Users
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Access keys: Used to make programmatic calls to AWS. However, there are more secure alternatives to consider before you create access keys for IAM users. For more information, see Considerations and alternatives for long-term access keys in the AWS General Reference. If the IAM user has active access keys, they continue to function and allow access through the AWS CLI, Tools for Windows PowerShell, AWS API, or the AWS Console Mobile Application.
Manage passwords for your IAM users. Create and change the passwords that permit access to the AWS Management Console. Set a password policy to enforce a minimum password complexity. Allow users to change their own passwords.
Enable multi-factor authentication (MFA) for the IAM user. As a best practice, we recommend that you require multi-factor authentication for all IAM users in your account. With MFA, users must provide two forms of identification: First, they provide the credentials that are part of their user identity (a password or access key). In addition, they provide a temporary numeric code that's generated on a hardware device or by an application on a smartphone or tablet.
Find unused passwords and access keys. Anyone who has a password or access keys for your account or an IAM user in your account has access to your AWS resources. The security best practice is to remove passwords and access keys when users no longer need them.
Download a credential report for your account. You can generate and download a credential report that lists all IAM users in your account and the status of their various credentials, including passwords, access keys, and MFA devices. For passwords and access keys, the credential report shows how recently the password or access key has been used.
By default, a new IAM user has no permissions to do anything. They are not authorized to perform any AWS operations or to access any AWS resources. An advantage of having individual IAM users is that you can assign permissions individually to each user. You might assign administrative permissions to a few users, who then can administer your AWS resources and can even create and manage other IAM users. In most cases, however, you want to limit a user's permissions to just the tasks (AWS actions or operations) and resources that are needed for the job.
Imagine a user named Diego. When you create the IAM user Diego, you create a password for him and attach permissions that let him launch a specific Amazon EC2 instance and read (GET) information from a table in an Amazon RDS database. For procedures on how to create users and grant them initial credentials and permissions, see Creating an IAM user in your AWS account. For procedures on how to change the permissions for existing users, see Changing permissions for an IAM user. For procedures on how to change the user's password or access keys, see Managing user passwords in AWS and Managing access keys for IAM users.
You can also add a permissions boundary to your IAM users. A permissions boundary is an advanced feature that allows you to use AWS managed policies to limit the maximum permissions that an identity-based policy can grant to an IAM user or role. For more information about policy types and uses, see Policies and permissions in IAM.
Each IAM user is associated with one and only one AWS account. Because IAM users are defined within your AWS account, they don't need to have a payment method on file with AWS. Any AWS activity performed by IAM users in your account is billed to your account.
End users are the ultimate human users (also referred to as operators) of a software product. The end user stands in contrast to users who support or maintain the product such as sysops, database administrators and computer technicians. The term is used to abstract and distinguish those who only use the software from the developers of the system, who enhance the software for end users.[1] In user-centered design, it also distinguishes the software operator from the client who pays for its development and other stakeholders who may not directly use the software, but help establish its requirements.[2][3] This abstraction is primarily useful in designing the user interface, and refers to a relevant subset of characteristics that most expected users would have in common.
In user-centered design, personas are created to represent the types of users. It is sometimes specified for each persona which types of user interfaces it is comfortable with (due to previous experience or the interface's inherent simplicity), and what technical expertise and degree of knowledge it has in specific fields or disciplines. When few constraints are imposed on the end-user category, especially when designing programs for use by the general public, it is common practice to expect minimal technical expertise or previous training in end users.[4]
The end-user development discipline blurs the typical distinction between users and developers. It designates activities or techniques in which people who are not professional developers create automated behavior and complex data objects without significant knowledge of a programming language.
Each user account on a multi-user system typically has a home directory, in which to store files pertaining exclusively to that user's activities, which is protected from access by other users (though a system administrator may have access). User accounts often contain a public user profile, which contains basic information provided by the account's owner. The files stored in the home directory (and all other directories in the system) have file system permissions which are inspected by the operating system to determine which users are granted access to read or execute a file, or to store a new file in that directory.
Some usability professionals have expressed their dislike of the term \"user\" and have proposed changing it.[9] Don Norman stated that \"One of the horrible words we use is 'users'. I am on a crusade to get rid of the word 'users'. I would prefer to call them 'people'.\"[10]
The term \"user\" may imply lack of the technical expertise required to fully understand how computer systems and software products work.[11] Power users use advanced features of programs, though they are not necessarily capable of computer programming and system administration.[12][13]
In order for Google Analytics to determine which traffic belongs to which user, a unique identifier associated with each user is sent with each hit. This identifier can be a single, first-party cookie named _ga that stores a Google Analytics client ID, or you can use the User-ID feature in conjunction with the client ID to more accurately identify users across all the devices they use to access your site or app. For more information on identifiers, read about cookies and user identification in our developer documentation.
In early 2017, Google Analytics began updating the calculation for the Users and Active Users metrics to more efficiently count users with high accuracy and low error rate (typically less than 2%). The metrics are available across your standard reports. You may notice a small difference in user count from the previous calculation method (explained below), with the exception of Unsampled Reports and BigQuery Export, which will continue to use the previous calculation method. The New Users calculation also still uses the previous method.
Although this calculation can quickly deliver unsampled data, it does have some disadvantages. It relies on number of sessions and client-side time, so if a user's client-side time is incorrect, or if you are using a reporting view that filters out some sessions from a user (instead of all users), the data can be inconsistent.
In order to get around any potential inaccuracies, you can create a custom report with a non-date dimension that will be the same across sessions for users (e.g., Browser, Operating System, or Mobile Device). This forces Analytics to use Calculation #2, instead.
Some people think that usability is very costly and complex and that user tests should be reserved for the rare web design project with a huge budget and a lavish time schedule. Not true. Elaborate usability tests are a waste of resources. The best results come from testing no more than 5 users and running as many small tests as you can afford.
As you add more and more users, you learn less and less because you will keep seeing the same things again and again. There is no real need to keep observing the same thing multiple times, and you will be very motivated to go back to the drawing board and redesign the site to eliminate the usability problems.
The curve clearly shows that you need to test with at least 15 users to discover all the usability problems in the design. So why do I recommend testing with a much smaller number of users
The main reason is that it is better to distribute your budget for user testing across many small tests instead of blowing everything on a single, elaborate study. Let us say that you do have the funding to recruit 15 representative customers and have them test your design. Great. Spend this budget on 3 studies with 5 users each!
Finally, the second study will be able to probe deeper into the usability of the fundamental structure of the site, assessing issues like information architecture, task flow, and match with user needs. These important issues are often obscured in initial studies where the users are stumped by stupid surface-level usability problems that prevent them from really digging into the site.
You might think that 15 studies with a single user would be even better than 3 studies with 5 users. The curve does show that we learn much more from the first user than from any subsequent users, so why keep going Two reasons:
You need to test additional users when a website has several highly distinct groups of users. The formula only holds for comparable users who will be using the site in fairly similar ways. 59ce067264
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