The observability landscape has evolved dramatically, with the market projected to reach $62.9 billion by 2025. As modern applications grow increasingly complex and distributed across cloud environments, traditional monitoring approaches no longer suffice. Organizations need comprehensive visibility into their systems’ health, performance, and behavior.
Understanding what observability truly means for modern infrastructure is crucial before selecting the right platform. Unlike simple monitoring, observability enables teams to understand system behavior through metrics, logs, and distributed traces. This comprehensive guide explores the top 10 observability platforms transforming how DevOps teams maintain and optimize their infrastructure in 2025.
Whether you’re running cloud-native Kubernetes clusters, managing microservices architectures, or operating legacy systems, this guide will help you choose the right observability solution. We’ll examine each platform’s strengths, ideal use cases, and how they integrate with your existing DevOps and monitoring workflows.
1. Last9 Levitate - High Cardinality Metrics Specialist
Last9 has emerged as the go-to solution for organizations struggling with high-cardinality metrics in cloud-native environments. Their flagship product, Levitate, handles an impressive 20 million+ cardinality per metric, making it ideal for Kubernetes environments with dynamic labels and tags.
Key Features
Streaming Aggregations: Levitate processes data in real-time as it arrives, massively reducing query overhead during analysis. This approach eliminates the performance bottlenecks that plague traditional time-series databases when handling high-cardinality data.
Cardinality Explorer: Unlike platforms that simply drop high-cardinality metrics when limits are exceeded, Last9’s Cardinality Explorer provides complete visibility into metric behavior. Teams can make informed decisions about which labels to keep rather than blindly dropping instrumentation.
Prometheus Compatibility: Organizations already invested in Prometheus monitoring infrastructure can seamlessly migrate to Levitate. It supports PromQL, OpenMetrics, and integrates with popular tools like InfluxDB and Telegraf.
No Data Loss Guarantee: Even metrics exceeding default cardinality limits are preserved, ensuring critical observability data is never dropped during production incidents.
Deployment Options
Last9 offers both SaaS and Bring Your Own Cloud (BYOC) deployment models. The BYOC option eliminates egress data transfer costs that can spiral out of control with traditional SaaS observability platforms—a common pain point for teams running large-scale cloud infrastructure.
Best For
- Kubernetes environments with dynamic pod labels
- Organizations with 10M+ active time series
- Teams requiring Prometheus-compatible long-term storage
- Companies managing observability costs at scale
Pricing: Usage-based with SaaS and BYOC options
2. Datadog - Enterprise SaaS Observability Leader
Datadog dominates the enterprise observability market with a commanding 51.82% market share in data center management. The platform’s strength lies in its comprehensive, unified approach to observability, combining application performance monitoring (APM), infrastructure monitoring, real user monitoring (RUM), and security observability in a single platform.
Comprehensive Integration Ecosystem
Datadog’s vast integration catalog supports 500+ technologies out of the box. From cloud providers (AWS, Azure, GCP) to databases, message queues, and container orchestration platforms, Datadog provides pre-built dashboards and monitors for virtually every component in modern tech stacks.
Key Capabilities
Unified Dashboards: Correlate metrics, traces, and logs in a single view. Jump from a latency spike in APM directly to relevant application logs without switching tools or contexts.
AI-Powered Anomaly Detection: Machine learning algorithms automatically detect anomalies in metrics, reducing alert fatigue by surfacing genuinely unusual behavior patterns.
Network Performance Monitoring: Gain visibility into network flows, DNS queries, and service dependencies across hybrid cloud environments.
Best For
- Large enterprises requiring comprehensive observability across diverse technology stacks
- Organizations prioritizing vendor-supported integrations over custom solutions
- Teams needing security and compliance observability alongside performance metrics
- Companies with budget for premium SaaS observability
Pricing: Per-host pricing model (can become expensive at scale)
3. Grafana Stack - Open Source Visualization Powerhouse
Grafana has become synonymous with observability visualization, powering dashboards for millions of users worldwide. The Grafana Stack combines multiple complementary projects: Grafana for visualization, Mimir for metrics storage, Loki for log aggregation, and Tempo for distributed tracing.
The Complete Stack
Grafana Dashboards: The industry-standard visualization layer supports querying data from dozens of data sources. Create beautiful, interactive dashboards that combine metrics, logs, and traces from disparate systems.
Grafana Mimir: A horizontally scalable, highly available metrics backend compatible with Prometheus. Mimir handles billions of active series while maintaining query performance, making it suitable for large-scale Prometheus deployments.
Grafana Loki: Designed to be cost-effective and easy to operate, Loki aggregates logs without indexing their contents. This approach dramatically reduces storage costs compared to traditional log management platforms.
Grafana Tempo: A high-scale distributed tracing backend that requires only object storage to operate. Tempo integrates seamlessly with Grafana’s unified query interface.
Deployment Flexibility
Organizations can choose between self-hosted open source deployments, Grafana Cloud’s fully managed service, or hybrid approaches. This flexibility makes Grafana ideal for teams wanting control over their observability infrastructure while benefiting from enterprise features.
Best For
- Teams already invested in Prometheus and seeking powerful visualization capabilities
- Organizations wanting open source flexibility with optional commercial support
- Companies requiring multi-tenancy in their observability platform
- DevOps teams comfortable managing their own infrastructure
Pricing: Free (open source) or Grafana Cloud usage-based pricing
4. New Relic - Unified Observability Platform
New Relic holds a significant 24% market share in system administration, offering a unified SaaS observability experience. The platform combines application performance monitoring, infrastructure monitoring, logs, distributed tracing, and synthetic monitoring under a single pricing model.
One Price, Full Platform Access
Unlike competitors charging separately for APM, logs, and infrastructure monitoring, New Relic’s unified pricing model provides access to all observability capabilities. This approach simplifies budgeting and encourages comprehensive instrumentation without worrying about per-feature costs.
Key Differentiators
Query Language (NRQL): New Relic’s custom query language enables powerful data exploration across all telemetry types. While not as widespread as PromQL, NRQL provides flexible analytics capabilities for custom insights.
Vulnerability Management: Integrated security vulnerability detection helps teams identify and prioritize security issues alongside performance problems, supporting comprehensive DevOps security practices.
Applied Intelligence: AI-driven incident intelligence automatically correlates related alerts, reducing noise and helping teams respond to genuine issues faster.
Best For
- Teams wanting simplicity and rapid adoption without complex pricing calculations
- Organizations consolidating multiple monitoring tools into a single platform
- Companies prioritizing developer experience and ease of use
- Businesses requiring both observability and basic security monitoring
Pricing: Data ingest-based pricing with full platform access
5. Dynatrace - AI-Powered Enterprise Observability
Dynatrace serves large enterprises that prioritize automation and deep analytics. The platform’s Davis AI engine represents its core differentiator, automatically discovering infrastructure components, mapping dependencies, and identifying root causes without manual configuration.
OneAgent Auto-Discovery
Dynatrace’s OneAgent technology automatically instruments applications and infrastructure. Deploy a single agent, and Dynatrace discovers and monitors your entire technology stack—from containers and VMs to applications and services—without code changes.
Davis AI Engine
The AI engine correlates billions of metrics and events to surface root causes automatically. During incidents, Davis identifies the probable root cause, impacted services, and business impact, dramatically reducing mean time to resolution (MTTR).
Advanced Capabilities
Automatic Baselining: Davis learns normal behavior patterns for every component, automatically detecting anomalies without manual threshold configuration.
Business Analytics: Connect technical metrics to business KPIs, measuring how performance issues impact revenue, user experience, and business outcomes.
Cloud Automation: Deep integrations with Kubernetes, AWS, Azure, and GCP provide cloud-specific insights and automated remediation workflows.
Best For
- Large enterprises with complex, dynamic environments
- Organizations requiring AI-driven root cause analysis and automation
- Teams lacking dedicated observability engineering resources
- Companies prioritizing automatic discovery over manual instrumentation
Pricing: Enterprise-focused pricing (contact sales)
6. Honeycomb - Event-Based Observability
Honeycomb pioneered event-based observability, focusing on high-cardinality data analysis for distributed systems. The platform excels at answering complex questions about system behavior through its powerful query interface and support for arbitrary dimensional data.
Query-Driven Investigation
Traditional metrics-based tools force teams to pre-aggregate data, losing valuable context. Honeycomb’s event-based approach preserves all context, enabling teams to ask novel questions during incidents without pre-planning which metrics to collect.
Natural Language Query Assistant
Honeycomb’s Query Assistant allows engineers to ask questions in plain English: “Show me slow requests from mobile users in Europe experiencing errors.” The AI translates these questions into powerful queries, democratizing observability for team members unfamiliar with query languages.
OpenTelemetry Leadership
As major contributors to the OpenTelemetry project, Honeycomb has built their platform around handling the rich, high-cardinality data that OpenTelemetry instrumentation provides. This makes migration straightforward for teams already adopting OpenTelemetry standards.
Best For
- Organizations debugging complex distributed systems with microservices
- Teams wanting to ask arbitrary questions about system behavior
- Companies committed to OpenTelemetry instrumentation standards
- Engineers who value query flexibility over pre-built dashboards
Pricing: Event-based pricing model
7. Elastic Observability - Search-Based Observability
Elastic brings its renowned search capabilities to observability, combining the power of Elasticsearch with purpose-built observability features. Organizations already using the ELK stack (Elasticsearch, Logstash, Kibana) for log management can extend their investment to comprehensive observability.
Unified Search Interface
Elastic’s observability solution leverages Elasticsearch’s distributed search and analytics engine. Correlate metrics, logs, and traces using the same powerful search capabilities that made Elasticsearch the de facto standard for log analysis.
Hybrid Deployment Flexibility
Deploy Elastic on-premises, in your own cloud infrastructure, or use Elastic Cloud’s managed service. This flexibility appeals to organizations with data sovereignty requirements or teams managing sensitive infrastructure.
Key Capabilities
APM with Distributed Tracing: Built-in application performance monitoring with automatic instrumentation for popular frameworks and languages.
Infrastructure Monitoring: Monitor hosts, containers, and cloud services with metrics and logs in a unified view.
Uptime Monitoring: Synthetic monitoring capabilities check endpoint availability and response times from multiple geographic locations.
SIEM Integration: Seamlessly integrate observability data with Elastic’s Security Information and Event Management (SIEM) capabilities.
Best For
- Organizations already invested in the Elastic ecosystem
- Teams requiring powerful search capabilities across observability data
- Companies needing hybrid deployment options
- Businesses combining security and observability workflows
Pricing: Open source (self-hosted) or Elastic Cloud usage-based pricing
8. Splunk - Enterprise Log Analytics & Observability
Splunk has long dominated enterprise log analytics and monitoring. The platform’s native OpenTelemetry support positions it well for modern observability needs while maintaining its traditional strengths in log analysis, security, and compliance.
OpenTelemetry-First Strategy
Splunk has made OpenTelemetry its default data collection standard, with Splunk employees contributing to OpenTelemetry’s development. This commitment ensures long-term compatibility and investment in the open standard.
Enterprise-Grade Capabilities
Log Analysis at Scale: Process and analyze petabytes of log data with Splunk’s distributed architecture, making it suitable for large enterprises with compliance requirements.
Security Operations (SIEM): Splunk’s security operations capabilities integrate observability data with security events, providing comprehensive threat detection and response workflows.
IT Service Intelligence: Correlate IT operations data with business services, measuring how infrastructure health impacts business KPIs and service level objectives.
Best For
- Large enterprises with existing Splunk investments
- Organizations requiring comprehensive security and compliance monitoring
- Teams needing mature integrations with enterprise software
- Companies prioritizing vendor support and enterprise SLAs
Pricing: Data ingest-based (can be expensive at scale)
9. SigNoz - Open Source OpenTelemetry-Native Platform
SigNoz has rapidly gained traction as a compelling open source alternative to Datadog and New Relic, with over 24,000 GitHub stars. Built specifically for OpenTelemetry, SigNoz provides a unified platform for metrics, traces, and logs in a single application.
OpenTelemetry-Native Architecture
Unlike platforms that retrofitted OpenTelemetry support, SigNoz was designed from the ground up for OpenTelemetry data. This native support ensures optimal performance and compatibility with OpenTelemetry’s semantic conventions.
ClickHouse Backend
SigNoz uses ClickHouse as its single datastore for all three telemetry signals. This architecture enables powerful correlations between metrics, traces, and logs without complex data pipelines or multiple storage backends.
Self-Hosted Control
Deploy SigNoz in your own infrastructure, maintaining full control over your observability data. This appeals to organizations with data privacy requirements or those wanting to avoid vendor lock-in.
Key Features
Unified Query Interface: Query metrics, traces, and logs using familiar query languages (PromQL for metrics, filter expressions for logs and traces).
Service Maps: Automatically generate service dependency maps from distributed trace data, visualizing microservices architectures.
Alert Management: Built-in alerting with integrations to PagerDuty, Slack, and other incident management tools.
Best For
- Teams committed to open source technologies
- Organizations wanting an alternative to expensive SaaS platforms
- Companies requiring data sovereignty and privacy controls
- DevOps teams comfortable managing their own infrastructure
Pricing: Free (open source) with optional SigNoz Cloud managed service
10. VictoriaMetrics - High-Performance Prometheus Alternative
VictoriaMetrics has established itself as the superior Prometheus alternative for organizations requiring efficient long-term metrics storage and multi-tenancy support. Known for exceptional resource efficiency, VictoriaMetrics uses less CPU and RAM while handling higher ingestion rates than Prometheus.
Performance and Efficiency
VictoriaMetrics consistently outperforms Prometheus in resource utilization benchmarks. Organizations report 10x reduction in memory usage and 7x reduction in CPU usage compared to Prometheus, making it ideal for cost-conscious teams.
Prometheus Compatibility
VictoriaMetrics is fully compatible with Prometheus, supporting PromQL queries, Prometheus remote write protocol, and Grafana integration. Teams can migrate from Prometheus to VictoriaMetrics without changing their dashboards or alerting rules.
Expanding Ecosystem
While primarily known for metrics, VictoriaMetrics now offers VictoriaLogs for log management and distributed tracing capabilities, evolving into a comprehensive observability platform.
Key Capabilities
Long-Term Storage: Efficiently store years of metrics data without performance degradation, solving the retention challenges that plague Prometheus deployments.
Multi-Tenancy: Native multi-tenancy support allows multiple teams or customers to share a single VictoriaMetrics deployment with isolated data and query performance.
Downsampling: Automatically downsample historical data to reduce storage costs while maintaining query performance for long-term trend analysis.
Best For
- Organizations requiring cost-effective long-term metrics storage
- Teams experiencing Prometheus scalability limitations
- Companies needing multi-tenant metrics infrastructure
- DevOps teams prioritizing resource efficiency
Pricing: Free (open source) with commercial support available
Comparison Table: Platform Overview
| Platform | Type | Deployment | Best For | OpenTelemetry | Pricing Model |
|---|---|---|---|---|---|
| Last9 Levitate | SaaS/BYOC | Cloud/Hybrid | High cardinality metrics | ✅ Native | Usage-based |
| Datadog | SaaS | Cloud | Enterprise unified observability | ✅ Supported | Per-host |
| Grafana Stack | OSS/SaaS | Any | Visualization & flexibility | ✅ Native | Free/Usage-based |
| New Relic | SaaS | Cloud | Simplified unified platform | ✅ Supported | Data ingest |
| Dynatrace | SaaS | Cloud | AI-powered automation | ✅ Supported | Enterprise |
| Honeycomb | SaaS | Cloud | Event-based debugging | ✅ Native | Event-based |
| Elastic | OSS/SaaS | Any | Search-based observability | ✅ Supported | Free/Usage-based |
| Splunk | SaaS/On-Prem | Any | Enterprise log analytics | ✅ Native | Data ingest |
| SigNoz | OSS/SaaS | Self-hosted/Cloud | Open source alternative | ✅ Native | Free/Managed |
| VictoriaMetrics | OSS | Self-hosted | Prometheus alternative | ✅ Supported | Free/Support |
How to Choose the Right Observability Platform
Selecting the optimal observability platform requires evaluating several critical factors beyond feature checklists. Consider these key dimensions when making your decision:
Scale and Cardinality Requirements
High-cardinality environments (Kubernetes with dynamic labels, microservices with detailed tags) benefit from platforms specifically designed for this challenge: Last9 Levitate, Honeycomb, or VictoriaMetrics. Traditional platforms may struggle or become prohibitively expensive with high-cardinality data.
Enterprise scale (hundreds of hosts, thousands of services) often requires robust SaaS platforms like Datadog, Dynatrace, or New Relic that handle infrastructure management, scaling, and reliability.
Small to medium deployments can achieve excellent results with open source solutions like Grafana Stack or SigNoz, especially when teams have DevOps expertise to manage infrastructure.
Budget Considerations
Ingest-based pricing (New Relic, Splunk) suits organizations with predictable data volumes but can become expensive with high log verbosity or frequent deployments generating trace spans.
Per-host pricing (Datadog) benefits teams running stable infrastructure but penalizes dynamic, auto-scaling environments where host counts fluctuate.
Open source platforms (Grafana, SigNoz, VictoriaMetrics) minimize licensing costs but require investment in engineering time for deployment, maintenance, and upgrades.
Usage-based models (Last9, Grafana Cloud) align costs with actual consumption, making them suitable for growing organizations or those with seasonal traffic patterns.
Team Expertise and Resources
Dedicated observability teams can maximize value from open source platforms, customizing deployments to exact requirements while maintaining full control.
General DevOps teams often prefer managed SaaS platforms that minimize operational overhead, allowing engineers to focus on application development rather than observability infrastructure.
Organizations lacking deep Kubernetes expertise benefit from platforms with automatic discovery and instrumentation (Dynatrace, Datadog) over solutions requiring extensive configuration.
Existing Technology Stack
Prometheus users should consider platforms with native Prometheus compatibility: Grafana Mimir, VictoriaMetrics, or Last9 Levitate maintain existing workflows while adding capabilities.
ELK stack users can extend their Elasticsearch investment to full observability with Elastic Observability rather than adopting entirely new platforms.
OpenTelemetry adopters benefit most from platforms built for OpenTelemetry: SigNoz, Honeycomb, or Grafana Tempo provide optimal experiences for OpenTelemetry data.
Data Sovereignty and Compliance
Regulated industries (healthcare, finance) may require on-premises deployments or BYOC options, making open source platforms or Dynatrace Managed suitable choices.
European organizations subject to GDPR may prefer platforms with EU data centers (most major vendors) or self-hosted solutions maintaining complete data control.
Government contractors often require FedRAMP-certified platforms or self-hosted deployments meeting specific security standards.
Integration Requirements
Multi-cloud environments benefit from platforms with robust cloud provider integrations: Datadog, Dynatrace, and New Relic offer pre-built dashboards for AWS, Azure, and GCP services.
Service mesh users (Istio, Linkerd) need platforms with deep service mesh integration for automatic trace context propagation and service-to-service metrics.
Incident management workflows require platforms integrating with PagerDuty, Slack, Jira, and ServiceNow. Most modern platforms support these integrations, but verify specific requirements.
Making the Decision
Start with a proof-of-concept deployment using 2-3 platforms that align with your requirements. Instrument a representative application or service, run realistic workloads, and evaluate each platform based on:
- Query performance: Can you quickly find answers during incidents?
- Ease of use: Can your entire team understand and use the platform?
- Total cost of ownership: Include licensing, infrastructure, and engineering time
- Vendor roadmap: Does the platform’s direction align with your architectural evolution?
Understanding key cloud service management KPIs helps define success criteria for your observability platform selection.
Conclusion
The observability landscape in 2025 offers unprecedented choice, from specialized platforms like Last9 Levitate handling extreme cardinality to comprehensive enterprise solutions like Datadog and Dynatrace providing all-in-one observability.
For high-cardinality cloud-native environments, Last9 Levitate, Honeycomb, or VictoriaMetrics deliver exceptional performance and cost efficiency.
Enterprise organizations valuing comprehensive features, integrations, and vendor support gravitate toward Datadog, Dynatrace, or New Relic.
Open source advocates and cost-conscious teams find tremendous value in Grafana Stack, SigNoz, or VictoriaMetrics while maintaining deployment flexibility.
Teams prioritizing simplicity appreciate New Relic’s unified pricing or Honeycomb’s event-based approach over complex platform configurations.
Regardless of which platform you choose, the key to successful observability lies in instrumentation quality, team adoption, and establishing clear practices for investigating and resolving issues. The best platform is the one your team actually uses effectively during incidents and for proactive problem detection.
Need expert guidance implementing observability for your infrastructure? Our team specializes in Prometheus deployments, Grafana consulting, and Thanos implementations. We help organizations design and deploy observability solutions that provide visibility without overwhelming complexity or cost. Contact our DevOps consulting team to discuss your observability requirements.
Sources
- Best Observability Platforms Reviews 2025 | Gartner Peer Insights
- Top 10 Observability Platforms in 2025 | OpenObserve
- The 11 Best Observability Tools in 2025 | Dash0
- Top 10 Observability Tools in 2025 | Uptrace
- Last9: Unified observability platform
- Understanding High Cardinality Metrics with Levitate | Last9
- Honeycomb’s OpenTelemetry Integration
- 12 OpenTelemetry-Compatible Platforms | Uptrace
- SigNoz: Open-source observability platform
- VictoriaMetrics: Time Series Monitoring
- VictoriaMetrics 2025 Developer Experience Review
- OpenTelemetry Tools and Supported Vendors | Logit.io