Elasticsearch Incidents. Root Cause. Fast.
NeuBird reads Elasticsearch cluster health, query performance, and indexing metrics to diagnose search and log infrastructure incidents automatically.
In place
Data queried where it lives, never copied
Every agent
Inherits the connection once it is made
100%
Human-approved actions
Full
Audit trail on every action
Core Capabilities
From signals to solutions
Prevent
Catch Elasticsearch degradation before your cluster goes red
NeuBird reads Elasticsearch cluster metrics continuously, learning normal patterns for query latency, indexing throughput, JVM heap usage, and shard allocation. It surfaces GC pressure, shard imbalance, and disk watermark approach before they cause cluster instability.
- JVM heap usage and GC pause trend detection
- Shard allocation imbalance and unassigned shard monitoring
- Disk watermark approach detection before indexing is blocked
Resolve
Know immediately whether Elasticsearch is the incident root cause
When a search outage or application latency incident occurs, NeuBird reads Elasticsearch metrics, slow logs, and cluster health simultaneously. It traces causality from the application symptom to the Elasticsearch root cause, whether that's a slow query, a GC storm, or a node failure.
- Slow query and slow indexing log correlation with incident timeline
- Node failure and shard relocation impact analysis
- JVM GC storm-to-latency spike causality tracing
Operate
Improve search performance and reduce cluster costs
NeuBird analyzes Elasticsearch index patterns, query workloads, and cluster sizing to surface opportunities for shard optimization, ILM policy improvements, and node rightsizing, reducing both query latency and infrastructure cost.
- Oversized index and hot shard identification
- Over-provisioned node and data tier identification
- Query pattern analysis for missing field mapping optimizations
Better Together
Elasticsearch + NeuBird
| Capability | Elasticsearch | NeuBird |
|---|---|---|
| Cluster health and metrics | ✓ | ✓ |
| Application incident correlation | Manual: requires cross-tool investigation | Automatic: Elasticsearch signals linked to app incidents |
| Root cause analysis | Requires Elasticsearch expertise | Evidence-based RCA delivered automatically |
| Slow query correlation | Slow log requires manual review | Slow queries correlated with incident timeline |
| Cross-layer analysis | Elasticsearch-only visibility | Search + app + infra signals in one investigation |
| JVM GC impact analysis | Metrics visible, causality requires manual work | GC storms linked to latency spikes automatically |
Ecosystem
Works across your entire stack
Elasticsearch is one piece of the picture. NeuBird queries it in place and correlates it with every other connected tool, and every agent in the center inherits the connection.
Databases
- OpenSearch
- MongoDB Atlas
- Redis
- Snowflake
Observability
- Datadog
- Grafana
- PagerDuty
- Splunk
- Elastic APM
Cloud
- Amazon CloudWatch
- Google Cloud Platform
- IBM Cloud
DevOps
- GitHub
- Jenkins
- Terraform
- ArgoCD
FAQ
Common questions
How does NeuBird connect to Elasticsearch?
NeuBird connects to Elasticsearch via the Elasticsearch REST API using scoped, least-privilege credentials. It reads cluster health, node stats, index stats, and slow logs without requiring any configuration changes to your cluster.
Does NeuBird support Elastic Cloud and self-hosted Elasticsearch?
Yes. NeuBird supports both Elastic Cloud (Elasticsearch Service) and self-hosted Elasticsearch deployments, as long as the REST API is accessible.
Can NeuBird tell me if Elasticsearch is causing application latency?
Yes. NeuBird correlates Elasticsearch query latency, slow logs, and cluster health events with application incident timelines to determine causality.
What Elasticsearch metrics does NeuBird read?
NeuBird reads cluster health status, node CPU and JVM heap metrics, GC statistics, search and indexing latency, slow query logs, shard allocation status, and disk watermark levels.
Get Started
Connect Elasticsearch to the center.
Elasticsearch gives you the data. Connect it to NeuBird once, and every agent that touches production inherits it, including the ones you build yourself.