With a blue/green deployment, you provision a new set of instances on which CodeDeploy installs the latest version of your application. CodeDeploy then reroutes load balancer traffic from an existing set of instances running the previous version of your application to the new set of instances running the latest version. After traffic is rerouted to the new instances, the existing instances can be terminated. Blue/green deployments allow you to test the new application version before sending production traffic to it. If there is an issue with the newly deployed application version, you can roll back to the previous version faster than with in-place deployments. Additionally, the instances provisioned for the blue/green deployment will reflect the most up-to-date server configurations since they are new. Problem with Blue/Green deployment is that once the fleet is replaces, if you had any EIP attached to the older instances, you have to manually reattch them to the new fleet. Her
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Voice based virtual assistance for CloudOps
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Why developed autobotAI....
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 mundane tasks which prevents them to innovate in new areas.
autobotAI is an artificial intelligence that helps you reduce your cloud cost, enhance cloud security.
Just ask and It will do it.
Now managing aws cost, security compliance and optimization is as easy as telling Alexa to turn on a light. autobotAI enables Alexa and Alexa for business users to execute mundane tasks within few seconds.
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 surface low and monitoring the behavioural pattern for security is as important. autobotAI can give security anomaly detection (in all layers). All you have to do is ask. In product pipeline AWS guardduty, WAF (AWS and cloudflare) and various security tool integration are there which can really help DevSecOps.
Cost optimisation:
autobotAI checks any unused aws resources and cleanup the same to reduce tangible aws cost or intangible operational cost. autobotAI 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 utilisation 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 auto recovery and basic alert management is still manual activity. autobotAI identifies new or modified resources and configure alarms for critical resource utilisation 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. autobotAI enables to configure same in seconds.
Troubleshoot network issue:
It can also help you troubleshoot network connectivity issues and gives recommendation to achieve high availability. Currently VPN related issues identification is available. other network correlation related network issue fix is on the roadmap.
Reserved instance utilization monitoring:
autobotAI helps to make sure you utilize your reserved instance and provides recommendation if identifies any anomaly in reserved instance utilization.
EC2, RDS instance state management:
Remember to turn off the lights and stop development or staging environment when you are not using it. Its a new rule of thumb for cost optimisation. It helps to save energy and cost for business. 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.
What is next in its road map:
Enable skill for many OS, application, Trend micro and other security tools integration level which can help DevSecOps, DevOps and SysOps team on day to day tasks cloud administrator tasks by just asking alexa. It is in development phase (with ML integration). AI integration for AWS resource monitoring is under development and the same will be released in 2nd phase.
Really nice information, This information will always help everyone for gaining knowledge. So please always share your valuable information. I am very thankful to you for providing good information about Cloud Maintenance And Tyre Management.
With a blue/green deployment, you provision a new set of instances on which CodeDeploy installs the latest version of your application. CodeDeploy then reroutes load balancer traffic from an existing set of instances running the previous version of your application to the new set of instances running the latest version. After traffic is rerouted to the new instances, the existing instances can be terminated. Blue/green deployments allow you to test the new application version before sending production traffic to it. If there is an issue with the newly deployed application version, you can roll back to the previous version faster than with in-place deployments. Additionally, the instances provisioned for the blue/green deployment will reflect the most up-to-date server configurations since they are new. Problem with Blue/Green deployment is that once the fleet is replaces, if you had any EIP attached to the older instances, you have to manually reattch them to the new fleet. Her
We at autobotAI take security very seriously. We know it is our responsibility to make sure that everything is secure when our customers are trusting us with their cloud infrastructure. We make sure that our system is security compliant all the time. We our self use autobotAI to keep the security compliance in check. Here's some of the things that we do/have that make us the most secure platform. OTP(Verification Code) based verification for critical skill invocations. We want to make sure that every task autobotAI can do is verified. For every critical skill invocation like shutting down instance or resource cleanup we require customers provide Verification Code(OTP) that is shown in Alexa App. This makes sure to avoid any unauthorised access to the autobotAI skill. It WILL NOT execute any critical tasks until the user is verified. This is a small inconvinience for security untill we have have voice recognition base authentication in place. Here's some of the t
Really nice information, This information will always help everyone for gaining knowledge. So please always share your valuable information. I am very thankful to you for providing good information about Cloud Maintenance And Tyre Management.
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