Amazon SageMaker in Machine Learning

Posted on January 5, 2018October 18, 2019 by Idexcel Technologies

Machine Learning (ML) has become the talk of the town, and its usage has grown inherent in virtually all spheres of the technology sector. As more applications are beginning to employ the use of ML in their functioning, there is a tremendous possible value for businesses. However, developers have still had to overcome many obstacles to harness the power of ML in their organizations.

Keeping the difficulty of deployment in mind many developers are turning to Amazon Web Services (AWS). Some of the challenges to processing include correctly collecting, cleaning, and formatting the available data. Once the dataset is available, it needs to be prepared, which is one of the most significant roadblocks. Post processing, there are many other procedures which need to be followed before the data can be utilized.

Why should developers use the AWS Sagemaker?
Developers need to visualize, transform, and prepare their data, before drawing insights from it. What’s incredible is that even simple models need a lot of power and time to train. From choosing the appropriate algorithm to tuning the parameters to measuring the accuracy of the model, everything requires plenty of resources and time in the long run.

With the use of AWS Sagemaker, data scientists provide easy to build, train and use Machine learning models, which don’t require extensive training knowledge for deployment. Being an end-to-end machine learning service, Amazon’s Sagemaker has enabled users to accelerate their machine learning efforts, thereby allowing them to set up and install production applications efficiently.

Bid farewell to heavy lifting along with guesswork, when it comes to using machine learning techniques. Amazon’s Sagemaker is trained to provide easy to handle pre-built development notebooks, while up-scaling popular machine learning algorithms aimed at handling petabyte-scale datasets. Sagemaker further simplifies the training process, which translates into shorter model tuning time. In the expressions of the AWS experts, the idea behind Sagemaker was to remove complexities, while allowing developers to use the concepts of Machine Learning more extensively and efficiently.

Visualize and Explore Stored Data
Being a fully managed environment, it’s easier for Sagemaker to help developers visualizer and explore stored data. The information can be modified with all of the available popular libraries, frameworks, and interfaces. Sagemaker has been designed to include the ten most commonly used algorithm structures, some of which include K-means clustering, linear regression, principal component analysis and factorization machines. All of these algorithms are designed to run ten times faster than their usual routines, allowing processing to reach more efficient speeds.

Increased Accessibility for Developers
Amazon SageMaker has been geared to make training all the more accessible. Developers can just select the quantity and the type of Amazon EC2 instances, along with the location of their data. Once the data processing process begins within Sagemaker, a distributed compute cluster is set up, along with the training, as the output is setup and directed towards Amazon S3. Amazon SageMaker is prepared to fine-tune models with a hyper-parameter optimization option, which helps adjust different combinations of algorithms, allowing the developers to arrive at the most precise predictions.

Faster One-Click Deployment
As mentioned before, Sagemaker takes care of all launching instances, which are used for setting up HTTPS end-points. This way, the application achieves high throughput with a combination of low latency predictions. At the same time, it auto-scales various Amazon EC2 instances across different availability zones (AZ) to accelerate the processing speeds and results. The main idea is to eliminate the need for heavy lifting within machine learning so that developers don’t have to indulge in elaborate coding and program development.

Conclusion
Amazon’s Sagemaker services are changing the way data is stored, processed, and trained. With a variety of algorithms in place, developers can wet their hands with the various concepts of Machine Learning, allowing themselves to understand what goes on behind the scenes. All this can be achieved without becoming too involved in algorithm preparations and logic creation. An ideal solution for companies looking forward to helping their developers focus on drawing more analytics from tons of data.

IoT Announcements from AWS re:Invent 2017

Posted on January 2, 2018October 18, 2019 by Idexcel Technologies

Amidst primitive turmoil in the IoT world, AWS unveiled its various solutions for IoT spreading over a large range of usage. The directionless forces of IoT will now meet the technologically advanced solutions through the hands of AWS which has offered a wide range of solutions in the arena.

AWS IoT Device Management
This product allows the user to securely onboard, organize, monitor, and remotely manage their IoT devices at scale throughout their lifecycle. The advanced features allow configuring, organizing the device inventory, monitoring the fleet of devices, and remotely managing devices deployed across many locations including updating device software over-the-air (OTA). This automatically results in reduction of the cost and effort of managing large IoT device infrastructure. It further lets the customer provision devices in bulk to register device information such as metadata, identity, and policies.

A new search capability has been added for querying against both the device attribute and device state for quickly finding devices in near real-time. Device logging levels for more granular control and remotely updating device software are also added in view of improving the device functionality.

AWS IoT Analytics
A new brain that will assist the IoT world in cleansing, processing, storing and analyzing IoT data at scale, IoT Analytics is also the easiest way to run analytics on IoT data and get insights that help project better resolutions for future acts.

IoT Analytics includes data preparation capabilities for common IoT use cases like predictive maintenance, asset usage patterns, and failure profiling etc. It also captures data from devices connected to AWS IoT Core, and filters, transforms, and enriches it before storing it in a time-series database for analysis.

The service can be set up to collect specific data for particular devices, apply mathematical transforms to process the data, and enrich the data with device-specific metadata such as device type and location before storing the processed data. IoT Analytics is used to run ad hoc queries using the built-in SQL query engine, or perform more complex processing and analytics like statistical inference and time series analysis.

AWS IoT Device Defender
The product is a fully managed service that allows the user to secure fleet of IoT devices on an ongoing basis. It audits your fleet to ensure it adheres to security best practices, detects abnormal device behavior, alerts you to security issues, and recommends mitigation actions for these security issues. AWS IoT Device Defender is currently not generally available.

Amazon FreeRTOS
Amazon FreeRTOS is an IoT operating system for microcontrollers that enables small, low-powered devices to be easily programed, deployed, secured, connected, and maintained. Amazon FreeRTOS provides the FreeRTOS kernel, a popular open source real-time operating system for microcontrollers, and includes various software libraries for security and connectivity. Amazon FreeRTOS enables the user to easily program connected microcontroller-based devices and collect data from them for IoT applications, along with scaling those applications across millions of devices. Amazon FreeRTOS is free of charge, open source, and available to all.

AWS Greengrass
AWS Greengrass Machine Learning (ML) Inference allows to perform ML inference locally on AWS Greengrass devices using models of machine learning. Formerly, building and training ML models and running ML inference was done almost exclusively in the cloud. Training ML models requires massive computing resources to naturally fit in the cloud. With AWS Greengrass ML Inference, AWS Greengrass devices can make smart decisions quickly as data is being generated, even when they are disconnected.

The product aims at simplifying each step of ML deployment. For example, with its help, the user can access a deep learning model built and trained in Amazon SageMaker directly from the AWS Greengrass console and then download it to the concerned device. AWS Greengrass ML Inference includes a prebuilt Apache MXNet framework to install on AWS Greengrass devices.

It also includes prebuilt AWS Lambda templates that is used to create an inference app. The Lambda blueprint shows common tasks such as loading models, importing Apache MXNet, and taking actions based on predictions.

AWS IoT Core
AWS IoT Core is providing new enhanced authentication mechanisms. Using the custom authentication feature, users will be able to utilize bearer token authentication strategies, such as OAuth, to connect to AWS without using a X.509 certificate on their devices. With this, they can reuse their existing authentication mechanism that they have already invested in.

AWS IoT Core also now makes it easier for devices to access other AWS services, such as to upload an image to S3. This feature removes the need for customers to store multiple credentials on their devices.

5 Exciting New Database Services from AWS re:Invent 2017

Posted on December 15, 2017October 18, 2019 by Idexcel Technologies

AWS cloud division has geared up for revolutionizing the cloud infrastructure with unveiling of its much anticipated AWS event re:Invent 2017 cloud user conference which had a distinct focus on data and so-called serverless computing. It was the sixth annual re:Invent of the cloud market leader AWS which additionally laid emphasis on competitive prices along with modern suit. Five most exciting data services of the event are as follows:

1. Amazon Neptune
A new, faster, more reliable and fully-managed graph database service that will make it easy to build and run applications that work with highly connected datasets. Besides being a high-performance graph database engine optimized for storing billions of relationships and querying the graph with milliseconds latency, Amazon Neptune supports popular graph models Apache TinkerPop and W3C’s RDF, and their associated query languages TinkerPop Gremlin and RDF SPARQL for easy query navigation. It also powers graph use cases such as recommendation engines, fraud detection, knowledge graphs, drug discovery, and network security. It is secured with support for encryption at rest and in transit; can be fully managed, to ease out hardware provisioning, software patching, setup, configuration, or backups.

Currently available in preview with sign-up only in US East (N. Virginia) only on the R4 instance family and supports Apache TinkerPop Version 3.3 and the RDF/SPARQL 1.1 API

2. Amazon Aurora Multi-Master
Amazon Aurora Multi-Master allows the user to create multiple read/write master instances across multiple Availability Zones. This empowers applications to read and write data to multiple database instances in a cluster. Multi-Master clusters improve Aurora’s already high availability. If the user’s master instances fail, the other instances in the cluster will take over immediately for smart and flawless procession, maintaining read and write availability through instance failures or even complete AZ failures, with zero application downtime. It is a fully managed relational database that combines the performance and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases.

The preview of the product will be available for the Aurora MySQL-compatible edition, and people can participate by filling out the signup form on AWS’ official website.

3. Amazon DynamoDB On-Demand Backup
On-Demand Backup allows one to create full backups of DynamoDB tables data for data archival, helping them meet corporate and governmental regulatory requirements. People can also backup tables from a few megabytes to hundreds of terabytes of data, with no impact on performance and availability to your production applications. It processes back up requests in no time regardless of the size of tables, which makes the operators carefree of the backup schedules or long-running processes. All backups are automatically encrypted, cataloged, easily discoverable, and retained until manually deleted. It allows the facility of single-click backup and restore operations in the AWS Management Console or a single API call.

Initially it is being rolled out only to US East (N. Virginia), US East (Ohio), US West (Oregon), EU (Ireland) regions. In early 2018, users will be able to opt-in to DynamoDB Point-in-Time Restore (PITR) which will allow to restore your data up to the minute for the past 35 days, further protecting your data from loss due to application errors.

4. Amazon Aurora Serverless
An on-demand auto-scaling configuration for Amazon Aurora, Serverless will enable database’s automatic start up, shut down, and scale up or down capacity based on application’s needs. It enables the user to run relational database in the cloud without managing any database instances or clusters. It is built for applications with infrequent, intermittent or unpredictable workloads of likes as online games, low-volume blogs, new applications where demand is unknown, and dev/test environments that don’t need to run all the time. Current database solutions require a significant provisioning and management effort to adjust capacity, leading to worries about over- or under-provisioning of resources.We can also optionally specify the minimum and maximum capacity that an application needs, and only pay for the resources are consumed. The serverless computing is going to hugely benefit the world of relational databases.

5. Amazon DynamoDB Global Tables

The advanced Global Tables builds upon DynamoDB’s global footprint to provide a fully managed multi-region, multi-master global database that renders fast local read and write performance for massively scaled applications across the globe. It replicates data between regions and resolves update conflicts, enabling developers to focus on the application logic when building globally distributed applications. In addition, it enables various applications to stay highly available even in the unlikely event of isolation or degradation of an entire region.

Global Tables is available at the time only in five regions: US East (Ohio), US East (N. Virginia), US West (Oregon), EU (Ireland, and EU (Frankfurt).

Posted on December 14, 2017October 18, 2019 by Idexcel Technologies

Why Choose AWS as Your Cloud Platform in 2018

Posted on November 24, 2017January 13, 2021 by Idexcel Technologies

The world today is envisaging the inception of an era which is going to define the upcoming future, for we are constantly engaged in technology and newer inventions to make a better tomorrow. It will be no surprise if we see cars floating in the sky by 2050. But, will we reach there if we don’t embrace the optimal services to make things happen? No. The height of success will be determined by the kind of ladder we choose to climb.

AWS Foreground

AWS cloud service provider has been the world’s most comprehensive and broadly adopted cloud platform right from its inception in 2006. to match brains with our catalogue, AWS offers over 90 fully featured services for computing, storage, networking, database, analytics, application services, deployment, management, developer, mobile, Internet of Things (IoT), Artificial Intelligence (AI), security, hybrid and enterprise applications, from 42 Availability Zones across 16 geographic regions in the U.S., Australia, Brazil, Canada, China, Germany, India, Ireland, Japan, Korea, Singapore, and the UK. AWS services are trusted by millions of active customers around the world monthly, including the fastest growing startups, largest enterprises, and leading government agencies—to power their infrastructure, make them more agile, and lower the costs.

Amazon’s AWS is best suited for companies that require cloud infrastructure as a service for their businesses. Purchasing physical servers and maintaining them to run your business can be very costly and this is where AWS comes in. the customer satisfaction is of utmost priority for Amazon. The price model of AWS is very affordable. AWS takes privilege in showcasing its many years of experience as they have been in the cloud industry since 11 years. Not just the hypothetical display of assertions, AWS has also stood upon the principles set by Amazon. They have been able To deliver a cutting edge service and support service While keeping their level of security tighter which has allowed them to have a great score in unmatched cloud products.

Services for Every Need

Covering all the aspects of cloud service, AWS cloud services provides its service seekers an opportunity to build the infrastructure that is right for them. For instance, one can run a web application, storefront, website, database and so on. AWS’s cloud services also render to its customers a complete management tools to make it easy for first-time users to try and use their services without any hitches.

With wide ranging possibilities, Is is not justifiable that cloud infrastructure is meant Only for big organisation. Most website owners and small business enterprises also depend on them, the area where AWS is utmost preferred. The reliability, ability to run updates a Service level support, are the specialities that people nowadays find more alluring due to its practicality. With due estimates of the vendor the Elastic Cloud Compute(EC2) And database usage help the client and AWS keep record, so that a smooth transaction of data exchange can be carried out.

In its multi dimensional domain, AWS Focuses more on the core features of the corporate world, namely compute, storage, database, networking and Content delivery. AWS controls These domains via a secure web portal right From the comfort of the office/house. It also deploys management tools such as auditing, monitoring/logging, storage creating and much more.

Even the diversified platform distribution in the tech fields does not hinder the AWS support, as it operates on both Linux and Windows Servers distributions with their data centres spreading all over the world and making it the best solution for multinational companies. Setting an Amazon AWS cloud is very easy especially if one is familiar with deploying operating systems instances and images such as Ubuntu. Also, one can perform SSH connection from a secure terminal such as Putty. From there, one can start running commands and everything will flow as expected.

Emerging Newer, Better Realities

In fact, it has never been about the industry for Amazon. The customer is of utmost priority it instead of the focus on competitors. It is guided by principles such as passion for invention, commitment to operational excellence and long term thinking. AWS, Kindle Direct Publishing, Kindle, Fire tablets, Fire TV, Amazon Echo, and Alexa are some of the products and services pioneered by Amazon that render us a different way of perceiving and interacting with the world.

As long as IoT keeps depending on cloud services, the load of the storage will keep advancing for the concerned firms. With optimal expertise over AWS’s ability to handle large database data, it will be a wise move to shake hands with AWS than with other cloud service providers. For instance, if you require a database management solution that can handle terabytes or petabytes of data, Amazon cloud service provider is the way to go. AWS is relatively more preferred by both in-house and third party applications that need secure cloud architecture with great computing powers and complicated storage needs. Going with the majority, AWS is likely to have even a greater impact on cloud infrastructure in 2018. And, it is no surprise nor discomforting that people will choose the omnipotent AWS cloud services. as a bridge towards their success.

Microservices: Building an Effective Business Model with AWS Architecture

Posted on November 16, 2017October 18, 2019 by Idexcel Technologies

One buzz-word that has been spreading across the IT industry for the last few years is ‘Microservices’. However, these are not completely new approach to the IT infrastructure, but a combination of best proven methods of concepts such as nimble software development, service related architecture and API-first design (building the API first and developing the web application on top of that).

Microservices can be simply defined as ‘a self-contained process fulfilling a unique business capability’.

Following are some characteristics of a microservice architecture:

– Redistributed data management: Microservices don’t rely on a single schema in their central database. They have different views for various data models and are unique in the ways they are developed, deployed and managed.

– Functional independence: Modules in the microservice architecture can act independently without affecting the functionality of other components. They can be changed or upgraded without affecting other microservice modules.

– Simplicity: Each component is built on a set of capabilities fulfilling a specific function. Depending on the level of complexity, it can be split up into two or more independent components.

– Flexible and heterogeneous approach: Microservice gives the teams a freedom to choose the best tools and methods for their specific problems, be it programming languages, operating systems or data stores.

– Black box design: Microservice components potentially hide the details of their complexity from other components. The internal communication between the components happen with very well defined APIs to prevent implicit data dependencies.

– DevOps: This means, when you build it, you operate it. This helps the developers to be in close contact with their consumers, precisely understanding their needs and expectations.

Benefits and challenges of Microservices:

When addressing the agility and scalability issues of traditional monolithic architecture deployments, microservices benefit consumers in various ways such as:

– Microservices create a sophisticated working environment where small and independent teams take the ownership of a particular service. Hence, empowering them to work quickly and independently shortening the cycle times.

– Having a Devops culture by merging the development and operational skills removes the hassles and contradictions, providing an agile deploying environment. Making it easy to test and implement new ideas faster, henceforth creating a low cost of failure.

– Dividing a software into small and well defined modules can be maintained, reused and composed easily, giving out a great output in-terms of quality and reliability.

– Each service can be developed and implemented with their best-suitable programming languages and frameworks, and can be finely tuned in-line with aptly performing service configurations.

– Failure isolation is made easier with microservices as techniques such as health-checking, caching or circuit breakers allow you to reduce the blast radius of a failing component.

Despite all these advantages we have discussed above, there are some disadvantages of these microservice approaches as diverse systems invite more complexity.

– Determining the right boundaries for a microservice architecture is crucial when you migrate from a traditional monolithic architecture.

– Versioning for a microservice architecture can be challenging.

– Developing an effective team structure, transforming the organization to follow a devops approach and streamlining an effective communication between them can be challenging.

– The more the number of microservice modules, the more is its complexity in interactions.

– In a microservice approach, we no longer run a single service, but a combination from dozens to even hundreds of services. This increases operational complexity to a greater level.

AWS, one of the most-preferred cloud service platforms has number of offerings those address the challenges of a microservice architecture.

Effective Scaling and Provisioning of resources:

AWS microservice architecture employ on-demand resources that are readily available and provisioned when needed. Multiple environments can co-exist correspondingly, so that you need not employ difficult forecasting methods to guess the storage capacity of the microservices.

You only pay for what you use:

You can potentially experiment the new features or services, and roll them out if they aren’t successful for your business goals in AWS microservice architecture. This helps you find the innovation best suiting your business goals and also fulfills a microservice’s goal of achieving high agility.

Versatile programmability:

AWS microservices come with a specific API, Command Line Interface (CLI) and SDKs for different programming languages. Even complete architectures can be cloned, scaled and monitored through custom codes and programming languages. And, in-case of any failure, they are capable in healing themselves automatically.

AWS microservices provide you with a flexible environment to programmatically build custom tools and deploy the suitable resources, thereby reducing the operational costs and efforts.

Infrastructure as a Code:

AWS microservice architecture lets you to describe the whole infrastructure as a code and allows you to manage it in a version-control environment. You can redeploy any specific version of an infrastructure at any time, and compare the quality and performance to any application version to ensure they are in sync.

Reduce operational complexity with Continuous deployment and delivery:

Managing multiple application cycles in parallel can lead to operational complexity. AWS microservices offer automation of the provisioning and deployment process, enabling the adoption of continuous integration. This ‘continuous integration’ of the development part of the life-cycle can be further extended to the operations part of the life-cycle.

Managed services with AWS microservice architecture:

One of the key benefits of cloud infrastructures is it relieves you of the hassles of provisioning virtual servers, installing and configuring the softwares, and dealing with scaling and reliable backups. Monitoring, scaling and security are already built into the AWS microservices, helping you to further reduce the operational complexity of running microservice based architectures.

Service-oriented and Polyglot approach:

Each AWS microservice focuses on solving a specific and well-defined problem by communicating with other services using clearly defined APIs. This approach breaks down the complex infrastructure into simpler bricks or modules, preventing the need of duplication of the processes.

With microservices definitely helping to break down the complex business process into simpler modules, AWS cloud microservices further reduces the operational and interactional complexity of the microservices, helping you to define and use the most ‘appropriate’ solution for your specific business problem.

Top Roles of Cloud Computing in IoT

Posted on November 13, 2017October 18, 2019 by Idexcel Technologies

Transformation is an ever going trend, which is becoming an absolute need of the hour in today’s fast paced world. With technology churning every bit of information in a refined new format, there is a lot of scope when it comes to data storage and manipulation.

As smart phones and social media begin to rule the roost, there is a lot of conversation happening around what’s coming next. The evident answer of the hour is, the Internet of Things or IoT. With the Internet churning out huge chunks of data every second, there is a pending strain on the data infrastructure, making it necessary to look for solutions to ease the use of data storage.

Since the rise of the Cloud, there is a massive shift towards using it as a means of storage for people and businesses alike. Given the scalability and the data dynamics, there is a lot of stress being given on the use of Cloud computing to make data available remotely.

Putting this scalability to use, the Cloud has proved to be an efficient tool for transferring data through the traditional Internet channels as well as through a dedicated direct link. The traditional method is not preferred extensively; however, at the same time, many businesses prefer to the use the direct link to transfer data to the Cloud, given the quality of the data and the security it ensures during the transfer phase.

This is not all; the Cloud has become an integral part of the Internet world. Simply put, the cloud can be termed as an enabler when it comes to IoT. The Cloud is undoubtedly an ideal solution to meet all data driven needs of businesses. As this technology is developing, it is providing an agile platform for developers to create meaningful apps to establish better data devices over the Internet.

How Cloud Computing Aids IoT?

The underlying idea behind IoT and the Cloud computing is increase efficiency in the day to day tasks, without disturbing the quality of the data being stored or transferred. Since the relationship is mutual, both the services complement each other effectively. The IoT becomes the source of the data, while the Cloud becomes the ultimate destination for it to be stored.

As we progress through the years, we will see a lot of changes happening; some of these changes will be gradual while others will be more rapid. Companies likes Amazon AWS, Google and Microsoft will become the undisputed leaders of Cloud IoT Services, making the challenge even more worthwhile.

As the Cloud gathers more attention and speed slowly, there are a multitude of Cloud service providers which are beginning to offer pay per use models to businesses. This way, businesses only need to pay for what the computer resources they use.

Some more Reasons which Highlight the Importance of the Cloud in the World of IoT are:

Reduced cost of ownership: Inflation is a never ending menace which every business has to face sooner or later. The Cloud technology provides ample resources to businesses so that they do not have to spend through the nose on setting up their infrastructure. In the absence of on-site systems, hardware and software, the IT department is more focused on their day to day up keeping activities, which are often an evident benefit with the Cloud.

Business continuity programs: The Cloud computing is capable of running businesses even in the midst of sudden disasters. Since the data is maintained on additional separate servers, there is no imminent danger to the private data, making the Cloud an indispensable part of Internet based firms.

How will the IoT and the Cloud Expand?

Startups: As more and more Cloud vendors pop up, startups will continue to evolve and become more efficient, making the technology flow stronger yet smoother. The transition from one source to another will become a cinch, making the Cloud a strong place to function.

Developing countries: The strongest and biggest source of revenue for the Cloud comes from the developing countries, as they are trying to play catch up with the times. However, this revenue will drastically dip, once these countries are able to adopt their technology to the Cloud, marking the adaptation as complete.

Category: AWS