Sqlcommenter now extending the vision of OpenTelemetry to databasesSqlcommenter now extending the vision of OpenTelemetry to databasesProduct Manager

Application developers can use observability information from Sqlcommenter to analyze slow query logs; or that observability information can be integrated into other products such as Cloud SQL Insights or APM tools from Datadog, Dynatrace, and Splunk to provide application-centric monitoring.

Extending the vision of OpenTelemetry to Databases

OpenTelemetry, which is now the second most active Cloud Native Computing Foundation (CNCF)  open-source project behind Kubernetes, makes it easy to create and collect telemetry data from your services and software, then forward that data to a variety of Application Performance Monitoring tools. But before today, OpenTelemetry lacked a common standard by which application tags and traces can be sent to databases and correlated with an application stack. To extend the vision of OpenTelemetry to databases, we merged Sqlcommenter with OpenTelemetry to unlock a rich choice of tools for database observability for developers. Bogdan Drutu, Co-founder of OpenCensus & OpenTelemetry and Senior Principal Software Engineer, Splunk, offered his perspective;

“With Google Cloud’s Sqlcommenter contribution to OpenTelemetry, a vendor-neutral open standard and library will enable a rich ecosystem of Application Performance Monitoring tools to easily integrate with databases, unlocking a rich choice of tools for database observability for the developers.”

OpenTelemetry, Google Cloud and our partners

We believe that a healthy observability ecosystem is necessary for end-to-end application stack visibility and this is reflected in our continued commitment to open-source initiatives. This belief is shared by other key contributors to the ecosystem including Datadog, Dynatrace and Splunk:

“Visibility into database performance and its impact on applications is critical to engineering.  A poorly performing query can impact every other layer of the stack making troubleshooting difficult.   Sqlcommenter bridges the gap between application requests and database queries, allowing APM users to troubleshoot requests in their entirety at all levels, from frontend to data tiers. As early contributors to OpenTelemetry, we are extremely pleased to see this contribution from Google Cloud as it brings us closer to the vision of open standards based observability.” – Ilan Rabinovitch, SVP Product, Datadog

“Observing datasets across thousands of companies, we’ve identified database access patterns and performance as among the top reasons for poor performing applications. Dynatrace, a core contributor to OpenTelemetry, natively supports telemetry data generated by Sqlcommenter in problem analysis, change detection, and real-time optimization analytics. We see the combination of Sqlcommenter and OpenTelemetry helping developers understand the impact of their database queries and make it easier to collaborate to optimize application performance.”—Alois Reitbauer, VP, Chief Technology Strategist, Dynatrace

“Splunk and Google have been behind OpenTelemetry since day one, and the merging of Sqlcommenter to OpenTelemetry means Splunk Observability Cloud customers can further empower developers with application centric database monitoring, accelerating their DevOps journeys for databases.”—Morgan McLean, Co-founder of OpenCensus & OpenTelemetry and Director of Product Management, Splunk

An example of how Cloud SQL Insights uses Sqlcommenter to simplify observability for developers

Troubleshooting databases is hard in modern application architectures
Today’s microservice-based architectures redefine an application as an interconnected mesh of services as seen in the picture below, many of which are third-party and/or open-source. This can make it challenging to understand the source of system performance issues. When a database is involved, it becomes even harder to correlate application code with database performance. Cloud SQL Insights leverages Sqlcommenter to simplify database troubleshooting in distributed architectures.

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