Best Observability Pipeline Software - Page 2

Enroute

Next-Gen Kubernetes Native API Gateway built on Envoy Proxy

Average Rating: 5.0/5.0

Total Reviews: 1

Falcon Onum

Falcon Onum is a real-time, security-native data pipeline and telemetry control platform that ingests, filters, enriches, and routes data in motion before it reaches SIEMs, data lakes, analytics platforms, and AI systems. Built for modern IT, SecOps, and SecDataOps teams, Onum enables organizations to reduce noise, control ingestion costs, accelerate migrations, and deliver high-fidelity, context-rich telemetry across heterogeneous environments. Unlike generic observability pipelines, Falcon Onum is purpose-built for security and IT use cases, with in-pipeline transformation, enrichment, masking, aggregation, and policy-based routing that ensures downstream systems receive the right data in the right format at the right time. Organizations use Onum to modernize legacy SIEM architectures, eliminate brittle point-to-point integrations, optimize storage spend, and create an AI-ready data foundation that improves detection accuracy and investigative speed. Designed for scale, flexibility, and ecosystem openness, Falcon Onum empowers enterprises to shape once and deliver anywhere — while maintaining full control over their security telemetry lifecycle.

Grepr Autonomous Telemetry Pipeline

GREPR: Eliminate telemetry noise without the pain. Grepr is an autonomous telemetry pipeline, built for the AI era, that automatically eliminates 90% of your telemetry noise and cuts observability TCO by 75% without toilsome rules to write for Engineering, impacts to dashboards or alerts, or tool migrations. Grepr detects millions of log patterns, trace signatures, and metric trends dynamically, instead of relying on static rules. It sits between your telemetry sources and the observability platforms you already run: Datadog, New Relic, Splunk, Dynatrace, Grafana, CloudWatch, and OpenTelemetry. One config change points your existing collectors at Grepr, and you are live in about 30 minutes. Most teams have been stuck with two bad options: collect everything and treat a soaring bill as an insurance premium, or hand-build drop rules that go blind mid-incident and bury engineers in toil. Grepr kills the tradeoff. Machine learning separates signal from noise automatically. High-value signal and compressed summaries flow to your observability tools. Every raw byte is preserved in low-cost storage in your own S3 bucket, ready for search, backfill, and compliance. Your dashboards and alerts never notice the difference. WHY OBSERVABILITY BROKE Modern architectures, especially the ones built with AI or for AI, generate far more telemetry and change far faster than anything before them. Gartner projects that by 2028, 80% of enterprises without observability cost controls will overspend by more than 50%. Grepr is how you keep full visibility and still get the bill under control. THREE THINGS GREPR DOES DIFFERENTLY - Instead of manual rules: noise reduction is automatic and dynamic. It evolves with your data. There is nothing to build and nothing to maintain. - Instead of sampling or dropping data: nothing is thrown away for good. All raw telemetry stays accessible for investigations and compliance, and Grepr can backfill it manually or automatically the moment an incident calls for it. - Instead of replacing tools: keep your tools, dashboards, and alerts. Send to multiple vendors at once. No migrations, no re-instrumentation. HOW THE REDUCTION ACTUALLY WORKS - Logs. Grepr's Log Reducer runs real-time clustering across every message, passes through the first few of each new pattern, then aggregates and summarizes the repetitive ones: the noisy heartbeats and the stray debug line someone shipped to prod. Errors and unique messages pass straight through. Noise gets compressed. Raw messages stay queryable in low-cost storage. - Traces. Path-based tail sampling assembles spans by trace ID into complete end-to-end traces, maps each to a structural signature of its exact execution path, buckets by that signature, and samples on uniqueness and performance within each path. Rare paths and anomalies that coarse bucketing loses are kept. Selected traces forward complete with zero missing spans, and every trace is preserved in low-cost storage. You get a far lower sampling rate, lower APM cost, and full application coverage. - Metrics. BUILT FOR THE TEAMS ON THE HOOK FOR COST AND RELIABILITY - Engineering leaders get their engineers back to building the business instead of babysitting observability. - Platform and SRE teams drop the endless routing and filtering rules and get a cleaner signal-to-noise ratio, so troubleshooting is faster when something breaks. - FinOps and cloud cost teams cut a major infrastructure line item without forcing anyone through a platform migration. PROOF - Jitsu cut logging costs by 90% while managing millions of shipments. Their CTO's line: find the needle in the haystack without paying for the haystack. - FOSSA saw a 95% reduction in log volume without changing a thing in their app. - Envoy stopped paying for 90% of log volume that was never doing anything. Engineers changed nothing about how they work, and dashboards and alerts kept working as expected. Trusted by teams including 7-Eleven, Jitsu, FOSSA, Siteimprove, HeartFlow, and Envoy. DEPLOY IT, SECURE IT, RUN IT - Live in 30 minutes. One config change points existing collectors at Grepr. No new infrastructure, no re-instrumentation. - Vendor-neutral. Datadog, New Relic, Splunk, Dynatrace, Grafana, CloudWatch, OpenTelemetry, and more, with simultaneous forwarding to multiple vendors. - Enterprise controls. Role-based access control for auditing and isolation, centralized or decentralized administration with guardrails, a Terraform provider for GitOps upgrades, and Draft and Live views to test config changes before they hit production. - Compliance and access. SOC 2 Type II- and HIPAA-compliant, single sign-on with SAML across most providers including Okta, and a public trust center at trust.grepr.ai. - Flexible hosting. Run Grepr as multi-tenant SaaS or inside your own AWS VPC with no external connections. Point your collectors at Grepr, keep your stack, and pay for signal instead of noise. Start free or book a demo at grepr.ai.

Netdata

Netdata is an AI-driven real-time observability platform that monitors systems, containers, applications, and infrastructure across servers, cloud environments, Kubernetes clusters, and IoT devices. With zero-configuration deployment, Netdata installs instantly, automatically discovers metrics, builds dashboards, and begins monitoring without setup. Netdata AI serves as an intelligent on-call assistant, automatically investigating alerts, correlating anomalies across thousands of metrics, identifying root causes, and explaining incidents with clear, actionable recommendations. By transforming raw telemetry into AI-guided insights, Netdata helps engineering teams move from alert to resolution in minutes instead of hours. The platform collects per-second metrics through 800+ integrations across operating systems, containers, databases, applications, OpenMetrics exporters, StatsD, and logs. Its distributed architecture processes data at the edge, enabling high-resolution monitoring and visibility into short-lived performance issues that traditional monitoring tools often miss. Netdata is available as a scalable SaaS platform with Netdata Cloud or as a private deployment within your own infrastructure, supporting on-prem, private cloud, and air-gapped environments while delivering automated dashboards, ML-based anomaly detection, and real-time troubleshooting.

Average Rating: 4.6/5.0

Total Reviews: 51

ObserveNow

Open source based observability stack featuring logs, traces and metrics – all under one roof. Observe any cloud infrastructure, VM, bare-metal servers, databases, or lambda functions with ObserveNow’s integrations available out of the box. Start observing at scale within minutes.

Onum

Onum observes and adds value to your data in transit to deliver pure real-time alerts on abnormalities, potential security risks, and system troubles.

OpenTelemetry

High-quality, ubiquitous, and portable telemetry to enable effective observability

PacketRanger

Intelligent packet broker that drives management application savings, reduces network congestion, simplifies network administration, and improves data-driven decision making via embedded analytics.

Riverbed Flow Gateway

The Alluvio Flow Gateway is a component of Alluvio NetProfiler. Please refer to the NetProfiler page for more information.

Sawmills

Sawmills is the agentic telemetry management platform for DevOps teams who want full control over the data powering their observability tools. Mills, the agent at the heart of Sawmills, manages the telemetry lifecycle from code, through CI, into production. It surfaces what's driving cost and eroding signal quality, and gives developers self-service fixes they can apply in seconds within guardrails DevOps controls. The result: 60-90% lower observability spend, higher-fidelity signal, and no migration off the stack you already use.

Splunk Cloud Platform

Search, analyze, visualize and act on your data with the flexible, secure and cost effective data platform service. Go live in as little as two days, and with your IT backend managed by Splunk experts you can focus on acting on your data. Search any kind of data in real-time to detect and prevent issues before they happen with access to the latest streaming and machine learning capabilities. Search any kind of data in real-time to detect and prevent issues before they happen with access to the latest streaming and machine learning capabilities.

Average Rating: 4.3/5.0

Total Reviews: 2

Tenzir

Tenzir lets security teams quickly create powerful data pipelines out of plug-and-play building blocks.

VirtualMetric DataStream

VirtualMetric DataStream is an intelligent security data pipeline for SIEMs that reduces data ingestion costs by up to 90% and cuts manual log handling by up to 60%. By automatically filtering noise, normalizing and enriching logs, and routing data to the right destinations, DataStream delivers clean, high-fidelity data for analysts and AI-driven detection. DataStream sits between data sources and analytics platforms, giving security teams full control over how telemetry is collected, processed, and delivered. It supports hybrid collection with an agentless-first approach, applies risk-free data reduction, and continuously adapts to schema and format changes to keep pipelines reliable as environments evolve. Built for scale and resilience, DataStream features a high-performance pipeline engine, clustered deployment options for high availability, and a write-ahead log architecture to prevent data loss. With VirtualMetric, SOC teams gain predictable SIEM costs, reduced operational overhead, and higher-quality security data that improves detection and investigation.