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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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How To Use Cluster Mesh for Multi-Region Kubernetes Pod Communication

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Thanks to services provided by AWS, GCP, and Azure it’s become relatively easy to develop applications that span multiple regions. This is great because slow apps kill businesses. There is one common problem with these applications: they are not supported by multi-region database architecture.

In this blog, I will provide a solution for the problem of getting Kubernetes pods to talk to each other in multi-region deployments.

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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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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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Execute Spark Applications on Databricks Using the REST API

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Introduction

While many of us are habituated to executing Spark applications using the ‘spark-submit’ command, with the popularity of Databricks, this seemingly easy activity is getting relegated to the background. Databricks has made it very easy to provision Spark-enabled VMs on the two most popular cloud platforms, namely AWS and Azure. A couple of weeks ago, Databricks announced their availability on GCP as well. The beauty of the Databricks platform is that they have made it very easy to become a part of their platform. While Spark application development will continue to have its challenges – depending on the problem being addressed – the Databricks platform has taken out the pain of having to establish and manage your own Spark cluster.

Using Databricks

Once registered on the platform, the Databricks platform allows us to define a cluster of one or more VMs, with configurable RAM and executor specifications. We can also define a cluster that can launch a minimum number of VMs at startup and then scale to a maximum number of VMs as required. After defining the cluster, we have to define jobs and notebooks. Notebooks contain the actual code executed on the cluster. We need to assign notebooks to jobs as the Databricks cluster executes jobs (and not Notebooks). Databricks also allows us to setup the cluster such that it can download additional JARs and/or Python packages during cluster startup. We can also upload and install our own packages (I used a Python wheel).

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Alexa and Kubernetes: Deploying the Alexa Skill on Google Kubernetes Engine (IX)

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Now, we have everything prepared and ready to go to a Kubernetes Cluster in a cloud provider. It is a fact that creating a cluster in any cloud provider manually is a difficult task. Moreover, if we want to automate this deployment, we need something that helps us in this tedious task. In this article, we will see how to create a Kubernetes Cluster and all of its required objects, deploying our Alexa Skill with Terraform using Google Kubernetes Engine.

Pre-Requisites

Here, you have the technologies used in this project:

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API Security Weekly: Issue #105

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This week, we take a look at API vulnerabilities in HashiCorp Vault, Azure App Services, and more. There is also an introductory video on finding information disclosure in JSON and XML API responses, and another cheat sheet and a webinar on OWASP API Security Top 10.

Vulnerability: HashiCorp Vault

Felix Wilhelm from Google’s Project Zero has written a very detailed write-up on an authentication bypass he found in the Amazon Web Services (AWS) and Google Cloud Platform (GCP) integration of HashiCorp Vault. As a central storage of credentials, Vault makes an attractive target for attackers, and therefore a vulnerability in it is also very bad news. Looking for the silver linings, this attack was definitely quite advanced, and thus not easily exploitable.

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Establish Connection Between Google Cloud Platform and MuleSoft Anypoint VPN Using BGP Routing (IPSec Tunneling)

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In my last article, we have deep dive into the architecture of Anypoint VPC, VPN (IPSec Tunneling and VPC Peering). We are going to see how we can establish the connection between Anypoint platform and GCP using the VPN IPSec tunneling.

Prerequisite

  • Anypoint Platform account with VPN
  • Set up Anypoint VPC.
  • GCP Account for creating VPN.

Lets understand how we can create or establish the connection between the Anypoint Cloudhub and GCP.

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Using Terraform for Managing Infrastructure

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What is Terraform?

Terraform is a tool that is used for building, changing and versioning infrastructure safely and effectively. Using the configuration file you describe to Terraform what components are needed. Terraform then goes and generates an execution plan describing what the desired state should be. And then it goes and executes and builds it. Terraform manages all this through a state file. Now there are two flavors of Terraform:

  • An open-source version
  • An enterprise version

Terraform supports a wide variety of cloud and infrastructure platforms. This includes AWS, OpenStack, Azure, GCP, Kubernetes and much more.

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