autobotAI Documentation

Welcome to the autobotAI documentation. This guide aims to provide you with comprehensive details on how to leverage the autobotAI platform for cloud security, compliance, and automation.

Getting Started with autobotAI

Welcome to autobotAI! In this section, we'll walk you through the initial steps to get started with this powerful hyperautomation platform. By the end of this guide, you'll have a fundamental understanding of the tool and be ready to harness its capabilities for your cloud operations.

Understanding autobotAI

Before diving into the technical details, it's essential to grasp the core concepts and components of autobotAI:

• Hyperautomation: At its heart, autobotAI is a hyperautomation platform. This means it goes beyond traditional automation by combining advanced technologies such as Generative AI, Machine Learning, and Intelligent Automation.

• AIOps for Cloud: autobotAI also falls under the category of AIOps tools for cloud operations. AIOps, or Artificial Intelligence for Cloud Operations, represents the fusion of AI and cloud operations. It's designed to manage and automate many aspects of cloud operations, especially in the context of complex cloud environments.

Reference: Hyperautomation

Setting Up Your Account

Before you can utilize autobotAI, you need to set up your account:

• Navigate to the autobotAI sign-up page.
• Enter your details.
• Verify your email address by clicking on the verification link sent to your inbox.
• Log in to your autobotAI dashboard using your credentials.

Signup to get started

Step 1: Decide Between SaaS or Workspace

Before diving into the realm of cloud automation with autobotAI, the first decision you need to make is the choice between the Software as a Service (SaaS) model or deploying your own dedicated autobotAI Workspace.

1.1 autobotAI Workspace

autobotAI Workspace offers a cloud-based automation platform powered by an AI engine. This allows users to build, deploy, and manage automation bots at scale, all within the secured boundaries of their AWS environment.

Key Features of autobotAI Workspace:

• Scalability: Customize services based on the size and complexity of your automation workloads. The platform can scale up or down seamlessly, ensuring that your operations run smoothly regardless of demand.

• Integration with AWS Services: The platform integrates with a suite of AWS services, including AWS Cognito for user authentication, AWS ECS and AWS Lambda for running automation workflows, AWS API Gateway for secure frontend connectivity, and AWS DynamoDB and DocumentDB for metadata and bot data storage.

• Security & Compliance: With autobotAI Workspace on AWS, you benefit from robust security features such as role-based access control, encryption, and compliance with industry standards like HIPAA and GDPR. Additionally, the integration with AWS services like IAM and VPC offers enhanced security measures for your automation workflows.

Resources Deployed with Workspace:

• Lambda Functions
• ECS Cluster (Fargate Based)
• DynamoDB (1 Instance)
• DocumentDB (2 Tables)
• Cloud9
• AWS VPC, Subnets, Elastic IP, and Internet Gateway
• API Gateway
• Cognito User Pools
• Cognito Identity Pools
• IAM Roles and Custom Policies
• Cloudwatch Events (Scheduled Events)
• Cloudwatch Logs

View Architecture Diagram []

1.2 autobotAI SaaS

For those looking for a hassle-free setup without diving deep into AWS configurations, autobotAI also offers a SaaS version. This option is ideal for smaller cloud environments and businesses looking for a quick start without infrastructure overhead.

Benefits of Choosing SaaS:

• Quick Setup: No need to worry about deploying and configuring any resources in your cloud environment. Get started with your automation tasks in no time.
• Managed Service: Let autobotAI handle the updates, maintenance, and infrastructure management.
• Cost-Effective: Ideal for businesses with smaller cloud environments, reducing infrastructure costs.

Step 2: Workspace Deployment (If Workspace Option is Selected)

2.1 Prerequisites for autobotAI Workspace Deployment

• Ensure you have an AWS account with the necessary permissions to deploy the listed resources.
• Familiarity with AWS services and their configurations is beneficial, though not mandatory.
• Ensure your AWS account is set up to handle the costs associated with deploying the mentioned AWS resources.

2.2 Deploying autobotAI Workspace

Access the autobotAI deployment guide and follow the step-by-step instructions to deploy the Workspace in your AWS account.

• Adding your first Automation account for Workspace.
• Deploying your first Workspace

Ensure all resources are correctly configured, and integrations with AWS services are established.

Once deployed, you can start building, deploying, and managing your automation bots within the Workspace.

Step 3: Integrate Cloud Accounts & Communication Tools

Whether you've chosen SaaS or Workspace, the next step involves integrating your cloud accounts (AWS, Azure, GCP) and communication tools (MS Teams, Google Chat, Email, etc.). This integration allows autobotAI to interact with your cloud resources and send notifications or gather approvals when necessary.

Follow the integration guide provided by autobotAI to establish these connections, ensuring a seamless automation experience.

Creating a Bot to make AWS S3 buckets private.

With these steps, you're now ready to dive into the world of cloud automation with autobotAI. Enjoy the journey and watch your operations become more efficient, secure, and automated!

Navigating the autobotAI

Once logged in, you'll be presented with the autobotAI custom dashboard. Familiarize yourself with the primary tabs:

• Dashboard: Overview of your cloud environment compliance violations, automation bot workflow execution, pending approvals, Cloud platforms and kubernetes inventory overview. You can customize this dashboard by adding or removing widgets for each custom dashboard tab.

• Integrations: Where you can connect autobotAI to cloud platforms like AWS, Azure, GCP, kubernetes, git, MS teams, google Chat, trendmicro and other tools.

• Fleets: Manage multiple bot workflow assignment to large number of cloud accounts with customised overrride variable for automation execution.

• Bots: Your automation workflows reside here. Create, manage, and monitor them from bots page.

• Bot marketplace: Bot Marketplace contains library of predefined bot automations that can be deployed to your environment with few clicks. You can customise marketplace bot once deployed to your workspace or SaaS environment.

• Workspaces: Ensure data privacy and compliance by setting up and managing separate workspaces. You can deploy multiple workspaces from your root autobotAI account. List of workspaces available at user management icon at the top right side of the page.

Integrating Cloud Platforms and Tools

Once you have the foundation set with either the SaaS model or the autobotAI Workspace, the next step is to bring your cloud platforms and tools into the mix.

1. Cloud Platforms

autobotAI is built to seamlessly integrate with major cloud providers:

• AWS: Connect your AWS accounts to autobotAI to harness the power of cloud automation across various AWS services.

• Azure: By integrating Azure, you can expand your automation capabilities to the vast array of services offered by Microsoft's cloud platform.

• GCP (Google Cloud Platform): Integrate GCP to ensure your Google Cloud resources are part of your automation workflows.

• Kubernetes: Integrate Kubernetes workload deployed with self managed cluster, RedHat openshift, or managed kubernetes services (e.g. AWS EKS, Azure AKS, GCP GKE). Security insights and automation can be implemented to execute security and operations automation actions for kubernetes workloads.

2. Communication Tools

autobotAI understands the importance of effective communication for notifications and approval processes. Hence, autobotAI offers integrations with:

• MS Teams: Get notified, approve tasks, or even trigger bots directly from your Teams channel.

• Google Chat: Stay updated and interact with your automation workflows without leaving your chat.

• Email: Receive notifications, summaries, and approvals right in your inbox.

Others (Jira, git, trendmicro)

Extend your automation capabilities by integrating tools like Jira for ticketing or Trend Micro for enhanced security.

Setting up Fleets

A fleet in autobotAI is a group of resources that can be managed and automated as a single unit. Setting up fleets allows you to efficiently manage, monitor, and automate tasks for a group of resources.

Steps to Set Up Fleets

• Access the Fleet Management: Navigate to the 'Fleets' section in your autobotAI interface.

• Define and create Fleet: Group your resources based on function, region, project, or any criteria that suits your organization's structure.

• Assign Automation Bots: Once your fleet is defined, assign specific bots to manage and automate tasks for this fleet.

Creating and Managing Bots

Bots are at the heart of autobotAI. They are automation workflows that carry out tasks, gather data, send notifications, and more.

Steps to Create a Bot

• Access the Bot Creation Dashboard: Navigate to the 'Bots' section in your autobotAI interface.

• Define Your Bot: Specify the tasks, triggers, and actions for your bot.

• Test Your Bot: Before deploying, ensure your bot is functioning as expected by running tests.

• Deploy: Once satisfied, deploy your bot to start its automation tasks.

Insight: Your Window into Cloud Compliance and Inventory

autobotAI's "Insight" is a powerful feature that gives users a comprehensive view into their cloud configurations and resources. Not only does it assist in identifying misconfigurations across multiple platforms, but it also provides an in-depth inventory of cloud and Kubernetes resources.

Key Capabilities of Insight

• Misconfiguration Visibility: Insight scans and reports misconfigurations across AWS, Azure, GCP, and Kubernetes.

• Cloud and Kubernetes Inventory Details: Users can view their inventory in various formats such as graph view, tree view, and even perform ad-hoc resource searches.

Compliance Standards Supported by Insight

Insight can check for compliance violations across several standards for different cloud platforms. Below is a breakdown of the supported standards for each platform:

Cloud Platform and Supported Compliance Standards

• AWS <br> - Audit Manager Control Tower<br>- CIS Controls v8 IG1<br>- CIS v120<br>- CIS v130<br>- CIS v140<br>- CIS v150<br>- CISA Cyber Essentials<br>- FedRAMP Low rev 4<br>- FedRAMP moderate rev 4<br>- FFIEC<br>- Foundational Security<br>- GDPR<br>- GxP 21 CFR part 11<br>- GxP EU Annex 11<br>- HIPAA Security Rules 2003<br>- HIPAA Final Omnibus Security rule 2013<br>- NIST 800 171 rev2<br>- NIST 800 53 rev 4<br>- NIST 800 53 rev 5<br>- NIST CSF<br>- PCI DSS v321<br>- RBI Cyber security <br>- SOC 2<br>- Other

• Azure<br> - CIS v130<br>- CIS v140<br>- CIS v150<br>- CIS v200<br>- HIPAA HiTrust v92<br>- NIST SP 800 53 rev 5<br>- PCI DSS v321

• GCP<br> - CFT Scorecard v1<br>- CIS v120<br>- CIS v130<br>- CIS v200<br>- Forseti Security v226

• Kubernetes<br> - CIS Kube v120<br>- Extra Checks<br>- NSA Cisa v1

How to Use Insight

• Integration: Start by adding integrations for each desired cloud platform or Kubernetes.

• Scheduling: Enable a schedule to fetch insights on compliance violations regularly.

Note: While Insight provides valuable insights into compliance violations, it is not intended to replace CSPM, CIEM, CWPP, or CNAPP tools. The primary objective of Insight is to guide users on prioritization in case any of the above tools are not being used from partner solutions (e.g., trendmicro). For instance, if a considerable number of resources consistently violate a specific compliance check, it indicates a pressing need for automation in that area. Also, remember, the compliance violations flagged by Insight are specific to the mentioned checks. To fetch these details, users must grant the necessary permissions for each cloud or Kubernetes integration.

Dive Deeper

For those looking to harness the full power of autobotAI, we recommend diving deeper into advanced features, integrations, and best practices.

• Generative AI: Explore how GenAI can revolutionize your automation workflows, from fetcher code generation to interactive bot creation.

• Advanced Integrations: Bring your own generative AI model or delve into the advanced capabilities of integrated tools.

• Best Practices: Stay updated with the latest in cloud automation best practices, ensuring efficiency, security, and scalability.

With these steps, you're not only started with autobotAI but also on the path to becoming a cloud automation maestro. Remember, automation is not just about tasks; it's about transforming operations, enhancing security, and driving efficiency.

Seeking Assistance and Accessing Resources

As you embark on your journey with autobotAI, remember that you're not alone. We've cultivated a range of resources to assist you:

• Documentation and User Guides: Dive deeper into specific features, integrations, and functionalities with our comprehensive guides.

• Community Forums: Join discussions, share your experiences, ask questions, and learn from other autobotAI users.

• Support: If you encounter any challenges or need technical assistance, our dedicated support team is here to help. Reach out through the support portal for timely and expert assistance.

• Tutorials and Webinars: Periodically, we conduct webinars and release tutorials to introduce new features, best practices, and advanced techniques. Stay tuned to our announcements!

• FAQs: Addressing common questions and troubleshooting issues can be helpful for users who might run into typical challenges.

Remember, every challenge is an opportunity to learn. We're here to ensure your experience with autobotAI is seamless and productive.