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Performing chaos in a serverless world  Gunnar Grosch  Failover Conf 2020

Chaos engineering is the practice of hypothesis testing through planned experiments to gain a better understanding of a system’s behavior. The principles of chaos engineering have been around for years, and we have now reached the point where chaos engineering has gone from just being a buzzword and practice used by a few large organizations in very specific fields, to it being put in to use by companies of all sizes and industries.

Swim Don't Sink: Why Training Matters to a Site Reliability Engineering Practice  Jennifer Petoff

Do you offer training to the engineers in your organization or do you throw them off the deep end to “sink or swim”? Providing training and education is universally important to set team members up for success in your organization and is critical for establishing a thriving Site Reliability Engineering (SRE) or DevOps practice and culture in the first place.

Fight, Flight, or Freeze - Releasing Organizational Trauma Matt Stratton Failover Conf 2020

When humans are faced with a traumatic experience, our brains kick in with survival mechanisms. These mechanisms are the familiar fight or flight response, but can also include the freeze response - which occurs when we are terrified or feel that there is no chance of escape.

Y2K and Other Disappointing Disasters: Risk Reduction and Harm Mitigation  Heidi Waterhouse

Every disaster is a concatenation of smaller failures. How can we design software and processes to accept that we live in an imperfect world? Explore the concepts of resiliency, harm reduction, over-engineering, and planning for failure with real examples.

How to fail with Serverless  Jeremy Daly Failover Conf 2020

Everything fails all the time. Knowing how to deal with these failures in serverless applications becomes essential to building resilient, highly-available systems. In traditional monolithic applications, catching errors and handling retries is relatively straightforward. But as our systems become more distributed, we now have multiple (often asynchronous) components processing events from several sources, all with vastly different retry behaviors and failure mechanisms. Utilizing old patterns can cause errors to get swallowed, creating brittle, unreliable systems that are difficult to debug and hard to maintain.