With the increasing importance of observability in digital operations, businesses need to ensure the reliability and relevance of their telemetry data in order to maintain system and application performance, debug, troubleshoot, respond to incidents and keep their systems secure.
We spoke to Tucker Callaway, CEO of Mezmo, to discuss the strategic considerations and concerns enterprises face in managing and optimizing their telemetry data.
BN: Why has telemetry data become so important?
TC: In the last five years, we have seen an accelerated shift to digital business and operations, which has led to a surge in telemetry data generated from those operations. Telemetry data includes metrics, events, logs, and traces from various systems, applications, and services. This data stream offers insights into application performance, infrastructure reliability, user experience, service interactions, and potential security threats.
As businesses move to the cloud and scale their digital infrastructures, the volume and complexity of telemetry data increase disproportionately to the value enterprises get from it. This discrepancy poses a critical problem, particularly for observability. Telemetry data is dynamic, continuously growing, and constantly changing with sporadic spikes. Enterprises struggle to confidently deliver the right data to the right systems for the right user, uncertain about data content, value, completeness, and ensuring that sensitive Personally Identifiable Information (PII) is handled properly, putting them at risk. These factors reduce trust in collected and distributed data. The organizations must change how they manage and extract value from telemetry data. Telemetry pipelines, systems designed to collect, process, and transmit telemetry data, can manage this dynamic and expansive data stream
