No more reports with colorful charts!! Just say and it should be done.
Today majority of cloud management teams go through multiple cost, performance and alert reports with 85% - 95% green charts. Today cloud service provider provides cost and performance management service but utilizing the same is a challenge because of static intelligence and lots of metrics correlation. technical team starts ignoring such reports after a period of time or stops focusing on daily bases. A true helpful tool should understand your development, staging or production environment and help you fix the real issues while you are having a cup of coffee.
Today multiple tools and platform has made SysOps and DevOps team busy in mondaine job which prevents them to innovate in new areas.
What it does
Skill will be released in mid April 2018. Autobot is an AI that helps Alexa for business and Alexa users to optimise cloud cost, enhance cloud security and make SysOps faster and secure. Just ask and It will do it.
Now managing aws cost, security compliance and optimisation is as easy as telling Alexa to turn on a light. Autobot enables Alexa and Alexa for business users to execute mondaine tasks within few seconds. Benefits *AWS maintenance events: * It gives you update on cloud maintenance events like scheduled ec2 reboot so you can plan maintenance without affecting application users. It also provides other cloud service provider’s planned and unplanned change management in different aws services.
*Check security compliance and configuration best practice: * It checks various security compliance rules so your infrastructure vulnerability can not expose attack surface for malicious activity.
*Check security anomaly detection: * Like performance monitoring , keeping the attack serface low and monitoring the behavioral pattern for security is as important. Autobot can give security anomaly detection (in all layers). All you have to do is ask.
*Cost optimization: * Autobot checks any unused aws resources and cleanup the same to reduce tangible aws cost or intangible operational cost. Autobot helps you to identify the old generation instances in the region where new generation instances are available. Moving to new generation instances (eg. M4 to M5) can optimise cost and improve performance.
*Billing and budget management: * You can set monthly, quarterly or yearly budget or update the same by asking autobot. You can also check the current budget utilization for month, quarter and annual forecast before budget exceeds the threshold.
*Alert and availability management: * Today cloud infrastructure is agile which can span 100s of server on demand. Configuring autorecovery and basic alert management is still manual activity. Autobot identifies new or modified resources and configure alarms for critical resource utilization and also configures ec2 auto recovery, so you can act before impaired system impacts application. Such manual alarm creation in aws takes days after detecting resources change. Autobot AI enables to configure same in seconds.
*Troubleshoot network issue: * It can also help you troubleshoot VPN connectivity issues and gives recommendation to achieve high availability.
*Reserved instance utilization monitoring: * Autobot helps to make sure you utilize your reserved instance and provides recommendation if identifies any anomaly in reserved instance utilisation.
*EC2, RDS instance state management: * Remember to turn off the lights and stop development or staging environment when you are not using it. It helps to save energy and cost. Now you can do both by telling alexa. It also helps you start the same when you need it.
*Clear CDN cache after content update: * Whenever development team does the update in application static content and you need to refresh cloudfront edge locations with new content, autobot will help you clear cloudfront cache in development, staging or production cdn distribution.
*AWS OS level automation integration: * Aws systems manager helps to secure serverless administration. Autobot helps you check weather systems manager is configured or not and configures cloud infrastructure with best practice.
*Check the state of production/development/qa environment: * The simplest activity like checking the state of development , production or staging servers across all AWS regions is also a time consuming task. Autobot enables user to enhance information gathering so team can take decision instantly.
*EC2 instance Backup management: * Instance backup is important task before or after completing any administrative activity. Any configuration change in environment can cause application impact because of chain reaction hence we take AMI backup before or after the change. Autobot can enable you to take backup of development/staging/production environment instances by just telling to take backup.
*S3 and EBS storage usage per environment and region: * Identify total s3 storage utilization and EBS usage in development, staging and production is a time consuming activity in aws. Autobot provides details for different type of storage utilization in different environments.
How we built it
Autobot AI is using AWS Lambda functions in back-end with python and node.js. Frontend web application is developed with AWS S3, API gateway, lambda function and DynamoDB integration.
Challenges we ran into
There were multiple challenges we ran into with respect to performance when dealing with large AWS infrastructure assessments. We have overcome this challenge with extensive automation with connected AWS infrastructure.
Accomplishments that we're proud of
Autobot AI is able to reduce any AWS L1 engineer by helping AWS team to complete day to day activity within few minute. without such automation such administration tasks consumes 80% of time. With autobot AI administrator can focus on innovation and new AWS architecture deployments.
What we learned
Many optimization and security best practice.
What's next for AutobotAI
Enable skill for many OS, application, trendmicro and other security tool integration level automations which can fix most of the L2 level cloud administrator tasks by just asking alexa. It is in development phase with ML integration for anomaly detection . next phase of development will be Backend support team (community level using Alexa call) to help user when AI reaches it's limitations in real time production issues