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9 certifications cloud basées sur les rôles pour les architectes de solutions en 2024

9 certifications cloud basées sur les rôles pour les architectes de solutions en 2024

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En 2024, les architectes de solutions pourront obtenir 9 certifications cloud basées sur les rôles pour développer leurs compétences et leurs connaissances dans le domaine.

Êtes-vous enthousiaste à devenir un architecte de solutions Cloud et à prendre votre carrière à de nouveaux sommets ?

Without further ado, let’s dive into the world of cloud certifications. 

Êtes-vous enthousiaste à devenir un architecte de solutions cloud et à porter votre carrière à de nouveaux sommets? Le cloud computing transforme la façon dont les organisations utilisent l’infrastructure numérique, ce qui en fait une compétence cruciale à maîtriser. Si vous êtes intéressé par le potentiel illimité de la technologie cloud, alors ce guide est fait pour vous. 

Dans ce guide, vous apprendrez les 9 certifications basées sur les rôles les plus importantes du cloud, spécialement conçues pour les architectes de solutions. Alors que nous nous dirigeons vers 2024, nous sommes à l’aube d’une ère passionnante de la technologie cloud. Ensemble, nous explorerons neuf certifications primordiales offertes par des leaders du secteur et des organisations respectées, chacune étant une pierre angulaire sur votre chemin vers une certification professionnelle en cloud. 

Sans plus tarder, plongeons dans le monde des certifications cloud. 

Les certifications cloud sont un excellent moyen de se démarquer dans un marché saturé et de se positionner comme un expert dans le domaine des technologies cloud. En tant qu’architecte de solutions cloud, vous serez en mesure d’utiliser les données pour aider les entreprises à développer des solutions innovantes et à prendre des décisions informées. Les certifications cloud vous permettront d’acquérir les compétences nécessaires pour réussir dans ce domaine. 

Les certifications cloud sont généralement divisées en trois catégories : les certifications de base, les certifications avancées et les certifications spécialisées. Les certifications de base sont conçues pour les débutants et offrent une introduction aux technologies cloud. Les certifications avancées sont conçues pour les professionnels expérimentés et offrent une solide compréhension des technologies cloud. Les certifications spécialisées sont conçues pour ceux qui souhaitent se spécialiser dans un domaine particulier des technologies cloud. 

Les certifications cloud peuvent être obtenues auprès de fournisseurs de services cloud tels que Amazon Web Services (AWS), Microsoft Azure et Google Cloud Platform (GCP). Chaque fournisseur propose une gamme complète de certifications qui couvrent tous les aspects des technologies cloud. Ces certifications sont conçues pour aider les professionnels à acquérir les compétences nécessaires pour gérer et développer des applications sur leurs plateformes respectives. 

Les certifications cloud peuvent également être obtenues auprès d’organisations tierces telles que CompTIA et Linux Foundation. Ces organisations proposent des certifications qui couvrent un large éventail de technologies cloud et qui sont reconnues par l’industrie. Ces certifications sont conçues pour aider les professionnels à développer leurs compétences en matière de gestion et de développement d’applications sur différentes plateformes cloud. 

Enfin

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Guide détaillé avec exemples de code pour l'entraînement personnalisé de grands modèles linguistiques

Guide détaillé avec exemples de code pour l’entraînement personnalisé de grands modèles linguistiques

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Vous souhaitez entraîner des modèles linguistiques complexes ? Ce guide vous fournira des exemples de code et des instructions détaillées pour vous aider à atteindre vos objectifs.

H2: Dans les dernières années, les grands modèles linguistiques (LLMs) tels que GPT-4 ont suscité un grand intérêt en raison de leurs incroyables capacités en compréhension et en génération du langage naturel. Cependant, pour adapter un LLM à des tâches ou des domaines spécifiques, une formation personnalisée est nécessaire. Cet article propose un guide détaillé et étape par étape sur la formation personnalisée des LLMs, accompagné d’exemples et d’extraits de code. Prérequis

• A GPU-enabled machine with at least 8GB of RAM

• An understanding of basic ML concepts

• Familiarity with Python and TensorFlow

• Access to a large dataset

Ces dernières années, les grands modèles linguistiques (LLMs) tels que GPT-4 ont suscité un intérêt considérable en raison de leurs incroyables capacités en compréhension et en génération du langage naturel. Cependant, pour adapter un LLM à des tâches ou des domaines spécifiques, une formation personnalisée est nécessaire. Cet article propose un guide détaillé étape par étape sur la formation personnalisée des LLMs, accompagné d’exemples et d’extraits de code.

Prérequis

Avant de plonger, assurez-vous d’avoir :

• Une machine dotée d’une carte graphique et d’au moins 8 Go de RAM

• Une compréhension des concepts de base d’apprentissage machine

• De la familiarité avec Python et TensorFlow

• Un accès à une grande base de données

Mise en œuvre

Une fois les prérequis remplis, vous êtes prêt à commencer à former votre modèle. La première étape consiste à préparer votre base de données. Vous devrez peut-être nettoyer et normaliser vos données avant de les charger dans votre modèle. Une fois que vos données sont prêtes, vous pouvez les charger dans votre modèle. Vous pouvez le faire en utilisant TensorFlow ou un autre framework de deep learning. Une fois que vos données sont chargées, vous pouvez commencer à entraîner votre modèle. Vous pouvez le faire en utilisant des algorithmes d’apprentissage supervisé ou non supervisé. Lorsque vous entraînez votre modèle, vous devrez définir des paramètres tels que le nombre d’itérations, le taux d’apprentissage et le nombre de couches cachées. Vous devrez également définir des métriques pour mesurer la performance de votre modèle.

Une fois que votre modèle est entraîné, vous pouvez le tester sur des données réelles pour voir comment il se comporte. Vous pouvez également effectuer une validation croisée pour vérifier si votre modèle est capable de généraliser ses résultats sur des données différentes. Une fois que vous êtes satisfait des performances de votre modèle, vous pouvez le déployer pour l’utiliser dans un environnement réel. Vous pouvez le déployer sur un serveur ou un cloud public tel que Google Cloud Platform ou Amazon Web Services. Une fois déployé, votre modèle sera prêt à être utilisé par les utilisateurs finaux.

Enfin, vous devrez peut-être maintenir et mettre à jour votre modèle au fil du temps. Vous devrez peut-être ajouter de nouvelles données à votre base de données ou ajuster les paramètres de votre modèle pour améliorer ses performances. Vous devrez également surveiller les performances de votre modèle pour vous assurer qu’il fonctionne correctement et qu’il ne se dégrade pas avec le temps. Enfin, vous devrez peut-être effectuer une analyse des performances pour comprendre comment votre modèle est utilisé et pourquoi il fonctionne bien ou mal.

En résumé, la

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Examine the Impact of Emptiness

Google Cloud Platform: Revolutionary Discovery

Examine the Impact of Emptiness

Google Cloud Platform: A Revolutionary Discovery

As a scientist, I am always looking for new and innovative ways to make discoveries and advance my research. Recently, I have made a revolutionary discovery that has the potential to revolutionize the way we conduct research and analyze data. This discovery is Google Cloud Platform.

Google Cloud Platform is a suite of cloud computing services that runs on the same infrastructure that Google uses internally for its end-user products, such as Google Search and YouTube. It provides a range of services including computing, storage, networking, big data, machine learning, and more. With Google Cloud Platform, researchers can access powerful computing resources without having to purchase and maintain their own hardware. This makes it much easier and more cost-effective to conduct research, analyze data, and develop new applications.

The power of Google Cloud Platform lies in its scalability. Researchers can easily scale up their computing resources as needed, without having to invest in additional hardware. This makes it ideal for large-scale research projects that require a lot of computing power. Additionally, Google Cloud Platform provides a wide range of tools and services that make it easy to manage and analyze data. This includes BigQuery, which allows researchers to query large datasets quickly and easily, as well as tools for machine learning and artificial intelligence.

In conclusion, Google Cloud Platform is a revolutionary discovery that has the potential to revolutionize the way we conduct research and analyze data. With its scalability and range of tools and services, it makes it much easier and more cost-effective to conduct research and develop new applications. I am excited to see how this discovery will continue to shape the future of research and data analysis.

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Cloud Key Management Services Use Cases

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Today, the cloud environment has been chosen by many business solutions as the major hosting environment for their applications. They can either choose Software-as-a-service (SaaS), Platform-as-a-service (PaaS), or Infrastructure-as-a-service (IaaS) different solution types to build up solutions to meet business requirements. However, storing business data in the Cloud environment will have a great challenge in exposing business data to the public. As the concerns data security issues, every Cloud platform vendor provides a different solution for data security. Understanding the similarity and differences in those solutions will help the business clients choose the proper solution for the business applications.  

This article will discuss the primary solution use cases and major differences in secret key management among the Microsoft Azure, Amazon AWS, and Google Cloud Platform for managing secret keys, certificates, and data encryptions.  Although a platform could provide a similar solution or indirect solution for a specific use case, it will still be compared as a difference as long as it is not a commonly used use case.

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Data Analysis Using Google Cloud Data Studio

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Introduction

Google Cloud Data Studio is a tool for transforming data into useful reports and data dashboards. As of now, Google Data Studio has 22 inbuilt Google Connectors and 571 different Partner connectors which help in connecting data from BigQuery, Google Ads, Google Sheets, Cloud Spanner, Facebook Ads Data, Adobe Analytics, and many more. 

Once the data is imported, reports and dashboards can be created by a simple drag and drop and using various filter options. Google Cloud Data Studio is out of the Google Cloud Platform, which is why it is completely free. 

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API Security Weekly: Issue 162

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This week, we have details of compromised Google Cloud accounts being used to mine cryptocurrency (mainly with weak or no passwords on API connections), there’s an article on how GraphQL can be used as an API gateway (including security controls), a very comprehensive guide to all things relating to API security, and a new API security training course from AppSecEngineer.

Vulnerability: Compromised Google Cloud Accounts Used to Mine Cryptocurrency

The main story this week comes from HackerNews and describes how attackers are able to exploit improperly secured Google Cloud Platform (GCP) tenants. The impact on affected users included compromising their cloud resources, like uploading cryptocurrency mining software, and ransomware and phishing attacks.

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Exciting New Tools For Designers, April 2022

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Bored with the same old design tools? There are plenty of new toys to experiment with, from fun divots to functional design tools that could become your new go-to’s.

Here’s what is new for designers this month…

Kosmo

Kosmo is a new project management and invoicing system designed just for freelancers. Designers and developers will love it because the interface is sleek and modern. The tool lets you send invoices, track time, manage projects, send proposals and contracts, and manage billing. You can customize everything from your brand to colors so that your invoices reflect your business style. The platform has a free option as well, making it easy to have the tools you need to run your business. (Plus, there’s a very affordable premium plan if you want more features.)

STUDIO

STUDIO lets designers layout and publish responsive websites, including the ability to connect to backend data, all with a low learning-curve GUI and no coding knowledge prerequisites. You can publish to a free URL with free hosting on the cloud. The free version also includes forms. STUDIO also has premium plans if you like the tool for websites of all sizes and bandwidth needs.

NFT.js

NFT.JS allows you to deploy an ERC721 contract that can perform all the required functions without writing a single line of code. Interact with the contract by calling functions and sending transactions to the contract with a couple of lines of NFT.JS. Provide the input file into the metadata object, and NFT.JS uploads all the files provided in the metadata to IPFS as well as uploads the metadata.json file to IPFS and mints the NFT.

Color Morph

Color Morph is a fun little tool to help you generate mesh gradients in SVG format, or generate CSS, that you can snag and use in projects. The patterns are trendy and fun to use.

Scripts Organizer

Scripts Organizer is an advanced code editor for WordPress. This premium tool helps you make workflow scripts work for you with scheduling, advanced functionality, live previews, safe mode, SCSS partials, code injections, import and export, and more.

Texture

Texture is a fun web project that creates generative art that you can use for backgrounds or pretty much anything else. Preview the textures, pull the JavaScript or CSS or even edit and continue to play with them on CodePen.

Avvvatars

Avvvatars are a set of unique placeholder avatars that are free. The tool is easy to use, includes 40 colors, is accessible and lightweight, comes with 60 shapes, and is customizable. You can grab it on GitHub or as a Figma file.

Epic Ruler

Epic Ruler is a premium design utility tool that measures distance, dimensions, position, pick colors, test contrast, and align on-screen elements anywhere on your screen. You can also create alignments, and it comes with a great color picker that helps you pinpoint hues down to the pixel.

Jotform Apps

Jotform Apps is a new set of app tools from the company you may know for form-building tools. The free no-code app builder lets you add forms, links, widgets, and branding to one fully customized app that can be downloaded onto any smartphone, tablet, or computer. Get started with a template to jumpstart projects.

Spruce

Spruce is an open-source, lightweight CSS design system that’s built on Sass. The tool, which is in beta, is designed to help you start with a solid foundation for projects. It includes structure and code, typography, tables, and buttons.

Yaade

Yaade is an open-source, self-hosted, collaborative API development environment. It’s made for those who want self-hosting in security – if you don’t know the password, there’s no way in! You can import OpenAPI v3 files, there’s data import and export, and a dark mode default.

Agnostic UI

Agnostic UI is one stylesheet that works with multiple frameworks. The user interface components work in React, Vue 3, Svelte, and Angular. It includes semantic and accessible HTML with unprocessed CSS so you can code on the platform to get ahead of web standards.

Turbulent Buttons

Turbulent Buttons is a button-and-hover animation that goes the extra mile. This is a fun button and animation that is anything but boring.

Never Install

Never Install is a cloud platform that allows you to run any application from the browser without installing it on your device. It is an alternative to traditional desktop application usage and enables people to stream applications over the web. The developers are working on a next-generation cloud platform to bring any GUI application regardless of the operating system, device, and system requirements to the browser. The tool is free to use.

Photoinsight

Photoinsight is a tool (free and paid) to manage digital assets, including photos, videos, and 3D elements, in one place. You can search, filter, and group views based on your preferences. Plus, there are tools such as batch renaming and statistics and trends to help you manage files.

Formspector

Formspector answers that nagging question – are my forms working? Use the tool to set automated tests that will notify you if anything stops working, from newsletter signups to contact forms to support requests.

Wikifox.js

Wikifox.js is a lightweight, powerful, and restful JavaScript library that connects to the Wikipedia API. This library can be used to get content from Wikipedia.

Lightning Builder

Lightning Builder is a free browser-based drag and drop website builder. You can design a mockup in minutes so that you can show developers or writers what you are thinking when you are planning a new design or website project. Use it to ease communication for teams with new project builds.

Waaard

Waaard is a tiny tool with a lot of practical applications. Use it to create a protected link or file that only people you want to access it can open. With plenty of verification methods, you’ll know your links are safe.

Doodle Ipsum

Doodle Ipsum is the lorem ipsum of illustrations. Customize doodles, grab the code, and use them on web prototypes, landing pages, or no-code tools.

FF Din Stencil

FF Din Stencil is a fun display typeface for just the right application with a distinct style. It comes in a variety of weights and styles and is part of a greater FF Din family.

Fontanella

Fontanella is a typeface designed by Coto Mendoza, which emerged from calligraphy and manual drawing exploring the skeleton and classic proportions of Roman capital letters. It has an easy-to-read style with interesting sans serif characters.

Sarlotte

Sarlotte is a statuesque typeface with long tails, swashes, and flourishes. From the type designer: It seduces your eyes with its curves yet still manages to maintain its classy serenity, it’s perfect for branding, logos, invitations, and more.

Source

The post Exciting New Tools For Designers, April 2022 first appeared on Webdesigner Depot.

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10 AWS Services That Use SQL

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Amazon Web Services (AWS) is the biggest cloud platform in the world, with over 200 features. In this article, we break down 10 AWS services that support at least some SQL syntax, talk about their use cases, and give examples of how to write queries.

Service Description SQL Support Use Case
RDS Postgres, MySQL, etc. Full Small-medium web apps
Aurora Serverless databases Full Serverless apps
Redshift Data warehouse Full OLAP, Petabytes of data, analytics
DynamoDB NoSQL database Some – PartiSQL Ecommerce, building fast
Keyspaces Managed Cassandra (key value) Some – CQL Messaging
Neptune Graph database Some – openCypher Social networks
Timestream Time series database Partial IOT, Logging
Quantum Ledger Cryptographically verified transactions Some – PartiSQL Finance
Athena Ad-hoc queries on S3 Some – CTAS Historical data
Babelfish MSFT SQL Server on Aurora Full .NET

The table above shows how SQL support varies between the services. A graph database cannot be queried in the same way as a classic relational database, and various subsets of SQL, like PartiQL, have emerged to fit these models. In fact, even within standard SQL, there are many SQL dialects for different companies like Oracle and Microsoft.

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Next-Gen Data Pipes With Spark, Kafka, and K8s: Part 2

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Introduction 

In our previous article, we discussed two emerging options for building new-age data pipes using stream processing. One option leverages Apache Spark for stream processing and the other makes use of a Kafka-Kubernetes combination of any cloud platform for distributed computing. The first approach is reasonably popular, and a lot has already been written about it. However, the second option is catching up in the market as that is far less complex to set up and easier to maintain. Also, data-on-the-cloud is a natural outcome of the technological drivers that are prevailing in the market. So, this article will focus on the second approach to see how it can be implemented in different cloud environments.

Kafka-K8s Streaming Approach in Cloud

In this approach, if the number of partitions in the Kafka topic matches with the replication factor of the pods in the Kubernetes cluster, then the pods together form a consumer group and ensure all the advantages of distributed computing. It can be well depicted through the below equation:

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Redshift vs. Snowflake: The Definitive Guide

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What Is Snowflake?

At its core Snowflake is a data platform. It’s not specifically based on any cloud service which means it can run any of the major cloud providers like Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP). As a SaaS (Software-as-a-Service) solution, it helps organizations consolidate data from different sources into a central repository for analytics purposes to help solve Business Intelligence use cases.

Once data is loaded into Snowflake, data scientists, engineers, and analysts can use business logic to transform and model that data in a way that makes sense for their company. With Snowflake users can easily query data using simple SQL. This information is then used to power reports and dashboards so business stakeholders can make key decisions based on relevant insights.

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