#azurebot

[samarpaninfotech]

NEW ARTICLE OUT👉We just published Part 1 of Tutorial Series , where you will learn How to Develop Echo Bots Robot faceUsing #Azure Bot Framework SDK C# and #DotNET ? - https://bit.ly/3eKK3bb #azurebot #Chatbots #EchoBots #AI #AzureDevOps (at Samarpan Infotech) https://www.instagram.com/p/CCyQjPUn3r2/?igshid=1tgkl0o3t6fqo

[akshay-s]

Intra Cloud DevOps using Azure Bot – Capstone Project

By Great Learning

Problem Statement

Organisations with multiple cloud platforms and On-premise environments have challenges in managing DevOps activities from a centralised application with an intuitive user interface. They had to rely on the admins of the respective environments to execute any manual build, deployment, or get status reports on DevOps activities.

Proposed Solution

The proposal is to build an Intra-cloud application which interacts with different cloud/on-premise environments which enables the development team to manage the DevOps activities. The solution will offer a cognitive Azure Bot application to:

1. Select the Build and Deployment Environment

Choose the environment for the manual build and deployment. The following environments are in scope:

Azure

AWS

On-premise

2. Build and Package the Application

List the applications which are available to build. Select the option and build the latest codebase for the selected option. Package using the build specification. Give the status as a response to the user.

3. Build and Deploy the Application

Build and deploy the latest code base for the given application. Provide the deployment details and status as response back to the user.

4. Analytics and Reporting

Reporting of the build and deployment statistics to the end-user. Available as a downloadable file.

This solution with Azure Chat-bot powered by Language understanding capability offered by LUIS would enable the users to take real-time and pre-emptive decisions to perform manual build and deployment DevOps activities in these environments.

Architecture :

The proposed template of the solution and the application architecture for the Chat bot application would look as shown in the below diagram.

The various components of the architecture in the diagram above have been explained briefly below:

Azure Platform

Azure DevOps :

Azure build Pipeline is setup in Azure DevOps. .Net and PHP applications are set up in the build and deployment pipeline.

Azure Functions :

Micro services are built using .Net Core Azure Function templates. To access the build, deployment and status reports.

Key Vaults :

This service stores secure data like Azure credentials and personal access tokens to call the pipeline rest API.

AWS Platform

Amazon API Gateway :

Secure Rest API created for AWS DevOps tasks are deployed in API Gateway. It acts as a single point of entry for the defined group of micro services.

AWS Elastic Beanstalk :

Elastic Beanstalk is used to deploy and manage web applications built on multiple technologies like Java and PHP. AWS Elastic Beanstalk is an orchestration service offered by Amazon Web Services for deploying applications which orchestrate various AWS services, including EC2, S3, Simple Notification Service, CloudWatch, autoscaling, and Elastic Load Balancers.

S3 Bucket :

Source provider for the build packages for the pipeline. After the generation of the build package, it is saved in the destination S3 bucket location.

AWS Lambda:

Microservices are built using AWS Lambda functions. .Net Core serverless applications are built using the AWS SDK. This service interfaces with AWS CodePipeline, Code Build, and Code Deploy API services.

IAM :

Policy to allow Lambda function to access CodePipeline API

Policy to allow Lambda function to access Code Build API

Policy to allow Lambda function to access S3 Bucket.

Cloud Watch :

This provides the log for monitoring serverless Lambda function executions we run on AWS.

On-Premise Platform

Jenkins build automation server is used for On-premise DevOps configuration. .Net Core web applications are set up in Jenkins using build job and pipelines. The API for continuous build and continuous pipeline deployment is exposed which is consumed by a Bot service.

In this environment source code is downloaded from GitHub. Applications source code is sourced from GitHub repositories.

UI Interface Azure Chat bot :

This chatbot is basically the UI interface that is capable of having human-like conversations powered by Language interpretations using LUIS. Each of the environments like AWS, Azure and On-prem have separate Dialogues which can be easily extended for adding new cloud platforms. Prompts for selection options and confirmation gives a real-time user interaction experience.  The sequence of questionnaires is implemented using the waterfall dialogue class and customised adaptive cards. All the microservices from the different environment are consumed using the rest API in the Bot application. No environment-specific credentials are configured in the Bot application source code to make it easily configure with rest API.  

Reports are generated and are downloaded in CSV format. The bot offers the build and deployment status reports which capture the status and details of the pipeline execution.

LUIS services provide the pre-defined intents while interpreting the chat messages for driving the user conversation with Bot.

Note: This project makes use of unauthenticated users in the Bot. The deployment is done in Teams or custom web application in the production environment.

Python Flask:

Additional Web UI interface is provided using Flask micro web framework. The rest API developed for the Azure Bot is reused in this Web UI. Users can perform the same operations provided from Bot in this Web UI.

Business and Technical Challenges:

Business challenges and Solutions:

Add reporting capability using data generated dynamically from build and release in different environment: Power BI reports replaced with CSV reports which are downloaded. Converted json data to CSV. No additional managed service cost for the reporting feature.

Cost of cloud resources should be minimal: Used serverless computing like lambda functions and azure functions instead of EC2. This will reduce computing costs.

Cost of setting up DevOps for on-premise applications: Used license-free Jenkins server for On-premise applications. DevOps setup completed without incurring any additional license fees.

Technical Challenges and Solutions:

As there are multiple environments involved, each cloud DevOps services developed with the microservice approach are built and deployed separately. Used AWS Lambda and Azure function to realise microservice architecture.

Maintainability of Bot for new platforms and clouds: used Waterfall dialogue and developed each environment actions using separate dialogue. With this design, it is easy to add/remove each environment cloud without much code changes.

Bot and service code maintainability:  Service implementation separated from the Bot core code structure. So, the changes in the service can be handled separately without impacting the Bot code.

Lightweight Service: Used rest API in .net Core platform.

Learning:

The following learning are made from this Capstone project:

Cost optimization using serverless computing like lambda and Azure functions.

Exposure to the setup DevOps pipeline in different cloud platforms and on-premise platforms.

Role of Micro service pattern in rest API service development.

Building secure cloud solutions using IAM, key vault, AWS API management etc.

To pursue a career in Cloud Computing, upskill with Great Learning’s PG Program in Cloud Computing.

[payment-providers]

New Post has been published on Payment-Providers.com

New Post has been published on https://payment-providers.com/10-platforms-to-build-a-chatbot-for-your-business/

10 Platforms to Build a Chatbot for Your Business

Chatbots are conversational applications that can be integrated into messaging platforms to perform automated tasks, such as collecting information from customers or helping shoppers find the right products. Chatbots don’t require users to install additional apps. And they are relatively simple and inexpensive to build.

Here is a list of platforms to help build a chatbot for your business. Some of these platforms have basic drag-and-drop builds, while others require basic coding. All of the platforms have free plans.

Platforms to Build Chatbots

Chatfuel. Chatfuel is a platform to create bots for Facebook or Telegram. Set up conversational rules without having to code. Your bot will recognize similar phrases, and send users your pre-defined answers. More than 360,000 chatbots have been created using Chatfuel, from brands such as CNBC, Adidas, and British Airways. Price: Free for up to 500,000 monthly active users.

Chatfuel

Motion.ai. Motion.ai is a platform to visually build, train, and deploy chatbots on Messenger, Slack, Smooch, or your website. Diagram your conversation flow, connect your bot to a messaging service, and go. No programming skills required. Motion.ai allows you to deploy Node.js code directly from its interface. Price: Free for two bots. Premium plans start at $15 per month.

Pandorabots. The Pandorabots Playground is a integrated development environment for building chatbots. Artificial Intelligence as a Service — AIaaS — provides API access to the bot-hosting platform and SDKs, allowing developers to integrate conversational interfaces into applications. Use the same content libraries as Loebner Prize winners. Pandorabots can also build a virtual agent to your specifications, and can even help integrate avatar or speech capabilities. Price: Free.

Microsoft Bot Framework. Use the Microsoft Bot Framework to build bots to interact with your users from your website to SMS, Skype, Slack, Messenger, Office 365 mail, and more. Bot Builder SDKs allow you to build dialogs. Cognitive Services enable your bot to see, hear, interpret, and interact in more human ways. The Connector will have your bot talking in full fidelity on the most popular conversation experiences, no additional coding necessary. Use a variety of tools to develop your bot, such as QnA Maker and language understanding. Test examples from Hipmunk, AzureBot, and StubHub. Price: Free.

Microsoft Bot Framework

Chattypeople. Chattypeople is a tool to create customer support chatbots for Facebook Messenger. Recognize variations on your trigger words and phrases. Take orders from Messenger and comments. Chattypeople integrates with Stripe and PayPal. Price: Free for up to 100 customers. Advanced plan is $12.99 per month.

Botsify. Automate your live chat support with a chatbot. Humans can take over chat from chatbot anytime. The chat updates in real-time. Use a simple drag-and-drop interface to design your template. Chatbot works with Facebook Messenger. Botsify offers several plugins that��allow you to integrate your platform with chatbot, such as via RSS feed or JSON API. Price: Free for one chatbot. Premium plans start at $10 per month.

Botkit. Use Botkit to create bot applications for Slack, Facebook Messenger, and other popular platforms where bots live. Botkit is a software development toolkit for Node.js — you’ll need to write some code. However, a lot of what you need is provided. Botkit provides a variety of useful tools, including Botkit Studio, boilerplate app starter kits, a core library, and plugins to extend your bot. Botkit is community-supported open-source software that is available on GitHub. Price: Free.

Botkit

Flow XO. Build an automated bot, human, or hybrid messaging presence. Use over 100 built-in services and integrations. Talk to users through email or helpdesk, or use a web widget to promote your bots. Push content to users on demand. Start interactions by direct message, mention, or overhear. Ask questions and validate the format of the answer. Price: Standard plan is $19 per month. Free plan is available.

Smooch. Smooch is a conversational platform for multichannel messaging. Turn on automation and deliver conversational experiences at scale by connecting to bot platforms. In addition to chatbot automation, sync conversations and expand from your existing customer management system, add payments to conversations, among other features. Support channels like Messenger or Viber, sell products in conversations using Stripe, and more. Price: Free up to 500 conversations per month. Premium plan is $60 per month.

Facebook Messenger. Use the tools on Facebook’s Messenger platform to build and promote a chatbot for your business. With some basic coding, receive and send messages, use plugins and integrations, set appearance and menu, get user info, and more. Use Facebook’s Wit.ai to build conversational bots. The Wit.ai API can help you parse messages into structured, actionable data, predicting the next actions your bot should execute. Price: Free.

Facebook Messenger

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[stefanstranger]

Run Azure Runbooks with a Bot in Microsoft Teams or Skype

While working on a customer scenario where Azure Automation Runbooks needed to be started as easy as possible by less technical people I suggested to use Bots. And it turned out to be very easy to get started. No deep technical knowledge is needed to get started So what do you need to do to get started?

Pre-requisites:

Azure Subscription

Azure Automation Runbook (s)

AzureBot

Microsoft Teams (or Skype)

Microsoft Bot Framework

Before I get into the details first some background information about Bots and the Microsoft Bot Framework. A bot is a web service that interacts with users in a conversational format. Users start conversations with your bot from any channel that you’ve configured your bot to work on (for example, Text/SMS, Skype, Slack, Facebook Messenger, Microsoft Teams, and other popular services).

The Microsoft Bot Framework is a comprehensive offering that you use to build and deploy high quality bots for your users to enjoy wherever they are talking.

AzureBot

The AzureBot was created to improve the productivity of any developer, admin, or team working with Azure. You can interact with resources in your own Azure subscriptions via natural language on the Microsoft Teams, Skype, and Slack messaging channels. The current implementation enables users to authenticate to the Azure subscriptions a user has access to, select and switch subscriptions, start and stop RM-based virtual machines, and list and start Azure Automation runbooks.

How does the solution works?

You can start using AzureBot by going to the AzureBot in the Bot Framework webpage directory. You first need to add the AzureBot to one or more of your conversation channels.

After adding the AzureBot to Microsoft Teams or Skype you can start talking to the AzureBot.

First we need to login to be able to interact with the AzureBot. After typing login, your browser is opened and you need to type a code into the Skype or Microsoft Teams chat window.

Remark: Don’t copy and paste the code. Just type the code.

Next step is to select your Azure Subscription if you have multiple Azure Subscriptions.

Let we first start with listing my Azure Runbooks, but now in Microsoft Teams. Type list runbooks.

For testing purposes I created a very simple HelloWorld Runbook.

Code:

param($firstname,$lastname) Write-Output "Hello $firstname $lastname"

  If we run this in a Runbook we get the following output. Make sure you publish the runbook before you can call the runbook with the AzureBot.

To start the runbook type “run runbook stsHelloWorldPS”

Confirm you want to run runbook and enter the parameters of the Runbook

And wait for the runbook to finish.

Finally retrieve the result of the runbook by typing show job3 output.

Hope this shows how easy it is to interact with Azure Resources in Azure using the AzureBot.

from Stefan Stranger's Weblog – Manage your IT Infrastructure http://ift.tt/2kdE1a3 via IFTTT