the search operation will be faster (rather than researching using scrapping again) the caching cluster adapts to the size of its container. Since the application was built using different technologies in order for web services to communicate whit each other and the application to be qualified for a cloud-native application the use of docker and Kubernetes along whit spring cloud was a must, and the application has modern features like infinite scrolling (each time the user reaches the end of page new product will appear), and it has the openID connect.
TechGadget recommendation.
This application was a microservices-based application since I was forced to use some libraries in python that does both some NLP treatment and also web scraping. This application works as a Search engine that searches e-commerce websites based on the user text input and the configuration for the filter(bestseller, location, etc), when the result is scrapped they should be cached(based on how many times they appear as result. so the search operation will be faster (rather than researching using scrapping again) the caching cluster adapts to the size of its container. Since the application was built using different technologies in order for web services to communicate whit each other and the application to be qualified for a cloud-native application the use of docker and Kubernetes along whit spring cloud was a must, and the application has modern features like infinite scrolling (each time the user reaches the end of page new product will appear), and it has the openID connect.
TechGadget recommendation.
This application was a microservices-based application since I was forced to use some libraries in python that does both some NLP treatment and also web scraping. This application works as a Search engine that searches e-commerce websites based on the user text input and the configuration for the filter(bestseller, location, etc), when the result is scrapped they should be cached(based on how many times they appear as result. so the search operation will be faster (rather than researching using scrapping again) the caching cluster adapts to the size of its container. Since the application was built using different technologies in order for web services to communicate whit each other and the application to be qualified for a cloud-native application the use of docker and Kubernetes along whit spring cloud was a must, and the application has modern features like infinite scrolling (each time the user reaches the end of page new product will appear), and it has the openID connect.
TechGadget recommendation.
9916626
In this project, I build a pipeline that extracts/formats/analyze/visualizes log data, the log data can be written directly on the same server, and for other servers that are outside the network, a Kafka cluster should be used to communicate data between the server that have spark streaming cluster on. And finally, all the data streamed to spark will be pre-processed in spark, and then spark streaming will forward it to an Elasticsearch cluster then the data will be visualized whit the help of Kibana.
Log analysing pipeline.
In this project, I build a pipeline that extracts/formats/analyze/visualizes log data, the log data can be written directly on the same server, and for other servers that are outside the network, a Kafka cluster should be used to communicate data between the server that have spark streaming cluster on. And finally, all the data streamed to spark will be pre-processed in spark, and then spark streaming will forward it to an Elasticsearch cluster then the data will be visualized whit the help of Kibana.
Log analysing pipeline.
In this project, I build a pipeline that extracts/formats/analyze/visualizes log data, the log data can be written directly on the same server, and for other servers that are outside the network, a Kafka cluster should be used to communicate data between the server that have spark streaming cluster on. And finally, all the data streamed to spark will be pre-processed in spark, and then spark streaming will forward it to an Elasticsearch cluster then the data will be visualized whit the help of Kibana.
Log analysing pipeline.
In this project, I build a pipeline that extracts/formats/analyze/visualizes log data, the log data can be written directly on the same server, and for other servers that are outside the network, a Kafka cluster should be used to communicate data between the server that have spark streaming cluster on. And finally, all the data streamed to spark will be pre-processed in spark, and then spark streaming will forward it to an Elasticsearch cluster then the data will be visualized whit the help of Kibana.
Log analysing pipeline.
9916612
One of my clients asked to provide an application whit the same WhatsApp functionality, but a possibility to add new features easily, so the application should have different front-ends that look the same one using react and one using angular. The backend was built using spring and TCP sockets plus Redis for caching messages to each user. the app architecture was microservices-based. other nonrealtime data ( last time connected etc) are built using KAFKA since there is a possibility that each user data (like last time connected) will be consumed by different clients.
Whatsapp clone.
One of my clients asked to provide an application whit the same WhatsApp functionality, but a possibility to add new features easily, so the application should have different front-ends that look the same one using react and one using angular. The backend was built using spring and TCP sockets plus Redis for caching messages to each user. the app architecture was microservices-based. other nonrealtime data ( last time connected etc) are built using KAFKA since there is a possibility that each user data (like last time connected) will be consumed by different clients.
Whatsapp clone.
9916748
One of my clients that organizes gaming competitions had an idea where there are pretalks before the matches where players make fun of each other and are hyped about the next game. But the client was a sponsor-based business, so he either used his solution or his sponsor's solution; he needed something like discord that could broadcast live to their Facebook/Instagram/youtube pages and also their application. The application was built using ElectronJS, angular, Typescript, and socket.IO for the front ends and Spring, WebRTC, TCP/UDP, Kafka, Kubernetes, Docker, MongoDB, and Keycloack for the back end. Also, the application was a microservices-based application.
Discord clone.
One of my clients that organizes gaming competitions had an idea where there are pretalks before the matches where players make fun of each other and are hyped about the next game. But the client was a sponsor-based business, so he either used his solution or his sponsor's solution; he needed something like discord that could broadcast live to their Facebook/Instagram/youtube pages and also their application. The application was built using ElectronJS, angular, Typescript, and socket.IO for the front ends and Spring, WebRTC, TCP/UDP, Kafka, Kubernetes, Docker, MongoDB, and Keycloack for the back end. Also, the application was a microservices-based application.
Discord clone.
9916717
A slack clone application whit the same functionalities plugins can be built using either python or javascript. but the dev should always consume the spring boot API for making new functionalities based on existing functionalities the application is microservices-based.
Slack clone, whit angular and spring.
9916701
A Netflix clone with the functionality of streaming videos from the servers dedicated to storage using webRTC for streaming. User and film information is stored in firebase, the business logic layer, and it's built whit spring boot. The application uses spring cloud and Kubernetes to guarantee cloud-native application features. And the application is microservice-based.
Netflix clone using angular,spring boot, firebase and webRTC
A Netflix clone with the functionality of streaming videos from the servers dedicated to storage using webRTC for streaming. User and film information is stored in firebase, the business logic layer, and it's built whit spring boot. The application uses spring cloud and Kubernetes to guarantee cloud-native application features. And the application is microservice-based.
Netflix clone using angular,spring boot, firebase and webRTC
9916696
This application was a microservices-based application since I was forced to use some libraries in python that does both some NLP treatment and also web scraping. This application works as a Search engine that searches e-commerce websites based on the user text input and the configuration for the filter(bestseller, location, etc), when the result is scrapped they should be cached(based on how many times they appear as result. so the search operation will be faster (rather than researching using scrapping again) the caching cluster adapts to the size of its container. Since the application was built using different technologies in order for web services to communicate whit each other and the application to be qualified for a cloud-native application the use of docker and Kubernetes along whit spring cloud was a must, and the application has modern features like infinite scrolling (each time the user reaches the end of page new product will appear), and it has the openID connect.
TechGadget recommendation.
This application was a microservices-based application since I was forced to use some libraries in python that does both some NLP treatment and also web scraping. This application works as a Search engine that searches e-commerce websites based on the user text input and the configuration for the filter(bestseller, location, etc), when the result is scrapped they should be cached(based on how many times they appear as result. so the search operation will be faster (rather than researching using scrapping again) the caching cluster adapts to the size of its container. Since the application was built using different technologies in order for web services to communicate whit each other and the application to be qualified for a cloud-native application the use of docker and Kubernetes along whit spring cloud was a must, and the application has modern features like infinite scrolling (each time the user reaches the end of page new product will appear), and it has the openID connect.
TechGadget recommendation.
This application was a microservices-based application since I was forced to use some libraries in python that does both some NLP treatment and also web scraping. This application works as a Search engine that searches e-commerce websites based on the user text input and the configuration for the filter(bestseller, location, etc), when the result is scrapped they should be cached(based on how many times they appear as result. so the search operation will be faster (rather than researching using scrapping again) the caching cluster adapts to the size of its container. Since the application was built using different technologies in order for web services to communicate whit each other and the application to be qualified for a cloud-native application the use of docker and Kubernetes along whit spring cloud was a must, and the application has modern features like infinite scrolling (each time the user reaches the end of page new product will appear), and it has the openID connect.
TechGadget recommendation.
This application was a microservices-based application since I was forced to use some libraries in python that does both some NLP treatment and also web scraping. This application works as a Search engine that searches e-commerce websites based on the user text input and the configuration for the filter(bestseller, location, etc), when the result is scrapped they should be cached(based on how many times they appear as result. so the search operation will be faster (rather than researching using scrapping again) the caching cluster adapts to the size of its container. Since the application was built using different technologies in order for web services to communicate whit each other and the application to be qualified for a cloud-native application the use of docker and Kubernetes along whit spring cloud was a must, and the application has modern features like infinite scrolling (each time the user reaches the end of page new product will appear), and it has the openID connect.
TechGadget recommendation.
This application was a microservices-based application since I was forced to use some libraries in python that does both some NLP treatment and also web scraping. This application works as a Search engine that searches e-commerce websites based on the user text input and the configuration for the filter(bestseller, location, etc), when the result is scrapped they should be cached(based on how many times they appear as result. so the search operation will be faster (rather than researching using scrapping again) the caching cluster adapts to the size of its container. Since the application was built using different technologies in order for web services to communicate whit each other and the application to be qualified for a cloud-native application the use of docker and Kubernetes along whit spring cloud was a must, and the application has modern features like infinite scrolling (each time the user reaches the end of page new product will appear), and it has the openID connect.
TechGadget recommendation.
This application was a microservices-based application since I was forced to use some libraries in python that does both some NLP treatment and also web scraping. This application works as a Search engine that searches e-commerce websites based on the user text input and the configuration for the filter(bestseller, location, etc), when the result is scrapped they should be cached(based on how many times they appear as result. so the search operation will be faster (rather than researching using scrapping again) the caching cluster adapts to the size of its container. Since the application was built using different technologies in order for web services to communicate whit each other and the application to be qualified for a cloud-native application the use of docker and Kubernetes along whit spring cloud was a must, and the application has modern features like infinite scrolling (each time the user reaches the end of page new product will appear), and it has the openID connect.
TechGadget recommendation.
This application was a microservices-based application since I was forced to use some libraries in python that does both some NLP treatment and also web scraping. This application works as a Search engine that searches e-commerce websites based on the user text input and the configuration for the filter(bestseller, location, etc), when the result is scrapped they should be cached(based on how many times they appear as result. so the search operation will be faster (rather than researching using scrapping again) the caching cluster adapts to the size of its container. Since the application was built using different technologies in order for web services to communicate whit each other and the application to be qualified for a cloud-native application the use of docker and Kubernetes along whit spring cloud was a must, and the application has modern features like infinite scrolling (each time the user reaches the end of page new product will appear), and it has the openID connect.
TechGadget recommendation.
9916626
In this project, I build a pipeline that extracts/formats/analyze/visualizes log data, the log data can be written directly on the same server, and for other servers that are outside the network, a Kafka cluster should be used to communicate data between the server that have spark streaming cluster on. And finally, all the data streamed to spark will be pre-processed in spark, and then spark streaming will forward it to an Elasticsearch cluster then the data will be visualized whit the help of Kibana.
Log analysing pipeline.
In this project, I build a pipeline that extracts/formats/analyze/visualizes log data, the log data can be written directly on the same server, and for other servers that are outside the network, a Kafka cluster should be used to communicate data between the server that have spark streaming cluster on. And finally, all the data streamed to spark will be pre-processed in spark, and then spark streaming will forward it to an Elasticsearch cluster then the data will be visualized whit the help of Kibana.
Log analysing pipeline.
In this project, I build a pipeline that extracts/formats/analyze/visualizes log data, the log data can be written directly on the same server, and for other servers that are outside the network, a Kafka cluster should be used to communicate data between the server that have spark streaming cluster on. And finally, all the data streamed to spark will be pre-processed in spark, and then spark streaming will forward it to an Elasticsearch cluster then the data will be visualized whit the help of Kibana.
Log analysing pipeline.
In this project, I build a pipeline that extracts/formats/analyze/visualizes log data, the log data can be written directly on the same server, and for other servers that are outside the network, a Kafka cluster should be used to communicate data between the server that have spark streaming cluster on. And finally, all the data streamed to spark will be pre-processed in spark, and then spark streaming will forward it to an Elasticsearch cluster then the data will be visualized whit the help of Kibana.
Log analysing pipeline.
9916612
One of my clients asked to provide an application whit the same WhatsApp functionality, but a possibility to add new features easily, so the application should have different front-ends that look the same one using react and one using angular. The backend was built using spring and TCP sockets plus Redis for caching messages to each user. the app architecture was microservices-based. other nonrealtime data ( last time connected etc) are built using KAFKA since there is a possibility that each user data (like last time connected) will be consumed by different clients.
Whatsapp clone.
One of my clients asked to provide an application whit the same WhatsApp functionality, but a possibility to add new features easily, so the application should have different front-ends that look the same one using react and one using angular. The backend was built using spring and TCP sockets plus Redis for caching messages to each user. the app architecture was microservices-based. other nonrealtime data ( last time connected etc) are built using KAFKA since there is a possibility that each user data (like last time connected) will be consumed by different clients.
Whatsapp clone.

レビュー

変更を保存しました
1 - 5 / 11 レビュー表示中
 レビューを絞り込む：
5.0
$800.00 USD
Full stack MERN Stack application conception, devlopment, securing and deployment: Express.js, Node.js, Nginx, Socket.io, React, material UI, docker.
An amazing person with a brilliant intellect. You want to build your complete stack application using any Javascript stack. or perhaps Java, Spring Boot, or Python? You request it, and he will deliver it in any possible technology. He delivered the finest possible outcomes and took an initiative to improve the platform. Technologies used in the project: React. MongoDB. Express. Node.js. Socket.io. Docker, and more. This individual is trustworthy for your project; I can vouch for him.
JavaScript
Node.js
Express JS
Backend Development
+1 もっと
ユーザーアバター
のフラグ Adnan A.
@adnanahs
•
2年前
5.0
$210.00 CAD
Project for Badr-Eddine E.
Badr again did an amazing job for us. Whenever we have a project that no-one else can fix, Badr is able to resolve our issue for us. He's our "go-to" guy
Java
JavaScript
.NET
Software Architecture
+1 もっと
ユーザーアバター
のフラグ Jerry H.
@jhobbs2
•
2年前
5.0
$50.00 USD
Project for Badr-Eddine E. -- 2
Badr is amazing! Will no longer count how much time did he help me! So professional
PHP
Java
JavaScript
Python
Software Architecture
+1 もっと
A
Closed User
@ayariyadh9
•
2年前
5.0
€80.00 EUR
Paraswap API Python
I enjoyed working with him very much, I loved his work. Great Job.
Python
Cryptocurrency
L
のフラグ Lukas S.
@lukasstaudter
•
2年前
5.0
$150.00 USD
Senior Java Expert
Badr is a fast turn-around skillful dev and I enjoyed working with him.
Java
JavaScript
OAuth
ユーザーアバター
のフラグ Tony L.
@tonylew
•
2年前

経験

Software development engineer

Amazon web services
2月 2023 - 現在
- Working on a distributed system migration service @AWS.

Software engineer

OCP maintenance solutions
6月 2022 - 9月 2022 (3 , 1 )
Full stack devlopper

仕事についてBadr-Eddine E.に連絡する

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認証済み支払方法
電話番号認証済み
メール認証済み
Facebook接続済み

認定

preferredfreelancer-1.png Preferred Freelancer Program SLA 1 84%

トップスキル

Java 6
JavaScript 6
Software Architecture 4
PostgreSQL 1
RESTful API 1

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