Simplifying Your Data Management with Amazon Data Lifecycle Manager
Published: 2023-03-10 11:44:46

Welcome to the post for today! Data management becomes more difficult and sophisticated as firms expand. It is simple to feel overwhelmed with data storage, backup, and archiving when several apps generate data from various sources and formats. For our collective benefit, Amazon Web Services (AWS) provides Amazon Data Lifecycle Manager (DLM), a potent solution that streamlines the entire procedure. In-depth discussion of DLM and how it can greatly simplify your data management approach and cut expenses will be provided in this article. So buckle up as we take you on an amazing adventure towards effective data management!

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## **Introduction to Amazon Data Lifecycle Manager**

Any organisation needs data, but managing it can be difficult and time-consuming. The fully managed solution Amazon Data Lifecycle Manager (DLM) makes it simple to specify and automate data management procedures throughout your AWS environment.

In order to transfer data between storage tiers, prevent data from being accidentally deleted, and archive data to save storage costs, DLM offers a simple method for creating and managing lifecycle policies. By centralising the administration of your data lifecycle policies in one location, DLM makes it simple to audit and review your policies.

Data management across several storage tiers is made simple by the integration of DLM with other AWS services including Amazon S3, Amazon EBS, and Amazon Glacier. Any large dataset, up to and including petabytes of data, can be used with DLM.

## **Benefits of Using Amazon Data Lifecycle Manager**

Utilising Amazon Data Lifecycle Manager (DLM) to manage your data has numerous advantages. The process of backing up and archiving your data may be automated with DLM, making data management simpler and more efficient. DLM also offers a cost-effective approach to manage and keep your data because you only pay for the space that you really use. DLM is also very scalable and able to handle a lot of data. The ability to define policies that indicate when and how often your data should be backed up, as well as the capability to check the status of your backups, are just a few of the capabilities that DLM offers to help you manage your data more effectively.


## **How to Use Amazon Data Lifecycle Manager**

You can create an Amazon Data Lifecycle Manager (DLM) resource in any location where DLM is offered, provided you have an AWS account. You can launch the DLM console and establish a new lifecycle policy after creating an Amazon S3 bucket and an IAM role using the steps below. Once the policy has been generated, you can either apply it when making a new Amazon S3 bucket or attach it to an existing one.

First, in the location where you wish to manage your data, build an Amazon S3 bucket. Name the bucket something distinctive, like MyDataBucket-123456789012. Then build an IAM role that enables access to your buckets for DLM and Amazon S3. You can find complete instructions for creating the role in the IAM User Guide.

Launch the DLM console after that, then select Create Policy. Give your policy a name and a description in the box titled "Policy Details." then pick your preferred AWS Region from the list.

You can set up when snapshots are taken (daily or weekly, for example), how long they should be kept (indefinitely or for a specific number of days), whether snapshot tags should be applied automatically, what should happen when snapshots are first created or expire, and whether notifications via Amazon Simple Notification Service (SNS) should be sent when these events occur in other sections of the console. Once you've set up all the required settings, select


## **Creating & Retaining Data with Data Lifecycle Manager**

The procedure for generating and keeping data across time is known as data lifecycle management. A tool called a data lifecycle management (DLM) aids in automating this procedure. Data may be backed up, tracked over time for changes, and restored if it is lost or corrupted using DLM.

DLM functions by taking periodic snapshots of your data. Your data can be restored using these snapshots if it is lost or damaged. Snapshots can be used to keep track of how your data has changed over time. DLM can be set up to automatically create snapshots, or you can do it yourself.

DLM offers a 30-day free trial and is free to use. DLM bills a monthly cost based on the volume of data you have and the number of photos you've taken after the free trial.

## **Setting Policy and Analyzing Outcomes**

You will surely gather more data as your firm expands. And as your data expands, so does the requirement for efficient management. You may automate the process of establishing policies and evaluating the results of your data management plan with the aid of Amazon Data Lifecycle Manager (DLM).

With DLM, you may establish guidelines for when and how frequently to take data snapshots, or backups. You can also select whether to encrypt them and how long to preserve such snapshots. In order to guarantee that your data is always adequately safeguarded, DLM will then automatically enforce those regulations.

DLM, however, does more than just take snapshots; it also keeps track of how your backup strategies are performing. Are your snapshots being made when they should be? When they are no longer required, are they deleted? Do you have excess storage needs? These and other detailed reports from DLM allow you to fine-tune your backup strategy for maximum effectiveness.

In summary, Amazon DLM streamlines the process of establishing a successful data management strategy and ensuring that it is operating as intended. So, if you're trying to streamline your data management, Amazon DLM is absolutely something to think about.

## **Managing Versioning with AWS Data Lifecycle Manager**

A robust tool called AWS Data Lifecycle Manager (DLM) can assist you in managing your data versioning requirements. Multiple versions of your data can be readily created and managed with DLM, and access to particular versions can be tracked and restricted.

When working with large or complex datasets, versioning is a crucial component of data management. Versioning enables you to maintain a history of your data so that you can quickly go back to earlier iterations if required. Additionally, it enables you to maintain separate copies of your data so that you may work with the most recent version without affecting older versions.

Managing different copies of your data is simple using DLM. You can indicate how frequently DLM should update your data's versions as well as which elements of your data you wish to be included in each update. For instance, you could wish to preserve three copies of your dataset: one entire, one with all changes, and one with just the most recent ones.

Using DLM, you can restrict access to particular versions of your data as well. If you want to give some individuals or groups read-only access to earlier versions of your data while giving others complete read/write access to the most recent version, for instance.
This allows you to easily restrict access to sensitive or outdated information while still giving users the ability to work with the most up-to-date version of your data.

## **Backup Storage Options for Your Data using Amazon DLM**

Your data can be stored in a variety of backup locations with the help of Amazon Data Lifecycle Manager (DLM). You have the option of storing your backups in an on-premises storage system, an Amazon Simple Storage Service (S3) account, or a hybrid storage system.

You have the option of using Standard or Reduced Redundancy Storage (RRS) if you store your backups in S3. High availability and durability are provided by the Standard storage class, but reduced availability and durability are provided by the RRS storage class at a lower cost.

You can use any kind of storage system, such a file system or object store, that is compatible with the Amazon S3 API if you choose to keep your backups on-site. On each server that you want to back up, the Amazon S3 Connector for Windows must be installed.

Either the EFS File Sync service or the Storage Gateway service can be used if your backups are kept in a hybrid storage system. You can synchronise files between an on-premises file server and an EFS file system using the EFS File Sync service, and you can backup files from an on-premises file server to S3 using the Storage Gateway service.

## **Conclusion**

We hope this post has provided you with some background information on Amazon Data Lifecycle Manager and how it can assist to make data management simpler. AWS DLM can give companies greater control over their data than ever before by automating backup and retention procedures, monitoring storage resource utilisation, and seamlessly transferring data between AWS services. We recommend giving Amazon Data Lifecycle Manager a try right away if you're searching for a simple approach to manage the data for your business effectively.