The Challenges and Benefits of Modernizing Legacy Applications in Cloud

The Challenges and Benefits of Modernizing Legacy Applications in Cloud
It was right from its inception that cloud computing displayed a revolutionizing potential—it had an unforeseen scope over diverse targets including individuals, companies and governments. The major services available in these sectors and the ever growing inventions of the modern world do indeed call for a more advanced and flexible application of cloud computing. It is seen by many as the new wave of information technology. In 2010, the World Economic Forum published a report which evaluated the impact of cloud computing technologies and signaled the large potential benefits of adoption, ranging from economic growth and potential improvements in employment to facilitating innovation and collaboration.

Need being the mother of invention, Cloud has evolved beyond basic SaaS, IaaS, and PaaS offerings, as the cloud matures to become the engine of enterprise technology innovation. It is moving towards a faster and more efficient world. However, the Information Technology is increasing its demands to solve the arising complexities. Take for example the modernizing of legacy applications in cloud. It extends both challenges and opportunities, as the facets of a coin, but in each way it moves towards a more advanced and intricate web of complexities.

Most of the large enterprises run at least some form of a legacy application, for which updates and replacements can sometimes be tricky. However, failing to modernize out-of-date systems may hinder the pace of information exchange due to slow runtime speeds and inefficient load balancing. Many organizations have, thus, begun to modernize their legacy applications which will yield long term benefits such as portability and scalability, better speed and resource management, and granular visibility.

Since the start, enterprises have run on time-consuming manual processes and tools that are involved with legacy applications also hinders modernizing efforts. Manual processes take up significant amount of time and still leave room for errors. However, at the same time, enterprises say they need to move to the cloud, but they don’t really understand why, nor do they realize how difficult it can be. This includes applying cloud services to a non-compatible old legacy application and facing challenges when trying to re-host. They must be cautious of the processes involved in migrating the valuable data. If one moves one application to cloud which has business logic or IT logic of another application that isn’t migrated to cloud, they might run into issues. Therefore, it is better to consult the professionals before landing into problems. In this league of advancement, the infrastructure might face challenges such as:

Cost adjustments: The cost of maintaining and upgrading Legacy systems renders the firm a challenge of combatting the financial balance. The challenge preparers the employees learn the skills of pulling the firm through the tight passage without de-establishing the financial pace of the organization.

Inflexible and closed architectures: There are some architectures used by organizations that hinder Web and mobile enabling and integration with contemporary platforms, therefore, they turn out to be challenging opportunities for the modern minds at work.

Limited Integration: Legacy systems might sometimes not go in cohesion with the integration to contemporary technologies like Mobile Apps/Devices, Enterprise Content Management Systems, Automated Workflow, E-Forms/E-Signatures, Geographic Information Systems, and so on, therefore pose a major obstacle for the integrators.

User Friendliness: The existing system uses command-based screens and cannot provide a contemporary Graphical User Interface (GUI), web, or mobile which have become commonplace, however, if it is in constant practice, the newer models of commanding may pose an oddity for quite some time for the old hands. Therefore, the migrators have to go an extra mile to ease the way by employing less complicated systems.

On the other hand, there are various benefits of applying this modernization. If the engineers handle the aforementioned challenges wisely and implement the newer technology with greater precision, there indeed some charming benefits await, such as:

Enhanced flexibility: Creates a flexible IT environment with new architectural paradigms such as web services; aligns IT systems to dynamic business needs.

Modern development tools: Legacy and new developers can use the same or similar tools, enabling both to develop Legacy applications.

Lower risks: Re-use of business rules where data becomes less risky than alternatives.

Shorter development times: Modernizes development tools and retrains developers which lead to shorter development times.

Reduced cost: Lowers high maintenance cost of existing old fashioned Legacy platforms and development tools, resulting in substantial savings in IT budgets.

Minimized disruption: Reduces the risk when modernizing Legacy platforms by combining two decades of development experience with contemporary platforms, a proven modernization framework and rich domain knowledge.

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Amazon ECS for Kubernetes: Bridging the Migration gaps

Amazon ECS for Kubernetes
AWS has unveiled a new container service that will allow its users to run Kubernetes on AWS server without needing to install and operate a separate Kubernetes cluster. The service can be identified as a major advancement for AWS which will allow the users migrate smoothly, who had, though, previously found Amazon ECS slightly rigid when it yielded optimum results only when operated on AWS’ own server.

Amazon Elastic Container Service for Kubernetes is a managed service that transcends this obstacle. With this cross platform achievement, AWS will certainly attract (or at least keep) its customers for it has eradicated one major obstacle of transferring clusters on personal server of AWS—inter-cloud exchange. Kubernetes is known to be an open-source system used for automating the deployment, scaling, and managing containerized applications. While Kubernetes had previously posed significant challenges to producing applications, where one was required to manage scaling and availability of Kubernetes masters and persistence layer, Amazon EKS has eased this tedious task by rendering an automatic selection of appropriate instance types. It runs them across multiple Availability Zones along with replacing unhealthy masters through constant heath monitoring. Even the patch and upgrade routines of master and worker nodes no longer need to be monitored manually, which required a lot of expertise and, above all, a tremendous amount of manpower and time. Amazon EKS automatically upgrades the nodes and prepares them for high availability. It runs three Kubernetes masters across three Availability Zones to achieve this flawless feat.

Amazon EKS, just like ECS, can be integrated with many AWS services to provide direct scalability and security for various applications, including Elastic Load Balancing for load distribution, IAM for authentication, Amazon VPC for isolation, AWS PrivateLink for private network access, and AWS CloudTrail for logging. It runs the latest version of the open-source Kubernetes software, which allows the user to have all the latest and existing plugins and tools from the Kubernetes community. Due to the absolute compatibility offered with Amazon EKS for application running on standard Kubernetes Environment, the user can easily migrate any standard Kubernetes application to Amazon EKS without any code modification.

Having stated the common properties of Amazon EKS, let’s look at the major benefits for opting it:

Secure
Security is of paramount importance in this cloud based IT world. With more advanced features, the Amazon EKS is loaded with highly advanced security features for the Kubernetes Environments of any managed cloud service. The migrated workers are launched on the user’s Amazon EC2 instances, where no compute resources are exposed to other customers.

It allows the users to manage the Kubernetes cluster using standard Kubernetes tools such as kubectl CLI for managing Kubernetes, through AWS Identity and Access Management (IAM) authenticated public endpoints or through PrivateLink.

Fully Compatible with Kubernetes Community Tools
Since Amazon EKS runs the latest version of the open-source Kubernetes software, all the existing and even newer features, plugins, and applications are supported in it. Applications that are already running in an existing Kubernetes environment will be fully compatible, and can be flawlessly moved to Amazon EKS cluster.

Fully Managed and Highly Available
Amazon EKS eradicates the need to install, manage, and scale personal Kubernetes clusters. With this development, EKS is one step ahead of the ECS. The worker and master clusters of Kubernetes are automatically made highly available which are distributed across three different Availability Zones for each cluster, due to which, worker and master servers start functioning more smoothly than ever before. Amazon EKS manages the multi Availability Zone architecture and delivers resiliency against the loss of an Availability Zone. Furthermore, it automatically detects and replaces unhealthy masters and provides automated version upgrades and patching for the masters.

Amazon EKS integrates IAM with Kubernetes which enables the user to register IAM entities with the native authentication system in Kubernetes. The user no longer has to worry about manually setting up credentials for authenticating with the Kubernetes masters which also allows IAM to directly authenticate with the master itself as well as granularly control access to the public endpoint with regards to the targeted Kubernetes masters.

Besides that, it also gives the option of using PrivateLink to access Kubernetes masters directly from personal Amazon VPC. With PrivateLink, Kubernetes masters and Amazon EKS service endpoint appear as an elastic network interface with private IP addresses in Amazon VPC, which opens the threshold for accessing the Kubernetes masters and the Amazon EKS service directly from Amazon VPC, without using public IP addresses or requiring the traffic to traverse the internet.

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Pink18: IT Service Management Conference & Exhibition

Pink18
Date : February 18-21, 2018
Location : Florida
Venue: JW Marriott Orlando, Grande Lakes

Event Details
The conference theme will be covered in over 120+ sessions and 12 tracks to show how you can master the dynamics of today’s business environments by adopting, adapting and applying tried and true best practices. Subjects include: ITSM, ITIL, Lean IT, Agile, Scrum, DevOps, COBIT®, Organizational Change Management, Business Relationship Management, and more!

[Know more about the Conference]

About Idexcel:idexcel is a global IT professional services and technology solutions provider specialized in AWS Cloud Services, DevOps, Cloud Application Modernization and Data Science. With keen focus on addressing immediate and strategic business challenges of customers, idexcel is centered at providing deep industry and business process expertise. The idexcel team thoroughly dedicates itself to the occupation of technology innovation and business improvisation. Aware that all businesses involve specific areas unique to their culture and environment, the Idexcel team encourages flexibility and transparency across all levels of interactions with clients. Our team of AWS certified experts ensure that clients benefit from the latest cutting-edge technology in AWS cloud.

Our Mission: Our mission is to provide effective, efficient and optimal IT professional services meeting our client’s needs. Our extensive and proven technical expertise enables us to provide the high quality of services and innovative solutions to our clients.

Allolankandy Anand Sr. Director Technical Sales & Delivery will be attending this event. For further queries, please write to anand@idexcel.com

Amazon ECS: Another Feather in AWS’ Cap

Amazon ECS Another Feather in AWS’ Cap
Amazon Elastic Container Service (Amazon ECS) is a newly developed, highly scalable and high-performance container orchestration service that supports Docker containers and allows the user to easily run and scale containerized applications on AWS. It outcasts the need for the user to install and operate their container orchestration software, manage and scale a cluster of virtual machines, or schedule containers on those virtual machines.

It is a service that renders simplicity to running application containers in a highly available manner across multiple Availability Zones within a region. The user can create Amazon ECS clusters within a new or existing VPC. After a cluster is built and starts running, they can define task definitions and services that specify which Docker container images has to be run across the opted cluster/s. Container images are stored in and pulled from container registries, which exist within or outside of the user’s AWS infrastructure.

For greater control, the user can host tasks on a cluster of Amazon Elastic Compute Cloud (Amazon EC2) instances that are managed using the EC2 launch type. Amazon ECS also enables the user to schedule the placement of containers across the concerned cluster based on resource needs, isolation policies, and availability requirements. It is helpful in creating a consistent deployment and build experience, manage, scale batch and Extract-Transform-Load (ETL) workloads, and build sophisticated application architectures on a micro-services model.

The user can launch and stop Docker-enabled applications with simple API calls, query about the complete state of application, and also access many features such as IAM roles, security groups, load balancers, Amazon CloudWatch Events, AWS CloudFormation templates, AWS CloudTrail logs and so on.

The recent IT developments have signaled an increasing dependency over smart cloud containers, and that is where Amazon ECS becomes an essential pick. The firms are seeking more efficient and ready-to-go type solutions that do not posit any obstacle to the organizational pace. Amazon ECS, thus, comes up with a greater edge, as far as the preference is concerned, for it offers various advantages like:

Containers without infrastructure management

Amazon ECS features AWS Fargate, which enables the user to deploy and manage containers without having to manage any of the embedded underlying infrastructure. With AWS Fargate technology, the user no longer needs to select Amazon EC2 instance types, provision, and scale clusters of virtual machines to run containers or schedule containers to run on clusters and maintain their availability. Fargate gives enough time to the user to focus on building and running the application without having to worry about the underlying infrastructure.

Containerize everything

Amazon ECS lets the user easily build all types of containerized applications, from long-running applications and micro-services to batch jobs and machine learning applications. They can migrate legacy Linux or Windows applications from on-premises to the cloud and run them as containerized applications using Amazon ECS.

Secure infrastructure

Amazon ECS gives the option of launching containers in one’s own Amazon VPC, allowing them to use the VPC security groups and network ACLs. None of the compute resources are exposed to other customers which makes the personal data all the more secure. It also enables the user to assign granular access permissions for each of the containers using IAM to exhibit restriction on access to each service and accessible resources that a container has. This intricate level of isolation helps the user use Amazon ECS to build highly secure and reliable applications.

Performance at scale

Amazon ECS is a product of gradually developed engineering spreading over years. Built on technology developed from many years of experience, it runs highly scalable services. The user can launch numerous Docker containers in seconds using Amazon ECS with no additional introduction of complexity.

Compliments other AWS services

Amazon ECS is a product that works well with other AWS services and renders to the user a complete solution for running a wide range of containerized applications. ECS can seamlessly integrate with services like Elastic Load Balancing, Amazon VPC, AWS RDS, AWS IAM, Amazon ECR, AWS Batch, Amazon CloudWatch, AWS CloudFormation, AWS CodeStar, AWS CloudTrail and many other AWS services.

However, it is important to highlight that Amazon ECS, only when integrated with Other AWS Services, will likely provide an optimum solution for running a wide range of containerized applications or services instead of running on different clouds. The other popular container services like Kubernetes is not restricted for optimum outcome while running only on any particular kind of infrastructure or a specific provider. In fact, Kubernetes can also be easily run on AWS EC2 as well.

The contenders are Kubernetes, Docker Swarm, Mesos and few others, all flag same or similar benefits, all competing still for securing the top spot of being the most powerful container orchestration platform.

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DEVELOPERWEEK 2018

DEVELOPERWEEK 2018
Date : February 3-7, 2018
Location : San Francisco Bay
Venue: Oakland Convention Center

Event Details
DeveloperWeek 2018 is San Francisco’s largest developer conference & event series with dozens of week-long events including the DeveloperWeek 2018 Conference & Expo, 1,000+ attendee hackathon, 1,000+ attendee tech hiring mixer, and a series of workshops, open houses, drink-ups, and city-wide events across San Francisco!

DeveloperWeek puts the spotlight on new technologies. Companies that participated in last year’s DeveloperWeek include Google, Facebook, Yelp, Rackspace, IBM, Cloudera, Red Hat, Optimizely, SendGrid, Blackberry, Microsoft, Neo Technology, Eventbrite, Klout, Built.io, Ripple, GNIP, Tagged, HackReactor, and 30+ more here!

Why Attend
Because DeveloperWeek covers all new technologies, our conference and workshops invite you to get intro lessons (or advanced tips and tricks) on technologies like HTML 5, WebRTC, Full-Stack Javascript Development, Mobile Web Design, Node.js, Data Science, and Distributed Computing to name a few.

[Know more about the Conference]

About Idexcel:idexcel is a global IT professional services and technology solutions provider specialized in AWS Cloud Services, DevOps, Cloud Application Modernization and Data Science. With keen focus on addressing immediate and strategic business challenges of customers, idexcel is centered at providing deep industry and business process expertise. The idexcel team thoroughly dedicates itself to the occupation of technology innovation and business improvisation. Aware that all businesses involve specific areas unique to their culture and environment, the Idexcel team encourages flexibility and transparency across all levels of interactions with clients. Our team of AWS certified experts ensure that clients benefit from the latest cutting-edge technology in AWS cloud.

Our Mission: Our mission is to provide effective, efficient and optimal IT professional services meeting our client’s needs. Our extensive and proven technical expertise enables us to provide the high quality of services and innovative solutions to our clients.

Allolankandy Anand Sr. Director Technical Sales & Delivery will be attending this event. For further queries, please write to anand@idexcel.com

Machine Learning’s Impact on Cloud Computing

Machine learnings impact on cloudcomputing

People’s overall increasing dependency on AI and IoT (IoT Announcements from AWS re:Invent 2017) has given new goals to the cloud computing infrastructure holders. The premises enfolding within this newly emerging subfield of Information and Technology are indeed very vast in which all the domains ranging from minimal smartphones to high end robots are coming together to share the common resource. Firms are developing machineries that require the least dependency on human resource. The attempts are rather to give the man-made machinery autonomy to a great extent over the resources it needs to utilize in order to become fully functional. Clearly, the intention of eliminating the human intervention is also on run.

In order to gain that autonomy over the soft resources, the inventors will have to depend on a mediator which will assist the “smart machines” gain their functional ability, and, cloud computing seems to be the only and the last resort. The “study material” for the machines will be store retrieved and used by them through cloud means. As the cloud computing is already taking over major domains of human efforts such as data storage, this technological advancement will result in unprecedented impacts on global economy, business and world in general.

The integrated cloud services would be even more beneficial than the current cloud services. The current usage of cloud involves computing, storage and networking but the intelligent cloud will multiply the capabilities of the cloud by rendering a capability of learning from the vast amount of data stored in the cloud, to build up predictions and analyze situations. This will result in a smart advancement in the IT field where tasks are performed much efficiently.

Cognitive computing

The large amounts of data stored in the cloud serves as a source of information for the machines to gain their functional state. The millions of functions happening daily on cloud computing will all provide a source of information for the machine to learn from. The whole process will equip the machine applications with sensory capabilities. The applications will be able to perform cognitive functions and make decisions best suited for them for the desired goal.

Even though the intelligent cloud is in its infantile age, the premises are predicted to be largely increasing in the coming years and revolutionize the world in the same way the internet did. The expected are that would utilize the cognitive computing will spread over the systemsof healthcare and hospitality, business and even personal lives.

Changing Artificial Intelligence infrastructure

with the help of intelligent cloud, AI as a platform service makes the process of intelligent automation easier for users by taking control of the complexities of the process. This will further increase the capabilities of cloud computing, in return increasing demand for the cloud. The intelligent will define the future. The interdependency of cloud computing and artificial intelligence will somewhat become the essence soaring realities.

New dimensions for IoT

AS we are aware how IoT has overtaken our lives and created an undeniable dependency over gadgets, cloud that will assist the machine leaning of these gadgets are increasing rapidly too. The smart sensors that take cars into cruise control will apprehend their source of data from the cloud only. In short, cloud computing will become the long term memory for IoT from where they can retrieve the data for solving in-time problems. The massive web of interconnectivity of various machines will generate and operate on a massive amount of data saved in that very cloud. This will expand the horizons of cloud computing and it will become as needful to machines as water is for humans, in coming years.

Personal assistance with minute ease

As we have already seen the likes of Jarvis, Siri, Cortana and Google doing great in the market, it is not absurd to think of a personal assistant existing in every metropolitan home by the next decade. These assistants make life easier for individuals through pre-coded voice recognition that also gives a feel of human touch to machines. The responses are generally very common and operate on a limited set of fed information. However, these assistants are very likely to be developed in a finer way so that their capabilities will not remain limited. Through increasing use of autonomous cognition, personal assistance will attain a state of reliability where it can replace human interaction. The role or cloud computing will be supremely vital in this regard, as it will become the heart and the brain of these machines.

Business intelligence

During extensive application, the task of the Intelligent cloud will be to make the tech world even smarter—autonomous learning coupled with the capabilities of figuring and rectifying real time anomalies. In the same way, the business Intelligence will also become smarter wherein along with identifying and rectifying faults, it will be able to predict future strategies in advance. Armed with proactive analytics and real-time dashboards, the businesses will operate upon predictive analytics that processes previously collected data, makes real time suggestions or even future predictions. These predictions from current trends and suggestions for actions would make things easier on leaders.

Revolutionizing the world

Fields like banking, education, hospital, and general services etc. would be able to make use of the intelligent cloud enhancing the precision and efficient of services they provide. Consider for example having an assistant in hospital which reduces the doctor’s customary load of decision making by analyzing the case, making comparisons and prompting new approaches to the treatment.

With the rapid development of both machine learning and the cloud, it seems in the future, cloud computing will become much easier to handle, scale and protect with machine learning. Along with that, the wider the business initiatives harping on the cloud will need machine learning to be implemented, to make it more efficient, to the point that we will have no cloud service that operates as it operates today.

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Amazon SageMaker in Machine Learning

Amazon SageMaker in machine Learning
Machine Learning (ML) has become the talk of the town. Its use has become inherent in almost all spheres of technology these days. As more and more applications are beginning to employ the use of ML in their functioning, there is a tremendous value add to the businesses. But the problem worth noting is that developers till date have a lot of issues in trying to develop ML based applications.

Keeping the difficulty of deployment in mind, many developers are turning to the AWS cloud services to access and store the power used in ML deployment. Some of the challenges include, but are not limited to, come to force with collecting, cleaning and formatting the available data. Once the dataset is available, it needs to be processed, which is one of the biggest blockers. Post processing, there are a lot of other procedures which need to be followed before the data can be significantly used.

Why should developers use the AWS Sagemaker?
Developers need to visualize, transform and prepare their data, before drawing insights from it. What’s incredible to note is that even simple models need a lot of power and time to train and compute different algorithms. Right from choosing the algorithm, to tuning the parameters to measuring the accuracy of the model, everything requires a great deal of power 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 endless users to accelerate their machine learning efforts, thereby allowing them to setup and install production applications efficiently.

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

Amazon SageMaker helps developers in the following ways:

Build machine learning models aimed at maximizing performance-optimized algorithms: Being a fully managed notebook environment, it’s easier for the Sagemaker to help developers in visualizing and exploring the stored data. In other words, the data can be transformed with all the popular libraries, frameworks, and interfaces. Sagemaker has been designed to include the ten most commonly used algorithm structures, some of which include the likes of the 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, making the processing power reach up to efficient speeds.

Fast, fully managed training: Amazon SageMaker has been geared to make training all the more easier. Developers can simply select the quantity and the type of Amazon EC2 instances, along with the location of the data. Once the data processing process begins within the Sagemaker, a distributed compute cluster is setup, along with the training, as the output is setup and directed towards Amazon S3. The cluster is torn down, as soon as the process comes to an end. Amazon SageMaker is prepared to fine tune the models with a hyper-parameter optimization option, which helps adjust different combinations of algorithms, allowing the developers to arrive at the most precise predictions.

Push models into production mode, all with one click: Amazon SageMaker, as mentioned before, takes care of all the launching instances, which are used for setting up the 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 (AZs) to quicken the processing speeds and results. The main idea is to eliminate the need of heavy lifting within machine learning, so that developers don’t have to indulge in complex coding and program development.

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

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IoT Announcements from AWS re:Invent 2017

IoT announcements
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.

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Agile & DevOps Conference 2018

Agile & DevOps Conference
Date : 29 Jan, 2018
Location : Dallas-TX, United States
Venue: Homewood Suites by Hilton

Event Details
The conference targets to feature presentation and discussion sessions by recognized thought-leaders addressing the actual developments and trends in Agile & DevOps highlighting implementation challenges and their solutions. The conference presentations by expert speakers will make it easier to understand how Agile & DevOps can successfully bring cross-functional business units together for delivering business results speedily in the Agile environment.

Why Attend
A full day event for professionals to meet their industry peers, exchange knowledge and take away ideas for making best use of Agile & DevOps practice. Based on the conference theme ‘Let’s switch it on’, this conference provides an opportunity to learn from industry experts the concept of Agile & DevOps and how to implement it in your organizations. Get to know critical challenges faced during implementation, and their solutions. This is a great platform to meet top solution providers and industry players in this domain.

[Know more about the Conference]

About Idexcel: Idexcel is a global business that supports Commercial & Public Sector organizations as they Modernize their Information Technology using DevOps methodology and Cloud infrastructure. Idexcel provides Professional Services for the AWS Cloud that includes Program Management, Cloud Strategy, Training, Applications Development, Managed Service, Integration, Migration, DevOps, AWS Optimization and Analytics. As we help our customers modernize their IT, our clients should expect a positive return on their investment in Idexcel, increased IT agility, reduced risk on development projects and improved organizational efficiency.

Allolankandy Anand Sr. Director Technical Sales & Delivery will be attending this event. For further queries, please write to anand@idexcel.com

Everything you need to Know about Serverless Microservices in AWS

Everything you need to Know about Serverless Microservices in AWS
It’s a well-known fact that handling multiple servers can be a painful experience, especially in the short run. Multiple servers mean multiple developers will need to work on the same code, making the code repository difficult to handle in the long run. One of the biggest disadvantages in the long run is the resiliency, which causes the whole back end to get bogged down, making the website crash and slow down eventually.

What are AWS Microservices?
The microservices architecture has been designed to solve all forms of front end and back end issues. The back end is wired to communicate with various small services through a network of HTTP or other messaging systems. Since the setup is rather elaborate, the whole procedure is time consuming and can take considerable time to setup. Post the setup formalities, a developer can benefit immensely by optimizing work through work parallelization and improved resiliency. Each developer can access and develop their own microservice, without worrying about code conflicts.

What does going Serverless mean?
The concept of going serverless is relatively new and has seen the day of light just recently. In an ideal situation, the traditional back end was deployed on a group of servers. Such an approach had its own set of advantages. It allowed the developers to control their own servers along with the infrastructure behind it. However, like everything else, it contributed a lot towards the cost, making it an inefficient solution for companies. Add a set of engineers to build, maintain and run the infrastructure, and your budget will increase manifold.

With the introduction of the serverless technology, all these problems can be solved considerably. You can make use of a service which will run your code, as well as take care of all your maintenance issues. What you do end up paying for is the time it usually takes to process each request thrown at the code. For this purpose, AWS offers the AWS Lambda service, which is somewhat similar to the functionality of Microsoft’s Azure Function and Google’s Cloud Functions.

What Services aid the Serverless Microservices?
Amazon API Gateway: API is a gateway service that offers the option to use a configurable REST API in the form of a service. You get to author your needs and create it in the form of a code. Say, for example, you decided what would happen if a particular HTTP Method is implemented and called on a certain HTTP Resource. In this case, say you want to execute and implement a Lambda function if the HTTP request comes through. API Gateway helps in mapping input and output data through a series of formats. Thankfully API Gateway is a fully fledged service, which is managed extensively, allowing you to pay for only what you use.

AWS Lambda Services: Being a pay as you go service, AWS Lambda is a well-managed service hub. It allows you to get rid of over provisioning costs, as well as avoid the need of any boot time, patching, as well as load balancing.

Amazon DynamoDB: Amazon DynamoDB is a document store wherein you can look up values through their key values multiple Availability Zones or data centers to bring about a subtle consistency. Like Lambda, it too is a 99% managed service, while the remaining 1% is free to perform reading and writing of code.

The Request Flow and how it Works with Microservices
In an ideal situation, it’s imperative to understand how the data flows through serverless microservices. The user’s HTTP hits the API Gateway; the API Gateway checks the HTTP request and figures if the request is valid or not. Through this approach, it makes multiple requests within the database and executes the business logic.

Another system which aids the processing of information within the serverless environment is the AWS CloudWatch. The AWS CloudWatch stores metrics in the form of numbers and text information in the form of logs. It also allows you to define your alarms over your metrics. At any given point of time, if your system begins to default, you can get an instant notification of the default using AWS SNS, making the process seamless and streamlined.

Summary
AWS Microservices are well balanced and fully managed, thereby allowing you to concentrate on performing multiple forms of other operational tasks. Through the concentration on other important tasks, the functionality of the code can be improved manifold, as it is performed through a series of automated tasks.

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