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Amazon Glacier


AWS Data Services
Course Summary
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1h 39m

To be prepared for the AWS Certified Cloud Practitioner Exam, this course will enable you to demonstrate Amazon Simple Storage Service (S3), Amazon Glacier, Amazon Elastic Block Store (EBS) and Amazon CloudFront storage solutions, and help you identify when to apply AWS solutions to common business scenarios.

This course covers a range of different services, including:

  • Amazon Simple Storage Service (S3)
  • Amazon Elastic Block Storage (EBS)
  • Amazon Glacier
  • Amazon RDS
  • Amazon DynamoDB, ElastiCache, and Redshift
  • Amazon CloudFront
  • AWS Import/Export Disk
  • AWS Import/Export Snowball
  • AWS Storage Gateway

Learning Objectives

By the end of this course, you should be able to:

  • Describe the basic functions that each storage service performs within a cloud solution
  • Recognize basic components and features of each storage service
  • Identify which storage service would be most appropriate to a general use case
  • Understand how each service utilizes the benefits of cloud computing, such as scalability or elasticity

Intended Audience

This course is designed for:

  • Anyone preparing for the AWS Certified Cloud Practitioner
  • Managers, sales professionals, and other non-technical roles


Before taking this course, you should have a general understanding of basic cloud computing concepts.


If you have thoughts or suggestions for this course, please contact Cloud Academy at support@cloudacademy.com.


Hello and welcome to this lecture focusing on Amazon Glacier. Amazon Glacier is similar in part to Amazon S3. It even directly interacts with the Amazon S3 lifecycle rules discussed in the previous lecture. However, the fundamental difference with Amazon Glacier is that it's a fraction of the cost when it comes to storing the same amount of data. So what's the catch? 

Well it doesn't provide you the same features, but more importantly, it doesn't provide you instant access to your data. So what is Amazon Glacier exactly? It's an extremely low cost, long-term, durable storage solution which is often referred to as cold storage, ideally suited for long-term backup and archival requirements. It's capable of storing the same data types as Amazon S3 effectively any object. However, it does not provide instant access to your data. In addition to this, there are other fundamental differences which makes this service fit for purpose for other use cases. 

The service itself again has eleven 9's of durability, making this just as durable as Amazon S3. Again, this is achieved by replicating your data across multiple different availability zones within a single region. But it provides the storage at considerable lower cost compared to that of Amazon S3. This is because retrieval of data stored in Glacier is not an instant access retrieval process. When retrieving your data, it can take up to several hours to gain access to it, depending on certain criteria. The data structure within Glacier is centered around vaults and archives. Buckets and folders are not used. They are purely for S3. 

A Glacier Vault simply acts as a container for Glacier Archives. These vaults are regional. And as such, during the creation of these vaults, you are asked to supply the region in which they will reside. Within these vaults, we then have our data which is stored as an archive. And these archives can be any object similarly to S3. For example, any document, audio, movie or image file, etc, and each will be saved as an archive. Thankfully, you can have unlimited archives within your Glacier Vaults. So from a capacity perspective, it follows the same rule as S3. Effectively, you have access to an unlimited quantity of storage for your archives and vaults. 

Now whereas Amazon S3 provided a nice graphical user interface to view, manage and retrieve your data within buckets and folders, Amazon Glacier does not offer this service. The Glacier Dashboard within AWS management console, only allows you to create your vaults. Any operational process to upload and retrieve data has to be done using some form of code, either with the Glacier web app service API, or by using the AWS SDKs which simplifies the process of authentication. More information on the API and the SDKs can be found with these links on screen. When it comes to moving data into Amazon Glacier for the first time, it's effectively a two-step process. Firstly, you need to create your vaults as a container for your archives, and this could be completed using the Glacier console. Secondly, you need to move your data into the Glacier vault using the API or SDKs. As you may be thinking, there's also another method of moving data into Glacier if it already exists in S3. This is by the S3 Lifecycle rules. There is an option to move your S3 data into Glacier after a set period of time as defined by you within the Lifecycle rule. When the rule is met, S3 will move the data into Glacier as required. When it comes to retrieving your archives, your data, you will again have to use some form of code to do so, either the APIs, SDKs or the AWS CLI. Either way, you must first create an archival retrieval job. Request an access to all or part of the archive. When doing so, you can also specify a retrieval option which can be one of three options. 

Expedited. This is used when you have an urgent requirement to retrieve your data but the request has to less than 250 meg. The data is then made available to you in one to five minutes. And the cost of this service is based upon three cents per gig and one cent per request. 

Standard. This can be used to retrieve any of your archives no matter their size, but your data will be available in three to five hours. So much longer than the Expedited option. This cost for the service is one cent per gig requested and five cent per thousand requests. 

Bulk. Finally, this option is used to retrieve petabytes of data at a time. However, this typically takes between five and twelve hours to complete. This is the cheapest of the retrieval options which is set at 0.25 cent per gig and 2.5 cents per thousand requests. So it really depends on how much data and how quickly you need it as to the retrieval speed and cost to you made by your retrieval option. 

By default, Amazon Glacier encrypts your data using the AES-256 algorithm which is the Advanced Encryption Standard 256 bit, and will manage all of the encryption keys on your behalf. In addition to IAM policies which govern access control to all of you AWS services, Glacier also uses additional methods of access control for protecting your data. And this comes in the form of Vault Access Policies and Vault Lock Policies. Whereas IAM policies are identity based, meaning the policies are associated to a particular user group or role, Vault Access Policies are classed as a resource-based policy as they are applied directly to your vault resource. This is similar to a bucket policy in Amazon S3. These Vault Access Policies govern access control to a particular vault and each vault can only have a single associated Vault Access Policy. They follow the same policy patent as identity policies using the JSON format. However, they also include a principal component to identify who is permitted or refused access. If a user has access to a vault through an identity policy, and there also happens to be a Vault Access Policy attached to the vault as well, then all access will be evaluated between the two policies to see if access is allowed. If there is an explicit deny in either policy, the identity will be refused access. For more information on policy evaluation logic, please view the link here

Vault Lock Policies are similar to Vault Access Policies. However, once they are set, they cannot be changed. This allows you to implement stringent security controls to help you abide by specific governance and compliance controls. For example, you may not be allowed to delete archives for three years due to regulatory requirements. In this case, you could set a Vault Lock Policy denying anyone from deleting archives that are less than 1,095 days old. This will ensure that no data less than three years old can be deleted. You would Vault Access Policies to govern access control features that may change over time and you would use Vault Lock Policies to help you maintain compliance using access controls that must not be changed. 

The pricing structure for Amazon Glacier is very simple. It has a single storage cost for all data despite how much data you are storing. However, this will vary between region. For example, within the London region, the cost of storage is set at 0.45 cents per gig. Similarly to Amazon S3, there also additional costs such as data transfer, request and retrieval pricing. Data transfer into Glacier is free. However, there is a charge for data transferred out of this service. For example, to another region, the transfer is set at 2 cent per gigabyte. The price varies if transferring out across the internet depending on the quantity of data transferred. As we know, there are three variants of data retrieval. Each with their own cost per gig, which is already been covered for standard, expedited and bulk. However, there's also a cost associated to how many of these retrieval request you make. As an example for the London region, this is priced as follows: For the latest pricing information, please refer to the Amazon Glacier Pricing Page

To quickly summarize, Amazon Glacier is designed to archive data for extended periods of time in cold storage for a very small cost. And so it is ideally suited for retaining data for regulatory reasons. However, it is not a good choice if you need to store data that changes frequently, and that requires immediate access.



About the Author
Andrew Larkin
Head of Content
Learning Paths

Andrew is fanatical about helping business teams gain the maximum ROI possible from adopting, using, and optimizing Public Cloud Services. Having built  70+ Cloud Academy courses, Andrew has helped over 50,000 students master cloud computing by sharing the skills and experiences he gained during 20+  years leading digital teams in code and consulting. Before joining Cloud Academy, Andrew worked for AWS and for AWS technology partners Ooyala and Adobe.