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What are the Benefits of Amazon EMR? What are the EMR use Cases?

Amazon EMR(Elastic MapReduce) is a cloud-based big data platform that allows the team to quickly process large amounts of data at an effective cost. For this, they use open source tools like Apache Hive, Apache Spark, Apache Flink, Apache HBase, and Presto. With the help of Amazon S3’s scalable storage and Amazon EC2’s dynamic stability, EMR provides the elasticity and engines for running Petabyte-scale analysis. The cost of this is just a fraction of the traditional on-premise clusters’ cost. For iterative collaboration, development, and data access across data products like Amazon DynamoDB, Amazon S3, and Amazon Redshift, you can use Jupyter-based EMR Notebooks. It helps in reducing time for insight and operationalizing analytics quickly. Several customers use EMR for reliably and securely handling the big data use cases like machine learning, deep learning, bioinformatics, financial and scientific stimulation, log analysis, and data transformations (ETL). With EMR, the team has the flexibility of running use cases on short lived, single-purpose clusters or highly available, long running clusters. Here are some other benefits of using EMR:1. Easy to useSince clusters are launched in minutes by EMR, you don’t have to worry about infrastructure setup, node provisioning, cluster tuning, and Hadoop configuration. All these tasks are taken care of by EMR so that you can concentrate on analysis. Data engineers, data scientists, and data analysts can use the EMR notebooks for launching a serverless Jupyter notebook within a matter of seconds. This also allows the team and individuals to interactively explore, visualize and process the data. 2. Low costThe pricing of EMR is simple as well as predictable. There is a one-minute minimum charge and the rest is paid according to per-instance rate for every second. You can use applications like Apache Hive and Apache Spark for launching a 10-node EMR cluster for a low cost of $0.15 per hour. Also, EMR has native support for Reserved instances and Amazon EC2 spot, which can help you save on the cost of the underlying instances by about 50-80%. The pricing of Amazon EMR depends on the number of deployed EC2 instances, the type of the instance and the region where you are launching your cluster. Since it is on-demand pricing, you can expect low rates. But for reducing the cost even further, you can purchase Spot instances or reserved instances. The cost of spot instanced is about one-tenth less than the on-demand pricing. Remember that if you are using services like Amazon D3, DynamoDB or Amazon Kinesis along with your EMR cluster, they will be charged separately from the usage for Amazon EMR. 3. ElasticityEMR allows provisioning of not one but thousands of compute instances for processing data at any scale. All these instances’ numbers can be decreased or increased manually or automatically with the help of Auto Scaling which can manage the size of clusters on the basis of utilization. This allows you to pay only for what you use. Also, unlike the on-premise clusters of the rigid infrastructure, EMR decouples persistent storage and compute which gives you the ability of scaling every one of them independently. 4. ReliabilityThanks to EMR, you can now spend less time monitoring and tuning your cluster. Tuned for the cloud, EMT monitors your cluster constantly. They retry failed tasks and replace poorly performed instances automatically. Also, you don’t have to manage bug fixes and updates as EMR provides the latest stable releases of open source software. This results in lesser efforts and fewer issues in maintaining the environment. With the help of multiple master nodes, clusters are not only highly available, but also failover in case of a node failure automatically. With Amazon EMR, you have a configuration option for controlling the termination of your cluster, whether you do it manually or automatically. If you go for the option of automatic termination, the cluster will be terminated once the steps are completed. This is known as a transient cluster. However, if you go for the manual option, the cluster will continue to run even after the processing is completed. You will have to manually terminate it when you no longer need it. The other option is creating a cluster, interacting directly with the installed applications, and then manually terminating the cluster. These are known as long-running clusters. Also, there is an option of configuring the termination protection for preventing the clusters’ instances from being terminated due to issues and errors during processing. This allows recovery of instances’ data before they are terminated. These options’ default settings depend on whether you launched your cluster with the console, API or CLI. 5. SecurityEMR is responsible for automatically configuring the firewall settings of EC2. these setting control and instances’ network access and launches the clusters in an Amazon VPC. For all the objects residing in S3, client-side or server-side encryption is used along with EMRFS, which is an object store on S3 for Hadoop. To achieve this, you can either use your own customer-managed keys or the AWS Key Management Service. With the help of EMR, you can easily enable other encryption options like at-rest and in-transit encryption. Amazon EMR can leverage AWS services like Amazon VPC and IAM and features like Amazon EC2 key pairs for securing the cluster and data. Let’s go through these leverages one by one: IAM When integrated with IAM, Amazon EMR allows managing of permissions. You can use the IAM policies for defining the permissions which are then attached to the IAM groups or IAM users. The defined permissions determine the actions the members of the group or the users can perform and accessible resources. Apart from this, IAM roles are used by the Amazon EMR for Amazon EMR service itself as well as EC2 instance profile. These roles can grant permissions for accessing other AWS services. There is a default role for EC2 instance profile and Amazon EMR service. The AWS managed policies are used by the default role which is automatically created when you launch the EMR cluster from the console for the first time and select default permissions. You can use the AWS CLI for creating default IAM roles. For managing permissions, you can select custom roles for instance and the service profile. Security Groups Security groups are used by Amazon EMR for controlling outbound and inbound traffic to the EC2 instances. When you are launching the cluster, a security group for master instance and to be shared by the task/core instance is used. The security group rules are configured by the Amazon EMR for ensuring communication between the instances. Apart from this, there is an option for configuring additional security groups and assigning them to the master as well as task/core instances for advanced rules. Encryption The Amazon S3 client-side and server-side encryption along with EMRFS is supported by the Amazon EMR, this allows protecting the data stored in Amazon S3. The server-side encryption allows encrypting the data after you have uploaded it. The client-side encryption allows encrypting the decrypting on the EMR cluster in the EMRFS client. You can use the AWS Key Management Service for managing the master key for the client-side encryption. Amazon VPC You can launch clusters in a Virtual Private Cloud (VPC). A VPC is a virtual network isolated in the AWS providing the ability to control network access and configuration’s advanced aspects. AWS CloudTrail When integrated with CloudTrail, Amazon EMR allows logging information regarding request made by the AWS account. You can use this information to track who is accessing the cluster and when and can even determine the IP address that made the request. Amazon EC2 Key Pairs A secure connection needs to be formed between the master node and your remote computer for monitoring and interacting with the cluster. For the connection, you can use the Secure Shell (SSH) network and for authentication, you can use Kerberos. An Amazon EC2 key pair will be required, if you are using SSH. 6. FlexibilityEMR allows you to have complete control over the cluster. This involves easy installation of additional applications, having root access to every instance, and customizing every cluster with bootstrap actions. Also, you won’t have to re-launch the cluster for reconfiguring the running clusters on the fly or using the custom Amazon Linux AMIs for launching EMR clusters. Also, you have the option of scaling up or down your clusters according to your computing needs. You can remove instances for controlling costs when peak workloads subside or add instances for peak overloads by resizing your clusters. Amazon EMR also allows running multiple instance groups so that on-demand instanced can be used in a single group for processing power with spot instances in other group. This helps faster completion of jobs at a lower price. You can even take advantage of low price on one spot instance type over another by mixing different types of instances together. Amazon EMR offers the flexibility of using different file systems for your input, intermediate and output data. For example: Hadoop Distributed File System (HDFS) for running the core and master nodes of your cluster to process that is not required after the lifecycle of the cluster. EMR File System (EMRFS) for using Amazon S3 as a data layer to run applications on the cluster for separating the storage and compute, and persist data after the lifecycle of the cluster. It also allows independent scaling up and down of your storage and compute needs. Scaling of the compute needs can also be done by using Amazon S3 or resizing your cluster. 7. AWS IntegrationIntegrating Amazon EMR with other services offered by the AWS can help in providing functionalities and capabilities of networking, security, storage and many more. Here are some of the examples of such integration: For the instances comprising the nodes in the cluster, Amazon EC2 For configuring the virtual network in which you will be launching your instances, Amazon Virtual Private Cloud (VPC) For storing input as well as output data, Amazon S3 For configuring alarms and monitoring cluster performance, Amazon CloudWatch For configuring permissions, AWS Identity and Access Management (IAM) For auditing requests made to the service, AWS CloudTrail For scheduling and starting your clusters, AWS Data Pipeline 8. DeploymentThe EMR clusters have EC2 instances which are responsible for performing the work that you are submitting to the cluster. When you are launching the cluster, the instances with the applications like Apache Spark or Apache Hadoop are configured by the Amazon EMR. You need to select the type and size of the instance that suits the cluster’s processing needs including streaming data, batch processing, large data storage, and low-latency queries. There are different ways of configuring the software on your cluster provided by the Amazon EMR. For example: Installation of an Amazon EMR release with applications that can include applications like Spark, Pig or Apache and versatile frameworks like Hadoop. Installation of several MapR distributions. Amazon Linus is used for the manual installation of the software on the cluster. For this, the yum package manager can be used. 9. MonitoringTroubleshooting of Cluster issues like errors or failures can be done by using the log files and Amazon EMR Management Interface. You will have the capability of archiving log files in Amazon S3 for storing log and troubleshoot issues even after the cluster has been terminated. There is also an optional debugging tool available in the Amazon EMR console that can be used for browsing log files based on tasks, jobs and steps. CloudWatch is integrated with Amazon EMR for tracking performance metrics for the cluster as well as the jobs within the cluster. Configuration of alarms is done based on metrics like what is the percentage of used storage or if the cluster is idle or not. 10. Management InterfacesThere are different ways for interacting with the Amazon EMR including the following: Console This is a graphical user interface that can be used for launching and managing clusters. You need to specify the details of the cluster to be launched and check out the details of the existing clusters, terminated clusters and debug by filling out web forms. It is the easiest way to start working with Amazon EMR as no programming knowledge is required. You can get the console online from here. AWS Command Line Interface (AWS CLI) This is a client application that you can run on your local machine for connecting to the Amazon EMR and creating and managing clusters. There is a set of commands available in the AWS CLI for the Amazon EMR, you can use this for writing scripts that can automate the launch and management of the cluster.  Software Development Kit (SDK) There are functions available in the SDKs that can call Amazon EMR for creating and managing clusters. You can even write applications for automating this process. It is the best way of extending and customizing the Amazon EMR’s functionality. The available SDKs for the Amazon EMR are Java, Go, PHP, Python, .NET, Ruby, and Node.js. Web Service API This is a low-level interface that uses JSON for calling the Amazon EMR directly. This can be used for creating a customized SDK that calls the web service. Now that we have discussed the benefits of EMR, let’s move on to the EMR use cases: Use Cases of EMR  1. Machine LearningEMR provides built-in machine learning tools for scalable machine learning algorithms like TensorFLow, Apache Spark MLib, and Apache MXNet. Also you can easily use Bootstrap Actions and Custom AMIs for easily adding the preferred tools and libraries for creating your very own predictive analytics toolset. 2. Extract Transform Load (ETL)For cost-effective and quick performance of data transformation workloads (ETL) like sort, join and aggregate on large datasets, you can use EMR. 3. Clickstream analysisWith EMR, along with Apache Hive and Apache Spark, you can segment users, deliver effective ads by understanding the user preferences. All this can be achieved by analyzing the clickstream data from Amazon S3. 4. Real-time streamingWith EMR and Amazon Spark Streaming, analyzing events from Amazon Kinesis, Amazon Kafka or any other streaming data source is possible. This helps in creating highly available, long running, and fault-tolerant streaming data pipelines. Persist transformed insights to Amazon Elasticsearch and datasets to HDFS or Amazon S3. 5. Interactive AnalyticsWith EMR Notebooks, you will be provided with an open-source Jupyter based, managed analytic environment. This will allow data analysts, developers and scientists in preparing and visualizing data, collaborating with peers, building applications, and performing interactive analysis. 6. GenomicsEMR can also be used for quickly and efficiently processing large amounts of genomic data or any other large, scientific dataset. Genomic data hosted on AWS can be accessed by researchers for free. In this article, you got a quick introduction to Amazon EMR and how it has different log files’ types. Also, you got to understand the benefits of Elastic MapReduce. To become an expert in AWS services, enroll in the AWS certification course offered by KnowledgeHut. 
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What are the Benefits of Amazon EMR? What are the EMR use Cases?

10K
  • by Joydip Kumar
  • 30th Sep, 2019
  • Last updated on 30th Sep, 2019
  • 8 mins read
What are the Benefits of Amazon EMR? What are the EMR use Cases?

Amazon EMR(Elastic MapReduce) is a cloud-based big data platform that allows the team to quickly process large amounts of data at an effective cost. For this, they use open source tools like Apache Hive, Apache Spark, Apache Flink, Apache HBase, and Presto. With the help of Amazon S3’s scalable storage and Amazon EC2’s dynamic stability, EMR provides the elasticity and engines for running Petabyte-scale analysis. The cost of this is just a fraction of the traditional on-premise clusters’ cost. For iterative collaboration, development, and data access across data products like Amazon DynamoDB, Amazon S3, and Amazon Redshift, you can use Jupyter-based EMR Notebooks. It helps in reducing time for insight and operationalizing analytics quickly. 

Several customers use EMR for reliably and securely handling the big data use cases like machine learning, deep learning, bioinformatics, financial and scientific stimulation, log analysis, and data transformations (ETL). With EMR, the team has the flexibility of running use cases on short lived, single-purpose clusters or highly available, long running clusters. 

Here are some other benefits of using EMR:

Benefits of using EMR

1. Easy to use

Since clusters are launched in minutes by EMR, you don’t have to worry about infrastructure setup, node provisioning, cluster tuning, and Hadoop configuration. All these tasks are taken care of by EMR so that you can concentrate on analysis. Data engineers, data scientists, and data analysts can use the EMR notebooks for launching a serverless Jupyter notebook within a matter of seconds. This also allows the team and individuals to interactively explore, visualize and process the data. 

2. Low cost

The pricing of EMR is simple as well as predictable. There is a one-minute minimum charge and the rest is paid according to per-instance rate for every second. You can use applications like Apache Hive and Apache Spark for launching a 10-node EMR cluster for a low cost of $0.15 per hour. Also, EMR has native support for Reserved instances and Amazon EC2 spot, which can help you save on the cost of the underlying instances by about 50-80%. The pricing of Amazon EMR depends on the number of deployed EC2 instances, the type of the instance and the region where you are launching your cluster. Since it is on-demand pricing, you can expect low rates. But for reducing the cost even further, you can purchase Spot instances or reserved instances. The cost of spot instanced is about one-tenth less than the on-demand pricing. Remember that if you are using services like Amazon D3, DynamoDB or Amazon Kinesis along with your EMR cluster, they will be charged separately from the usage for Amazon EMR. 

3. Elasticity

EMR allows provisioning of not one but thousands of compute instances for processing data at any scale. All these instances’ numbers can be decreased or increased manually or automatically with the help of Auto Scaling which can manage the size of clusters on the basis of utilization. This allows you to pay only for what you use. Also, unlike the on-premise clusters of the rigid infrastructure, EMR decouples persistent storage and compute which gives you the ability of scaling every one of them independently. 

4. Reliability

Thanks to EMR, you can now spend less time monitoring and tuning your cluster. Tuned for the cloud, EMT monitors your cluster constantly. They retry failed tasks and replace poorly performed instances automatically. Also, you don’t have to manage bug fixes and updates as EMR provides the latest stable releases of open source software. This results in lesser efforts and fewer issues in maintaining the environment. With the help of multiple master nodes, clusters are not only highly available, but also failover in case of a node failure automatically. 

With Amazon EMR, you have a configuration option for controlling the termination of your cluster, whether you do it manually or automatically. If you go for the option of automatic termination, the cluster will be terminated once the steps are completed. This is known as a transient cluster. However, if you go for the manual option, the cluster will continue to run even after the processing is completed. You will have to manually terminate it when you no longer need it. The other option is creating a cluster, interacting directly with the installed applications, and then manually terminating the cluster. These are known as long-running clusters. 

Also, there is an option of configuring the termination protection for preventing the clusters’ instances from being terminated due to issues and errors during processing. This allows recovery of instances’ data before they are terminated. These options’ default settings depend on whether you launched your cluster with the console, API or CLI. 

5. Security

EMR is responsible for automatically configuring the firewall settings of EC2. these setting control and instances’ network access and launches the clusters in an Amazon VPC. For all the objects residing in S3, client-side or server-side encryption is used along with EMRFS, which is an object store on S3 for Hadoop. To achieve this, you can either use your own customer-managed keys or the AWS Key Management Service. With the help of EMR, you can easily enable other encryption options like at-rest and in-transit encryption. 

Amazon EMR can leverage AWS services like Amazon VPC and IAM and features like Amazon EC2 key pairs for securing the cluster and data. Let’s go through these leverages one by one: 

  • IAM 

When integrated with IAM, Amazon EMR allows managing of permissions. You can use the IAM policies for defining the permissions which are then attached to the IAM groups or IAM users. The defined permissions determine the actions the members of the group or the users can perform and accessible resources. 

Apart from this, IAM roles are used by the Amazon EMR for Amazon EMR service itself as well as EC2 instance profile. These roles can grant permissions for accessing other AWS services. There is a default role for EC2 instance profile and Amazon EMR service. The AWS managed policies are used by the default role which is automatically created when you launch the EMR cluster from the console for the first time and select default permissions. You can use the AWS CLI for creating default IAM roles. For managing permissions, you can select custom roles for instance and the service profile. 

  • Security Groups 

Security groups are used by Amazon EMR for controlling outbound and inbound traffic to the EC2 instances. When you are launching the cluster, a security group for master instance and to be shared by the task/core instance is used. The security group rules are configured by the Amazon EMR for ensuring communication between the instances. Apart from this, there is an option for configuring additional security groups and assigning them to the master as well as task/core instances for advanced rules. 

  • Encryption 

The Amazon S3 client-side and server-side encryption along with EMRFS is supported by the Amazon EMR, this allows protecting the data stored in Amazon S3. The server-side encryption allows encrypting the data after you have uploaded it. The client-side encryption allows encrypting the decrypting on the EMR cluster in the EMRFS client. You can use the AWS Key Management Service for managing the master key for the client-side encryption. 

  • Amazon VPC 

You can launch clusters in a Virtual Private Cloud (VPC). A VPC is a virtual network isolated in the AWS providing the ability to control network access and configuration’s advanced aspects. 

  • AWS CloudTrail 

When integrated with CloudTrail, Amazon EMR allows logging information regarding request made by the AWS account. You can use this information to track who is accessing the cluster and when and can even determine the IP address that made the request. 

  • Amazon EC2 Key Pairs 

A secure connection needs to be formed between the master node and your remote computer for monitoring and interacting with the cluster. For the connection, you can use the Secure Shell (SSH) network and for authentication, you can use Kerberos. An Amazon EC2 key pair will be required, if you are using SSH. 

6. Flexibility

EMR allows you to have complete control over the cluster. This involves easy installation of additional applications, having root access to every instance, and customizing every cluster with bootstrap actions. Also, you won’t have to re-launch the cluster for reconfiguring the running clusters on the fly or using the custom Amazon Linux AMIs for launching EMR clusters. 

Also, you have the option of scaling up or down your clusters according to your computing needs. You can remove instances for controlling costs when peak workloads subside or add instances for peak overloads by resizing your clusters. 

Amazon EMR also allows running multiple instance groups so that on-demand instanced can be used in a single group for processing power with spot instances in other group. This helps faster completion of jobs at a lower price. You can even take advantage of low price on one spot instance type over another by mixing different types of instances together. 

Amazon EMR offers the flexibility of using different file systems for your input, intermediate and output data. For example: 

  • Hadoop Distributed File System (HDFS) for running the core and master nodes of your cluster to process that is not required after the lifecycle of the cluster. 
  • EMR File System (EMRFS) for using Amazon S3 as a data layer to run applications on the cluster for separating the storage and compute, and persist data after the lifecycle of the cluster. It also allows independent scaling up and down of your storage and compute needs. Scaling of the compute needs can also be done by using Amazon S3 or resizing your cluster. 

7. AWS Integration

Integrating Amazon EMR with other services offered by the AWS can help in providing functionalities and capabilities of networking, security, storage and many more. Here are some of the examples of such integration: 

  • For the instances comprising the nodes in the cluster, Amazon EC2 
  • For configuring the virtual network in which you will be launching your instances, Amazon Virtual Private Cloud (VPC) 
  • For storing input as well as output data, Amazon S3 
  • For configuring alarms and monitoring cluster performance, Amazon CloudWatch 
  • For configuring permissions, AWS Identity and Access Management (IAM) 
  • For auditing requests made to the service, AWS CloudTrail 
  • For scheduling and starting your clusters, AWS Data Pipeline 

8. Deployment

The EMR clusters have EC2 instances which are responsible for performing the work that you are submitting to the cluster. When you are launching the cluster, the instances with the applications like Apache Spark or Apache Hadoop are configured by the Amazon EMR. You need to select the type and size of the instance that suits the cluster’s processing needs including streaming data, batch processing, large data storage, and low-latency queries. There are different ways of configuring the software on your cluster provided by the Amazon EMR. For example: 

  • Installation of an Amazon EMR release with applications that can include applications like Spark, Pig or Apache and versatile frameworks like Hadoop. 
  • Installation of several MapR distributions. Amazon Linus is used for the manual installation of the software on the cluster. For this, the yum package manager can be used. 

9. Monitoring

Troubleshooting of Cluster issues like errors or failures can be done by using the log files and Amazon EMR Management Interface. You will have the capability of archiving log files in Amazon S3 for storing log and troubleshoot issues even after the cluster has been terminated. There is also an optional debugging tool available in the Amazon EMR console that can be used for browsing log files based on tasks, jobs and steps. 

CloudWatch is integrated with Amazon EMR for tracking performance metrics for the cluster as well as the jobs within the cluster. Configuration of alarms is done based on metrics like what is the percentage of used storage or if the cluster is idle or not. 

10. Management Interfaces

There are different ways for interacting with the Amazon EMR including the following: 

  • Console 

This is a graphical user interface that can be used for launching and managing clusters. You need to specify the details of the cluster to be launched and check out the details of the existing clusters, terminated clusters and debug by filling out web forms. It is the easiest way to start working with Amazon EMR as no programming knowledge is required. You can get the console online from here

  • AWS Command Line Interface (AWS CLI) 

This is a client application that you can run on your local machine for connecting to the Amazon EMR and creating and managing clusters. There is a set of commands available in the AWS CLI for the Amazon EMR, you can use this for writing scripts that can automate the launch and management of the cluster.  

  • Software Development Kit (SDK) 

There are functions available in the SDKs that can call Amazon EMR for creating and managing clusters. You can even write applications for automating this process. It is the best way of extending and customizing the Amazon EMR’s functionality. The available SDKs for the Amazon EMR are Java, Go, PHP, Python, .NET, Ruby, and Node.js. 

  • Web Service API 

This is a low-level interface that uses JSON for calling the Amazon EMR directly. This can be used for creating a customized SDK that calls the web service. Now that we have discussed the benefits of EMR, let’s move on to the EMR use cases: 

Use Cases of EMR Use Cases of EMR

 1. Machine Learning

EMR provides built-in machine learning tools for scalable machine learning algorithms like TensorFLow, Apache Spark MLib, and Apache MXNet. Also you can easily use Bootstrap Actions and Custom AMIs for easily adding the preferred tools and libraries for creating your very own predictive analytics toolset. 

2. Extract Transform Load (ETL)

For cost-effective and quick performance of data transformation workloads (ETL) like sort, join and aggregate on large datasets, you can use EMR. 

3. Clickstream analysis

With EMR, along with Apache Hive and Apache Spark, you can segment users, deliver effective ads by understanding the user preferences. All this can be achieved by analyzing the clickstream data from Amazon S3. 

4. Real-time streaming

With EMR and Amazon Spark Streaming, analyzing events from Amazon Kinesis, Amazon Kafka or any other streaming data source is possible. This helps in creating highly available, long running, and fault-tolerant streaming data pipelines. Persist transformed insights to Amazon Elasticsearch and datasets to HDFS or Amazon S3. 

5. Interactive Analytics

With EMR Notebooks, you will be provided with an open-source Jupyter based, managed analytic environment. This will allow data analysts, developers and scientists in preparing and visualizing data, collaborating with peers, building applications, and performing interactive analysis. 

6. Genomics

EMR can also be used for quickly and efficiently processing large amounts of genomic data or any other large, scientific dataset. Genomic data hosted on AWS can be accessed by researchers for free. 

In this article, you got a quick introduction to Amazon EMR and how it has different log files’ types. Also, you got to understand the benefits of Elastic MapReduce. To become an expert in AWS services, enroll in the AWS certification course offered by KnowledgeHut. 

Joydip

Joydip Kumar

Solution Architect

Joydip is passionate about building cloud-based applications and has been providing solutions to various multinational clients. Being a java programmer and an AWS certified cloud architect, he loves to design, develop, and integrate solutions. Amidst his busy work schedule, Joydip loves to spend time on writing blogs and contributing to the opensource community.


Website : http://geeks18.com/

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Through an understanding of these processes, they will be able to design a solution best fit for the environment.Meeting stakeholders’ requirements: A particularly challenging aspect of software product development is to meet the requirements of stakeholders. A product usually has many technical and non-technical stakeholders. The aim of a solution architecture is to make sure all their requirements are taken into consideration. Stakeholders need to be informed about the processes, budgeting, and costs of product development on a regular basis. A solution architect performs this task by translating the technical details of the project into a language that non-technical stakeholders and management can understand.Taking project constraints into account: There are always certain limitations or constraints associated with a project, including:technologyscoperisks cost timequality    resourcesFor example, the technologies used for building a product should suit the requirements of its modules. The software documentation defines the scope of a project, which includes its goals, features, functions, and tasks. There is also a budget allocated for every project.Aspects like these are project constraints and they have their own limitations. A solution architect needs to understand all the constraints and compare them for making managerial and technological decisions as per the project goals.Selecting the technology stack for the project: A vital task performed by solutions architect is to select the right technologies for the development of products. The strategy of technical architecture depends directly on the technology stack that is chosen. Several different practices exist with regards to platforms, tools and programming languages. The function of a solution architect is finding which of these practices are most suitable for the project. It is a complicated task that requires assessing and comparing technology.Complying to the non-functional requirements: There are non-functional requirements as well that a software project has to meet. These requirements describing the system characteristics are called quality attributes. Non-functional requirements can differ according to the complexity of the product. The common requirements include security, maintainability, performance, usability, reliability, and scalability of a product. All these non-functional requirements are analyzed by the solution architect for ensuring product engineering meets these requirements. Main Roles and Duties of a Solution ArchitectConducting architectural evaluation, analysis, and design of enterprise-wide systemsStimulating appropriate design discipline and design tools like IBM RationalEnsuring delivery of robust system solutions by the application architecture team to the architect businessDeveloping, enhancing and maintaining established process and procedure of service design for assuring appropriate and robust service designWork with the enterprise architect for making sure the architecture and strategic blueprints are complied withForming part of a high-performance solution architecture team that supports the developmental effort of a business-oriented projectPlanning, designing and executing complex company level solution configurationPreparation and presentation of a test plan, lab reports, technical presentations and analyst briefings for covering different solution areasBe responsible for the best current practices and suggestionsCollaboration with the IT development team for ensuring suitable translation of architectural solution into robust and effective implementationMaking sure configuration management continues the way it shouldIdentification of customer requirements, analysis of alternatives and conducting product recommendations associated with platform, software and network configurationsWork with sales department for performing demonstration and conversing requirementsInitiate contact with the client to provide a complete team effortPrimary responsibilities:Understanding the needs of the company for defining system specificationsPlanning and designing the technology solution structureCommunication system requirements to the software development teamEvaluation and choosing suitable hardware or software and suggesting methods for integrationOverseeing assigned programs and guiding the team membersProviding assistance when technical problems ariseMaking sure the agreed infrastructure and architecture are implementedAddressing the technical concerns, suggestions, and ideasMonitoring systems to make sure they meet business goals as well as user requirementsSkills Required to become a Solution ArchitectThe role of a solution architect is a technical one and involves the translation of functional requirements into robust solutions. Individuals looking to get a job as a solution architect must possess AWS solutions architect certification and have a relevant degree along with certain skills, including:Technical literacy: A high level of technical literacy is required to become a solution architect. It allows them to figure out how a particular solution fits with the current structure of the organization. They also need to assist the development of requirements and specificationsAnalytical assessment: Solution architects are required to examine the current system of the client, which involves extreme analysis. They also need to analyze to determine the overall scope and requirements of the projectManaging schedule: Right time management skills are required for determining milestones and schedules for development and ensuring timely completion of deliverablesLeading the team: Solution architects need to know how to motivate and lead since they directly oversee development teams throughout the development lifecycles of projectsCommunication skills: Excellent verbal and written communication skills are also required since the role involves communication with clients, external vendors and team membersSolving problems: The system limitations or client specification can change during development. Solution architects need to use their problem-solving skills for changing directions quickly as per the updated limitations or specifications.When is Solution Architecture Needed by a Company?Technology consulting organizations can introduce solution architecture to the corporate structure if the integration process of the software system is not systematic. A solution architect is not required for all the projects. Solution architecture won’t be required if a single proven tech module is being implemented. However, it is advisable to consider solution architecture services when the projects grow to be more complicated, entailing different risks and processes. A solution architect is needed when:It is unknown which solution is the best fit for the company ecosystem: It is important that there exists a link between a particular project and enterprise architecture. Solution architectures make sure company environment standards are met by the solutionA digital transformation project is being run: Projects involving digital transformation requires businesses to reevaluate what they deliver to customers or how they deliver it. It cannot be done without linking business and technological tasks, which is what a solution architect doesThere are a lot of risks involved: In projects that involve different technological risks, uncertain requirements, implementation of multiple products or unapproved underlying technologies, it is necessary to have a solution architectA future product has to be presented to investors: In this case, solution architects help suggest suitable technologies for matching production requirements. They also communicate in clear and understandable business termsCommunications between engineers and stakeholders have to be set up: There can be a communication gap between a non-technical and technical specialist. Solution architects help bridge that gapThe project involves multiple teams: Larger projects require someone for managing the designers, business or technical architect teams for producing quality outcomes. To sum it all up, solution architecture forms the underpinning of all IT projects, regardless of whether the company actually adopts this practice or not. Deliberate introduction of solution architecture allows the building of the framework that aligns with skills, resources, and technology of defined business goals. Conventionally, mid-size and small companies do not practice solution architecture. The problems related to solution architecture are delegated across different roles with the product and development team. It is a good option for small projects that have predictable outcomes. However, a specialist will definitely be required if the enterprise architecture itself is complex with multiple software products being introduced into the ecosystem. A solution architect is a specialist for such needs.
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What are the Eligibility Requirements to Get AWS Certified?

AWS has dominated the field of cloud computing in recent years as a robust and infallible provider of cloud services. As more and more companies are shifting their workload to the cloud, cloud computing has become a must-have, core competency in the organization. AWS offers different levels for different certifications. If you are working in AWS, a certification will help you demonstrate your skills. So, you need to select one that matches your domain and experience. With an AWS certification in your hand, you will be able to display the most-in demand skills that are validated by none other than Amazon.  As per the RightScale State of the Cloud report of 2018, 68% of SMBs and 64% of the enterprises are using AWS to run their applications. A continuous stream of new, improved services, geographic expansion, and financial performance indicates that AWS is going to be in demand for a long time.Currently, AWS offers 11 different certifications. To earn these certifications, there are no set-in-stone steps. However, we have enlisted a few straight-forward steps that will help you create a plan to become AWS certified:The first step is to enroll in a training class. This will help you get an in-depth knowledge of AWS and cloud computing.Gather all the exams and study guides you can find and review them.Practice as much as you can. It will help reduce any stress you might have regarding the certification exam.Once you think  you are prepared, schedule the exam.It is important to choose the right certification exam to attempt based on your expertise, qualification and experience. The AWS certifications have four levels:FoundationalAssociateProfessionalSpecialty.Let’s learn about the certifications offered by AWS and their eligibility requirements:1. AWS Certified Cloud Practitioner – Foundational CertificationThis entry-level certification is the newest certification offered by the AWS. This was created to test the candidate’s knowledge of the AWS Cloud. In the Cloud Practitioner certification exam, the areas that will be covered include knowledge of AWS cloud and its infrastructure, fundamental principles of the AWS architecture, basic compliance and security measures, the shared responsibility model, identifying technical assistance and sources of documentation, defining billing, pricing models, and account management, key services and common use cases of AWS, AWS cloud’s value proposition, and operating and deploying principles. It is recommended to take this exam before you move on to associate or professional level certifications.To be eligible for this certification exam, a candidate must have: Basic knowledge of the IT services and solutions and how they are used in the AWS platform. Minimum of 6 months of working experience in AWS cloud in a sales, managerial, purchase, technical, or financial role.The average annual salary of an AWS Certified Cloud Practitioner is between $90,512 and $113,932.2. AWS Certified Solutions Architect – AssociateIf you know how to design distributed applications, then solutions architect certification exam is for you. It will allow you to validate your skills of designing, implementing, and managing applications using services and tools available on the AWS platform.The exam will test your knowledge of networking technologies and their application in AWS, working of AWS-based applications, connecting AWS platform to the client’s interfaces, building applications on the AWS platform that are secure and reliable, deploying hybrid systems with AWS components and on-premises data center, designing scalable and highly available systems, deploying and implementing applications on AWS, and troubleshooting, data security practices, and disaster recovery techniques related to AWS.The eligibility requirements for this certification exam include:At least 1 year of working experience in designing and deploying applications on the AWS platform. Expertise in at least 1 high-level programming language,  ability to identify the requirements of an application, defining best practices for securing the AWS application and deploying hybrid systems with AWS components is required.An AWS Certified Solutions Architect – Associate level has an annual income of $117,773 per year.3. AWS Certified Developer – AssociateThis Developer Associate Certification exam is all about how to develop and maintain applications on the AWS platform. You must have the knowledge and skills of writing code that can access the AWS applications from the custom business application using the AWS software.During the exam, your understanding of the core AWS services and basic architecture of the AWS platform will be tested. You must have had experience in designing, implementing, deploying, and maintaining AWS-based applications. Apart from this, you must also have knowledge of key AWS services like databases, change management services, workflow services, notifications, and storage services.One must satisfy certain eligibility criteria to take the AWS Certified Developer – Associate exam:Knowledge of the AWS architecture, services offered by the AWS and their uses. Proficiency in using the AWS platform for designing, building, and deploying cloud-based applications as well as applications built for Amazon SNS, SQS, SWS, DynamoDB, S3, CloudFormation, and Elastic Beanstalk. Knowledge of at least one high-level programming language. At least 1 year of working experience in designing and maintaining AWS-based cloud applicationsAn AWS Certified Developer- Associate’s average annual income is $130, 272.4. AWS Certified SysOps Administrator – AssociateThe SysOps Administrator certification exam is the only exam offered by AWS that is completely for system administrators.  To pass this exam, a candidate must have conceptual knowledge as well as technical expertise in operational aspects of the AWS. During the exam, you skills in using the AWS platform for deploying applications, transferring data between the AWS and the data centers, meeting the needs of an organization by selecting the right AWS service, knowledge of how to provision, secure, and manage systems deployed in an AWS environment will be tested.To be eligible for the AWS Certified Developer – Associate exam, the following are required: One or more years of working experience in operating and managing applications deployed on the AWS platform. Must be able to provide guidance on how to deploy and operate applications on AWS, define and identify the best practices available on the AWS for the complete project’s lifecycle as well as the solutions for the applications based on AWS, and understand how to operate, provision and maintain AWS based systems.Every year, an AWS Certified SysOps Administrator – Associate makes about $130,6105. AWS Certified Solutions Architect – ProfessionalA professional AWS architect is responsible for evaluating the requirements of the organization and then making architectural recommendations in order to implement and deploy AWS-based applications. To get this certification, a candidate must have experience and technical skills required to design applications on the AWS platform.The exam for the AWS Solutions Architect – Professional certification will include practices implemented for architecting the AWS-based applications. The candidate must have knowledge of the strategies used for cost optimizations. Also, they must know how to fulfill the application’s requirements by choosing the correct AWS service and how to migrate different, complex applications system to the AWS platform.To be eligible for this certification exam, a candidate must have:At least 2 years of working experience in designing and deploying AWS-based cloud architecture. Skills to recommend services that can be used to design, provision, and deploy AWS-based applications Familiarity with the practices involved in implementing the AWS application’s architecture. Expertise in high-level programming language.As an AWS Certified Solutions Architect – Professional, you will be able to earn $167,500 per year.6. AWS Certified DevOps Engineer – ProfessionalThis certification validates your skills to provision, operate and manage AWS-based applications. The focus of the exam is on the fundamental concepts of the DevOps movement – automation of processes and continuous delivery.During the certification exam, the candidate will be tested on concepts like the modern continuous delivery methodologies and their implementation in the CD systems, setting up, logging, and monitoring systems on AWS, implementation of scalable and highly available systems on AWS, and designing and managing tools required for enabling the automation of production operations.As a DevOps Engineer, a candidate must fulfill certain requirements to be eligible for the AWS Certified DevOps – Professional exam. This includes:Two or more years of working experience in provisioning, managing, and operating applications deployed in the AWS environmentExperience in developing code in a high-level programming languageKnowledge of automation and testing using scripting and programming languages as well as other development processes and methodologies like Agile.The average annual salary of an AWS Certified DevOps Engineer – Professional is $137,724.7. AWS Certified Big Data – SpecialtyThis specialty certification from AWS is for a candidate working in the field of data analytics and have worked with AWS services to design and architect solutions for big data. The certification exam validates the candidate’s skills to use the AWS services to extract the value from data.The areas covered in the exam include implementation of big data services of AWS through best architectural practices, automating the data analysis process using the AWS tools, providing best security practices for big data solutions, knowing how to design and maintain big data, and other AWS services like Athena, Kinesis, Rekognition, and Quicksight.To be eligible for the AWS Certified Big Data – Specialty exam, a candidate must satisfy certain requirements:At least 5 years of experience working in the field of data analytics. Experience in designing and developing robust, scalable, and cost-effective architecture for data processing. Understanding of how to define and architect big data services of AWS and how they exist in the lifecycle of data this includes how to collect, ingest, store, process or visualize.An AWS Certified Big Data – Specialty professional can earn up to $99,909 per year.8. AWS Certified Advanced Networking – SpecialtyThis certification will validate your skills of using the hybrid IT networking architecture and the AWS platform to perform complex tasks related to networking. To ace this exam, one must have experience in implementing and architecting network solutions and knowledge of using the AWS for networking.The areas covered during this exam includes how to design, develop, and deploy AWS-based cloud solutions, using the best architectural practices to implement core services, troubleshooting, optimizing network, implementing compliance and security design, automating the tasks of AWS for network deployments. Also, they must know how to design and maintain network architecture for the AWS platform and leverage analysis and automation tools used for networking tasks on the AWS platform.One must fulfill certain requirements to be eligible for the AWS Certified Advanced Networking – Specialty exam. They must have: Minimum 5 years of working experience in architecting and implementing network solutions. Knowledge and understanding of concepts and technologies used in AWS networking.An AWS Certified Networking specialist can earn up to $113,065 per year.9. AWS Certified Security - SpecialtyFor this certification, you will have to master the fundamentals of the security, the best practices used and have a deep understanding of the key security services on the AWS platform. You will be tested on topics like encryption, data protection, identity and access management, logging, infrastructure security, monitoring, and incident response.The certification exam will cover topics like how to use AWS services to get the desired security level depending on the deployment method and data sensitivity. This also includes using the best data protection techniques like encryption mechanisms, monitoring solutions and implementing logging for analyzing and detecting weaknesses and vulnerabilities in the infrastructure’s security.The eligibility requirements for the AWS Certified Security – Specialty exam are:At least 5 years of experience as an IT security personnel on designing and implementing security solutions. 2 or more years of working experience in securing AWS workloads and knowledge of using security controls for AWS workloads.The annual remuneration of an AWS Certified Security – Specialty professional is $122,155.10. AWS Certified Alexa Skill Builder – SpecialtyThis certification will help you demonstrate your skill in creating, deploying, and testing Amazon Alexa. If you are currently working as an Alexa skill builder, this exam is for you.The exam will cover concepts like the value of the voice, Alexa developer console, implementing security measures by following Alexa and AWS practices, and user experience design.Anyone wanting to get AWS Certified Alexa Skill Builder – Specialty must have:More than 6 months of working experience in a programming knowledge as well as using Alexa Skills Kit to build Alexa skills11. AWS Certified Machine Learning SpecialtyThis certification exam will validate your skills in creating, implementing, and maintaining machine learning solutions for different business problems.During the certification exam, the covered areas will be selecting the best machine learning approach for a given problem, designing and implementing machine learning solutions that are secure, scalable, cost-optimized, and reliable, and identifying the right AWS solution for creating and deploying ML solutions.The eligibility requirement for this certification is:1 to 2 years of working experience in using the AWS cloud for implementing concepts of Machine Learning as well as deep learning. Background in developing and data science.AWS Services have become a major player in the internet infrastructure industry. With the AWS certifications in your hand, you will be able to beat the crowd for the best opportunities. Knowing the eligibility requirements for AWS will help you select which AWS certification is the best for you. This will allow you to prepare for the exam accordingly. All the figures mentioned above are accurate as of August 2019 and are sourced from online job portals such as Indeed.com, Salary.com, Glassdoor.com, etc.
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How Much Salary do Top AWS Certified Professionals earn?

Since the advent of Amazon Web Services, the landscape of the internet’s infrastructure has vastly changed. The services are becoming quite popular because of the ease and scalability they provide in a number of processes. Getting an AWS certification today will help you stay ahead of the crowd. As per a recent salary survey from Global Knowledge, the average yearly salary of an AWS Amazon Certifications holder is $113,932. Salaries have gone up by 10% in just one year and with AWS being the primary computing platform in hundreds of enterprises, there is quite a good chance that they will continue growing.Getting an AWS certification will help you land a better, and more lucrative job. The certification will also open doors for jobs like:Operational Support EngineerThe job of an operational support engineer includes monitoring and resolving operational issues that are reported. Also, they assist in any environment upgrade. Their average annual salary is between $59,000 and $92,000.Cloud Software EngineerA cloud software engineer designs and implements new systems and software services in a high-level programming language like C++, JavaScript, Python, Ruby, etc. They also mentor new junior employees and explain complex processes to non-technical members of the team. They can earn anything between $63,000 and $93,000 per year.System Integrator – CloudFor this job, you need to have a thorough understanding of information systems and cloud computing. They work with the team to help troubleshoot and support complex development processes. A System Integrator can have an average annual income of $81,000.Cloud DeveloperAs a cloud developer, you will be responsible for developing enterprise-level applications and software services. You must have knowledge of common cloud orchestration tools as well as working experience as a software developer to get a high-paying job as a Cloud Developer. The average annual salary of a cloud developer is $95,000.DevOps EngineerA DevOps Engineer is responsible for designing AWS Cloud Solutions that can significantly impact and improve your business. Also, they implement patching or debugging and perform the required server maintenance. Depending on their experience and the company they are working for, the average annual income of a DevOps Engineer varies between $93,000 and $144,000.AWS Solutions ArchitectThe job of an AWS Solutions architect is to design, build, and maintain scalable, cost-efficient, and highly available AWS cloud environments. They keep up with the latest updates in the field of cloud computing and based on this knowledge, make recommendations regarding the AWS toolsets. The average annual income of an AWS Solutions architect ranges between $98,000 and $150,000.AWS SysOps AdministratorTo effectively provision, install, configure, operate and maintain software, virtual systems, and infrastructure, you need an AWS SysOps Administrator. They are also responsible for building dashboards for reporting and maintaining analytics software. Their average salary varies between $111,000 and $160,000 per year.Senior AWS Cloud ArchitectAs a senior AWS cloud architect, they work with engineers and customers. So, they are the technical leader as well as interface with the stakeholders from the client-side. Their responsibilities include leading the implementation process, delivering technical architectures, and successfully integrating the customer environments with new technologies. The average yearly remuneration of a senior AWS Cloud Architect is $165,000.According to Forrester, by 2020, the market for the Amazon cloud will reach $236B. With more and more companies adopting cloud services, the shortage of AWS Certified Professionals continues, driving up salaries and incentives. The AWS provides associate and professional level certification for developers, solutions architects, and system operations administrators to help bridge this gap. Here, we have explained in detail all the different certifications offered by1. AWS Cloud Practitioner – FundamentalThis certification is for managers, sales, C-level executives, and marketing associates who need to have a basic knowledge of the AWS cloud. To prepare for this certification, there is a digital course offered by AWS for free. The average annual salary of a professional holding an AWS Cloud Practitioner certification is $113,932.2. AWS Certified Solutions ArchitectThis certification is offered at two levels; the Associate level and the Professional level. To advance to the professional level, you must first earn an associate-level certification.Solutions Architect AssociateAWS Certified Solutions Architect Associate one of the most popular AWS certifications, it is mostly preferred by professionals who are just entering the arena of cloud architecting and want to use the AWS platform for designing distributed applications. This certification will help you demonstrate your skill in designing and developing efficient and effective solutions on the platform of Amazon Web Services. Before taking the exam, you must know how to:  Use the AWS platform to deploy on-premise apps  Design and deploy highly available and scalable systems on AWS  Select the AWS service according to your requirementsIn the United States and Canada, the average annual income of an IT professional with AWS Certified Solutions Architect – Associate Level is $130,883.Solutions Architect ProfessionalThis AWS certification will display your advanced expert skills in designing the applications and distributed systems on the AWS platform. You need to have the Associate level certification to take up the exam. Before you take the exam, you must have the following skills:2+years of working experience in designing and deploying cloud architecture on the AWS platform.Using the AWS for migrating complex, multi-tier applications.An IT associate with the AWS Certified Solutions Architect – Professional can earn an average income of $148,456 per year.3. AWS Certified DeveloperAWS Developer Certification will allow you to demonstrate your skills in developing and maintaining AWS applications. To achieve this certification, you must know how to:  Select the right AWS service according to the application  Write optimized code in a high-level programming language  Interact with other services from the application using software development kits (SDKs)  Maintain application security at the code levelThe average salary of an IT professional with the AWS Certified Developer certificate is about $130,272 in North America.4. AWS Certified SysOps AdministratorSysOps Administrator certification from the Amazon Web Services will demonstrate how well you can deploy, scale, migrate, and manage systems on the AWS platform. To ace this certification, you must have the following skills:  Managing the cloud applications deployed on the AWS platform  Controlling and implementing the data flow to and from AWS  Identifying the cost control mechanism of the operations  Migrating the on-premises apps to the AWS platformIn North America, the average salary of an AWS Certified SysOps Administrator is about $130,610.5. AWS Certified DevOps EngineerThis certification validates your skills to provision, manage, secure, and operate distributed application systems and the AWS solutions. For obtaining this certification, you must have professional-level certification for SysOps Administrator as well as Developer. Candidates planning to take up this exam must have a thorough understanding of the following:  How to provision and manage AWS environments  Implement and manage continuous delivery methodologies and systems on the AWS platform  Governance processes and security controls  Automating the operational process by maintaining the tools required to do soIn the United States and Canada, the average annual earnings of an AWS Certified DevOps Engineer is about $137,724.6. AWS Certified Big Data – SpecialtyAs an individual with the AWS Big Data certification, you will be able to display your skills of designing and managing AWS solutions of organizations that use business data for extracting actionable intelligence and valuable insights. All candidates must have at least one AWS associate-level certification. Also, 5+years of working experience in data analytics is recommended. With this certification, an IT professional can bag an annual pay of more than $130,000.7. AWS Certified Advanced Networking – SpecialtyThis AWS certification validates your skills in designing and deploying AWS to scale as part of an IT network hybrid architecture. To get this certification, you must have one of the AWS Associate credentials. Apart from that, +5 years of working experience in managing and architecting network solutions for the enterprise is recommended.8. AWS Certified Security – SpecialtyThis certification validates your skills to use advanced methods to secure the AWS platform. This includes data protection by using encryption techniques. For this certification, you must have any one of the Associate certifications or an AWS Cloud Practitioner certification. Also, +5 years of working experience in securing the AWS platform is a must.9. AWS Certified Alexa Skill Builder – SpecialityWith this certification, you will be able to create, test, and deploy Amazon’s Alexa. To be eligible for this certification, you must be an expert in a high-level programming language and have at least 6 months of experience working with Alexa skills kit.10. AWS Certified Machine Learning – SpecialtyYou must take this certification for demonstrating your skills of designing, implementing, and maintaining the machine learning solutions of the organization. For this, you must have a data science and development background as well as 1-2 years of working experience with machine learning and deep learning. Since all the AWS services are continuously updated, you need to take the recertification exam every three years. The market for cloud services is rapidly evolving. AWS is releasing new services and products to stay in the competition. New certifications are launched along with new solutions to help validate the skills of an IT professional. The importance and need for validating the AWS skills with the certifications are only going to grow in the future. There are so many people working in the IT industry. You need something that will help you outshine the others. AWS provides all the resources that you will need to get the certification including hands-on practice labs and questionnaires. Apart from this, there are exam readiness workshops and authorized training courses that will help you learn the skills and focus on the exam.All the figures mentioned above are accurate as of August 2019 and are sourced from online job portals such as Indeed.com, Salary.com, Glassdoor.com, etc. 
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How Much Salary do Top AWS Certified Professionals...

Since the advent of Amazon Web Services, the lands... Read More