5 Key Points for Operational Managers before Saving Data in the Cloud

5 key points before saving data in the cloud


Data backup in the cloud is an exercise to evaluate and prepare infrastructure spending for data security!

More and more companies of all sizes are beginning to deploy their data in the cloud due to the promise of increased agility and lower management costs to run infrastructure appropriately. What could be more normal?

When the calculation of functions and data are transformed together to the cloud, the key points to consider are very similar to those which we must reflect upon deployment or migration of an application on site. However, when the main calculation of operations is performed on site and that only the data is transferred off site (for backups, disaster recovery management, or archive meet for a monitoring requirement, etc.…), The deployment may be more complex.

In this case, operational managers should consider 5 key points for successful migration to the cloud, including allocated budget and service level agreement contract with customers.

1 – Identify and anticipate shipping volumes

You may surprise to see that one of the maximum potential costs linked to storing data in the cloud is actually a data transfer. When you purchase a cloud service (whether it’s Public cloud computing or Private Cloud Services), you just acquire a location for your data, but you must pay for the data transfer from existing to its new destination. Depending on the available network capacity you have with the existing network, the volume of data you need to transfer and its geographical origin significantly impacts on the network and cost.

You may like to check some insights from our CEO: Why Domestic Data should be made Free within India

So when you think about your data deployment strategy in the cloud, first you need to identify how you will route your initial data, but also the volume of data you add each month. Several questions you can ask to yourself, such as, how can I transfer the data into the cloud? Can I deliver it during off-hours to limit the impact on existing infrastructure? Etc…

2 – Provide the frequency of use

The recall frequency of data stored in the cloud is another key aspect to take into account. If the cost of outsourced storage of data at rest is very low and initial transfer of such data to the cloud storage seems almost free, believe me that the cost of the recall data from cloud archiving could be greater than you estimated. And all this before you yet to think about the cost that will add up to the actual network transfer. In other words, if you keep the data in cloud glacier, but recall only 9 to 10% of it, the bill could eventually be doubled compared to what you had expected.

3 – Evaluate the performance booster

This aspect is also very important. Recall performance should be consistent with the guaranteed restoration time for users in the service level agreement. Fundamentally, it can be your cloud service provider reproduces quickly enough data you are looking for. To meet regulatory requirement for storing data, for example, if the service level agreement stipulates a period of several hours to several days, you can take advantage of cloud storage options, less costly, and their recall performance could be several hours only.

However, you will not make this choice if you need immediate restoration. For example, can it be programmed in reminders or do I tend to need an instant restoration? The service you choose will depend on the answer to these questions.

4 – Integrate existing applications

How to integrate project to create a data pool in the cloud for existing applications? If your workflow environment resembles that of many customers, this is the main question you have to answer then. While it is easy to adapt to the cloud capacity, but the initial configuration is not so simple. Presumable, your existing applications are not configured to write data to a cloud interface, nor designed to handle the additional latency that may induce Cloud. You could end-up exporting data from your application and create movement to the web manuals or custom integration code.

The workload related to these operations has led many customers to use gateways to the cloud that establish continuity between remote and cloud applications that communicate with a local file or block processing devices. However, deciding to use a gateway also means to select, acquire and manage a new technology layer. These facilities offer a wide range of features, performance and usage. You will require planning for the various steps involved in the new program such as selection, deployment, testing of applications and maintenance. May be you also need to consider adding a layer of workflow automation when migrating data to the cloud, and in doing limit necessary manual interventions.

5 – Set the daily management

The last aspect which you should consider is that of the daily management. How will you ensure a system level monitoring for routine management metric of data stored in the cloud, capacity, performance, etc…? Cloud provider may provide you some information, but many tech savvy users find it useful or necessary to have their own tools centered on the cloud to track and manage these essentials to meet SLAs of service. As for the integration of applications, you may want to take this opportunity to add a new layer of visualization and data automation to your data management system.


A proper plan of cloud integration can handle these five key points that start with a comprehensive analysis of the situation. You must evaluate the volume of data you plan to transfer and observes the internal processes. This analysis will be the guarantee of data deployment architecture in the successful and sustainable Cloud, and should also allow you to identify aspects of your website practices that you could improve.

Perhaps, you will find that beyond giving you the ability to measure and justify new automation applications and management tools; the main ROI of moving to the cloud is the opportunity to question the data you store, where and how long. Given the speed at which the volume of data increases, if your data pilot project in the cloud turned into cross-functional and comprehensive evaluation of general practices to use along with multi-level data storage, then it would probably not a very thing for your data storage budget, now and in the future as well.


Leave a Reply

Follow by Email