Startseite
Podcasts
Software Engineering Radio - The Podcast for Professional Software Developers Podcast
SE Radio 717: Eric Tschetter on Decoupling Observability

SE Radio 717: Eric Tschetter on Decoupling Observability

Software Engineering Radio - The Podcast for Professional Software Developers vor 4 Monaten

0:00

1:00:13

In this episode, host Amey Ambade sits with Eric
Tschetter, co-founder of Apache Druid and Chief
Architect at Imply, to dissect the critical move toward
Decoupling Observability. To begin, they define
three pillars—logs, metrics, and traces—and consider why the rise
of microservices has made traditional, tightly coupled stacks a
major source of pain. Such coupled systems can lead to issues
such as vendor lock-in, prohibitive scaling costs, and
operational complexity.

Drawing parallels to the Business Intelligence world's
separation, Tschetter presents an architectural solution with
four distinct layers: Ingest/Route, Data Storage, Query/Compute,
and Visualization. This framework aims to provide flexibility to
combat the limitations of monolithic observability tools. The
conversation moves into the practical challenges and significant
benefits of this decoupled model, focusing heavily on
data portability and the role of technologies
such as OpenTelemetry in standardizing schemas so that data can
flow freely between multiple back-ends. A significant portion of
the discussion is dedicated to the Query/Compute
layer, specifically how Apache Druid addresses the
unique demands of real-time analytics on observability data,
including indexing strategies and unifying results across hot and
cold storage. They also delve into operational survival, covering
critical topics like smart sampling to preserve
high-value signals, best practices for buffering and
backpressure, and the governance models required for
multiple teams to safely access the same data lake.

The episode concludes with an honest look at the complexity
trade-offs and a roadmap for organizations considering a
migration from a coupled vendor stack.