Traces offer insight, but new methods fight data overload
Traces let you see exactly where a request fails as it moves through your software, but saving every trace can slow you down and eat up expensive storage. Instead of keeping everything, engineers are using smarter sampling—only saving the most useful pieces, or skipping traces that repeat. According to Sarah Hudspeth of Chronosphere, it keeps monitoring useful but manageable.
- Storing every trace can be expensive and slow systems
- Head, tail, and dynamic sampling cut storage needs
- Sampling focuses on useful, not repetitive, trace data
- Chronosphere’s approach aims to balance insight and efficiency
Sources covering this
More in Enterprise
Google Data Cloud adds new AI and analytics tools
Google just launched several new features for its Data Cloud. BigQuery now supports stateful processing in streaming queries, letting you do things like rolling averages in real time (currently in preview). There’s also a ready-to-use synthetic data generator for Managed Kafka, now generally available. And Lakehouse managed tables for Apache Iceberg are in preview, promising easier data management and cross-tool compatibility. Updates to Dataflow pipelines are also rolling out.
Salesforce launches new Agentforce bundles with built-in AI
Salesforce just unveiled three bundled versions—Core, Advanced, and Max—of its Agentforce tools for sales, service, and industry customers. These bundles now include built-in AI, Slack, upgraded analytics, enterprise-level security, and customer support, all for a single price. The Max edition, according to Salesforce, offers 60% more value than the previous Agentforce 1, with existing customers able to upgrade at no extra charge.
Salesforce details Engineering360 operational data platform
Salesforce has unveiled Engineering360, its new operational intelligence platform designed to integrate data from various sources within the company’s engineering operations. The system brings together records from code repositories, incident logs, and performance metrics, consolidating ninety billion records in real time. Salesforce says Engineering360 provides a unified, actionable view of enterprise data, seeking to enable faster decision-making for its engineering teams across its product portfolio.
Databricks Shares Guide for High-Quality Data Products
Databricks has published recommendations on building high-quality, trustworthy data products, emphasizing the importance of data quality and usability for organizations making data-driven decisions. The company encourages assigning dedicated data product owners and applying "product thinking" to manage and monitor data assets, whether or not enterprises use a data mesh structure. The advice is aimed at helping users deliver the right data in the right format, reliably.