“When things broke,” Molly explained, “you’re mad scrambling—jumping from website to website to website, trying to put the pieces together.” Molly was able to use Honeycomb to fix things up: “It makes my job easier as an SRE.” Getting started with Honeycomb doesn’t require a lot of work: at dev.to, they used the Ruby Beeline to get it going: “I didn’t do that much,” she said.
This is a guest post by Ryan Ordway, DevOps Engineer at Oregon State University. At Oregon State University Libraries & Press (OSULP) we have been using Honeycomb for about 18 months. We were in the beginnings of automating our infrastructure and needed an APM solution that we could scale with. New Relic was becoming too expensive, and we couldn’t afford to monitor our whole infrastructure and trace all of our applications anymore. Thus began our Observability journey.
A few months ago, Honeycomb released our SLO — Service Level Objective — feature to the world. We’ve written before about how to use it and some of the use scenarios. Today, I’d like to say a little more about how the feature has evolved, and what we did in the process of creating it. (Some of these notes are based on my talk, “Pitfalls in Measuring SLOs;” you can find the slides to that talk here, or view the video on our Honeycomb Talks page).
We’re really big fans of OpenTelemetry at Honeycomb. As we’ve blogged about before, OpenTelemetry is the next phase of the OpenTracing and OpenCensus projects. Instead of working on separate but similar efforts, those two projects have merged to create OpenTelemetry. This is wonderful for the larger community as it gives people a clear way to instrument their code for metrics and traces that isn’t specific to any tool or vendor. OpenTelemetry is a CNCF sandbox project.
At re:Invent in December, Amazon announced the AWS Graviton2 processor and its forthcoming availability powering Amazon EC2 M6g instances. While the first-generation Graviton processor that powered A1 instances was better suited to less compute-intensive workloads, this processor is intended to offer AWS customers a compelling alternative to conventional x86-powered instances on both performance and cost.
“Sociotechnical” — I learned this word from Liz Fong-Jones recently, and it immediately entered my daily lexicon. You know exactly what it means as soon as you hear it, and then you wonder how you ever lived without it. Our systems are sociotechnical systems. This is why technical problems are never just technical problems, and why social problems are never just social problems. I work on a company, Honeycomb, which develops next-gen observability tooling.
To have Observability is to have the ability to understand your system’s internal state based on signals and externally-visible output. Honeycomb’s approach to Observability is to strive toward this: every feature of the product attempts to move closer to a unified vision of figuring out what your system did, and how it got there.
Have you ever experienced a time when someone on your team takes off to recharge or takes unplanned downtime away from work? It may feel a bit scary as workloads shift, priorities change and the team has to pick up some slack. We all need to recharge and in some org’s, it’s imperative. The covering for each other builds trust among the team which is invaluable when you’re in the trenches daily, working hard.
What do a test engineer and a DevOps or SRE team member have in common? The reality is that different teams need to proactively understand what is happening in production at critical milestones along the software engineering delivery cycle. In the words of Abby Bangser, senior test engineer at Moo, “Testing has so much in common with Ops and SRE teams. We need to ask interesting questions of production. We need no more debates whether a bug gets fixed.
New eGuide takes a closer look at Prometheus, ELK and Jaeger:
