Hyperautomation

Hyperautomation is a business-driven, disciplined approach that organizations use to rapidly identify, vet and automate as many business and IT processes as possible. Hyperautomation involves the orchestrated use of multiple technologies, tools or platforms, including: artificial intelligence (AI), machine learning, event-driven software architecture, robotic process automation (RPA), business process management (BPM) and intelligent business process management suites (iBPMS), integration platform as a service (iPaaS), low-code/no-code tools, packaged software, and other types of decision, process and task automation tools.

Gartner

Here are some use cases:

1. Accounts Payable and Receivable: Hyperautomation can be used to automate the process of invoicing, payment, and reconciliation in the finance and accounting department.
2. Customer Service: Hyperautomation can be used to automate the process of handling customer inquiries, complaints, and support tickets by using chatbots and automated email responses.
3. Human Resources: Hyperautomation can be used to automate the process of onboarding, employee records management, and payroll processing in the HR department.
4. Sales and Marketing: Hyperautomation can be used to automate the process of lead generation, lead nurturing, and customer relationship management in the sales and marketing department.
5. Supply Chain and Logistics: Hyperautomation can be used to automate the process of order processing, inventory management, and shipping and logistics.
6. Healthcare: Hyperautomation can be used to automate patient record management, appointment scheduling, and billing in the healthcare industry.
7. Legal: Hyperautomation can be used to automate the process of contract management, document review, and legal research in the legal industry.
8. Manufacturing: Hyperautomation can be used to automate the process of quality control, inventory management, and production planning in the manufacturing industry.
9. IT Operations: Hyperautomation can be used to automate the process of software deployment, system monitoring, and incident management in the IT department.
10. Research and Development: Hyperautomation can be used to automate the process of data analysis, experiment management, and knowledge sharing in the research and development department.

Prime: AI

Artificial intelligence (AI) is a key component of hyperautomation, as it enables organizations to automate more complex and cognitive tasks that previously required human intervention. AI technologies, such as machine learning (ML), natural language processing (NLP), and computer vision, can be used to automate tasks such as data analysis, decision-making, and customer service.

In the hyperautomation context, AI is often used in conjunction with other automation technologies, such as robotic process automation (RPA) and low-code development platforms, to create end-to-end automated workflows. For example, an RPA bot could be used to collect and process data, which could then be fed into an ML model to make predictions or generate insights. These insights could then be used to trigger automated actions or inform human decision-making.

Prime: RPA

Robotic Process Automation (RPA) is a technology that enables organizations to automate repetitive, rules-based tasks using software robots or “bots”. RPA bots are designed to mimic the actions of human workers, interacting with software applications in the same way that a human worker would.

RPA is often used in conjunction with other automation technologies, such as artificial intelligence (AI), machine learning (ML), and natural language processing (NLP), to create more sophisticated and intelligent automation solutions. For example, an RPA bot could be used to collect and process data, which could then be fed into an ML model to make predictions or generate insights. These insights could then be used to trigger automated actions or inform human decision-making.

There are many RPA (Robotic Process Automation) platforms available in the market today, each with its own set of features and capabilities. Here are a few examples of popular RPA platforms:

1. UiPath: UiPath is a leading RPA platform that provides a range of features for automating routine and repetitive tasks. It includes a visual interface for designing and managing bots, as well as pre-built connectors and adapters for popular applications and systems.
2. Automation Anywhere: Automation Anywhere is an RPA platform that provides a range of features for automating routine and repetitive tasks. It includes a visual interface for designing and managing bots, as well as pre-built connectors and adapters for popular applications and systems.
3. Blue Prism: Blue Prism is an RPA platform that provides a range of features for automating routine and repetitive tasks. It includes a visual interface for designing and managing bots, as well as pre-built connectors and adapters for popular applications and systems.
4. WorkFusion: WorkFusion is an RPA platform that provides a range of features for automating routine and repetitive tasks. It includes a visual interface for designing and managing bots, as well as pre-built connectors and adapters for popular applications and systems.
5. Kryon: Kryon is an RPA platform that provides a range of features for automating routine and repetitive tasks. It includes a visual interface for designing and managing bots, as well as pre-built connectors and adapters for popular applications and systems.

Prime: iBPMS

Intelligent Business Process Management Suites (iBPMS) is a category of business process management (BPM) software that uses artificial intelligence (AI) and other advanced technologies to automate and optimize business processes.

An iBPMS platform provides a range of features for managing and automating business processes, including process modeling, workflow automation, rules management, analytics, and integration with other systems and services. iBPMS solutions typically include advanced analytics and AI capabilities, such as machine learning and predictive analytics, which enable organizations to analyze process data and make better decisions in real-time.

iBPMS platforms are designed to support the entire process lifecycle, from process design and modeling to execution and monitoring. They provide a visual interface for designing and managing workflows, and allow users to set up rules and triggers for automated actions.

There are several iBPMS (Intelligent Business Process Management Suite) solutions available in the market today, each with its own set of features and capabilities. Here are a few examples of popular iBPMS solutions:

1. Appian: Appian is an iBPMS solution that provides a range of features for managing and automating business processes. It includes a visual interface for designing and managing workflows, as well as pre-built connectors and adapters for popular applications and systems. Appian also includes AI capabilities, such as machine learning and natural language processing, to automate and optimize business processes.
2. IBM Business Automation Workflow: IBM Business Automation Workflow is an iBPMS solution that provides a range of features for managing and automating business processes. It includes a visual interface for designing and managing workflows, as well as pre-built connectors and adapters for popular applications and systems. IBM Business Automation Workflow also includes AI capabilities, such as machine learning and predictive analytics, to automate and optimize business processes.
3. Pegasystems: Pegasystems is an iBPMS solution that provides a range of features for managing and automating business processes. It includes a visual interface for designing and managing workflows, as well as pre-built connectors and adapters for popular applications and systems. Pegasystems also includes AI capabilities, such as machine learning and natural language processing, to automate and optimize business processes.
4. Kofax TotalAgility: Kofax TotalAgility is an iBPMS solution that provides a range of features for managing and automating business processes. It includes a visual interface for designing and managing workflows, as well as pre-built connectors and adapters for popular applications and systems. Kofax TotalAgility also includes AI capabilities, such as machine learning and predictive analytics, to automate and optimize business processes.

Prime: iPaaS

Integration Platform as a Service (iPaaS) is a cloud-based platform that provides a set of tools and services for integrating applications, data, and systems across different cloud and on-premise environments.

iPaaS solutions typically provide a range of features for connecting and integrating systems, including pre-built connectors and adapters, data mapping and transformation, workflow automation, and data governance and security. iPaaS platforms also typically provide a range of tools and services for managing and monitoring integrations, including dashboards, alerts, and analytics.

There are many iPaaS solutions available in the market today, each with its own set of features and capabilities. Here are a few examples of popular iPaaS solutions:

1. Dell Boomi: Dell Boomi is a cloud-based iPaaS platform that provides a range of features for integrating applications, data, and systems across different cloud and on-premise environments. It includes pre-built connectors and adapters for popular applications and systems, as well as a visual interface for designing and managing integrations.
2. MuleSoft Anypoint Platform: MuleSoft Anypoint Platform is a cloud-based iPaaS platform that enables organizations to connect and integrate applications, data, and systems across different cloud and on-premise environments. It includes a range of tools and services for designing, managing, and monitoring integrations, as well as pre-built connectors and adapters for popular applications and systems.
3. Jitterbit: Jitterbit is a cloud-based iPaaS platform that provides a range of features for integrating applications, data, and systems across different cloud and on-premise environments. It includes a visual interface for designing and managing integrations, as well as pre-built connectors and adapters for popular applications and systems.
4. SnapLogic: SnapLogic is a cloud-based iPaaS platform that enables organizations to connect and integrate applications, data, and systems across different cloud and on-premise environments. It includes pre-built connectors and adapters for popular applications and systems, as well as a visual interface for designing and managing integrations.

Prime: Low-Code

Low-code is a visual development approach to software development that allows users to create applications through a drag-and-drop interface with minimal coding. The idea behind low-code is to simplify the development process by abstracting away much of the complexity of traditional coding, allowing users with little to no programming experience to create functional applications.

Low-code platforms typically provide a set of pre-built components and modules that can be pieced together to create a custom application. These platforms also offer a range of tools and features to help users design, develop, test, and deploy applications quickly and easily.

Low-code development is being increasingly used by businesses to rapidly develop and deploy custom applications that meet their specific needs, without the need for dedicated software development teams. The low-code approach can help reduce costs, accelerate development times, and improve the agility and responsiveness of businesses to changing market conditions.

Low-code development platforms are an important aspect of hyperautomation because they provide a way for non-technical users to create applications and workflows quickly and easily. This enables organizations to automate processes that might have previously required custom software development, reducing costs and accelerating time to value.

There are many low-code development platforms available in the market today, each with its own set of features and capabilities. Here are a few examples of popular low-code platforms:

1. Microsoft Power Apps: Microsoft Power Apps is a low-code platform that enables users to build custom business applications quickly and easily. It includes a visual interface for designing and building applications, as well as pre-built templates and connectors for popular data sources and services.
2. OutSystems: OutSystems is a low-code platform that enables users to build custom business applications quickly and easily. It includes a visual interface for designing and building applications, as well as pre-built templates and connectors for popular data sources and services.
3. Mendix: Mendix is a low-code platform that enables users to build custom business applications quickly and easily. It includes a visual interface for designing and building applications, as well as pre-built templates and connectors for popular data sources and services.
4. Salesforce Lightning: Salesforce Lightning is a low-code platform that enables users to build custom business applications quickly and easily. It includes a visual interface for designing and building applications, as well as pre-built templates and connectors for popular data sources and services.
5. Appian: Appian is a low-code platform that enables users to build custom business applications quickly and easily. It includes a visual interface for designing and building applications, as well as pre-built templates and connectors for popular data sources and services.

Architecture

The architecture of a hyperautomation system should be designed to support the different components and technologies used in the system. Here’s a high-level overview of the architecture of a hyperautomation system:

1. Data Ingestion: This component is responsible for collecting data from various sources such as emails, documents, databases, and other systems.
2. Intelligent Automation: This component is responsible for processing the data using AI and ML algorithms to extract relevant information and automate tasks.
3. Process Automation: This component is responsible for automating end-to-end business processes by using RPA tools to automate repetitive tasks and human workflows.
4. Integration and Orchestration: This component is responsible for integrating the hyperautomation system with other enterprise systems and orchestrating the automation workflows.
5. Analytics and Reporting: This component is responsible for providing insights and analytics on the performance of the hyperautomation system.

Google Cloud

Google Cloud offers a variety of services and tools that can be used to implement a hyperautomation system:

1. Data Ingestion: Google Cloud offers several services for data ingestion, including Cloud Storage for storing data, Cloud Pub/Sub for messaging, and Cloud Dataflow for data processing.
2. Intelligent Automation: Google Cloud offers several AI and ML services, such as Cloud AutoML, Cloud AI Platform, and Cloud Vision API, which can be used for intelligent automation.
3. Process Automation: Google Cloud offers a service called Cloud Composer, which is a fully managed workflow orchestration service that can be used for process automation. It also supports integrating with RPA tools such as UiPath.
4. Integration and Orchestration: Google Cloud offers several services for integration and orchestration, including Cloud Functions, Cloud Run, and Cloud Workflows.
5. Analytics and Reporting: Google Cloud offers several services for analytics and reporting, including BigQuery for data warehousing and analysis, and Data Studio for creating and sharing reports.

Google AppSheet

Google offers a low-code development platform called Google AppSheet. Google AppSheet allows users to create custom business applications quickly and easily using a drag-and-drop interface, without the need for extensive coding.

Google AppSheet provides a range of features for building custom applications, including data modeling, workflow automation, and integration with other Google services, such as Google Drive, Google Sheets, and Google Cloud services. AppSheet can be used to build applications for a variety of use cases, including inventory management, project management, and field service management, among others.

Proof of Concept Architecture

1. VPC Flow Logs: Enable VPC Flow Logs on your network to capture all network traffic to and from instances in your VPC.
2. BigQuery: Set up a BigQuery dataset and table to store your VPC Flow Logs.
3. Cloud Functions: Create a Cloud Function to process new VPC Flow Log events and trigger a notification to the user to ask if the flow should be allowed.
4. Pub/Sub: Create a Pub/Sub topic to receive messages from the Cloud Function when a new flow is detected.
5. Dialogflow: Use Dialogflow to create a chatbot or voicebot that prompts the user to allow or deny the new flow.
6. Cloud Functions: Create another Cloud Function to handle the response from the user. If the user allows the new flow, the Cloud Function should create a firewall rule to allow the traffic.
7. Google AppSheet: Create a custom mobile or web application using Google AppSheet that enables users to manage firewall rules and alerts, including viewing new flow alerts, approving or denying new flows, and creating new firewall rules.
8. Integrate with the workflow: Use AppSheet’s connectors and APIs to integrate the application with the rest of the workflow.
9. Monitor the workflow and application: Use monitoring and analytics tools such as Stackdriver Logging and AppSheet’s built-in monitoring and analytics to track usage, identify issues, and optimize the workflow and application.

This hyperautomation solution combines several Google Cloud Platform services to automate the process of managing firewall rules based on VPC Flow Logs. The solution enables real-time monitoring of network traffic and quickly responds to potential security threats. By automating the process of asking for permission to allow new flows and creating firewall rules, the workflow ensures that all firewall rules are reviewed and approved by authorized users, reducing the risk of unauthorized access. The use of Google AppSheet enables users to manage firewall rules and alerts from their mobile or web devices, providing quick access to relevant data. The workflow is also monitored using Stackdriver Logging and AppSheet’s built-in monitoring and analytics tools to ensure optimal performance.

VPC Flow Logs

VPC Flow Logs and Big Query is covered here:

All those (vpc) flow logs… Consolidate vpc flow logs using BigQuery

Pub/Sub

Function

Dialogflow

Functions

AppSheet

Monitoring

References

https://www.gartner.com/en/information-technology/glossary/hyperautomation

BrainStorm Area

Implementation

To implement a hyperautomation system, you need to follow these steps:

1. Identify the processes to be automated: The first step is to identify the processes that can be automated using hyperautomation technologies.
2. Design the architecture: Once the processes are identified, design the architecture that best suits your requirements.
3. Choose the technologies: Choose the right technologies for each component of the hyperautomation system.
4. Build the system: Build the system using the selected technologies and architecture.
5. Test and validate the system: Test and validate the system to ensure that it meets the business requirements and objectives.
6. Deploy the system: Deploy the system in the production environment.

Documentation

Documentation is an essential part of any hyperautomation system. Here are the documents that you need to prepare:

1. Architecture document: This document should provide a detailed overview of the hyperautomation system’s architecture and design.
2. Implementation document: This document should provide a step-by-step guide on how to implement the hyperautomation system.
3. User manual: This document should provide instructions on how to use the hyperautomation system.
4. Test plan: This document should provide a detailed plan for testing the hyperautomation system.
5. Maintenance and support document: This document should provide information on how to maintain and support the hyperautomation system.

IT Operations

Here’s an example architecture for an IT operations hyperautomation system using Google Cloud services:

1. Data Ingestion: Use Google Cloud Storage to store log files from various systems and applications, and Cloud Pub/Sub to receive notifications of new log files.
2. Intelligent Automation: Use Cloud AI Platform to analyze log data and identify patterns, anomalies, and errors. You can also use Cloud AutoML to train custom models for specific use cases.
3. Process Automation: Use Cloud Composer to create and manage workflows for incident management, such as deploying new code, restarting services, and sending notifications to stakeholders.
4. Integration and Orchestration: Use Cloud Functions to trigger automation workflows based on events in other systems or applications. Use Cloud Run to deploy containerized applications that can be scaled automatically based on demand.
5. Analytics and Reporting: Use BigQuery to store and analyze log data over time, and use Data Studio to create dashboards and reports that provide insights into the performance of the IT operations system.