Formed in 2009, the Archive Team (not to be confused with the archive.org Archive-It Team) is a rogue archivist collective dedicated to saving copies of rapidly dying or deleted websites for the sake of history and digital heritage. The group is 100% composed of volunteers and interested parties, and has expanded into a large amount of related projects for saving online and digital history.
Cribl today announced general availability of a search capability that makes it simpler to query observability data where it resides without having to first collect and centrally store it.
Nick Heudecker, senior director for market strategy for Cribl, said Cribl Search makes it possible to analyze telemetry data at its point of origin or when it is stored in a low-cost object storage platform to minimize costs.
As the volume of telemetry data being collected continues to grow, DevOps teams are struggling with ingesting it all. Cribl takes advantage of a platform it created to stream and normalize the collection of telemetry data. Cribl Search adds the ability to also query that data at the endpoint where it resides, said Heudecker.
While observability has always been a core tenet of DevOps, achieving it has been a major challenge. In addition to deploying and managing agent software to instrument IT environments, there’s a significant amount of time and effort required to set up the pipelines necessary to transfer data to a platform for storage and analysis. The more data is collected, the greater storage costs become. Cribl is making a case for automating those tasks using a tier of software that abstracts data into a format that can be more easily collected and analyzed.
In general, observability is emerging as the next logical evolution of continuous monitoring. Existing monitoring tools enable DevOps teams to track specific pre-defined metrics. Observability platforms are intended to make it easier to query telemetry data to discover the root cause of an issue that is not being tracked by a set of pre-defined metrics.
It’s not clear yet whether IT organizations perceive observability to be an evolution of monitoring or a distinctly separate but complementary capability, but it’s apparent IT teams need a lot more context than they have historically been able to attain using legacy monitoring tools. Each platform used within an enterprise typically comes with its own monitoring tools that are used by the IT teams tasked with managing it. Whenever there is an issue, it’s not uncommon for DevOps teams to spend hours correlating data from multiple tools to ascertain the root cause of a problem. Observability platforms promise to reduce that time and effort by applying analytics to data collected from multiple platforms. The challenge is finding a way to efficiently collect all that data, which in the past has often required a data engineer to build a pipeline spanning multiple sources of telemetry data.
One way or another, observability platforms should make it easier for DevOps teams to manage IT issues more proactively. The goal, as always, is to identify issues before they cause a major disruption. In that sense, it may be difficult to prove the ROI of deploying an observability platform. However, the best IT incident is always going to be the one that never happened or, at the very least, never escalated to a level of noticeable disruption.
