Episode #13 - Running MELT through analytics at the edge
from Ink8r (in·cu·ba·tor) Podcast Hosted by ink8r
There is always tremendous value in decreasing latency in any decision-making process, particularly when we are dealing with stream processing in support of system and application observability. By running Metrics, Events, Logs, and Trace (MELT) data through an analytics algorithm at time of creation, on the very devices emitting the signals, organizations can set parameters on what information is worth sending to an observability platform, and what information is not. In this episode, we speak with Zachary Quiring, Director of Product at Edge Delta regarding how they view observability and how distributed queries are the most economical approach to scale and efficiency for modern architectures. This is truly a novel approach and as Edge Delta puts it, the only way to achieve "observability without compromise".
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There is always tremendous value in decreasing latency in any decision-making process, particularly when we are dealing with stream processing in support of system and application observability. By running Metrics, Events, Logs, and Trace (MELT) data through an analytics algorithm at time of creation, on the very devices emitting the signals, organizations can set parameters on what information is worth sending to an observability platform, and what information is not. In this episode, ...
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