Companies are adopting Cloud computing as they shift from on-premise platforms. However, it is essential to have a comprehensive understanding of Cloud computing before starting the migration process. Imarticus Learning's SCBI can help you gain the necessary expertise. The software engineer course is industry-oriented and helps students focus on specialized fields.
Top 5 Reasons Why People Misunderstand Cloud Computing
While Cloud computing is essential for companies that wish to optimize and automate various processes, it can often be misunderstood. Cloud computing is one aspect of the technological developments that assist in securing and reducing errors in business. Therefore, you cannot wholly depend on the Cloud without using any external solutions.
If you have a professional Cloud DevOps engineer certification, you will identify the issues and provide the necessary software solutions. However, people expect a lot from cloud computing. Following are some of the reasons why these unrealistic expectations occur.
- Trying to Use Cloud Computing for Multiple Purposes
Cloud computing may not be ideal for all purposes. Before using it to replace on-premise platforms completely, companies should invest in a few trials runs to ensure the Cloud migration is the best option before using it to replace on-premise platforms completely.
Even then, you cannot migrate all applications. For example, you might have legacy applications or specific workloads which are not suitable for the Cloud. It would be best if you considered these aspects before depending on Cloud to solve all issues.
- Focusing on Cost Reduction
Companies often migrate from on-premise architecture to Cloud infrastructure to reduce the cost of business. However, cost reduction is not always a given when it comes to Cloud computing. It depends on what the business processes are and the total cost of ownership. So if cost is an issue, you will have to check the business model. Apart from this, Cloud computing improves agility which boosts businesses. So that is more important than reducing the cost for specific processes.
- Using Only One Cloud Strategy
Most companies use Cloud computing to simplify business procedures, and in doing so, they try to use one strategy for everything. But as a Cloud DevOps engineer, you will see that Cloud computing works differently for different workloads. Therefore, you need to analyze available processes and come up with strategies specific to those processes. Cloud strategies also need to work for various Cloud services. So, a strategy cannot be too simple.
- Assuming that Cloud is Always Secure
Cloud does offer enhanced security, but people often depend on that and do not use any other measures. Third-party hackers have attacked the public Cloud in the past few years. But people continue to misunderstand Cloud security. It is not something that is automatically enabled. Instead, Cloud security is your and the provider's responsibility. Additional cybersecurity solutions need to be used to enhance security.
- No Monitoring After Cloud Migration
After the migration to Cloud is complete, people assume that there is nothing more to do. However, constant monitoring is essential. You need to monitor every operation to ensure that the company's performance is precisely what it needs to be. Lack of post-migration management can lead to various issues and affect performance.
How Can You Learn Cloud Computing?
If you wish to learn Cloud computing, you will need to enrol in a software engineer course. Imarticus Learning offers Certification in Software Engineering for Cloud, Blockchain, and IoT. This course is in collaboration with IIT Guwahati and E&ICT Academy. Therefore, you can easily interact with professionals in the field and learn more about the practical applications of Cloud computing. You will receive professional Cloud DevOps engineer certification, and you can land a successful job in your field of interest.
Imarticus Learning will ensure that you become a successful Cloud DevOps engineer. You can also explore careers in data science or computer vision or develop skills in machine learning, deep learning, and NLP.
