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See How Edge Analytics Complements Cloud Computing To Design Better Industrial Solutions

Connected applications and systems are moving to the cloud with the implementation of IoT. Parallelly, the number of end-devices and their data generated on the cloud is also increasing. Sensors, mobile devices, wearable, and many other connected devices in the IoT ecosystem generate a huge amount of decentralized data. Lack of reliable connectivity, delays, and difficulties in processing this huge data on the cloud, raised a challenge in analyzing and extracting important insights from this data.

To overcome this challenge, enterprises are leveraging edge analytics along with cloud computing. This will bring instability in the IoT network by bringing the computational power near to the data source and will reduce the delays in analytics, resulting in instantaneous vision and resolutions. Edge analytics brings algorithms to the data and provide important insights.

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How Cloud and DevOps Are Helping the Remote Working World Today?

With companies adjusting their entire remote workforce into a new normal, the IT industry still struggles to maintain its productivity and workflows. In the present times, remote teams should be more agile, ready to adapt, and efficient to easily manage their IT infrastructure from remote locations.

To eliminate this restriction, businesses need to understand the true potential of the DevOps and Cloud environment.

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Tips to Choose the Right Cloud Solution for Your Web App Development

The cloud computing environment considerably matured last year. Cloud-native computing is now the beating heart of enterprise Information Technology. Nonetheless, the ecosystem of the industry continues to evolve fast, and new trends are on the horizon this year and for the years to come. It’s expected that by the end of 2020, over 80 percent of the entire enterprises would be in the cloud. 

Organizations are unearthing the power of mixing and matching cloud service to solutions that address almost any organization need as the adoption to the cloud hits another growth spurt. These days, the cloud has become a metaphor for modern computing itself in which everything is a service that could connect and combine with other services in order to meet an endless number of app needs. 

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Practical Serverless: A Scalable OCR Solution in 10 Minutes

Introduction

In this article, we will show you how to create a serverless solution for implementing a scalable Optical Character Recognition (OCR) system. In a system like this, scalability is a requirement. At certain times, we can expect possible bursts of traffic into the system where we need to process all of these requests and communicate the result back to the user in a timely manner.  To cater to this, we need a system that scales dynamically. One possible solution is to model the required workers and deploy them in a Kubernetes environment to achieve our scaling requirements. This approach has been implemented and discussed in this article.

Here, we will implement the same solution using Azure Functions in Ballerina (referred to as Ballerinalang in the rest of the article) and show how it can be implemented with considerably fewer lines of code, which resulted in lesser complexity and better maintainability.

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Why You Should Consider Database-as-a-Service

Let’s say you’re kicking off a project, maybe it’s an app, data store, IoT project, etc. No matter what you’re building, you will almost always need a database, the foundation of most applications. While this initial decision is easy, it gets infinitely more complicated from there. 

What kind of database do I need? Where do I put it? How many do I need? Why am I doing this to myself? Ahhhh, this was supposed to be a simple project!

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The Unforeseen Challenges of SAP S/4HANA Implementation

SAP customers are moving to implement SAP S/4HANA, SAP’s latest technological advancement, to take advantage of improved user experience, streamlined transactions, real-time data, table simplification, flexible APIs, and new functionality. As a suite of cloud-based applications, it’s the next step in Enterprise Resource Planning (ERP), which make migration an attractive option.

SAP S/4 HANA has continued to evolve over the last few years since it first launched, which has inspired some business to take a wait-and-see approach. The hesitancy of businesses to jump in with the latest technology is also linked to the reported challenges that business face when implementing SAP S/4HANA. Despite the challenges, more businesses are moving forward with implementation, due in large part to SAP’s end-of-support deadline in 2025 on legacy software like ECC.

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Ideal Opportunity for Cloud Management with Automated Fixes

For two decades now, tech has reshaped the business environment globally. Today, cloud computing services, which use remote servers hosted on the internet, have significantly changed the way businesses store, manage, and process data. 

However, cloud computing is not without its challenges. In order to achieve the desired efficiency, these services have to be evaluated, monitored, and optimized in a process known as cloud management. Still, systems that inform you of problems but do not fix them are only halfway managed. As such, you should consider cloud management with automated fixes.

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What is Cloud Computing and What is it For?

Cloud computing, one of the most influential technology trends of this century, came to light more than ten years ago and seemed to be here to stay. However, it is still common to find many doubts as to what it is, what it is for, what service models exist, and what the advantages of cloud computing are. 

In particular, there are still industries that fear the implementation of these services because they don't know about them. But you can rest assured. When you finish reading this blog post, you will have a broader picture to decide whether or not you should implement cloud services in your business.

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Snowflake External Functions

Introduction

Snowflake has recently announced external functions available in public preview. This allows developers to invoke external APIs from within their Snowflake SQL queries and blend the response into their query result, in the same way as if they were internal Snowflake functions.

In this article, we will demonstrate how to invoke an API via Amazon Web Services API Gateway that will trigger an AWS Lambda function. The Lambda function (written in Python) then  invokes a public API from to return the exchange rate for USD and multiple foreign currencies that can be used to calculate our sales values in USD and a number of selected currencies in SQL query running in our Snowflake warehouse. This solution eliminates the need for loading exchange rates into Snowflake regularly and also guarantees accurate, reliable real-time currency values.

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Deep Learning at Alibaba Cloud With Alluxio – Running PyTorch on HDFS

Google’s TensorFlow and Facebook’s PyTorch are two Deep Learning frameworks that have been popular with the open source community. Although PyTorch is still a relatively new framework, many developers have successfully adopted it due to its ease of use.

By default, PyTorch does not support Deep Learning model training directly in HDFS, which brings challenges to users who store data sets in HDFS. These users need to either export HDFS data at the start of each training job or modify the source code of PyTorch to support reading from HDFS. Both approaches are not ideal because they require additional manual work that may introduce additional uncertainties to the training job.

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AWS vs Azure vs Google Cloud

With the competition heating up in the public cloud service vendors, the addition of new features and a regular drop in the price will decide who the winner is. In this article, we intend to throw light on the mounting competition between AWS, Microsoft’s Azure, and GCP. AWS already has a head start of years over the others, but there is no denying the other two public cloud service providers are not far behind. It is important to compare them to understand which one suits your project the most.

A Detailed Comparison

Our comparison guide is a thorough take on all the three cloud service providers based on parameters like:

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4 Self-Deployable Ways to Digitize Your Business

Migrating to the cloud has always been an onus for organizations looking to step ahead of competitors. Given the current situation, where every business activity is forced to slow down, cloud platforms might bring harmony. The question that arises here is how? 

When the entire workforce is isolated and at distant locations, dealing and tackling a whole new environment, let alone setting it up, seems inappropriate. But do you know you can still move on with cloud transformations with ease?   

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OpenStack Ussuri – Intelligent Automation

On May 13th, the OpenStack Foundation released the 21st version of OpenStack, the popular open-source cloud software platform.

Since its initial release ten years ago, when it pioneered the concept and practices of open infrastructure, OpenStack has grown and adapted to become the open infrastructure-as-a-service standard and to support newer workload requirements such as AI, ML, IoT, and edge computing.

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What’s Next for Your Enterprise: Must-Win Battles for Tomorrow’s Industry Leaders

Let me start by stating a simple fact: Information Technology is a key capability that must be mastered if you want your company to be leading within your industry. You do not have to take my word for it, Didier Bonnet and associates said it best in their “Leading Digital”:

We discovered all kinds of companies, both those struggling and those succeeding in the great challenge of becoming digital. [...] the companies that are succeeding — and they range across industries and sectors — we’re calling Digital Masters. And Digital Masters outperform their peers. Our work indicates that the masters are 26 percent more profitable than their average industry competitors. They generate 9 percent more revenue with their existing physical capacity and drive more efficiency in their existing products and processes.

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The Do’s and Don’ts of Cloud Computing

As digital transformation becomes crucial for all businesses, the pace of cloud adoption continues to accelerate. Higher flexibility, scalability, reliability, and affordability are some of the key factors that contribute to the drastic increase in cloud computing trends. Cloud technology not only enables businesses to scale their computing needs as they grow, but also ensure operational success and satisfy evolving customer demands. 

According to the stats published by Cisco, 94 percent of workloads and compute instances will be processed in cloud data centers by 2021.  Whether you have decided to move your business operations to the cloud or not, it is imperative to conduct detailed research. Having a brief understanding of what you can do and what you should avoid will help in taking an informed decision. 

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Serverless Apache Spark: Data Flow Cloud Service

Apache Spark is a technology that is very close to becoming the industry standard among distributed big data processing platforms. It is possible to encounter Spark in almost every company working on big data. We can use this technology, which is widely used with the support of performance and many programming interfaces, in our on-premises systems as well as the interfaces opened by cloud providers.

In the past few weeks, Oracle added another one to its cloud services and launched the serverless Spark Execution Engine infrastructure on the Oracle Cloud infrastructure, and this service was designated as Data Flow. Now, users who want to use Spark can easily and quickly raise their Spark Execution Engines and deploy their applications to this environment.

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Testing Serverless Applications Like a Pro

Like any other application, continuous testing of serverless applications is essential to ensure the quality of the product. Testing a serverless application is not drastically different from testing a regular application. In traditional application testing, we configure an environment similar to the production environment in the development area and test it. But when dealing with the serverless providers, you cannot simulate the exact production environment. In this article, let's talk about testing serverless applications and the alterations we should make to the normal testing process.

Serverless Applications: Unit Testing

In unit testing, we test each unit of code individually without involving other third-party code and services. In the serverless context, unit testing is pretty much the same as in traditional application testing. So, you can use the same test frameworks like Jasmine, Mocha, Jest, etc., when testing serverless applications. In the serverless concept, most of the complexities are around serverless functions and their integrations. So, the effort of the unit testing for a serverless application is comparatively low.