The Cloudcast #169 - DevOps Incident Management with BigPanda

Big Panda - http://bigpanda.io/

• Golden Age of Developers = Nightmare for Ops: http://blog.bigpanda.io/golden-age-of-developers-nightmare-for-ops

Topic 1 - Announced A Round and came out of stealth yesterday. Give us a quick overview of Big Panda and the problem you are trying to solve

Topic 1.5 - The service - Is it an aggregator, a single interface or a different way to create a contextual view of apps? “Command and Control?”

Topic 2 - Is this a service for Ops teams, or do you see developers wanting access to validate what Ops might be telling them? (Mention the Blog Post Above)

Topic 3 - What Big Data do you have in the background to drive faster incident closure?

Topic 4 - You integrate with ticketing systems like Service Now, Jira, BMC Remedy. What's a typical incident workflow when integrating with those tools?

Topic 5 - How do you keep the incident tagging consistent from all the different sources? How do you avoid conflicts as environments get larger, or the downstream services (generating events) change over time?

Topic 6 - Early use cases? Anything surprising emerging from the data?

The Cloudcast #162 - Building and Managing Scalable SaaS Services

• Loggly - http://www.loggly.com
• Six Critical SaaS Mistakes to Avoid - http://www.slideshare.net/loggly/loggly-6saa-sengineeringmistakesv2aa#2
• AWS Centralized Log Management - https://www.loggly.com/blog/aws-cloudwatch-log-management/

Topic 1 - Manoj, you and your team came highly recommended to us by the team at Evident.io (Tim Prendergast) and we learned about your service at AWS Summit in NYC. Tell us about your background and how it eventually led you to Loggly.

Topic 2 - You have an excellent talk/presentation on Critical SaaS Mistakes to Avoid. You mention that scalability needs to be priority #1. How much different is building applications/service in the cloud vs. building packaged software?

Topic 3 - We presume that Loggly was built from Day 1 was a web-scale SaaS application. Having built it, what might you do differently or major lessons learned? Realistically, is it possible for someone to SaaS-ify an existing application?

Topic 4 - Let’s talk about Loggly. Every company, every application has logs and they are a cluttered mess of potentially valuable information. People throw them at Loggly. What happens next?

Topic 5 - That has to be a really complex system on the backend to be able to ingest, parse, analyze, tag all the data - keep it isolated by customer - manage historical logs - then visualize it and give recommendations in real-times. Can you give us some sense of what goes on behind the scenes?

Topic 6 - Logging became somewhat more visible at AWS Summit when AWS announced centralized log management. How does your world change when AWS elevates a service that is in your domain?

Topic 7- What are the most common scenarios where companies decide they need help with log management?