TABLE OF CONTENTS1. Introduction
2. Amazon Data Life Cycle Manager (DLM)
3. Management of the Data Life Cycle
4. Data Life Cycle Management has many advantages
5. About CloudThat
Introduction
What is Data? Data is statistics, facts or information about an entity. This allows us to see how important data can be. Let’s imagine the following scenario. All your contacts that you have saved on your phone suddenly vanish. These contacts are also a type data stored on your mobile phone. They can be either of one person or a group. Imagine how frustrating it could be if all your contacts were lost. Right?! We back it up with our Email IDs, so you can retrieve them anywhere and at any time in case of accidental deletion.
IT terminology is that the most important thing when managing an IT infrastructure is the data being stored and the security of the data that is backed up by the services. Security is a major concern, especially when the data is stored in the cloud.
We know that Amazon Cloud has Elastic Block Storage (EBS), which stores all data. We know that taking snapshots of EBS volumes is the best way to backup your data in case of accidental deletion or hardware degradation by the cloud provider is the best way. Are you assuming that just taking snapshots can suffice in this situation? NO! Other attributes such as retaining these snapshots and automation or deletion of the snapshots should also be considered.
This blog will cover the use and automation of Amazon Data Life Cycle Manager policies (DLM) to create, delete, and retain EBS snapshots.
Amazon Data Life Cycle Manager (DLM)
While most organizations are moving to Cloud Computing, there are some risks involved. For example, servers can be downed by multiple web attacks. This could lead to data loss. AWS Data Lifecycle Manager is a service that manages data lifecycle management in Cloud Computing.
Data lifecycle management is the process of setting up policies to control where data is stored, how long it can stay (retention period), who can access it, and other details. It increases efficiency and also shows the potential for a better data protection policy. Many businesses are able to easily comply with the many standards being imposed today.
Data lifecycle management refers to the process of managing data at various stages. This includes data creation/capture, deletion, and more. This allows organizations to protect their data against any unanticipated deletion, loss, cyber-attacks and more. An organization can monitor and track how its data are treated, processed, used. Below is a simplified stage of Data within a data lifecycle.
Management of the Data Life Cycle
Data Lifecycle Management’s three main goals are:
Integrity – ensuring that all users have the same data.
Confidentiality – Only authorized individuals can have access to the data.
Accessibility – Data can be accessed when it is needed.
Data Life Cycle Management has many advantages
The above-mentioned goals have many benefits in the day to day operations of a company that implements data management and ensures the effective handling of information.
All users have access to accurate and clean data, which increases efficiency and agility in the company’s processes.
It is important to ensure data availability. Data must be well maintained and extracted throughout the data processing cycle.
Data Lifecycl
