Issue #028

Hey folks, welcome to another installment of Monitoring Weekly! Did you write something about monitoring recently? Maybe got an idea rolling around in your head? Send it on over and let the community learn from you. 😀

Monitoring News, Articles, and Blog posts
CNCF Hosts Jaeger

Uber’s OpenZipkin-inspired distributed tracing framework was accepted into the Cloud Native Computing Foundation this past week, making it project #12. I imagine we’ll be seeing increased development activity for the Jaeger project coming soon. I do like that the CNCF is increasingly putting their weight behind the OpenTracing standard with their hosting of both Jaeger and OpenTracing.

Time Series Database Lectures – Karthik Ramasamy (Streamlio)

Do you like real-time stream processing? How about Heron? The former Program Manager for Heron at Twitter is the second installment in CMU’s Time Series Database lecture. This video is a fantastic dive into Heron and how it works.

An Often Overlooked Tool In Workplace Safety Prevention: The Near-Miss Investigation

Pulling lessons from other fields, this article points out the value in having incident investigations not only for actual incidents but for incidents that almost happened. I’m still pondering all the ways this applies to our world. What if we could catch outages that almost happened, but didn’t? What would we learn from investigating why the event didn’t turn into an outage?

Forge by Sentry: Connect, Learn, Eat, Drink

Sentry.io, a previous sponsor of this newsletter, is putting on their first-ever conference in Napa, California. The speaker lineup looks incredible! I’ll be there covering the event with my ‘Editor of Monitoring Weekly’ hat, so look out for me if you come. In fact, Sentry is offering 20% off to Monitoring Weekly readers! Note that the price of the ticket also includes a night at the super sweet Maritage Resort in Napa Valley. Use this promo code at checkout: MLXForge17

Predicting Resource Exhaustion with Double Exponential Smoothing

Ignoring the SignalFx-specific examples, this article is one of the simplest explanations I’ve seen yet for predictive statistical functions. The author goes over linear projection and double exponential smoothing, which are two of the most effective predictive functions for our sort of date. Chances are high that whatever you’re using for metrics also support these functions.

See you next week!

— Mike (@mike_julian) Monitoring Weekly editor