450+ Integrations.
Your Entire Stack.

Ingest CloudWatch metrics and alarms directly into TigerOps for unified cloud visibility.

Monitor EC2 instances with auto-discovered host metrics, CPU, memory, and network telemetry.

Track container health, task counts, and service metrics across your ECS clusters.

Full Kubernetes observability for EKS clusters with node, pod, and control plane metrics.

Observe serverless function invocations, durations, cold starts, and errors in real time.

Monitor relational database performance, query latency, and connection pool utilization.

Track Aurora cluster metrics, replica lag, failover events, and query performance.

Track bucket request metrics, error rates, data transfer, and access patterns.

Monitor load balancer health, target response times, and HTTP error rates.

Track message publish rates, delivery failures, and subscription health across topics.

Queue depth, message age, DLQ monitoring, and processing rate visibility.

Read/write capacity, throttling events, and item-level latency for DynamoDB tables.

Redis and Memcached node metrics, eviction rates, and replication health.

Serverless container monitoring with CPU, memory, and network metrics per task.

Workflow execution metrics, state transition latency, and failure tracking.

Request count, latency, 4xx/5xx error rates, and integration latency by stage.

Shard-level metrics, iterator age, throughput, and consumer lag monitoring.

CDN cache hit ratio, origin latency, error rates, and bandwidth metrics by distribution.

DNS query metrics, health check status, and latency-based routing monitoring.

Full Kubernetes visibility for GKE clusters including node, pod, and workload metrics.

Monitor serverless container deployments with request metrics and instance scaling data.

Track query performance, slot utilization, and cost metrics for your data warehouse.

Serverless function execution metrics, cold starts, and error tracking on GCP.

Managed database metrics for PostgreSQL, MySQL, and SQL Server on GCP.

Topic throughput, subscription backlog, and acknowledgment latency monitoring.

Bucket operation metrics, data transfer rates, and access pattern analysis.

Backend latency, request distribution, and health check status monitoring.

Monitor Azure Kubernetes Service clusters with full node, workload, and network telemetry.

Observe serverless function executions, bindings, and cold start metrics on Azure.

Track request units, latency percentiles, and partition health for Cosmos DB.

Web app performance metrics, deployment slots, and auto-scale monitoring.

DTU usage, query performance insights, and geo-replication lag tracking.

Queue and topic metrics, dead-letter monitoring, and message throughput.

Storage account metrics, transaction rates, and availability monitoring.

Partition throughput, consumer offset lag, and capture metrics.

Query performance, WLM queue metrics, cluster storage, and COPY/UNLOAD throughput.

Training job metrics, endpoint invocation latency, and model accuracy tracking.

Managed Kafka broker metrics, partition health, and consumer lag monitoring.

Cluster health, index metrics, and search latency for managed OpenSearch.

Web ACL request metrics, rule match counts, and blocked request analytics.

Security finding ingestion, threat severity distribution, and detection trends.

Service request metrics, auto-scaling events, and deployment status tracking.

Job queue depth, compute environment utilization, and job duration metrics.

ETL job run metrics, DPU utilization, and crawler execution monitoring.

Cluster step metrics, HDFS utilization, and Spark/MapReduce job performance.

MongoDB-compatible cluster metrics, query performance, and replica lag.

Graph query performance, Gremlin/SPARQL latency, and storage utilization.

Write and query metrics, storage utilization, and magnetic store transitions.

File system throughput, burst credits, and client connection monitoring.

Pipeline execution status, stage duration, and deployment frequency metrics.

Event bus metrics, rule invocation counts, and dead-letter queue monitoring.

Transaction latency, read/write throughput, and node CPU utilization.

Pipeline throughput, worker utilization, and watermark lag monitoring.

Redis and Memcached instance metrics on GCP with auto-failover monitoring.

Document read/write rates, index utilization, and real-time listener counts.

Security policy metrics, rule match rates, and adaptive protection events.

Multi-cluster management metrics, policy enforcement, and service mesh health.

Cache hit ratios, memory usage, and connection count for Azure Cache for Redis.

Container group metrics, restart counts, and resource utilization.

Workflow run metrics, action success rates, and trigger execution counts.

Cluster metrics, job run performance, and notebook execution monitoring.

Global routing metrics, WAF events, and origin health monitoring.

Pipeline run metrics, activity duration, and integration runtime health.

SQL pool metrics, Spark pool utilization, and pipeline execution stats.

Droplet CPU/memory, managed database metrics, and Kubernetes cluster health.

Dyno metrics, router latency, and add-on performance through log drains.

Machine metrics, volume health, and global edge deployment monitoring.

End-to-end Kubernetes observability: nodes, pods, namespaces, deployments, and HPA metrics.

Container-level CPU, memory, network, and I/O metrics with automatic service discovery.

Track Helm release lifecycle events and correlate deployments with metric changes.

Service mesh telemetry including request rates, error ratios, and P99 latency per service.

Ingest Linkerd golden signals and trace inter-service traffic with zero instrumentation.

HashiCorp Nomad job allocation metrics, task health, and resource utilization.

Service mesh health checks, catalog metrics, and KV store monitoring.

Proxy-level metrics including upstream/downstream latency, retries, and circuit breaker stats.

Seal status, token metrics, audit log events, and secret engine health.

Track infrastructure changes and correlate Terraform applies with operational anomalies.

Monitor CI pipeline duration, failure rates, and correlate deploys with error spikes.

Ingest pipeline events and deployment markers directly into your TigerOps timeline.

Forward Jenkins build events and annotate your dashboards with deployment context.

Track GitOps sync events and application health state changes from ArgoCD.

Pipeline run metrics, job durations, and deployment event ingestion.

Auto-instrumented APM for Node.js: event loop lag, memory, async traces, and more.

Instrument Django, FastAPI, Flask, and bare Python apps with a single SDK install.

JVM metrics, Spring Boot traces, and heap analysis with the TigerOps Java agent.

Low-overhead Go instrumentation with goroutine metrics, GC stats, and trace propagation.

Rails and Rack middleware tracing with database query capture and background job visibility.

Auto-instrument .NET Core and ASP.NET apps with full CLR runtime and trace support.

PHP-FPM monitoring, Laravel and Symfony tracing, and slow query detection.

Lightweight Rust SDK for async instrumentation and propagating OpenTelemetry context.

BEAM VM metrics, Phoenix request tracing, and GenServer process monitoring.

Full-stack observability for Next.js apps: SSR traces, Core Web Vitals, and API routes.

Django middleware integration for request tracing, ORM queries, and Celery tasks.

Spring Boot auto-configuration for metrics, traces, and actuator endpoint monitoring.

ASGI middleware integration for FastAPI with async trace propagation and pydantic insights.

ActiveRecord, ActionController, and Sidekiq tracing with N+1 query detection built in.

Middleware-based Express.js instrumentation with automatic route and handler tracing.

Decorator-based tracing for NestJS with automatic module and guard instrumentation.

Full Laravel tracing: Eloquent queries, queue jobs, scheduled tasks, and Blade rendering.

Client-side performance, HTTP interceptor tracing, and Core Web Vitals.

Component render performance, React Server Components, and error boundary tracking.

Client-side rendering metrics, Vue Router navigation, and Pinia store tracing.

Query-level performance metrics, lock contention, vacuum stats, and replication lag.

Slow query analysis, InnoDB buffer pool metrics, and replica lag monitoring.

Collection-level operation metrics, index usage, and oplog replication monitoring.

Keyspace metrics, command latency, memory fragmentation, and cluster health.

Cache hit/miss ratios, eviction rates, and connection count monitoring.

Index, shard, and cluster-level metrics with query latency and JVM heap tracking.

Node health, read/write latency, compaction metrics, and GC pause monitoring.

Query throughput, merge tree metrics, and replication lag for ClickHouse clusters.

Distributed SQL metrics, range rebalancing, and transaction conflict monitoring.

Warehouse credit usage, query queue times, and data transfer monitoring.

Write throughput, query latency, and series cardinality tracking.

Consumer group lag, partition metrics, broker health, and producer throughput.

Queue depth, message rates, consumer counts, and node-level resource metrics.

JetStream stream metrics, consumer lag, and NATS server health monitoring.

Task queue depth, worker utilization, failure rates, and task duration histograms.

Job queue sizes, worker thread utilization, retry counts, and dead job monitoring.

Workflow execution metrics, activity task latency, and worker throughput.

Route TigerOps alerts and AI incident summaries directly to your Slack channels.

Trigger and resolve PagerDuty incidents automatically from TigerOps detections.

Create and close Opsgenie alerts with full context and runbook links attached.

Post rich incident cards and alert digests to Teams channels and adaptive cards.

Auto-create and update Jira issues from TigerOps incidents with full trace context.

Push production incidents to Linear as issues with severity, labels, and SLO context.

Send alert notifications and AI summaries to Discord servers and channels.

Native OTLP ingest for traces, metrics, and logs — no vendor lock-in required.

Scrape Prometheus exporters and remote-write metrics directly into TigerOps.

Drop-in StatsD server compatibility — forward metrics from any StatsD client.

Import Jaeger traces via OTLP or the Thrift protocol for unified trace analysis.

Ingest Zipkin spans and correlate them with infrastructure metrics and logs.

Route log streams from Fluentd pipelines into TigerOps log management.

Lightweight log forwarding from Fluent Bit to TigerOps with zero configuration.

Ingest logs from Logstash pipelines with full field mapping support.

High-performance log and metric routing from Datadog Vector to TigerOps.

Drop-in compatibility with Datadog agent metrics and DogStatsD protocol.

Request rates, upstream latency, connection counts, and error code distribution.

Frontend/backend session rates, queue depths, and health check status.

Entrypoint metrics, router-level latency, and middleware error tracking.

Edge request metrics, cache ratios, firewall events, and Worker execution stats.

Serverless function metrics, edge middleware latency, and deployment event tracking.

Ingest logs from Loki-compatible sources with label-based querying support.

Accept Prometheus remote-write via Mimir-compatible endpoints.