Chronosphere recently partnered with analyst firm ESG to commission a study on observability in cloud-native environments. ESG surveyed 357 IT, DevOps, and application development professionals at organizations in North America responsible for evaluating, purchasing, managing, and building application infrastructure. Everyone who took the survey either employs today, or plans to employ, an observability practice.
Observability data growth is out of control
The first key finding from this study is that nearly two thirds (71%) of organizations are concerned with observability data (metrics, logs, traces, etc.) growth. This is a trend we’ve seen emerge over the past several years as more and more organizations adopt cloud-native architectures. Why is this? It’s a law of numbers: virtual machines and containers both emit about the same volumes of observability data. But if you previously had 100 VMs and now you have 500 containers, your volume of data increases by 5x. The same goes for the shift to microservices. On top of this, with the move to open source standards for collecting data, developers are responsible for instrumenting their own applications and infrastructure for emitting observability data, which also contributes to this explosion in observability data.
Signal to noise ratios a top observability burden, especially for the tech industry
With so much data, it’s not surprising that organizations are struggling to separate out the signal from the noise. According to the study, nearly a quarter (22%) of organizations said it was extremely burdensome to sift through all the alerts/logs/traces to identify the valuable information. This challenge was consistently ranked as one of the biggest burdens when respondents were asked to rate the level of burden/complexity when maintaining and troubleshooting applications. Interestingly, this is most pronounced for organizations in the tech industry: 44% of respondents from tech companies said it is extremely burdensome to sift through the increasing volumes of metrics, logs, and traces.
Reliability and scalability top challenge for observability solutions
Increasing volumes of data not only puts a strain on the individual engineers trying to sort out the signal from the noise, it also puts a significant strain on observability systems. When asked what are their organization’s biggest challenges or concerns when it comes to deploying observability technology solutions, the most popular response was scalability and reliability of solutions at more than a quarter (27%) of respondents.
According to Rob Strechay, Senior Analyst, Observability, Cloud, & IT/DevOps at ESG, “One of the attributes of modern application development is to build and run anywhere at scale, especially in a containerized, microservices-based architecture. But scalability and reliability are hard to automate effectively, and organizations are struggling to instrument the applications. Operating at scale is always a tough achievement for even the most sophisticated organizations. This is the case not only for the applications themselves, but also during initial deployments and ongoing support of observability solutions.”
These three trends around observability in cloud-native environments are from the first in a series of surveys conducted by ESG in partnership with Chronosphere, and just scratch the surface of fascinating data that was uncovered. There’s more to come, so stay tuned for the next survey in the Distributed Cloud Series on Cloud-native Applications.
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