7 Best Alternatives to Datadog for Observability in 2026

Why look beyond Datadog

Datadog provides a broad suite of observability tools, consolidating metrics, logs, and traces into a single platform. This integrated approach can simplify operations for large organizations managing complex, distributed systems. Its strength lies in its extensive integrations, allowing it to collect data from a wide array of services and infrastructure components, including cloud providers, databases, and message queues Datadog Integrations documentation. Real User Monitoring (RUM) and Synthetic Monitoring capabilities extend visibility to user experience.

However, the comprehensive nature of Datadog can lead to a steep learning curve for new users, due to the sheer volume of features and configuration options. The module-based pricing model, while flexible, can result in high costs for organizations with large data volumes or extensive monitoring requirements across multiple product areas, such as infrastructure, APM, and log management Datadog Pricing page. Some users may seek alternatives that offer a more focused feature set, a different pricing structure, or a simpler user experience tailored to specific needs.

Top alternatives ranked

1. 1. New Relic — Observability platform for engineering teams

   New Relic offers a unified observability platform designed to help engineering teams monitor, debug, and optimize their entire software stack. It provides capabilities for APM, infrastructure monitoring, log management, browser monitoring (RUM), synthetic monitoring, and mobile monitoring New Relic Platform overview. New Relic's strength lies in its ability to correlate data across different layers of the stack, enabling users to gain insights into application performance and user experience. The platform supports a wide range of programming languages and frameworks through its agents and integrations.

   New Relic's pricing model, based on data ingest and user seats, can offer predictability for some organizations, especially those with stable data volumes New Relic Pricing details. Its APM features are particularly robust, providing deep code-level visibility, transaction tracing, and error tracking. The platform also emphasizes AI-powered anomaly detection and incident intelligence to help teams identify and resolve issues faster. For organizations prioritizing a comprehensive, developer-centric observability experience with strong APM capabilities, New Relic presents a viable alternative.

   Best for:

   • End-to-end application performance monitoring (APM)
   • Unified platform for metrics, logs, and traces
   • AI-driven anomaly detection and incident intelligence

2. 2. Dynatrace — AI-powered observability and security platform

   Dynatrace provides an AI-powered observability and security platform that offers continuous automation and intelligence across the entire software lifecycle. Its core strength is its OneAgent technology, which automatically discovers and monitors all components of an application environment, from infrastructure to user experience, without manual configuration Dynatrace Platform overview. Dynatrace offers APM, infrastructure monitoring, log management, RUM, synthetic monitoring, and application security capabilities.

   The platform's AI engine, Davis, automatically identifies the root cause of performance issues and security vulnerabilities, reducing alert fatigue and accelerating problem resolution. This high degree of automation and AI assistance can be particularly beneficial for large, complex enterprise environments that require deep insights and proactive problem detection. Dynatrace's focus on autonomous observability and application security makes it a strong contender for organizations seeking to reduce operational overhead while maintaining high levels of visibility and control Dynatrace Pricing information.

   Best for:

   • AI-powered root cause analysis and automation
   • Autonomous observability for complex enterprise environments
   • Integrated application security monitoring

3. 3. Grafana Labs — Open and composable observability stack

   Grafana Labs offers an open and composable observability stack centered around Grafana, an open-source data visualization and dashboarding tool. While Datadog provides a fully integrated, proprietary solution, Grafana Labs focuses on providing the tools and services to build an observability stack using open-source components like Prometheus for metrics, Loki for logs, and Tempo for traces Grafana product page. This approach allows organizations greater flexibility and control over their data and tooling.

   Grafana Cloud provides a managed service for these open-source tools, offering scalability and reduced operational burden without sacrificing the benefits of open standards. This can be attractive for organizations that prefer open-source solutions, want to avoid vendor lock-in, or have specific requirements that can be met by customizing individual components. While it may require more integration effort than a single vendor solution, Grafana Labs provides a powerful, cost-effective, and highly customizable alternative for building an observability system Grafana Cloud Pricing.

   Best for:

   • Open-source first observability stack
   • Customizable dashboards and data visualization
   • Cost-effective monitoring for metrics, logs, and traces

4. 4. Google Cloud Platform — Suite of cloud monitoring and logging tools

   Google Cloud Platform (GCP) provides a suite of integrated monitoring and logging services, primarily through Google Cloud Operations (formerly Stackdriver). This includes Cloud Monitoring for infrastructure and application metrics, Cloud Logging for centralized log management, and Cloud Trace for distributed tracing of applications running on GCP Google Cloud Operations documentation. These services are deeply integrated with other GCP products, offering a native observability solution for workloads deployed within Google Cloud.

   For organizations heavily invested in the Google Cloud ecosystem, leveraging these native tools can simplify setup and reduce operational overhead compared to integrating third-party solutions. While they may not offer the same breadth of cross-cloud or on-premises integrations as some dedicated observability platforms, they provide robust capabilities for monitoring GCP resources, GKE clusters, and serverless functions. The pricing is typically based on data ingest, storage, and API calls, aligning with general cloud usage patterns Google Cloud Operations pricing.

   Best for:

   • Native monitoring for Google Cloud environments
   • Integrated logging and tracing for GCP services
   • Organizations with significant Google Cloud infrastructure

5. 5. Microsoft Azure — Comprehensive monitoring for Azure environments

   Microsoft Azure offers Azure Monitor, a comprehensive solution for collecting, analyzing, and acting on telemetry data from Azure and on-premises environments. Azure Monitor provides capabilities for collecting metrics and logs, monitoring application performance, and analyzing infrastructure health Azure Monitor overview. It integrates natively with Azure services, making it a primary choice for organizations operating predominantly within the Azure ecosystem.

   Key components include Log Analytics for querying and analyzing logs, Application Insights for APM, and various dashboards and alerting features. Azure Monitor can also collect data from virtual machines and applications outside of Azure through agents, offering some hybrid cloud capabilities. Its pricing is largely based on data ingested and stored, and the number of monitored entities Azure Monitor pricing. For enterprises with a strong commitment to Microsoft technologies and Azure infrastructure, Azure Monitor provides an integrated, platform-native observability solution.

   Best for:

   • Native monitoring and logging for Azure services
   • Integrated APM for applications hosted on Azure
   • Hybrid cloud observability with Azure-centric focus

6. 6. AWS EC2 — Infrastructure monitoring focused on EC2 instances

   While AWS EC2 itself is an Infrastructure-as-a-Service (IaaS) offering, AWS provides monitoring capabilities primarily through Amazon CloudWatch, which integrates with EC2 and other AWS services Monitoring EC2 instance health. CloudWatch collects metrics, logs, and events, allowing users to monitor their AWS resources, including EC2 instances, and to set up alarms and dashboards. For organizations primarily running workloads on AWS EC2, CloudWatch provides fundamental infrastructure metrics like CPU utilization, disk I/O, and network activity.

   CloudWatch can be extended with the CloudWatch Agent to collect more detailed metrics and logs from EC2 instances, including custom metrics and application logs. While not a full-stack observability platform on its own, when combined with other AWS services like AWS X-Ray for tracing and Amazon OpenSearch Service for log analysis, it can form a foundational observability stack within AWS. Its pricing is based on metrics, alarms, logs ingested, and dashboards used Amazon CloudWatch pricing.

   Best for:

   • Basic infrastructure monitoring for AWS EC2 instances
   • Organizations deeply integrated within the AWS ecosystem
   • Cost-effective metric collection within AWS

7. 7. OpenStack — Open-source cloud infrastructure monitoring

   OpenStack is an open-source cloud operating system that controls large pools of compute, storage, and networking resources. For monitoring within an OpenStack environment, organizations typically leverage a combination of open-source tools. Ceilometer is the primary monitoring service in OpenStack, designed to collect metering and monitoring data from OpenStack components OpenStack Ceilometer documentation. It collects metrics like CPU utilization, disk usage, and network traffic from instances and other OpenStack resources.

   For more advanced observability, OpenStack users often integrate with external open-source solutions such as Prometheus for metrics collection, Grafana for visualization, and Loki for log aggregation. This approach offers complete control over the monitoring stack and avoids vendor lock-in, aligning with the principles of OpenStack itself. While it requires more setup and maintenance expertise than a managed service, it provides a highly customizable and cost-effective solution for monitoring private cloud infrastructure built on OpenStack.

   Best for:

   • Monitoring private cloud infrastructure built on OpenStack
   • Organizations seeking complete control over their monitoring stack
   • Cost-conscious users preferring open-source solutions

Side-by-side

How to pick

Selecting an observability platform requires evaluating your specific technical requirements, budget constraints, and organizational preferences. Start by assessing your current infrastructure:

• Cloud-Native vs. Hybrid vs. On-Premises: If your environment is primarily on a single public cloud (e.g., AWS, GCP, Azure), leveraging their native monitoring solutions like AWS CloudWatch, Google Cloud Operations, or Azure Monitor might offer the most seamless integration and potentially lower initial costs for basic monitoring. For hybrid or multi-cloud deployments, or extensive on-premises infrastructure, solutions like Datadog, New Relic, or Dynatrace offer broader support and centralized visibility. OpenStack users will likely find open-source combinations more suitable.
• Depth of APM: Consider the level of application performance visibility you need. If code-level tracing, detailed transaction analysis, and automatic root cause identification are critical, New Relic and Dynatrace offer advanced APM capabilities that can be more granular than some alternatives.
• Log Management Requirements: Evaluate your log volume, retention needs, and the complexity of your log analysis. Platforms with robust log management features (e.g., Datadog, New Relic, Dynatrace, or dedicated open-source solutions like Loki) are better suited for high-volume logging and complex querying. Native cloud solutions also offer strong log services.
• Open Source Preference: If your organization prioritizes flexibility, customization, and avoiding vendor lock-in, an open-source-centric approach with Grafana Labs (for managed open source) or a self-managed stack (e.g., Prometheus, Grafana, Loki) might be preferable. This often requires more operational effort but offers greater control.
• Automation and AI: For environments with high complexity or limited operational staff, platforms with strong AI-driven automation for anomaly detection and root cause analysis, such as Dynatrace, can significantly reduce manual effort and accelerate incident response.
• Pricing Model: Understand the pricing structure of each alternative. Datadog's module-based pricing can scale with usage, but costs can accumulate across multiple products. New Relic and Dynatrace often use host or data ingest models. Cloud providers typically charge based on resource consumption. Compare these models against your expected data volumes and resource usage to project total cost of ownership.
• Ease of Use and Learning Curve: A comprehensive platform like Datadog offers extensive features but can be overwhelming initially. Some alternatives might offer a more focused or streamlined user experience depending on your primary monitoring needs. Open-source solutions often require more expertise for setup and maintenance.

By systematically evaluating these factors against your organization's specific context, you can identify the observability solution that best aligns with your technical requirements and strategic goals.