Manage episode 232295439 series 2504282
Have you ever been on-call duty as an IT person or otherwise? Woken up at 3 a.m. to solve a problem? Did you have to go through log files or look at a dashboard to figure out what was going on? Did you think there has got to be a better way to troubleshoot and solve problems?
Today, we’re talking to Sam Bashton, who previously ran a premiere consulting partner with Amazon Web Services (AWS). Recently, he started runbook.cloud, which is a tool built on top of serverless technology that helps people find and troubleshoot problems within their AWS environment.
Some of the highlights of the show include:
- Runbook.cloud looks at metrics to generate machine learning (ML) intelligence to pinpoint issues and present users with a pre-written set of solutions
- Runbook.cloud looks at all potential problems that can be detected in context with how the infrastructure is being used without being annoying and useless
- ML is used to do trend analysis and understand how a specific customer is using a service for a specific auto scaling group or Lambda functions
- Runbook.cloud takes all aggregate data to influence alerts; if there’s a problem in a specific region with a specific service, the tool is careful to caveat it
- Various monitoring solutions are on the market; runbook.cloud is designed for a mass market environment; it takes metrics that AWS provides for free and makes it so you don’t need to worry about them
- Will runbook.cloud compete with or sell out to AWS? Amazon wants to build underlying infrastructure, other people to use its APIs to build interfaces for users
- Runbook.cloud is sold through AWS Marketplace; it’s a subscription service where you pay by the hour and the charges are added to your AWS bill
- Amazon vs. Other Cloud Providers: Work is involved to detect problems that address multiple Clouds; it doesn’t make sense to branch out to other Clouds
- Runbook.cloud was built on top of serverless technology for business financial reasons; way to align outlay and costs because you pay for exactly what you use
- Analysis paralysis is real; it comes down to getting the emotional toil of making decisions down to as few decision points as possible
- Save money on Lambda; instead of using several Lambda functions concurrently, put everything into a single function using Go
- AWS responds to customers to discover how they use its services; it comes down to what customers need
69 episodes available. A new episode about every 0 hours averaging 35 mins duration .