The Indian Premier League is a unique sporting event for a dozen reasons. But for engineers in India, it’s one of a kind. Very few companies can boast of managing 30+ million concurrent users. Every year, this number grows. Last year, we witnessed ~60 million concurrent users. And things get bigger and larger every year.

Predicting the future is hard, especially with metrics-based monitoring systems, because metrics cardinality can snowball. This is important because it affects query performance adversely. Having visibility into what’s happening now and workflows to manage cardinality is crucial. Because the answers depend on the quality of questions, a system allows you to ask. The questions one may have is —

We have Carson Anderson, Sr. DevOps Engineer at Weave HQ, talking about how they implemented SLOs using Prometheus, what went wrong, and how they fixed it. This talk was given at "Last9 of Reliability" Discord community on 13th December. Talk Description: First thing's first: Yes, it really did take us 5 tries to implement our SLOs with Prometheus. While that may seem embarrassing, we are very happy to be able to share our SLO journey so that we can hopefully help you avoid the same mistakes.

Aniket and Prathamesh team up to discuss how high cardinality is solved today, and Aniket shows the Streaming Aggregation pipeline of Levitate to manage High Cardinality.

Most of your outages are probably caused by a change, and having observability around that will make a lot of difference. Dive into this walkthrough, where we showcase tracking Canary deployments in Argo CD, correlating events and metrics seamlessly with Levitate. For Site Reliability Engineers, DevOps engineers, Software Engineers, and Product Managers seeking to elevate their observability and ensure smooth deployments every time.

The Reliability podcast aims to speak with engineers who have worked on large, complex systems and glean through their learnings. What best practices should one imbibe? What are non-negotiable learnings to become better at a craft? What’s ‘engineering’ going to be like with the advent of AI? We answer these and more tracing personal journeys of engineers who have built stellar careers around decoding the innumerable intricacies of software engineering.

The Reliability podcast aims to speak with engineers who have worked on large, complex systems and glean through their learnings. What best practices should one imbibe? What are non-negotiable learnings to become better at a craft? What’s ‘engineering’ going to be like with the advent of AI? We answer these and more tracing personal journeys of engineers who have built stellar careers around decoding the innumerable intricacies of software engineering.

The Reliability podcast aims to speak with engineers who have worked on large, complex systems and glean through their learnings. What best practices should one imbibe? What are non-negotiable learnings to become better at a craft? What’s ‘engineering’ going to be like with the advent of AI? We answer these and more tracing personal journeys of engineers who have built stellar careers around decoding the innumerable intricacies of software engineering.

The Reliability podcast aims to speak with engineers who have worked on large, complex systems and glean through their learnings. What best practices should one imbibe? What are non-negotiable learnings to become better at a craft? What’s ‘engineering’ going to be like with the advent of AI? We answer these and more tracing personal journeys of engineers who have built stellar careers around decoding the innumerable intricacies of software engineering.

The Reliability podcast aims to speak with engineers who have worked on large, complex systems and glean through their learnings. What best practices should one imbibe? What are non-negotiable learnings to become better at a craft? What’s ‘engineering’ going to be like with the advent of AI? We answer these and more tracing personal journeys of engineers who have built stellar careers around decoding the innumerable intricacies of software engineering.