Operations | Monitoring | ITSM | DevOps | Cloud

Digital-first businesses are striving for service assurance, which has become the lifeblood for their businesses processes. But they are increasingly getting complex across legacy and cloud-native applications, multi-cloud distributed services, with the rise of edge and when leveraged with Kubernetes and microservices architectures. Service assurance needs full-stack observability; however, customers need an approach to tame the data deluge while enabling actionable insights.

When I speak at conferences, I often fall back to the fact that just a couple of decades ago we’d observe production by kicking the server. This is obviously no longer practical. We can’t see our production. It’s an amorphous cloud that we can’t touch or feel. A power that we read about but don’t fully grasp. In this case, we have physical evidence that the cloud is there. A part of this major shift in our industry is a change to our fundamental roles as engineers.

Sometimes the simplest questions prompt the most spirited discussion. Questions like: What is the airspeed velocity of an unladen swallow? What should we have for dinner tonight? Or, as we find out in this episode of “Grafana’s Big Tent" what even is observability?

Monitoring is often not the first thing on the mind of the modern developer. Yet, it’s necessary at many points of the software development lifecycle, including: before deprecating an API, before launching a new feature, after launching the feature, and more. In fact, monitoring needs can vary much more than the classic Ops monitoring.

Are you overspending on monitoring and APM tools? Forrester’s Total Economic Impact analysis of Honeycomb identified significant ROI in customers using us to reduce spend on less efficient APM workflows. But this isn’t about budget reallocation to a newly branded set of similar but shinier tools.

Remember the old days where if you had an uptime of 99.9 you could be fairly confident everyone was having a good experience with your application? That’s not really how it works anymore. Modern, distributed systems are so complex they typically fail unpredictably, making it much harder to diagnose issues. Traditional monitoring grew out of those early days, allowing you to check the health of simpler systems.

Honeycomb uses AWS Lambda as a core part of our query execution architecture; Lambda’s ability to quickly allocate lots of resources and charge us only for use is invaluable to keeping Honeycomb fast and affordable. Our total Lambda bill is easily accessible in the AWS Console, but how do we know which customers or application areas dominate this bill? How do we judge the cost of changes we make to our own software?

Note 8.3.0 has an issue that could cause creating and accessing snapshots against Azure snapshot repositories to fail authenticating when using SAS tokens. This impacts self-managed customers who have deployed 8.3.0. Elastic Cloud Azure deployments are not currently being upgraded to 8.3.0 and are not impacted as a result. Visibility is crucial for ensuring application performance but it can be difficult to efficiently scale monitoring across all your critical infrastructures, platforms, and services.

I recently attended Sapphire Ventures' Hypergrowth Engineering Summit (thank you David Carter and Sapphire for the invitation! I wrote a separate blog post on the whole thing), and one of the sessions was a panel discussion with Rob Zuber, CTO at CircleCI and Jonathan Nolen, SVP of Engineering and Product at LaunchDarkly. The session was illuminating: they talked about how in this world of everyone shifting left, teams should actually consider shifting right.