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Intelligent Cloud: Machine Learning Integration in the Cloud

Today, artificial intelligence-powered machine learning (ML) and data analytics solutions are high in demand by companies in almost every area, whether it’s the financial sector, power industry, retail, healthcare, technology, or telecommunications. ML allows companies to work through a massive amount of raw data to extract actionable information. It equips businesses to understand their targeted audience better, automate their operations and production, align customer demand, and predict future business development with reliable results to make conversant decisions.

However, implementing ML technologies and algorithms like decision trees, logistic/linear regression, KNN, etc., remained a big challenge for businesses. Given that it is a costly affair with elaborate infrastructures, subject matter experts, high computing and processing power systems, etc., to leverage ML technologies and solutions in the business infrastructure. 

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How to Hive on GCP Using Google DataProc and Cloud Storage: Part 1

Google Cloud Dataproc is a managed Spark and Hadoop service that lets you take advantage of open-source data tools for batch processing, querying, streaming, and machine learning. This includes the Hadoop ecosystem (HDFS, Map/Reduce processing framework, and a number of applications such as Hive, Mahout, Pig, Spark, and Hue that are built on top of Hadoop). Hive gives an SQL-like interface to query data stored in various databases and file systems that integrate with Hadoop. Queries submitted via HIVE are converted into Map/Reduce jobs that access stored data,  results are then aggregated and returned to the user or application. 

For this exercise, we will be using New York city's yellow and green taxi trip data accumulated for the year 2019. Yellow Taxis are the only vehicles licensed to pick up street-hailing passengers anywhere in NYC while Green Taxis provide street hail service and prearranged service in northern Manhattan (above E 96th St and W 110th St) and in the outer boroughs. The dataset is available at the city portal.

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Interaction With Autonomous Database via Docker Container

Docker Container WhaleIn this article, I will show you to access the Autonomous Database service, one of the database services offered on Oracle Cloud infrastructure, through a Docker image. I hope it will be a useful article in terms of awareness.

As we all follow, one of the indispensable components of the application development world is container technologies. Container technologies have long been the main factor that triggers the transformation in the world of application development with the opportunities and advantages it offers. For this reason, software developers continue to build their solutions on containers.

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An Approach to Cloud Transformation and Cloud Migration

Overview

The ongoing COVID 19 pandemic is creating new challenges to almost all industries. It is causing a significant impact on business and operating models. Organizations are rethinking, "how to make business resilient for such large disruptions," " how to innovate faster and enable new business services to customers," "how to reduce TCO," and "how to enable better connectivity and collaborations." Such challenges existed before the pandemic era as well, but have become more relevant and important now.

Businesses that have already embarked on their cloud journey have shown greater resiliency and responsiveness to this pandemic. In the near future, it's expected that cloud adoption will significantly increase across industries with a combination of different cloud service models (SaaS, PaaS, IaaS) along with hybrid and multi-cloud topologies. Cloud hosting will become a new essential IT service for businesses.

A well-defined approach for cloud transformation is expected to realize business goals, cost savings, and strategic benefits. This article will briefly outline the elements of a typical approach for application cloud migration, modernization, and transformation. The article combines portfolio rationalization methods that can identify potential savings by reducing spending on non-valuable portfolios, along with cloud migration methods to realize the benefits of the cloud. This article will explain the methodical approach to a successful cloud transformation.

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Exploring Kubernetes With Gigi Sayfan

You have probably read about Kubernetes, and maybe even dipped your toes in and used it in a side project or even at work. But understanding what Kubernetes is all about, how to use it effectively, and what the best practices are requires much more effort. Kubernetes is a big open-source project and ecosystem with a lot of code and a lot of functionality. Kubernetes came out of Google, but joined the Cloud Native Computing Foundation (CNCF) and became the clear leader in the space of container-based applications.

Let's hear from Gigi Sayfan, author of the bestseller Mastering Kubernetes, Third Edition, about his methodologies and the approach he followed to create a powerful resource to acquaint learners all over the globe with the fundamentals and more advanced concepts of Kubernetes.

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Deploy Friday: E32 Elasticsearch Lightning-fast Search at Scale With Ease

Elasticsearch is a highly scalable open-source full-text search and analytics engine. It allows you to store, search, and analyze big volumes of data quickly and in real-time. Today, we'll discuss the success cases, tips, why you should use a search engine in your project, and where the project is headed in the future.

Hosts

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How to Set Up a Bare Metal Kubernetes Cluster Using kubeadm

Introduction

Kubernetes is a very popular container orchestrator used by most of the organizations. It is open source and managed by Cloud Native Computing Foundation. A lot among us might be wanting to know how to install and use a Kubernetes cluster. A typical kubernetes cluster looks like the below diagram.

                                                         [Figure 1: Kubernetes Architecture]

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The Low-Code and No-Code Movement Can Transform Your Startup Into Category Leaders

No-code and low-code technologies have been making inroads for years but have never quite delivered on their promise as reliable alternatives to traditional software development for complex, business-critical applications. Then COVID-19 forced a new, expedited timeline for moving analog in-person processes to semi- or fully-automated online ones. At the same time, IT and engineering roadmaps have been thrown out the window as technical teams scramble to adjust to new distributed working conditions while juggling multiple "hair on fire" problems. As a result, operations and business teams have been left with urgent needs for new business applications and scant developer resources, creating the perfect storm for no- or low-code solutions to emerge as the savior of productivity. But decision-makers should be wary of treating these platforms as a panacea to avoid costly failures and lost time.

What Are No-Code and Low-Code Technologies?

To understand how no- and low-code solutions fill the gap between business demand for development and supply of technical resources, it is helpful to understand what those terms mean exactly. No-code platforms allow people with no technical knowledge to stand up complex, cloud-based business applications using simple, drag-and-drop tooling. Relatedly, low-code platforms are also based on the concept of abstraction through pre-built software building blocks oriented towards accelerating time to development by reducing the amount of “original” code that needs to be written in any given application. Perhaps because of their shared DNA, there is a trend towards convergence; as no-code platforms become more powerful and versatile with add-ons and application marketplaces, and low-code platforms build features to require less coding. Given this trend, we can collectively refer to these platforms as Low-code Development Platforms.

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Deploy-Friday: E22 MicroProfile: Optimizing Java for a Microservices Architecture

A Question and Answer session with guests: 

The MicroProfile project defines a programming model for developing microservice applications in an Enterprise Java environment.  In this session, we'll briefly introduce MicroProfile, then discuss its current technical and community status, including efforts to standardize Java microservices.

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Design Cloud-Native Secure Environment to Host Your Enterprise Application

Let's assume your organization is planning to develop an enterprise solution (name it opendrapp) using microservice architecture having below components and host them in a private cloud.

  • OpenDrApp-UI: Reactjs based app.
  • OpenDrApp-ACL: OpenID based user access control.
  • OpenDrApp-CRM.
  • OpenDrApp -PC &OrderCare with PMS, PIS, CAM, BM, WM, NIM etc
  • OpenDrApp-Charging.
  • OpenDr - Billing.

Database: Cloud-native database hosted on Kubernetes in HA &FT config.

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Deploy Friday EP — 16 Micronaut: A Modern Full-Stack Framework for Building Microservice and Serverless

A Question and Answer session with guests: 

Micronaut is an open-source, JVM-based framework for building full-stack, modular, easily testable microservice and serverless applications. Unlike reflection-based IoC frameworks that load and cache reflection data for every single field, method, and constructor in your code, with Micronaut, your application startup time and memory consumption are not bound to the size of your codebase. Micronaut's cloud support is built right in, including support for common discovery services, distributed tracing tools, and cloud runtimes. 

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Micronaut in the Cloud: Intro to MongoDB in Microservices

Micronaut is an open-source, JVM-based framework for building full-stack, modular, easily testable microservice and serverless applications.

Unlike reflection-based IoC frameworks that load and cache reflection data for every single field, method, and constructor in your code, with Micronaut, your application startup time and memory consumption are not bound to the size of your codebase. Micronaut's cloud support is built right in, including support for common discovery services, distributed tracing tools, and cloud runtimes.

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Kubernetes Authentication

There are three steps that Kubernetes uses to enforce security access and permissions — Authentication, Authorization and Admission. In this article we are going to consider Authentication first.

              The Authentication, Authorization and Admission Control Process

The first thing in Authentication is Identity.

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Sysdig: What It Is and How to Use It

Sysdig is a universal system visibility tool with support for containers. What makes Sysdig special, is that it hooks itself into the machine's kernel and segregates the information on a per-container basis.
For the scope of this tutorial, we will focus on the open-source version of Sysdig.

In the next sections, you will: