Open Issues Need Help
View All on GitHubA horizontally scalable, highly available, multi-tenant, long term Prometheus.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.
AI Summary: Implement support for Prometheus type and unit labels within the Cortex OTLP receiver. This involves adapting the receiver to handle these labels from incoming OTLP data, ensuring compatibility with the Prometheus proposal (linked in the issue description), and writing thorough tests to validate the implementation. The upstream Prometheus PR (also linked) provides a reference implementation.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.
AI Summary: The task involves enhancing the Cortex project's query functionality by integrating Parquet file support into the store gateway. This requires migrating the existing stateless Parquet query implementation to a stateful service within the gateway, improving cache utilization and enabling more efficient data access. Alternatives, such as using sticky sessions for queriers, are also considered but deemed less scalable.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.
AI Summary: The task involves integrating the existing Cortex User Scanner module into the alertmanager and rule bucket stores to improve performance and reduce load on the object storage's LIST API. This will prevent potential outages by caching user scan results, mirroring the successful implementation in the metric data bucket store. Alternatives, such as introducing separate caching buckets, are considered but the preferred solution leverages the existing User Scanner.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.
AI Summary: Implement experimental support for ingesting OpenTelemetry (OTEL) delta metrics in Cortex, initially as a tenant-configurable feature. This involves leveraging recent Prometheus advancements and potentially adapting the existing ingestion pipeline to handle OTEL delta values.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.
AI Summary: Create an integration test for the Cortex project to verify that query response compression is functioning correctly. This test should prevent regressions like the one introduced in PR #6763 and subsequently fixed in PR #6844.
A horizontally scalable, highly available, multi-tenant, long term Prometheus.