Wednesday, 20 March 2019

Now Amazon GameLift Realtime Servers Available in Preview

Now Amazon GameLift Realtime Servers available in preview which aid developers swiftly build inexpensive game servers. Creating a great multiplayer game experience on conventional commercial answers has obstacles which frequently block game developers from creating a multiplayer game. It can be time consuming, expensive, and needs proficiency which not every game developers may have. You can offer these multiplayer games with a game server which can be modified with simply some lines of JavaScript with the utilization of new GameLift Realtime Servers, and then scale to millions of players for a small amount of money per player per month. To know further about Amazon GameLift, refer product page. Those who are interested in participating in the preview, can sign up here

Tuesday, 19 March 2019

Now Offline Content And Offline Search Supported By Amazon WorkDocs Drive

Now, you can utilize WorkDocs Drive offline potentials to access content although you are not joined to the network. Besides, with Smart Search, you and your users can search the content you require in both online and offline modes. WorkDocs Smart Search allows you query over content, comments, and document labels moreover looking for files by name. To start, bring up the WorkDocs Drive application user interface by clicking on the WorkDocs Drive icon, and click on the Gear icon. If you are using Windows it is in the system tray, if you are using Mac it is on the top menu bar. Choose Work Offline to open a dialog box to configure offline access. Amazon WorkDocs Drive will automatically download the current version of the file to your computer. Any modifications you do are automatically updated in Amazon WorkDocs when you are back online. Now this new offline feature is accessible to every WorkDocs customers. No user or administrator activity is needed to start it. To sign up for a 30-day trial or to read further about Amazon WorkDocs.

Monday, 18 March 2019

AWS IoT Greengrass Includes New Connector for AWS IoT Analytics

AWS IoT Greengrass smoothly increases AWS to edge devices to proceed locally on the data they create, while however utilizing the cloud for management, analytics, and durable storage. Connected devices can function AWS Lambda functions, perform forecasts depends on Machine Learning models, maintain device data in synchronize and transmit with other devices safely with AWS IoT Greengrass. Now AWS IoT Greengrass provides new connector for AWS IoT Analytics and assists AWS CloudFormation templates. You can now swiftly install connections between your IoT Greengrass cores and AWS IoT Analytics for analysis of complex IoT data and IoT Greengrass deployments is possible for more than one accounts with the use of CloudFormation templates. This new IoT Analytics connector can be set up through either the API or console. You can configure the extreme memory footprint and data retention performance of the connector, and after deployment the connector will use data through a described MQTT topic and transfer them to IoT Analytics instantly or in batches. To start with this connector, refer AWS IoT Greengrass Developer Guide. This features is accessible to every customers in each regions where IoT Greengrass is available.

Saturday, 16 March 2019

AWS Glue Allows Executing Apache Spark SQL queries

AWS Glue is a fully organized ETL (extract, transform, and load) service which makes it easy and profitable to classify your data, clean it, enhance it, and move it reliably between several data stores. AWS Glue made up of a central metadata repository familiar as the AWS Glue Data Catalog, an ETL engine which automatically creates Python or Scala code, and a flexible scheduler which controls dependency resolution, job monitoring, and retries. AWS Glue is serverless, so there’s no infrastructure to set up or manage. AWS Glue Data Catalog is an Apache Hive Metastore compatible catalog. Now users can configure their AWS Glue jobs and development endpoints to use AWS Glue Data Catalog as an external Apache Hive Metastore. This enables them to straight execute Apache Spark SQL queries versus the tables saved in the AWS Glue Data Catalog. This feature is accessible in every assisted regions for AWS Glue. To know further about this new potential, refer documentation.

Friday, 15 March 2019

AWS IoT Analytics now supports Single Step Setup of IoT Analytics Resources

AWS IoT Analytics is a completely-organized service which makes it simple to execute and operationalize sophisticated analytics on great volumes of IoT data excluding all trouble about the price and difficulty usually needed to create an IoT analytics platform. It is the simplest process to execute analytics on IoT data and get vision to make effective and extra perfect conclusions for IoT applications and machine learning use cases. Now, AWS IoT Analytics declared guidance for single step setup of IoT Analytics resources, that enables you to build your IoT Analytics resources of channel, pipeline, data store, and SQL data set from the IoT Analytics console with just a click of a button, excluding manually configuring IAM role or authorization. Single step setup of IoT Analytics permits you to smoothly setup your IoT Analytics resources, making your data ingestion and resource building more simpler. To start with Single step setup of IoT Analytics, refer AWS IoT Analytics Console. And to get further information on AWS IoT Analytics, click documentation

Thursday, 14 March 2019

Amazon Guard​Duty

Amazon GuardDuty is a threat detection service which continuously monitors for malicious or unauthorized behavior to help customer protect their AWS accounts and workloads. GuardDuty monitors for activities such as unusual API calls or potentially unauthorized deployments that indicates a possible account compromise. It also notices potentially compromised instances or reconnaissance by attackers.

Amazon GuardDuty does not require an IT team to deploy, manage and scale additional security software. Instead, an administrator or security analyst enables GuardDuty via the AWS Management Console, and the service immediately begins to analyze cloud environment. However, some of the more advanced threat detection capabilities require one or two week to establish normal baselines for comparison.

How It Works :

Amazon GuardDuty continuously analyzes cloud events in AWS CloudTrail, Amazon Virtual Private Cloud (VPC) Flow Logs and domain name system (DNS) logs for possible malicious activity.

Enable it with a few clicks in the AWS Management Console, Amazon GuardDuty can immediately start analyzing billions of events across AWS accounts for signs of risk. It recognizes suspected attackers through integrated threat intelligence feeds and uses machine learning to find anomalies in account and workload activity. Whenever a potential threat is detected, the service delivers a detailed security alert to the GuardDuty console and AWS CloudWatch Events. This flow makes alerts actionable and easy to integrate into existing event management and workflow systems.

The service utilizes built-in threat intelligence, anomaly detection and machine learning potentials developed by the AWS security team to do analysis in near real time.

GuardDuty Detects Following Types Of Threats On The AWS Cloud :

  • Attacker Reconnaissance : These types of threats contains failed login patterns, unusual API activity and port scanning.
  • Compromised Resources : This category of threats includes cryptojacking, unusual spikes in network traffic and temporary access to EC2 instances by an external IP address.
  • Compromised Accounts : Examples of these threats contains API calls from an odd location, attempts to disable CloudTrail and unusual instance or infrastructure deployments.

While an admin can supply GuardDuty with his or her own list of "safe" IP addresses, the service does not otherwise support customized detection rules. An admin can, however, respond to each GuardDuty finding with thumbs-up or thumbs-down responses to provide feedback for future detections.
Amazon GuardDuty compiles and delivers security findings in a JSON format to the Management Console, which enables an admin or automated workflow to take action accordingly. For example, Amazon CloudWatch Events can accept findings from GuardDuty, then trigger an AWS Lambda function to modify security configurations. The GuardDuty console and APIs retain security findings for 90 days.

GuardDuty Management and Costs :
Amazon GuardDuty works independently from cloud resources, which means it has no performance impact on running systems. Additionally, GuardDuty uses service-linked roles through AWS Identity and Access Management, which means an admin doesn't have to manage or modify S3 bucket policies or log collection.
Amazon GuardDuty is cost effective and easy. It does not require customer to deploy and maintain software or security infrastructure. There are no upfront costs with GuardDuty, no software requires to be deploy, and no threat intelligence feeds required.
An AWS customer pays for GuardDuty based on the quantity of AWS CloudTrail Events and volume of VPC Flow Logs and DNS logs the service analyzes. AWS provides a 30-day free trial for GuardDuty.  
Amazon Macie, another machine learning-enabled security service, differs from GuardDuty in that it focuses on data classification and protection.

Wednesday, 13 March 2019

Now Amazon FSx for Lustre Is Accessible from Amazon Linux

Amazon FSx for Lustre offers a high-performance file system optimized for rapid processing of workloads like machine learning, high performance computing (HPC), video processing, financial modeling, and electronic design automation (EDA). These workloads frequently need data to be offered through a swift and scalable file system interface, and usually have data sets saved on long-term data stores like Amazon S3. Now you can access Amazon FSx for Lustre file systems from Amazon EC2 instances executing the Amazon Linux or Amazon Linux 2 Amazon Machine Image (AMI) by installing the open-source Lustre client from the Amazon Linux package repository. Amazon Linux is an adjunct to the wide set of Linux-based operating systems already assisted by FSx for Lustre, covering Red Hat Enterprise Linux (RHEL), CentOS, SUSE Linux, and Ubuntu. This feature Fsx for Lustre file systems is accessible from Amazon Linux in every regions where FSx for Lustre is obtainable. To know further on installing the Lustre client on Amazon Linux or Amazon Linux 2, click here.

Now Amazon GameLift Realtime Servers Available in Preview

Now Amazon GameLift Realtime Servers available in preview which aid developers swiftly build inexpensive game servers. Creating a great...