Best Application Performance Monitoring Software

Elastic Observability is the observability product built on Elasticsearch, collecting and analysing logs, metrics and traces alongside Elastic's search and security offerings, deployed as Elastic Cloud Serverless, Elastic Cloud Hosted or self-managed.

Sharing one data store across observability, search and security is the structural argument and it produces a real operational advantage. Investigating an incident routinely means correlating an application error with a security event and a business record, and when those live in three products the correlation is done by a person with three browser tabs. One engine holding all of it makes that a query.

The self-managed option is what distinguishes Elastic commercially from the cloud-only observability vendors, and it matters for two reasons: telemetry volumes make hosted pricing unpredictable at scale, and some organisations cannot send operational data to a third party at all. Being able to run the same product locally, on Kubernetes or under an organisation's own orchestration removes both objections.

Elastic has moved firmly into the AI retrieval space alongside observability, with a vector database, context engineering for grounding agents, an Agent Builder, Jina AI models for embeddings and reranking, and workflows combining scripted automation with reasoning inside Elasticsearch. AutoOps provides cluster management with performance recommendations and cost insights, which addresses the long-standing criticism that operating Elasticsearch well requires real expertise. Kibana handles exploration and dashboards. Rates are published separately on the Elastic pricing pages rather than on the product page.

Grafana is a full-stack observability platform from Grafana Labs, covering metrics, logs, traces, profiles and k6 performance tests on an OpenTelemetry-native foundation, and named a Leader in the 2026 Gartner Magic Quadrant for Observability Platforms.

Adaptive Telemetry is the feature that addresses the problem every observability buyer eventually has. Grafana states plainly that half of telemetry spend is wasted, which matches the experience of most teams: instrumentation is added generously, nobody ever removes it, and the bill grows with data volume rather than with value. The suite identifies the data worth keeping at full fidelity and aggregates the rest, with the company claiming cost reductions of up to 80 percent.

Being OpenTelemetry-native rather than OpenTelemetry-compatible is the architectural point worth checking when comparing vendors. A platform built on the open standard means instrumentation is not proprietary, so changing vendor later does not mean re-instrumenting every service, which is otherwise the reason observability contracts renew regardless of satisfaction.

The AI work runs in two directions, which Grafana summarises as AI for observability and observability for AI. Grafana Assistant interprets production telemetry, Investigations accelerates root cause analysis, and Agent Observability evaluates and improves production AI agents. The Free Forever plan costs nothing and suits personal projects, Pro self-serve starts at 19 dollars a month plus usage with volume discounts, and Enterprise starts at a 25,000 dollar annual spend commitment. Metrics start at 6.50 dollars per thousand active series, falling to 5.90 dollars between 10,000 and 100,000.

Datadog is a cloud based observability and security platform that unifies infrastructure monitoring, application performance monitoring (APM), log management, real user monitoring, and security monitoring in a single product. It correlates metrics, traces, and logs so engineering teams can pivot between them to investigate issues down to the code level, and it offers more than 1,000 integrations with cloud providers and other tools.

Datadog's pricing is modular and usage based, with each product billed separately, such as per host for infrastructure and APM, or per GB and per million events for log management. A limited free tier covers up to 5 hosts with 1-day retention. Datadog also offers AI powered features including anomaly detection and autonomous investigation agents.

Dynatrace is an enterprise observability and security platform that automatically discovers and maps applications, infrastructure, and cloud services across hybrid and multi-cloud environments. It combines application performance monitoring, infrastructure monitoring, log analytics, real user monitoring, and application security into one platform, using its Davis AI engine for automated root cause analysis rather than manual dashboard digging.

The platform uses consumption-based pricing tied to host units, memory-GiB-hours, and session counts rather than flat per-seat licensing, which lets large organizations scale monitoring across thousands of hosts and services. Dynatrace is aimed primarily at mid-size to large enterprises running complex, distributed systems that need automated instrumentation, distributed tracing, and unified security and reliability insights.

New Relic is a cloud based observability platform that unifies infrastructure monitoring, application performance monitoring, error tracking, log management, and distributed tracing in a single dashboard. All telemetry data is stored in a proprietary database called NRDB and queried with NRQL, a SQL like language built for observability data. The platform serves engineering teams that need to correlate metrics, events, logs, and traces to find the root cause of production issues quickly.

New Relic offers a permanent free tier with 100GB of monthly data ingest and one full platform user, alongside paid Standard, Pro, and Enterprise editions priced per user with additional data charged per gigabyte. Over 800 pre built integrations connect New Relic to popular cloud providers, container platforms, and alerting tools, and an AI powered engine helps predict and diagnose issues before they affect customers.

SigNoz is an open source observability platform positioned explicitly as a Datadog alternative, bringing traces, metrics and logs into one OpenTelemetry-native product available as SigNoz Cloud or self-hosted on a customer's own infrastructure.

The self-hosting option is what makes the cost argument credible rather than rhetorical. Any vendor can claim to be cheaper; a product that can be run on the customer's own hardware sets a ceiling on what the hosted version can charge, because the alternative is always available. SigNoz publishes a customer describing a Datadog trial ending with a bill over two thousand dollars, which is the moment that sends teams looking.

Usage-based pricing with retention as a separate dimension is the sensible structure for this workload. Logs and traces are 0.30 dollars per gigabyte ingested and metrics 0.10 dollars per million samples, with retention selectable from 15 days through 30, 90 and 180 days to a full year. Separating retention from ingestion matters because the two have completely different value profiles: recent data is queried constantly and old data is kept for compliance.

Agent-native observability is the newer positioning, covering both a team's services and the AI agents running alongside them, built on open standards throughout. Published customers include Cisco, which describes using SigNoz as a first-class dependency in a new agent framework, alongside teams that migrated from Grafana and CloudWatch. SigNoz Cloud starts at 49 dollars a month including 49 dollars of usage, and the self-hosted version is free.