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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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Google Cloud vs AWS- Which is Better: A Comparison

Cloud computing has become an integral part of the IT sector. The days of struggling with complicated networking and on-premise server rooms are long gone. Thanks to cloud computing, services are now secure, reliable, and cost-effective.  When we talk of top cloud computing providers, there are 2 names that are ruling the markets right now- AWS and Google Cloud. Here, we are going to compare both of them, determining the pros and cons of both. 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However, other cloud computing providers like Google Cloud and Azure have seen significant growth too.  Let’s take an in-depth look at these two market leaders in cloud computing to help you select the best one for your organization. Google Cloud Platform With all the different solutions and services provided by the Google Cloud Platform, you will be able to use the same hardware and software infrastructure used by Google for its own products like Gmail and YouTube. Their first service, Google App Engine, was launched in 2008 in public purview. Here are some of their products: Google Compute Engine Google Cloud Bigtable Google Cloud CDN Google Cloud Datastore Google Cloud DNS Google Cloud Functions Google Container Engine Google BigQuery Google Storage According to the Chief Executive Officer of Google, Sundar Pichai, Google Cloud Platform is one of the top three priorities for the company. 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For virtual machines, Google cloud uses KVM while AWS EC2 uses Xen. Both the technologies offer predefined configurations with a specified amount of network, RAM, and virtual CPU. However, Amazon EC2 refers to them as instance types while Google Compute Engine refers to them as machine types. With AWS EC2, you can equip up to 3,904 GB of RAM and 128 vCPUs. For Google Compute Engine instances, you can equip 3,844 GB of RAM and 160 vCPUs. Google Cloud also allows departing from the predefined configuration and customizing your RAM and CPU resources for fitting your workload. There are other types including AWS EC2 Spot Instances and Google Cloud Preemptible VMs. 2. StorageThis is a very important consideration as it will directly impact the performance of your applications like max IOP per instance/volume, expected throughput (IO), and the ability of bursting capacity for short times. When comparing AWS and Google, there are two types of primary storage that need to be considered: object storage and block storage. Block storage is the virtual disk volume that is used in conjunction with cloud-based virtual machines. AWS EC2 provides this with its Elastic Block Store (EBS) while Google Compute engine uses persistent disks. Object Storage, also known as distributed object storage, are hosted services used to store and access a large number of blobs or binary data. Google Compute Engine uses Google Cloud Storage to provide this service while AWS uses the S3 service for this. Apart from the above-mentioned, both the providers also allow the usage of disks locally attached to the physical machine that is used to run the instance. When compared to persistent disks, this local storage provides very low latency, very high input/output operations per second, and superior performance. You can even achieve several GBs of read and write speeds with this storage, which is incredibly huge. AWS EC2 calls them instance store volumes while Google Cloud refers to them as local SSDs. Google Cloud allows attaching local SSDs to any type of instance. In the case of AWS, only the X1, R3, M3, I3, I2, HI1, G2, F1, and C3 can support instance store volumes. In 2017, Google Cloud announced a price cut on local SSDs for preemptable and on-demand instances. 3. NetworkBoth the providers use different partners and networks for interconnecting their data centers and delivering content to end users via ISPs. For accomplishing this, different products are used. When it comes to Google Compute Engine instances, the achievable network capacity is based on your VM’s CPUs quantity. For peak performance, every core is provided with a 2 Gbits/second cap. Every core increases the network capabilities to a maximum of 16 Gbps for every virtual machine. Amazon EC2 instances, for the large instance sizes, have a maximum bandwidth of 25 Gbps. 10 Gbps/second is the maximum speed for standard instances. When you are comparing the network capabilities of both the providers, network latency plays a major part. When you are working with the business with visitors from a particular geographic location, latency is important. For example, if you have a website in Frankfurt and more than 90% of your customers are from Germany, you will benefit from placing the site on a server in Germany rather than placing it in Asia or the United States. This can make a difference of about 2 seconds. It includes other factors as well like TTFB, DNS, etc. Both, the AWS and Google Cloud, have multiple locations across the globe for you to choose from. On a latency test conducted using Cloud Harmony that offers impartial, reliable, and objective analysis of the performance, 50 servers located around the globe were utilized. The results showed that Google Cloud offered better latency. But the test was run from a specific location. Different location can give different results. For measuring ping times and latency, you can try spinning up small instances on both the providers and running your own tests. 4. BillingBoth providers have a different approach for billing. Both of them also have a very complicated way of doing it. You can try checking out their monthly calculators: Google Cloud Platform Pricing Calculator AWS Simple Monthly Calculator Calculating this monthly amount is not an easy task. There are tools like Cloudability and reOptimize that are built entirely for helping you better understand your bills. Google Cloud Platform uses its BigQuery tool for providing estimated exports. AWS has a dashboard providing insights to your bill. However, both of the cloud platforms are working their best to reduce costs and making billing easier. In September 2017, AWS announced per second billing. This works great for clients who are working on spinning up new instances and carry out a large amount of work in a short duration. After this, Google Cloud also launched the per second billing. This just shows the intense competition between the two where they are simultaneously launching new products. If you are seriously invested in one of the platforms, they will provide you with various ways to save costs. Reserved Instances is one such way by which AWS EC2 offers a significant discount and when used in a particular availability zone, provides a capacity reservation. There are 3 types of reserved instances: Standard Reserved Instances Scheduled Reserved Instances Convertible Reserved Instances Google Cloud uses Committed Use Discounts to all the customers of Compute Engine. So basically, in return for discounted prices, you have to buy the committed use contracts. After analysis, it was found that on using the 1 year standard RI of AWS vs the 1 year committed use discount of Google, the Google’s environment cost 28 percent less than AWS. The 3 year program for both the discount types led to 35 percent less cost in Google environment as opposed to the AWS. 5. Support and UptimeBoth, the AWS and Google Cloud, have multiple community forums and documentation that can help you understand their services for free. AWS Forums Google Cloud Forums AWS Documentation Google Cloud Documentation However, you will have to pay for instant support or assistance. Both of them have support plans. We strongly recommend that you read the fees involved in both before availing of the assistance services. Both of them offer unlimited number of billing and account support cases without any long-term contracts. For Google, there are 3 levels of support available - Silver, Gold, and Platinum. The cheapest plan is the Silver one starting at $150/month. The Gold plan starts at $400/month. You will also be charged a product usage fee of minimum 9% which will decrease as your spend increases. AWS provides 4 levels of support - Basic, Developer, Business, and Enterprise. The cheapest paid plan is the developer starting at $29 per month of 3% of your monthly usage. The Business plan starts at $100 per month along with 10% of product usage fees which will also decrease as the spend increases. When it comes to monthly uptime percentage, both have SLAs providing at least 99.95%. For staying up to date with the incidents, you need to subscribe to their status page. However, both the providers have delayed updating their status dashboards. With AWS, you have the advantage of having different machines within multiple availability zones per region. On the Google Cloud, the same machine per region might have all your instances. However, with Google Cloud you have the ability of live migrating the virtual machines which allow addressing issues like patching, updating and repairing without worrying about the machine reboots. 6. SecurityIn the Clutch’s Second Annual Cloud Computing Survey, it was found that about 70% of professionals felt secure storing their data in the cloud than on their previous, on-premises legacy systems. With Google Cloud Security, you get the benefit of a security model that has been developing over a period of 15 years and is securing products like Gmail, Search, etc. There are about 500 full-time security professionals employed by Google. It provides security features like: All the data in the cloud platform services and in transit between Google, data centers, and the customers is encrypted by default. 256-bit AES is used for encrypting the data stored on persistent disks. A set of regularly changed master keys are used for encrypting the encryption key. Regular audits are used to commit to the security certifications of the enterprise for PCI, SSAE16, ISO 27018, ISO 27017, and HIPAA compliance. Thanks to Google’s relationship with the biggest ISPs in the world, there are fewer hops across the public internet which improves data security. The layers of the storage stack and Google application require that all requests coming from other components must be authorized and authenticated. Google Cloud’s Identity and Access Management uses predefined roles for giving granular access to the specific resources of the Google Cloud Platform. This helps in preventing unwanted access. AWS platform also has a security model with the following features: All the data in transit between the AWS, data centers and the customers is encrypted. 256-bit AES is used for encrypting the data stores on EC2 instances. All the encryption keys are encrypted using regularly changed master keys. It allows creating private networks and controlling access to the applications and instances through AWS WAF’s web application firewall capabilities and Amazon VPC’s network firewalls. AWS Key Management Service allows selecting whether you or AWS will be managing the encryption keys and controlling them. Using AWS CloudHSM, you get hardware-based cryptographic key storage that satisfies all the compliance requirements. You can define, enforce, and manage user access policies using AWS Identity and Access Management (IAM), AWS Directory Services, and AWS Multi-Factor Authentication. It has service features like SOC, PCI, HIPAA, ISO and other compliance standards that are audit-friendly. From the above it is clear that both cloud computing providers have their pros and cons. Google Cloud has seen rapid global expansion over the past few years. It is also the one to go for if you favour speed and affordable pricing. AWS has been a long-standing name in the history of cloud computing. AWS started it all and is still being copied by other major players in the market. AWS redundancy, support and availability per region have helped it stay at the top. Rest assured, the constant battle between both the cloud providers will result in increased performance, more services and products, and lower prices benefitting hosting partners and customers. You can try the AWS Certification course  for learning about all the services offered by AWS. 
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Google Cloud vs AWS- Which is Better: A Comparison...

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Which Azure Certification is Good for You?

Over the past few years, there has been a paradigm shift in the world of computing, with cloud computing being on the forefront. It is a computing model based on the internet and it provides on-demand data and shared computer processing to computers and devices.  With cloud computing, a pool of computing resources can be shared and accessed. This allows the transfer of information in an effortless manner. Cloud computing has enabled enterprises and users to store and process data in third-party data storage centers. This makes it cost effective for companies as overhead costs for IT infrastructure is avoided.  Since a large majority of organizations all over the world are adopting cloud computing, there is a high demand for professionals who are skilled in this particular area. Cloud computing experts have a wide range of options in addition to getting lucrative salaries, which is why it is an extremely sought-after position in the world of IT. Do you need to be cloud certified? Before thinking of Azure certification, it is important to know whether getting any cloud certification is worth it for your career. Immense growth of the cloud: The cloud has taken the IT industry by storm and its use is growing by leaps and bounds. Looking at the figures provided by IDC (International Data Corporation), Gartner, Forbes, and others, it is evident that the market revenue for cloud services is increasing at an annual rate of 20% on an average.  Businesses of all sizes are being powered by the cloud: Both small businesses and big enterprises are being positively impacted by the cloud. Enterprises have the confidence of PaaS being a scalable and secure application development platform of the future. It is predicted that in a few years, a majority of IT expenditure will amount for cloud-based infrastructure, application, middleware and business process services. Shortage of cloud expertise: Cloud services are becoming the focal point of the IT infrastructure of enterprises. Businesses will have tremendous opportunity if they decide on moving to the cloud. However, they aren’t actually being able to utilize these benefits, mainly because skilled resources are lacking. Lack of skill can cause a company to lose revenue. Also, the skill gap is  preventing several enterprises from deploying more cloud platforms.  Why Azure Certification over AWS Certification? An IT professional considering taking a cloud certification may be confused whether to go for Microsoft Azure or AWS (Amazon Web Services) certification. For such professionals, the following points should be considered before making a decision: Azure is growing rapidly: The rate of growth of Azure has been better in comparison to AWS over the recent past. It seems Microsoft is beginning to bridge the gap that exists between the two. Microsoft is also improving integration with on-premise software. Azure for Microsoft products: Microsoft has always been associated with large enterprises. Microsoft’s products and services are being used by almost all Fortune 500 companies. Azure remains a worthy proposition for those enterprises that have heavily invested in Microsoft based developer skills and technology.  Open source and Linux incorporation: Microsoft didn’t have an open source community until recently. On the other hand, AWS has been open source since the beginning, which is what gave it an advantage over Azure in the open source cloud hosting space. Microsoft and Azure are incorporating open source both in the cloud and on-premises. Moreover, around 1 in every 3 Azure virtual machines run on Linux. .NET Core and PowerShell are open sourced, Hyper-V will run Docker and SQL Server is running on Linux.  What certifications and exams are on offer? Microsoft has a vast platform with lots of features. Furthermore, new features are released by Microsoft on a regular basis. As such, the landscape of Azure continuous to evolve regularly. Having said that, with an Azure certification exam, you will gain a good understanding on certain feature sets that form the core of the entire platform. These features include Cloud Services, Web Apps, Messaging, Storage, Virtual Machines and a lot more.  Microsoft doesn’t have certifications specifically for each set of Azure features. Instead, the certifications target a particular work role through more encompassing exams. The three main roles targeted in this regard are IT Professional, Developer and Architect. Hence, the materials for each specific exam do end up overlapping, although they target a particular work role.  Why Microsoft Azure Certification? Getting certified in Microsoft Azure is indicative of a skill that certainly increases the chances of a candidate getting hired. Given the increasing demand, there has also been a drastic increase in opportunities for Microsoft Azure certified aspirants in recent years. According to reports from Microsoft, more than 1000 new customers daily sign up to MS Azure. This means that around 365,000 companies adopt Azure over the course of a year More than 57% of the Fortune 500 companies are using Azure With the help of Azure, the commercial cloud revenue of Microsoft has increased by 104%.  The UK government has officially accredited MS Azure There is also MS Azure Government offering that is backed by the US Government.  Key reasons to get a certification in Microsoft Azure Public cloud is on the focus: Around 88% of companies have already used the public cloud, 13% of which are already running over 1000 virtual machines in the public cloud. It is an impressive statistic that should convince you to take some time to learn cloud technologies such as MS Azure. Microsoft Azure holds a fair share of the market: Azure is catching up to its competition at an amazing rate. In fact, a recently conducted survey has found the user base of Azure to be quite comparable to that of AWS.  A future-proof technology: The rate at which cloud technologies such as Azure are evolving is tremendous. It is growing at a rate that is faster than the IT sector in its entirety.  Easy to learn and adaptable: Microsoft has monopolized the American personal computer market. Most regular users are familiar with the Windows operating system from Microsoft. What this means is that the learning curve for Microsoft is flatter as compared to other platforms. It is definitely advantageous to be aware of the working principles of Azure. If you are exposed to Microsoft tools at work, you will find it easy to learn concepts like Operational Insights and Azure automation.  Extreme Potential: The IT space is set to be dominated by the cloud infrastructure. The potential of MS Azure is evident from its rate of growth, which is faster than any other cloud services provider. Extremely efficient tool: Azure can handle most of the conventional tasks of designing, deploying and managing platforms. For gauging the efficiency of cloud platforms such as Azure, the following factors need to be considered: The value added to a large app development project Assistance provided to the Ops facet of Dev/Ops Integration provided with Powershell integration Microsoft Azure meets all the needs for satisfying millions of users across the world.  Which certification exam should you take? The industry recognized Microsoft Certified Professional (MCP) certifications demonstrate your IT professional and developer technical expertise through various industry-recognized exams. On passing your first qualifying MCP exam, you will automatically become a Microsoft Certified Professional. Note that the Microsoft Certified Professional(MCP) certification is no longer available, but will be added to your transcript when you pass an MCP exam. However, you may not be able to get all the program benefits until you successfully earn your first certification. The main consideration is which exam should you take first? To decide that you need to consider the following factors: Your technological experience: The experience you have in technical field will help you determine whether you should go for advanced certification or start with a fundamental one. For instance, a professional having 2 years of experience can’t take up architect-level certification. A strong technical background is a must if you are willing to take an architect-level certification Your present job role: It is always advisable to take a certification that is relatable to your present job role. For instance, a windows or network admin should consider attempting Azure Infrastructure Solutions whereas a .NET developer may attempt Azure developer certification. If you are a professional who is completely new to the technology, it is recommended that you first begin with the Fundamentals certification.  Your objective: Any certification that you wish to attempt should align with your goal for the future. For instance, if your aspiration in the future is to become a big data architect, you should first take a big data cloud certification followed by an architect level certification. There is a prerequisite for each exam. Although not mandatory, a good background prepares you for job roles in future that align with the certification you plan on attempting.  Azure certifications for IT professionals In 2018, new Azure certifications were added for the IT professionals and some of the existing ones were retired. The new Azure role-based Azure certifications were launched after getting feedback from the previous exam takers. To select the best certification, you must know about all the certifications Microsoft has to offer. Here, we are providing you with six different Azure Certifications path based on the roles: Azure Fundamentals AZ-900 is the foundational level exam created for IT professionals wanting to validate their knowledge of the Microsoft Azure platform. You can take this exam even if you are not from a technical background but have a basic knowledge of the cloud concepts. This exam is also a stepping stone for other associate and expert level Azure certifications. The exam will cover the cloud concepts, the core services of Azure, Azure support and pricing, and security, trust, compliance, and privacy. The exam is available in English and costs $99 USD. Azure Administrator Associate For this role, you need to pass Exam AZ-103. To be eligible for this exam, you must have an understanding of Azure applications, cloud, operating systems, and storage infrastructure. Apart from this, you must know how the virtualization tools and networking components work. Having a basic understanding of Command Line Interface and PowerShell will act as an advantage. In the exam, there will be a number of different domains covered including Implementing and managing storage, configuring and managing virtual networks, managing Azure resources and subscriptions, managing identities, and deploying and managing virtual machines. It is available in English and costs $165 USD. Azure Developer Associate For this role, you need to pass AZ-203 exam. The prerequisites for this exam include expertise in developing apps and services by implementing tools and technologies provided on the Azure platform. At least 1 year of working experience in developing solutions that are scalable is required. Also, the candidate must be proficient in at least one programming language supported by the cloud. During the exam, you will be asked questions regarding developing for Azure storage, developing Azure infrastructure as a solution for service compute, implementing Azure security, troubleshooting, monitoring, and optimizing Azure solutions, and connecting and consuming services from third-parties and Azure. The exam is only available in English and costs $165 USD. Azure Solutions Architect Expert You need to pass two exams for this role, AZ-300 and AZ-301. For the AZ-300 exam: Microsoft Azure Architect Technologies, you must have at least 1 year of experience working with the Azure platform. A basic knowledge of data management, identity, security, and IT operations is also required. Also, you must be familiar with DevOps, Azure administration, and Azure development. The exam covers several domains including deploying and configuring infrastructure, implementing security and workloads, creating and deploying apps, architecting solutions using cloud technology, developing for the cloud, securing data, and implementing authentication. The exam, costing about $165 USD, is only available in English.  For the AZ-301 exam: Microsoft Azure Architect Design, the prerequisites are the same as for the AZ-300. However, you also need to pass the AZ-300 exam to be eligible for the AZ-301 exam. The domains of this exam include determining requirements of the workload, designing for security and identity, designing a strategy for business continuity, designing a solution for data platform, designing to deploy, migrate, and integrate, and designing a strategy for infrastructure. The exam is only available in English and costs $165 USD. Azure DevOps Engineer Expert The exam for this role is the AZ-400: Microsoft Azure DevOps Solutions. To be eligible for this exam, candidates must have knowledge of Azure administration and development. You must have the ability of designing and implementing DevOps practices for version control, infrastructure as code, configuration management, releasing, compliance, building, and testing using the Azure technologies. Also, you must be proficient in Agile practices. The exam will include domains like designing a DevOps strategy, implementing continuous integration and delivery, DevOps Development Processes, continuous feedback, dependency management, and application infrastructure. The exam costs $165 USD and is only available in English. Azure Security Engineer Associate For this new role, you need to pass the AZ-500 exam: Microsoft Azure Security Technologies. The prerequisites for this exam include knowledge of how to implement security controls on the Azure platform, virtualization, Amazon Kubernetes Service, and cloud N-tier architecture. You must have the ability of using security tools for recognizing and addressing vulnerabilities and protecting applications, data, and networks by implementing the security solutions. Expertise in maintaining security status, identity and access management, and scripting and automation is also required. The domains covered in this exam include management of identity and access, and security operations, implementing platform protection, and securing applications and data. The exam is available in English and costs $165 USD. Now that you have all the information regarding the different Azure certifications, you can select the one that best suits your needs. To learn about the Microsoft Azure cloud platform, check out Microsoft Azure Fundamentals course.  
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Which Azure Certification is Good for You?

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What are the Best Free Cloud Storages in 2019?

Cloud storage helps slash data on hardware in a remote physical location, which can be accessed from any device with the help of the internet. Below are some of the best free cloud storage in 2019: 1. Microsoft OneDrive: Microsoft provides a cloud storage service and offers 15 GB of free storage to its users. OneDrive, earlier called Skydrive, can be used to store important files securely at one location and these can be accessed from anywhere and from any compatible system. Cloud storage works like a traditional hard drive, the difference being that it is available online and can be accessed from anywhere around the world. Also, companies offer to extend the storage capacity if required. Files of any format can be stored in Microsoft OneDrive, though it is better for Office documents. It offers cross-device and cross-platform design, which implies that you can resume your work from where you left without the need for saving it or making a copy of it. Due to its Office365 integration, it is easy to share your content and files with other users and hence facilitates collaboration among a team. One prominent feature of Microsoft OneDrive is Files on demand. This means you can access your files stored in the cloud from anywhere, without downloading them to your local device which saves a lot of local storage. Since the files are stored and changes are saved in the cloud, the recovery is very convenient in case the system you are working on gets crashed, damaged or stolen. You can easily upgrade your account by buying extra storage in case you are running low on memory.  The important features of Microsoft OneDrive: Create and share folders Save notebooks to OneDrive View Office documents online Upload multimedia files from your personal mobile phones. Real time co-authoring File type support Desktop synchronization Search and discovery tools Device reports Documents storage and tracking Permission management Photo management Microsoft Office integration Device specific selective sync 2. Dropbox: Dropbox is operated by the American company Dropbox, Inc., and provides cloud storage and is used for file sharing and collaboration. Dropbox is available as an application for desktop for Windows, Linux and Macintosh operating systems. It is also available as an app for Android, iPad, iPhone and Blackberry. It provides a limited storage capacity of 2GB, which can be upgraded up to 100 GB by purchasing from several plans offered. The upgraded version of Dropbox is called Dropbox Plus. Upgrading to this version offers many benefits like automatic camera roll back up, which implies that all the photos that you click from your personal mobile phone get backed in Dropbox.  Dropbox provides a robust API that allows other apps to collaborate with it and use it for file storage and sync. Dropbox does not require a complicated upgrade or timely installations. It is mainly focused on file exchange. It does not limit the number of files you can share or a number of users you can share with. You can even share your files with users who do not have a Dropbox account. It supports the exchange of files among any operating system and any device.  Dropbox facilitates easy collaboration among team members. If you edit or make changes to any file that is shared with your team, they will receive a notification about the changes made. Teams can communicate and edit files at a minimal cost. You can easily get started with Dropbox by just downloading the app on your phone. After you create an account, you can start sharing your content. You can even use it offline if you sync your local storage or additional account data with it. To ensure the security of your stored files, Dropbox is designed with multiple layers of protection.  Layers of protection include the following: Dropbox files are encrypted using 256 bit Advanced Encryption Standard (AES). It uses Secure Socket layer or transport layer security to secure data being exchanged with Dropbox apps and servers. Dropbox applications are regularly tested for security threats and if such vulnerabilities exist, it is fixed immediately. During login, two step verification is available to provide additional privacy. The important features of Dropbox are as follows: Automatic updates File storage and file sync Offline access Manually set bandwidth Automatic organization and backup Preview and download Any device accessibility Large files sharing Easy link sharing 3. Google Drive Google Drive is a file storage and sharing service offered by Google. The first 15 GB is free. You can store any kind of files like photos, videos, design, drawings, recordings, and stories. Just like most other cloud services, you can upload your files online, and can access it from anywhere and any device. You can even invite people to view, download or contribute to your project.  Google drive provides storage options to any kind of files such as images, sheets, pdf, videos, word documents etc, one can even save their email attachment in google drive directly through Gmail without going through the hassle of moving files. One of the greatest features of Google Drive is that it allows the user to view the file in the browser without having to download it. The files that can be previewed are Adobe, Microsoft Office, images, audios, texts and video files, such an option is not provided by most of the zero knowledge services as those services are unable to decrypt the files. Google Drive's versatility makes it more user-friendly than any other storage platforms. Significant features of Google Drive are:  Google drive provides 15 GB free storage on signing up. With the assistance of Google's homegrown office suite, Google docs and other third party applications it is more productive and efficient than most other storage options. It is very versatile as one can store almost any kind of files and preview the same without downloading it. Google drive can be accessed by logging in with your Google account. Many different types of programs can be integrated with Google drive. Google drive's browser interface is fairly intuitive and user friendly. With the help of Google client, one can make optimum use of its sync capabilities. File replication. It provides third party applications library. The only drawback Google Drive has is that it does not provide any specific way to share files, however, it is one of the best storage options as its strength surpasses its weaknesses. 4. pCloud Though pCloud is new in the market compared to its counterparts, it has emerged as a versatile cloud solution for both business and personal use. The features of pCloud which make it stand out among other cloud services, are as follows: pCloud crypto: It provides you with an option to secure your files and data with encryption on your device before uploading on cloud to protect them from any unwanted and insecure access. Lifetime subscription: Unlike other cloud services available in the market, pCloud offers a lifetime subscription, that means you can use its services permanently without going through limited and expensive subscriptions. The advantages of using pCloud are as follows: pCloud rewind: The main reason why people go for cloud storage is data recovery in case of any issue occurring in the local device. It should be easy to recover  files in case it is lost due to corruption, virus, or hardware problems. To ensure this, pCloud stores five separate copies of every file you upload at three different locations at a centralized data center facility in Dallas, Texas, so you always have a copy of your file available for download. pCloud has a feature called pCloud rewind which tracks and saves your file history from last 30 days in case if you make any mistakes or accidentally deleted your original file. You can also go for long periods of history by including the extended file history add on (EFH) that keeps previous file versions for up to 360 days. High level security: The sensitive files and data are highly vulnerable in the current date of technologies for hacking and stealing data. Organizations dealing with sensitive data can opt for pCloud since it provides client side encryption service called pCloud crypto. Other cloud service providers use AES (Advanced Encryption Standard) TLS/SSL 256 bit encryption which helps secure your files in transit from device to server. But after these files are uploaded on the cloud storage server, it gets back to its original format. This means that anyone who has access to the server can access the data as well. pCloud offers an additional level of data security where the responsibility of encryption is in the hands of the client. You can encrypt your files or data on your personal system before you upload it on the storage server. You can unlock these files by using the generated key called CryptoPass.  Convenient file management: pCloud is available on all digital platforms including Mac, Windows, Linux and also mobile systems like iOS, Android and Windows. This lets you access your file on the go from any system even while you are traveling. All the changes made are saved to the files irrespective of the device it is made on. You can access your files from any device without extra charges. Store your files from other online platforms: If your files or work is saved on Google Drive, Dropbox or any other third party cloud storage platforms, pCloud offers to easily exchange information with these services conveniently and also upload them. You can even sync your information with social media platforms like Facebook, Picasa, and Instagram. 5. Mega Mega is a secure cloud storage offered by Mega Limited, an Auckland based company. Mega offers 50 GB of free storage space. Mega is also available for Windows phone, iOS and Android in the form of mobile apps. It provides services basically through a web based app. For Windows, Linux, and Mac desktop programs, one can download MEGAsync. A folder is created in which one can drag and drop the files that one needs to upload on the MEGA account. For Mozilla Thunderbird users have the option of MEGAbird add on to share large files over email.  It was founded by Kim Dotcom in 2013 and was launched on January 19, 2013. Kim Dotcom left the company in 2015 when the company was taken over by a Chinese investor who was wanted for fraud in China and the consequent seizure of the investor's shares by the New Zealand government. The site is now controlled by the New Zealand government. Mega was created for privacy and security reasons and all files are end-to-end encrypted locally before they are uploaded. It has bandwidth limits that have to be set in account settings while uploading through a browser and through desktop client while working in the application. The users of free account receive 15 GB of base storage data and 35 GB trial on signup for one month. Through various achievements, one can activate additional storage but the maximum limit is 50 GB. On the other hand, paid account users have four levels of options: 200 GB (1 TB bandwidth per month) 1 TB storage (2 TB of bandwidth per month ) 4 TB storage ( 8TB bandwidth per month ) 8 TB storage (16 TB bandwidth per month) Significant features of Mega: MEGAchat - It was launched in 2015 as an encrypted alternative to applications such as Skype and others. It is a browser-based chat service that covers email, video, chat, voice, and mobile. Browser extension- They launched a plugin extension MEGA chrome extension in 2015, marketed for its improved downloading and loading and improved security. Later in 2018 it was found that chrome web store extension was compromised due to the addition of code which was designed to steal credentials of cryptocurrency however the original code on GitHub was secure. Desktop sync client- It assists in removing file uploads which have keywords in common that reduces uploading of unnecessary content. API - Mega has recently released a feature of documentation of its API enabling the developers to write their own applications. The whole folder can be uploaded through the browser. Limitations of Mega There is no option to share files among a group of users. One can experience inconvenience while working with browsers other than Google Chrome or Mozilla Firefox. There is no advanced sharing features, one can send Mega file only by creating a public link. There is a 10 GB bandwidth limit which is refilled every 30 minutes. Hope this article helped you get an understanding of all the best cloud storage available for free. If you want to learn about AWS, you should try the AWS Certification course 
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What are the Best Free Cloud Storages in 2019?

Cloud storage helps slash data on hardware in a re... Read More