Vous visez à exceller dans le cloud computing. Quelles sont les compétences qui vous distingueront à l’avenir ?

First, understand the differences between Cloud and a traditional data center. Get a solid footing on any of the cloud provider (AWS / Google / Azure / other) and get to fully understand their offerings (Infrastructure, Software and Platform as services) and the premises with which they have built the cloud data centers. Check out their documentations on well architected framework for developing/deploying apps into Cloud. Once you are able to explain about cloud thoroughly to anyone (ex. 5th grader) consider yourself a person with strong basic understanding of cloud.

Experience building on any Cloud. Broad experience of many solutions. Deep experience of specific solutions. Good at hot topics: Generative AI, Security.

Excelling in cloud computing demands a blend of technical and soft skills. Mastering cloud platforms (AWS, Azure, GCP), containerization (Docker, Kubernetes), and CI/CD tools is essential. Understanding cybersecurity, automation, and infrastructure-as-code (Terraform, Ansible) enhances operational efficiency. Proficiency in scripting languages (Python, Java) and a solid grasp of DevOps principles are vital. Additionally, keeping abreast of emerging technologies like AI/ML and serverless computing is crucial. Strong problem-solving abilities, continuous learning, and effective communication skills will set you apart, ensuring you stay ahead in the evolving cloud landscape.

Mastering DevOps practices is crucial in cloud computing. Focus on learning tools and methodologies that support DevOps, such as Infrastructure as Code (IaC), to streamline development workflows and improve deployment strategies. Familiarity with CI/CD (Continuous Integration/Continuous Deployment) pipelines will ensure smooth operations in the cloud. By emphasizing collaboration and automation, you can enhance your team's efficiency and adaptability in the evolving cloud environment. This blend of skills will make you a valuable asset in any cloud-based project.

To thrive in cloud computing and DevOps, mastering automation tools like Terraform for infrastructure and CI/CD pipelines is crucial. Strong Git skills for version control and collaborative development, coupled with adeptness in cloud platforms such as Azure, ensure efficient resource management and scalability. Integrating robust security measures into CI/CD pipelines enhances deployment reliability. Utilizing tools like Azure DevOps. Strong problem-solving abilities, continuous learning, and soft skills like communication and adaptability round out a profile that aligns technical solutions with business objectives, positioning you as a leader in cloud computing and DevOps innovation.

One of the the reasons Cloud is so popular is its tools for automated deployment (as many times as you want in a day) which is called CI/CD (Continuous Integration / Continuous Deployment). One such tool that is Terraform that enables one to create entire infrastructure in a touch of a button (of course with some coding). Deploying Terraform with Jenkins / CircleCI (CI/CD tools) will give you an edge with automation to the core. Learn these tools and get cracking on creating/maintaining Infrastructure in cloud.

To stand out in cloud security, focus on being proactive about threat detection and response. Learn to use real-time monitoring tools and SIEM systems, and have solid incident response plans ready. Use automation and AI to quickly spot and respond to threats. Make sure your practices comply with industry standards and adopt a zero-trust approach to secure access. Promote a security-first mindset by regularly training and updating your team. Stay current with security best practices by following industry news, joining professional groups, and earning certifications like AWS Certified Security, Azure Security Engineer, or Google Cloud Security Engineer. These steps will help you build a strong foundation and keep your skills up to date.

Security is one of pillars of the Well-Architected framework. Without water tight security, the infrastructure and data would be as high risk from cyber criminals. Get yourself a good lessons on IAM and usage of encryption keys as first step to secure the infra and data. Then comes setting up security between different services/networks of your eco system. This is a very niche area many are not available. Capitalize on this and become an expert in Cloud security.

Alright, let’s talk about efficient data practices - the low hanging fruit that’s ready to be picked. Instead of changing your entire toolkit, why not reach for the obvious wins? Mastering data doesn’t mean you need to dive into every new trend! Focus on reliability, stability, and the fundamentals. For instance, I optimized a project by refining our ETL processes on Databricks, avoiding the need for a new platform. This saved time, cut costs, and boosted efficiency. Data Actions I recommend: 1. Auditing Existing Processes: Identify inefficiencies. 2. Pinpointing Bottlenecks: Identify slow processes. 3. Optimising: Remove redundancies. 4. Implementing Data Quality Checks: Ensure accurate and reliable data.

Data is the new Gold / New Oil. With cloud computing it has gotten even more attention. What are apps (applications) with out data? Creating data stores in Cloud (various large/small/efficient/SQL/no-SQL databases in different flavors and Object stores storing unstructured data), migrating from existing data center to Cloud, migrating from one DB to other DB etc. are the vital part of handling data for which knowledge of working with data is a must. Go out and acquire skills in the data field to be an all rounder in the cloud computing area.

With the explosion of AI, join the bandwagon of AI/ML. AI/ML workloads are compute intensive and cloud is a perfect place to get that squared away. Cloud provides compute power at scale and knowledge of AI/ML offerings (AWS Sagemaker and Bedrock) would give you a great boost in your career. There are 3rd party hosted LLMs that can be easily integrated to any cloud platform and run the NLU or Predictive modelling jobs in cloud.

My first cloud learning course was Microsoft's AI Odyssey, which included learning paths in Generative AI, NLP, Computer Vision, and OCR. With the pre-built tools from cloud platforms, solutions can be easily developed and deployed to streamline enterprise efficiency. For example, using established Q&A documentation as a data source, one can build a chatbot employing the RAG technique to answer generic questions. This allows customer service teams to focus on addressing more personalized issues raised by customers.

To stand out in cloud computing, develop cross-disciplinary expertise by learning about related fields like data science, AI, and cybersecurity. Attend interdisciplinary workshops, online events hosted by organizations where experts share their insights, and work on collaborative projects. Engage with diverse tech professionals and pursue certifications to broaden your skill set. This approach enhances your adaptability and makes you a versatile asset in the cloud industry.

Change is the only constant and be a life long learner. Cloud related tech like Cyber security, AI/ML, IoT are the new tech in the block and frequently the topology is changing. Awareness and considerable knowledge on them will give you a better leverage when needed. Attend workshops and most importantly contribute in LinkedIn about your learnings to set yourself apart.