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Weaviate Monitoring


Weaviate is an open-source vector database that stores and searches vector embeddings. Applications Manager monitors Weaviate through Prometheus integration and provides visibility into instance health, query performance, memory usage, indexing activity, and class-level metrics.

Overview

Weaviate is supported only through Prometheus integration. You cannot add Weaviate through the standard Add Monitor workflow or the AddMonitor API. Configure the Prometheus integration before discovering Weaviate. For general setup steps, see Prometheus Integration.

Adding a Weaviate monitor

  1. Configure Prometheus to scrape metrics from the Weaviate instance and make the Prometheus server accessible to Applications Manager.
  2. Open the Prometheus integration configuration and select Weaviate as the monitor type.
  3. During discovery, Applications Manager uses the object_count metric to identify Weaviate scrape targets.
  4. Test the credentials. Applications Manager checks the go_memstats_sys_bytes metric to verify connectivity and authentication.

Note: Weaviate must expose the required Prometheus metrics. Metrics in the Async Indexing section are available only when ASYNC_INDEXING=true is enabled in Weaviate.

Monitored Parameters

Applications Manager monitors Weaviate based on the performance attributes listed below. These metrics provide visibility into the health and operational status of your vector database. You can also configure thresholds for these attributes to receive alerts when performance limits are exceeded.

The following is a list of tabs that are shown in the Weaviate monitor:

Overview

The Overview tab summarizes the instance uptime, schema size, shard count, and object count. Object counts are deduplicated across replicas.

MetricDescription
SERVER SUMMARY
UptimeDuration for which the Weaviate process has been running since its last restart.
Class CountNumber of collections (classes) in the Weaviate schema.
Shard CountTotal number of shards across all collections. In multi-tenant setups, each tenant is a separate shard.
RESPONSE TIME
Response TimeTime taken to collect metrics from the Prometheus server (in milliseconds).
OBJECTS
Object CountTotal number of data objects stored in the instance, deduplicated across replicas.

Memory & GC

The Memory and GC tab shows heap utilization and runtime memory statistics. Sustained high heap use can indicate memory pressure, while a continuously growing goroutine count may indicate a goroutine leak.

MetricDescription
Heap UtilizationPercentage of reserved heap memory currently in use, calculated as Heap In Use / Heap Reserved x 100 (in %).
HEAP DETAILS
Total MemoryTotal virtual memory reserved from the operating system by the Weaviate Go runtime (in MB).
Heap ReservedHeap memory reserved from the operating system (in MB).
Heap AllocatedHeap memory occupied by allocated objects (in MB).
Heap In UseHeap memory actively in use (in MB).
Heap IdleHeap memory reserved but currently unused and available to be returned to the operating system (in MB).
Heap ReleasedHeap memory already returned to the operating system (in MB).
Stack In UseMemory used by goroutine stacks (in MB).
Next GC TargetHeap size at which the next garbage collection cycle is triggered (in MB).
ALLOCATION DETAILS
Allocation RateRate at which heap memory is allocated (in KB/s).
Object Allocation RateNumber of heap objects allocated per second.
GOROUTINE DETAILS
GoroutinesNumber of live goroutines in the Weaviate process.
GC PAUSE DETAILS
GC Pause (Max)Maximum garbage collection pause duration observed (in milliseconds).
GC Pause (Median)Median garbage collection pause duration observed (in milliseconds).

Queries

The Queries tab tracks query throughput, latency, and concurrent requests.

MetricDescription
QUERY RATE
Query RateNumber of queries executed per second.
QUERY LATENCY
Average Query LatencyAverage time taken to execute queries (in milliseconds).
Query Latency (P90)90th percentile query latency estimated from histogram buckets (in milliseconds).
Query Latency (P95)95th percentile query latency estimated from histogram buckets (in milliseconds).
CONCURRENT REQUESTS
Concurrent Read RequestsNumber of read requests, including GraphQL Get, Aggregate, and object reads, currently in progress.
Concurrent Write RequestsNumber of write requests, including add, update, batch, and delete operations, currently in progress.
QUERY TYPE DETAILS
Query TypeType of operation.
Query RateQueries of this type executed per second.
Average Query LatencyAverage latency for this query type (in milliseconds).
Query Latency (P95)95th percentile latency for this query type (in milliseconds).
Concurrent RequestsRequests of this type currently in progress.

Object Operations

The Object Operations tab shows latencies across the write path and helps identify slow write stages.

MetricDescription
OBJECT OPERATION LATENCY
Average PUT Object LatencyAverage time taken for single-object PUT (create or replace) operations (in milliseconds).
Average Batch PUT LatencyAverage time taken for batch object import operations (in milliseconds).
Average Batch Delete LatencyAverage time taken for batch delete operations (in milliseconds).
WRITE PIPELINE STAGES
Average Object Store Upsert LatencyTime spent in the object-store upsert stage of the write pipeline (in milliseconds).
Average Inverted Index LatencyTime spent updating the inverted index during writes (in milliseconds).

Vector Index

The Vector Index tab reports HNSW vector index activity and cleanup state. Vector Index Size can exceed object count when deleted vectors are waiting for background cleanup.

MetricDescription
VECTOR INDEX SUMMARY
Vector Insert OperationsCumulative number of vectors added to the HNSW index since the process started.
Vector Delete OperationsCumulative number of vectors removed from the HNSW index since the process started.
Net VectorsDifference between vector insert and delete operations.
VECTOR INDEX DETAILS
Vector Index SizeNumber of vectors currently held in the HNSW index. This can exceed object count when deleted vectors are pending cleanup.
Active TombstonesNumber of deleted vectors marked for removal but not yet cleaned up. A continuously rising value indicates a delete-heavy workload and can slow vector searches.

Async Indexing

The Async Indexing tab displays vector-indexing queue metrics when asynchronous indexing is enabled in Weaviate.

MetricDescription
QUEUE SUMMARY
Queue CountNumber of asynchronous vector-indexing queues.
Queues PausedNumber of indexing queues currently paused.
QUEUE DETAILS
Queue SizeNumber of vectors waiting to be indexed across all queues. A continuously growing value indicates indexing is falling behind ingestion.
Queue Disk UsageDisk space consumed by on-disk indexing queues (in MB).
Average Partition Processing TimeAverage time a worker takes to process one queue partition (in milliseconds).
VECTOR INDEX QUEUE OPERATIONS
Vector Queue Insert RateNumber of vectors entering the indexing queues per second.
Vector Queue Delete RateNumber of vectors removed from the indexing queues per second.

Classes

The Classes tab lists details for up to 50 collections, ordered by object count. Class Details and Query Type Details rows are secondary monitor objects with their own availability and health. When a class or query type disappears, its row is retained and marked unavailable.

MetricDescription
CLASS DETAILS
Class NameName of the collection (class).
Object CountNumber of objects stored in this collection.
Shard CountNumber of shards (tenants in multi-tenant setups) in this collection.
Vector Index SizeNumber of vectors in this collection's HNSW index.
Active TombstonesDeleted vectors pending cleanup in this collection's index.
Query RateQueries per second served by this collection.
Average Query LatencyAverage query latency for this collection (in milliseconds).

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