11 Best Distributed Tracing Tools in 2024

Imagine losing users due to hidden performance issues or bottlenecks only evident in complex systems. Distributed tracing isn't just a "nice-to-have"—it's essential for monitoring the health of your applications, especially in modern, microservices-based architectures. With the right tracing tools, you can diagnose and resolve issues swiftly, ensuring your users experience seamless performance.

To help you find the best option, we've curated a list of top distributed tracing tools.

What is a distributed tracing tool?

Distributed tracing tools comprehensively show how application requests move through different services and databases, providing critical insights into each processing stage. These tools help you understand request flows, identify bottlenecks, and troubleshoot issues like latency and errors. By capturing the complete journey of a request—from the initial user action to every backend interaction—distributed tracing enables quick diagnosis of slowdowns or failures, making it essential for managing complex, microservices-based systems

Key factors to consider when choosing a distributed tracing tool

Before we delve into the leading tools, let's explore the core criteria to remember when selecting the right distributed tracing solution for your infrastructure.

Feature set and functionality

A good distributed tracing tool should provide comprehensive visibility and troubleshooting capabilities, such as:

• Trace visualization: Flame graphs or waterfall views to analyze request flow and latency.
• Span-level details: Insights on individual service calls, queries, and custom metrics.
• Real-time monitoring and alerting: Notifications of high latency or error occurrences as they happen.
• Service maps: Visualization of service dependencies to analyze relationships between components.
• Tagging and filtering: The ability to segment and prioritize traces by tags, error status, or other metadata.

Scalability

In distributed systems, data volumes grow fast. Look for tools that can handle high-throughput environments, supporting scalability as your traffic and user base increase. Key features include tail-based sampling or selective trace retention to prioritize critical insights without overwhelming storage or analysis capabilities.

Integration with existing observability stack

Distributed tracing often complements logs, metrics, and application performance monitoring (APM). Look for tools that integrate smoothly with your observability stack—be it log management solutions, infrastructure monitoring, or APM platforms. Integrations with key DevOps tools like Slack, Jira, and GitHub can also simplify workflows, fostering faster collaboration across teams.

Open standards and flexibility

Open standards like OpenTelemetry and compatibility with other open-source tracing systems (such as Jaeger or Zipkin) offer flexibility and ensure you aren’t locked into a single vendor’s ecosystem. Tools that leverage open standards make switching providers or customizing your observability setup easier based on your needs.

User experience and support

A distributed tracing tool’s value depends on how easily your team can use it. Choose a solution with an intuitive UI, quick setup options, and easy integration into your workflow, allowing you to focus on troubleshooting rather than grappling with a complex interface. Strong support options—like responsive technical support, documentation, and community resources—are also vital for resolving any challenges you encounter.

By considering these factors, you can find a distributed tracing tool to help you gain a holistic view of your application's performance and optimize the user experience effectively. Now, let's explore the best distributed tracing tools available.

1. Better Stack

Better Stack kicks off our list as a user-friendly, all-in-one observability platform that combines simplicity with robust functionality. With its sleek interface, managing infrastructure and uptime feels seamless. While distributed tracing is still in development (exciting things are on the way!), Better Stack shines in centralizing logs and metrics, which it automatically parses into structured formats like JSON, making analysis smooth and quick. With ClickHouse SQL, complex queries are easy to run, and the visual query builder is there if SQL isn’t your thing.

To keep your web apps, APIs, cron tasks, and containers running smoothly, Better Stack’s monitoring tools are on it—pinging servers every 30 seconds from multiple global locations for reliable uptime monitoring. If any issues arise, detailed alerts via email, SMS, or phone come with enough context, like screenshots or error messages, to resolve problems quickly.

🌟 Key features

• Infrastructure and uptime monitoring
• Observability dashboards
• Status pages
• Incident management
• Log management

➕ Pros

• Pre-built dashboards make data analysis a breeze
• ClickHouse SQL query builder gives flexibility, even for non-SQL users
• Affordable pricing
• Real-time team collaboration during incidents with shadowing options
• Customizable status pages keep users in the loop
• Integrates smoothly with popular tools like Datadog, Slack, and AWS

➖ Cons

• No distributed tracing just yet—but it’s coming!

💲 Pricing

Better Stack makes it easy to get started with a generous free plan that includes up to 10 monitors, 3 GB of log retention, and a single status page. For more features, the pay-as-you-go plan starts at $29/month, with unlimited alerts via phone, SMS, and push notifications, along with 30 GB of log retention and advanced options like incident management and custom status pages. Enterprise plans offer AI-powered insights, custom dashboards, and premium support.

For all the details, check out the pricing page.

2. Dynatrace

Next on our list is Dynatrace, an observability platform known for its seamless distributed tracing capabilities, advanced infrastructure monitoring, and security insights. What sets Dynatrace apart is its PurePath technology, which automatically captures end-to-end traces for every transaction across your environments—whether traditional infrastructure, cloud-native, or serverless—without needing manual setup or code changes. PurePath’s automatic trace capture makes it effortless to monitor the full path of requests, enabling fast root-cause analysis and detailed insights.

Dynatrace’s distributed tracing is built to provide a comprehensive view of application performance. It collects metrics for individual transactions at the method and code levels, displaying every service dependency, database query, and request path. Additionally, its out-of-the-box integration with open-source standards like OpenTelemetry enhances flexibility by letting you use the tool alongside existing telemetry solutions.

In addition, Dynatrace includes Smartscape, which creates a dynamic, real-time map of all system dependencies, showing how applications, services, processes, and hosts interact. As systems change, Smartscape updates automatically, always giving you an accurate topological view .

🌟 Key features

• Distributed tracing with PurePath and Smartscape
• Infrastructure and application performance monitoring
• Cloud monitoring
• Log management and analytics
• Real user monitoring
• Synthetic monitoring
• Application security

➕ Pros

• Automatic trace collection and code-level visibility with no manual configuration
• Real-time Smartscape maps for continuous, interactive visualization of dependencies
• Davis AI provides real-time anomaly detection and root-cause insights
• Unified log, metric, and trace management through Grail technology
• Effortless deployment with a single host-level agent
• Comprehensive security alerts for code and infrastructure vulnerabilities

➖ Cons

• Can be expensive to use
• The extensive feature set can feel overwhelming

💲 Pricing

Dynatrace offers a flexible, pay-as-you-go model. Full-stack monitoring starts at $0.08 per hour for an 8 GiB host, covering applications, infrastructure, and microservices. Infrastructure monitoring is available at $0.04 per hour per host, and additional services like Kubernetes monitoring, log management, and application security can be added as needed. With transparent pricing, Dynatrace scales as your requirements grow, allowing you to pay only for what you need.

3. Datadog

Datadog is a comprehensive platform that combines application monitoring, infrastructure tracking, log management, and security in one unified view. Datadog shines with its distributed tracing, which delivers real-time, end-to-end visibility into applications, making it easy to pinpoint bottlenecks, resolve customer-reported issues, and maintain optimal stack performance.

Datadog’s distributed tracing allows you to trace every request across environments—from frontend to backend services—and real-time analysis through the trace explorer. Datadog’s live search and live analytics can investigate traces with any tag, helping pinpoint issues precisely as they happen.

Datadog also offers customizable trace retention and sampling, letting you retain only high-value traces to manage costs. Combined with OpenTelemetry support, real user monitoring, and synthetic monitoring, Datadog is ideal for proactively addressing performance issues and improving user experience.

🌟 Key features

• Distributed tracing
• Application performance monitoring
• Real user monitoring and synthetic monitoring
• Profiling and network monitoring
• Log management and security monitoring

➕ Pros

• Real-time trace querying via live search, allowing quick issue resolution for customer-reported problems
• Tail-based sampling and tag-based retention filters to optimize trace storage costs
• Unified metrics, traces, logs, and security insights in a single platform for simplified monitoring
• Dynamic request flow maps and dependency visualization for understanding service interactions
• Over 750 integrations, ensuring compatibility with your existing tools and platforms
• AI-driven Watchdog alerts and anomaly detection, offering proactive monitoring to catch potential issues early

➖ Cons

• Pricing can sometimes be unclear, and costs may rise quickly with increased usage.
• Overwhelming feature set if you only want distributed tracing.

💲 Pricing

Datadog’s free tier supports up to 5 hosts, with core tools and 1-day metric retention. The pro plan starts at $15 per host per month (billed annually), featuring over 400 integrations, 15-month metric retention, and container monitoring. Starting at $23 per host per month, the enterprise plan adds AI-driven alerts, live process monitoring, and enhanced trace management, scaling effortlessly with your needs.

4. New Relic

New Relic provides a powerful, unified platform for full-stack observability, built to manage all your telemetry data in one place. New Relic distributed tracing features offer end-to-end visibility into complex, distributed systems, making monitoring request flows and identifying performance bottlenecks across services straightforward. Its auto-instrumentation means setup is minimal—just update your agent, and you’re ready to go.

One of New Relic’s most advanced features, infinite tracing, applies tail-based sampling to filter and retain only the most crucial traces after collection, ensuring you always have relevant data without overwhelming your storage. This approach allows New Relic to process 100% of your trace data and select the most actionable insights for long-term analysis, helping you troubleshoot faster and prevent issues from impacting users. Additionally, New Relic integrates with OpenTelemetry and W3C Trace Context, providing flexibility to work seamlessly within hybrid environments and across various technologies.

New Relic’s trace explorer also allows for deep trace investigation, including real-time span grouping and error analysis, while its Logs-in-context feature correlates logs, traces, and metrics to streamline troubleshooting across distributed systems. Beyond tracing, New Relic supports a wide range of monitoring features for infrastructure, mobile, security, and more, providing an all-in-one observability solution.

🌟 Key features

• Infrastructure monitoring
• Application performance monitoring
• Log management
• Mobile monitoring
• Browser monitoring
• Security monitoring
• Synthetic monitoring
• Real user monitoring
• Digital experience monitoring

➕ Pros

• Simple, agent-based setup and auto-instrumentation, making tracing accessible without extensive configuration
• Infinite tracing’s tail-based sampling retains critical traces, enabling efficient data storage and analysis without losing valuable insights
• Robust OpenTelemetry and W3C Trace Context support for flexible data integration and interoperability
• Logs-in-context feature links logs with traces and metrics, helping resolve issues faster
• NRQL query language allows for custom dashboards and precise alerting tailored to your needs
• User-friendly platform accessible even with minimal DevOps experience

➖ Cons

• Per-user fees and data ingestion charges can increase costs, particularly for high-traffic environments

💲 Pricing

New Relic’s free tier includes 100 GB of data ingestion per month and full access for one user. Beyond this, pricing starts at $0.30 per GB on a pay-as-you-go basis. Pro and enterprise plans are available if you need advanced features, enhanced security, and priority support, making New Relic adaptable to various team sizes and requirements.

5. Splunk

Splunk is another observability platform that offers deep, real-time insights into application, network, and infrastructure performance. Its distributed tracing capability collects and visualizes spans from microservices, helping you pinpoint the source of latency and optimize performance.

Essential tools like the dynamic service map offer a clear view of service dependencies and latency across your system, enabling you to identify issues in real-time. The platform’s tag spotlight feature also enables granular analysis by highlighting latency or error trends for specific tags, giving you immediate insight into trace behavior throughout the system.

With Splunk’s network explorer, you can monitor the health of your cloud network, simplifying troubleshooting across application and network layers.

🌟 Key features

• Application performance monitoring
• Log management
• Synthetic API monitoring
• Infrastructure monitoring
• Real user monitoring
• Network explorer
• Browser monitoring
• Synthetic uptime monitoring
• Dynamic service maps with latency and dependency views

➕ Pros

• Dynamic service map provides a real-time overview of microservice dependencies, making it simple to diagnose issues and errors quickly
• OpenTelemetry integration supports a wide range of instrumentation across services, languages, and environments
• Consolidates logs, metrics, and traces for unified observability, enabling you to track down issues faster
• Customizable analytics with ingest actions and edge processor, allowing data to be filtered, masked, or routed as needed

➖ Cons

• Splunk's query language (SPL) has a learning curve, which can be challenging for new users
• Data manipulation capabilities, while robust, may not match the flexibility offered by specialized tools like Cribl

💲 Pricing

Splunk’s pricing is designed to fit a range of use cases. Infrastructure monitoring costs $15 per month per host, while full end-to-end observability costs $75. Splunk APM is priced at $55 per host, with real user monitoring available at $14 per 10,000 sessions. Additional options include workload-based, entity-based, and data ingestion-based pricing models and standard and premium plans for advanced needs.

6. Jaeger

Jaeger is an open-source distributed tracing platform developed by Uber to monitor and troubleshoot complex workflows within microservices architectures. Jaeger provides end-to-end visibility into requests as they traverse services, helping you identify bottlenecks, errors, and performance issues. With native support for OpenTracing and compatibility with Zipkin, Jaeger is highly versatile and integrates smoothly with various environments.

Jaeger’s features include adaptive sampling, which dynamically adjusts trace collection to optimize storage and performance, and topology graphs that offer insights into service dependencies and network interactions. The platform’s service architecture and deep dependency graphs provide detailed views of system dependencies, helping you understand both direct and transitive dependencies between services. Additionally, Jaeger’s cloud-native setup, multiple backend options, and observability tools ensure high scalability and flexibility.

🌟 Key features

• Distributed tracing with OpenTracing support
• Service performance monitoring (SPM)
• Adaptive sampling for dynamic trace management
• Cloud-native deployment options with Docker and Kubernetes support

➕ Pros

• Fully open-source and backed by a strong, active community
• Integrates easily with OpenTelemetry, Kubernetes, and Prometheus, offering flexible observability options
• Multiple storage backends like Elasticsearch, Cassandra, and ClickHouse provide versatility in data storage
• Advanced service dependency graphs make it easier to visualize complex interactions and dependencies in real-time
• Backwards compatibility with Zipkin

➖ Cons

• Initial setup and configuration can be challenging
• Lacks dedicated customer support and documentation depth compared to commercial alternatives

💲 Pricing

Jaeger is entirely free as an open-source tool, with no licensing costs. However, you should budget for hosting expenses, especially storage backends like Elasticsearch or Cassandra, and additional cloud resources for larger deployments.

7. Honeycomb

Honeycomb reimagines distributed tracing as the primary tool for debugging and observability, integrating logs, metrics, and traces into a single, cohesive workflow. While other platforms use traces as a complementary data point, Honeycomb places them at the core, using a unique "wide events" approach to capture rich, event-based insights into system performance and user interactions. This lets you detect and resolve issues faster by showing how users interact with their systems.

Honeycomb’s BubbleUp anomaly detection feature enhances tracing by automatically analyzing millions of requests, highlighting the exact attributes linked to bad user experiences. This, combined with support for OpenTelemetry, ensures you can gather telemetry data from various environments without overhauling your instrumentation. Honeycomb’s focus on deep trace analysis makes it a valuable tool for quickly identifying and addressing issues impacting user experience.

🌟 Key features

• Distributed tracing
• BubbleUp anomaly detection
• Service maps
• Service Level Objectives (SLOs)

➕ Pros

• Combines logs, metrics, and traces into one comprehensive workflow, reducing complexity
• BubbleUp automatically identifies anomalies by analyzing attributes across events, saving time on manual tracing
• OpenTelemetry support ensures vendor-agnostic flexibility for telemetry data collection
• Event-driven tracing offers rich, detailed insights, revealing precise patterns impacting user experience

➖ Cons

• The query builder UI can be hard to use

💲 Pricing

Honeycomb offers a free plan supporting up to 20 million monthly events. The pro plan begins at $130/month for 100 million events, with scaling options for up to 1.5 billion events in higher tiers. The pro plan includes features like SLOs and premium support, and Honeycomb also offers custom pricing for unique needs.

8. Logz.io

Logz.io is an observability platform that stands out for integrating popular open-source tools like Grafana, Prometheus, and Jaeger with a great user experience. Like the other tools, Logz.io’s distributed tracing offers complete visibility into microservices by letting you trace requests as they move through your architecture.

Its distributed tracing feature is designed to provide quick insights, surfacing potential bottlenecks, latency issues, and failures through clear, actionable metrics. Features like the service overview and service map allow you to visualize service dependencies and diagnose problems at both macro and micro levels.

Logz.io simplifies the setup process by auto-discovering services and enabling easy instrumentation, making it an accessible tool if you need a reliable, low-effort observability solution. Real-time alerts and deployment tracking further enhance its diagnostic power, alerting you to issues as they arise and showing the impact of recent deployments.

🌟 Key features

• Distributed tracing
• Service Overview
• Service Map
• Kubernetes 360
• OpenTelemetry integration
• Real-time alerting

➕ Pros

• OpenTelemetry integration makes it easy to set up instrumentation and enables vendor-neutral observability.
• Compatible with popular open-source tools, offering familiarity and flexibility to open-source enthusiasts.
• Service maps and dependency visualizations help you understand and troubleshoot complex system interactions.
• Real-time alerting and deployment tracking assist in monitoring new changes and quickly identifying critical issues.
• Comprehensive support for multi-cloud and multi-region deployments, allowing flexibility across different environments.

➖ Cons

• Logz.io’s multiple integrated tools can create a learning curve for beginners.

💲 Pricing

Logz.io offers a flexible pricing model based on data volume and service type, with a 14-day free trial. For log management, costs start at $0.90 per GB ingested. Distributed tracing and metrics monitoring begin at around $29 per month, with enterprise plans available for more extensive needs, including custom alerting and data retention options.

9. Elastic Cloud

Elastic Cloud is a comprehensive managed service created by the team behind the Elastic Stack, which includes Elasticsearch, Kibana, Beats, and Logstash. Elastic Cloud unifies logs, metrics, traces, and profiling into one platform, providing powerful visibility into every part of your application’s performance and health.

Elastic Cloud’s distributed tracing is tailored for modern microservices architectures, tracking every request through each service and backend. This feature makes it simple to spot bottlenecks, analyze latency, and identify errors across complex systems. Elastic Cloud supports the W3C Trace Context standard, which ensures propagation across services, making every trace accessible across different teams and environments. Its OpenTelemetry integration simplifies setup, allowing you to easily collect and visualize trace data and understand application flow through its robust APM UI. Paired with real user monitoring, distributed tracing gives deep insights into user interactions and highlights system behavior affecting the user experience.

Elastic Cloud also offers advanced visualization and search capabilities with Elastic Stack, allowing you to correlate metrics, logs, and traces for a complete view of your system’s health. This consolidated approach to observability makes it a versatile choice if you seek a unified platform.

🌟 Key features

• Distributed tracing
  
• Infrastructure monitoring
  
• Synthetic monitoring
  
• Cross-cluster search
  
• Data security
  
• OpenTelemetry and Jaeger integration
  
• Real user monitoring
  
• Span compression and transaction sampling
  
• Service maps and dependency analysis

➕ Pros

• Supports W3C Trace Context standard and OpenTelemetry for easy instrumentation across services
• Elastic’s intuitive UI allows for easy visualization of traces and rapid debugging
• Built on Elasticsearch and Kibana, with advanced search and data analysis capabilities
• Integrates with other tools like Jaeger and Zipkin, supported by a strong community
• Combines backend traces with real user monitoring to provide a complete view of user experience
• You can self-host most of the Elastic Stack tools

➖ Cons

• Initial setup may be complex
  
• Costs can escalate with higher data usage, especially for larger deployments

💲 Pricing

Elastic Cloud’s pricing is flexible, with the standard plan starting at $95 per month, covering core Elastic Stack tools, basic security, and Kibana. The gold plan at $109 per month includes reporting and alerting, while the platinum plan at $125 per month adds advanced security and 24/7 support. For enterprise-level features, plans start at $175 monthly, offering extended data retention, advanced machine learning, and premium support for complex requirements.

10. Coralogix

Another distributed tracing tool is Coralogix, a full observability platform that allows you to centralize and analyze logs, metrics, and traces. With a focus on distributed tracing, Coralogix enables you to track the flow of requests across microservices architectures, uncovering valuable insights into performance, bottlenecks, and errors. The platform’s tracing feature visualizes traces and spans, making it easy to understand how requests move through your system and pinpoint potential issues.

Coralogix allows seamless linkage between traces and logs for efficient troubleshooting and offers multiple visualization modes, including Gantt charts and flame views, for exploring trace data in depth. Its integration with OpenTelemetry makes setup straightforward, while advanced filtering and query tools help you quickly search through traces and spans to isolate issues.

🌟 Key features

• Real user monitoring
  
• Application performance monitoring
  
• Log and metrics management
  
• Advanced filtering and querying for traces and spans
  
• Synthetic monitoring
  
• Alerting
  

➕ Pros

• Integrates with open-source tools such as PromQL, Lucene, and Grafana
  
• Efficient filtering and query options make trace analysis smoother
  
• Reduces costs with first-pass analysis in Kafka Streams
  
• Enables querying of S3 archives without rehydration or reindexing, providing fast access to historical data
  

➖ Cons

• Documentation may occasionally lack completeness or updates
  

💲 Pricing

Coralogix uses a flexible, usage-based pricing model for maximum control over data costs and management.

• Frequent searches: $1.15 per GB
  
• Monitoring: $0.50 per GB
  
• Compliance storage: $0.17 per GB
  
• Metrics and tracing: Priced based on data ingestion
  
• TCO Optimizer: Tool to help estimate and optimize costs
  
• Free trial: Available for getting started
  
• Custom plans: Tailored options for larger or specialized needs can be arranged with the sales team

11. Bugsnag

Last on our list is Bugsnag, an observability platform focused on helping you monitor and improve application stability across web, mobile, and server environments. Its distributed tracing capabilities provide in-depth insights into the performance of microservices, enabling you to trace requests as they flow through different services, detect bottlenecks, and diagnose issues across a distributed system.

The platform’s OpenTelemetry integration allows you to capture, customize, and correlate telemetry data from every part of their tech stack. Bugsnag’s distributed tracing doesn’t just capture spans and logs side-by-side; it visualizes them intuitively, making it easy to identify service dependencies and spot issues without bouncing between contexts.

Bugsnag also supports remote sampling for cost-efficiency, letting you scale distributed tracing efforts without soaring costs. Bugsnag’s UI simplifies trace filtering and search, allowing you to move swiftly from high-level views to granular problem areas.

🌟 Key features

• Error monitoring
  
• Real user monitoring
  
• Distributed tracing
  
• Customizable trace search, filtering, and segmentation
  
• App stability management
  

➕ Pros

• Cost-effective distributed tracing with remote sampling
  
• Stability scores for quick app health overview
  
• Correlates logs and traces side-by-side for efficient troubleshooting
  

➖ Cons

• Documentation may be difficult to navigate
  

💲 Pricing

Bugsnag offers a free plan with 7.5K events and 1M monthly spans, ideal for small projects or trial use. For more extensive needs, paid plans start at $20/month, covering 50,000 events and 1M spans monthly. The preferred plan, offering advanced features like custom notifications and error prioritization, starts at $33/month. Enterprise pricing is available for large-scale deployments.

Final thoughts

This article explored distributed tracing tools with unique features and strengths in troubleshooting across complex architectures. We hope this article helps you choose the right solution for your project. If you're still undecided, consider taking advantage of the free trials or starter plans offered by many of these platforms. Testing them firsthand is a great way to assess which one aligns best with your workflow, requirements, and goals. This should provide some relief from the overwhelming task of choosing the right tool.

Happy tracing!

Article by

Stanley Ulili

Stanley is a freelance web developer and researcher from Malawi. He loves learning new things and writing about them to understand and solidify concepts. He hopes that by sharing his experience, others can learn something from them too!

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