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AWS Data Pipeline Documentation

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AWS Data Pipeline

AWS Data Pipeline is defined as one of the top web services which are used to dehumanize the particular movement and the conversion of data in between the storage services and AWS compute. With the help of this data pipeline in Amazon, it is very easy to redefine all the workflows of data-driven where entire tasks can be completely dependable on the completion of previously defined tasks. You can also define each and every parameter of the transformed data that ensures the logic to set up fully. By using the data pipeline in AWS, the users are eligible to access the data that is stored, transformed and process at its scale efficiently with the help of Amazon RDS, Amazon S3, Amazon EMR and Amazon DynamoDB.

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The AWS data pipeline will help the user to create the difficult data processing workloads easily which are repeatable, high available and fault tolerant. There is nothing to worry when the ensured resource availability, task dependencies and timeouts for the individual tasks. As the AWS data Pipeline is allowing the users to process and move the sufficient data that is already locked in the premises of data silos.

AWS Data Pipeline

Components of Data Pipeline in AWS:

The following listed below are described as some of the components, which will work together in order to manage the large amount and bulk data at fingertips.

  • Basically, the definition of Pipeline particularly evaluates the logic in the business which contains the management of your data.
  • This is used to schedule and runs the tasks via creating the Amazon Ec2 instance in order to perform all the work activities perfectly. You can also upload your own definition of pipeline in order to activate the respective current pipeline. Make use of the edit option to run the pipeline for the best effect. If you want to delete the pipeline you just need to modify the source of the respective data and can remove it automatically.
  • The runner polls task in the data pipeline of AWS is completely used to poll and perform the tasks. Consider an example that the task runner may copy all the log files that are saved in your AWS account to the respective of S3 Amazon and EMR clusters. Then the task runner can be installed and started working automatically on the resources which are created by using your definitions of the pipeline. You are eligible to write your own runner application which is provided in the AWS data pipeline.

Components of AWS Data Pipeline

How to access the AWS Data Pipeline?

The following are some of the interfaces that are used to access, manage and create your own created pipelines easily without any difficulties.

1. Management Console of AWS: It is used to provide the best web interface in order to give a user access to the data pipeline of AWS.
2. Command Line Interface (AWS CLI) in AWS: This command in the AWS data Pipeline will help in providing a wide range of services, which includes all the data that supports well on Linux, UNIX, Mac, and windows.
3. AWS SDKs: The AWS SDKs in the pipeline will be used to provide a particular language API by calculating the signatures, handling the request retires as well as the error handling. 
4. Query API: The query API in the pipeline is used to provide the low-level API that specifically handles the HTTPs requests. By using this query API, it very easy to get a direct access to your data pipeline of AWS. However, it may require the application to handle all the least level details by generating them as error handling free.

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Pricing:

When coming to the pricing in the Amazon web services, you just need to pay only for the data that you have used. For this data pipeline in AWS, you need to pay on the basis of the pipeline according to the preconditions and activities that can be used to schedule and run where they are often used. For example, if your AWS account is not more than a year, then you are qualified to use the no-cost version, as it consists of 5 low-frequency activities and 3 low-frequency preconditions with zero cost.

Benefits of AWS Data Pipeline:

Reliable: 

Basically, the AWS data pipeline is used to build on the highly available, distributed infrastructure that is designed for the tolerant of different activities.  Whenever the failure occurs the data sources and activity log will automatically damage the other activity. The same failure occurs several times then they can send the notifications through Amazon SNS. You can also start configuring the notifications in order to run the activities without any delay

Easy to use:

The creating a pipeline in the AWS data pipeline is very easy and quick with the help of drag-and-drop options. All the common services in the pipeline are built in, so there is no need to write a new logic for them. However, the AWS data pipeline is a complete library of pipeline templates which can give an access to create a set of a pipeline for number difficult use cases like archiving data, periodic queries and processing all the log files.

Flexible:

The AWS data pipeline will allow the users to take a great advantage over the variety of features like dependency tracking, error handling, and scheduling. The users are allowed to write their own preconditions and activities with the custom ones, which is used to configure the AWS data pipeline by running the EMR jobs, SQL queries directly to the databases or by executing them to run on the Amazon EC2 instance or data center. All these processes will help the users to create the custom pipeline by analyzing and processing the data without any complexities in executing the application logic.

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Scalable:

In order to dispatch the worked data in the Pipeline either by serially or parallel, AWS data pipeline makes this process as easy as possible. Through this, you can process the flexible design by evaluating the millions of files within a single file.

Low Cost:

When compared to the other AWS services, the AWS data pipeline services may cost less, which is billed at a monthly rate only. The users can also avail this service at a free cost under the AWS free usage.

Transparent:

The AWS data pipeline will have a complete control in handling all the computational resources by executing them in the business logic, which is easy to enhance and debug the logic efficiently. In addition to this, all the execution logs are automatically delivered to the Amazon S3 with detailed about the pipeline.

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