1/11/2024 0 Comments Chatbot aws![]() ![]() Ref: SecurityIssuesSnsTopic Id: SecurityTopic EcrVulnerabilitiesEventRule: ! Sub arn:aws:securityhub:$:action/custom/reportfindings Targets: Security Hub Findings - Custom Action resources: Name: detect-securityhub-findings Description: A CloudWatch Event Rule that triggers on Amazon Security Hub findings. Ref: SecurityIssuesSnsTopic Id: SecurityTopic SecurityHubFindingEventRule: Name: detect-guardduty-findings Description: A CloudWatch Event Rule that triggers on Amazon GuardDuty findings. Type: String Description: Contains the ARN of the SNS topic on which security issues are published. ![]() The hardest part is capturing the EventBridge events and forwarding them to SNS, so here the CloudFormation to help you out on that part:ĪWSTemplateFormatVersion: '' Description: Forward EventBridge security events to AWS SNS Parameters: On top of that AWS Chatbot is configured to listen to that SNS topic and to forward all messages to Slack.Ĭreating the SNS Topic and setting up AWS Chatbot to listen to the SNS Topic and forward the messages to your chat client is very easy and done in a few clicks. Using AWS Eventbridge, we collect all notifications on a single SNS topic named ‘security-issues’. It turns out that showing all your security findings and alerts in your chat client is quite easy. So ideally, we just had to add our security notifications to the same chatroom to get notified and to never miss a security issue again. All these notifications are collected in a dedicated room for which a company policy dictates those should be all read. On the other side, we heavily use Slack for chat and notifications from build pipelines, service changes, system errors, etc. I’m not the person to check all these dashboards on a daily basis for new findings, I simply forget to do so. The only issue I had, is that often their findings stayed under the radar way too long. Integration with Amazon Lex is available with Amazon Connect, a simple to use, cloud-based contact center service, but you can also take advantage of the 8kHz feature with Amazon Lex in your preferred call center solution.To secure our AWS Cloud setup we use quite some tools:ĪWS Security Hub, AWS Inspector, AWS Guardduty and ECR Vulnerability Scanning just to name a few.Īll these tools are both easy to set up and do a very nice job finding weaknesses and treats. Additionally, Amazon Lex chatbots support an optimal (8 kHz) telephony audio sampling rate, to provide increased speech recognition accuracy and fidelity for your contact center interactions. Amazon Lex maintains context and manages the dialogue, dynamically adjusting the responses based on the conversation, so your contact center can perform common tasks for callers, to address many customer inquiries through self-service interactions. ![]() Using the same technology that powers Amazon Alexa, an Amazon Lex chatbot can be attached to your contact flow to recognize the intent of your caller, ask follow-up questions, and provide answers. Using Amazon Lex, a service that allows you to create intelligent conversational chatbots, you can turn your call center contact flows into natural conversations that provide personalized experiences for your callers. Callers can perform tasks such as changing a password, requesting a balance on an account, or scheduling an appointment, without the need to speak to an agent. These chatbots are able to recognize human speech and understand the caller’s intent without requiring the caller to speak in specific phrases. Today, AI is playing a role in improving this customer experience in call centers to include engagement through chatbots - intelligent, natural language virtual assistants. Waiting on hold, repeating information from one agent to the next, and generally spending too much time getting answers to questions can all lead to a lengthy and often frustrating customer journey. Contacting customer service can often be a challenging experience, since the conversation engagement does not always meet the caller’s expectation. ![]()
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