Distributed Tracing

Troubleshoot and analyze performance issues with LOGIQ.AI’s OpenTelemetry and Jaeger-compatible Distributed Tracing implementation.

More insights. More affordable. 
Less hassle.


Dealing with instrumentation, collecting, and tracing issues ?



Distributed tracing can be complex to set up and maintain, especially in large and distributed systems.


Collecting and transmitting trace data can add significant overhead to application performance.


The amount of trace data that can be generated in a large and distributed system can be overwhelming and difficult to scale.


Data privacy

Storing and transmitting trace data can raise concerns about data privacy and security.

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Data Analysis

Analyzing and making sense of large amounts of trace data can be challenging, requiring specialized tools and expertise.

Data Correlation

Correlating trace data across different services and systems can be difficult, especially when dealing with different data formats and structures.


Distributed Tracing Can Help.
See How.

Correlate and analyze data from different parts of your system

View timings, errors, logs, and flows on one screen.

Save time by having all the relevant data in one place.

Trace the flow of a request to identify the root cause of an issue.

Troubleshoot your distributed applications quickly and easily.


Controls In Your Hands

Compatible with OpenTelemetry and Jaeger

LOGIQ.AI’s distributed tracing implementation has built-in support for OpenTelemetry and Jaeger protocols. Use either a Jaeger agent or an OpenTelemetry collector to stream logs, metrics, and traces at scale. Our SpanStore is built on InstaStore, LOGIQ.AI’s indexed object storage built for observability.

Pinpoint failures across your distributed applications

Traces can help see the flow of data in your distributed application. Speed up root causes by viewing timings, errors, logs, and flows in one single screen. Find performance bottlenecks!

Switch from Traces to Logs

LOGIQ.AI integrates Logs and Traces into a seamless experience. Switch over from Traces and go to Logs to view all logs for a given trace identifier. Even download them as CSV and JSON. Troubleshooting and integrating with your workflows could not get easier than this.

….. And Back, And More!

Our deep integration between Logs, Metrics, and Traces means you and navigate to a trace from a log you search. Not only that, go from Metric to a Log to a Trace.


Tracing refers to the process of tracking the flow of a request or transaction as it moves through an organization’s systems and applications. This involves tracking things like request latency, error rates, and the dependencies between different services.

Tracing transactions between distributed services can help developers understand the flow of data between different parts of their systems and identify bottlenecks or issues that may be impacting performance. However, Tracing transactions between distributed services can be challenging, as it requires tracking the flow of a request or transaction through multiple systems and components. This can involve collecting and analyzing data from various sources, such as log files, network packets, and application metrics.

In order to effectively trace transactions between distributed services, it is important to have a comprehensive and centralized view of an organization’s systems and applications. Our observability platform provides this view, allowing for a deeper understanding of your systems and making informed decisions about how to optimize their operations.

Distributed tracing is a technique used to profile and debug distributed systems. A distributed system is a system where components are distributed across multiple machines. Distributed tracing allows you to trace the flow of a request as it goes through the different components of a distributed system. OpenTelemetry and Jaeger are two of the most popular distributed tracing tools.

Distributed systems are systems that are made up of multiple components or services that communicate with each other over a network. These systems can be complex and difficult to understand, especially when things go wrong. Tracing can help to provide visibility into how these systems are functioning and identify potential issues.

Distributed tracing tracks the flow of a request as it travels through various components of a distributed system. It is particularly useful for identifying bottlenecks and debugging issues that may arise in such systems.

LOGIQ.AI ingests traces and logs from the OpenTelemetry collector and Jaeger agent. It implements scalable streaming and indexing of spans, traces and logs directly to any object storage. Users can search and visualize spans, traces, and logs using a simple intuitive built-in UI. Our UI borrows several key aspects from the Jaeger UI project while integrating it seamlessly with LOGIQ.AI’s infinitely scalable InstaStore backend built on top of object storage.

Finding Traces

In the LOGIQ.AI UI, navigate to Traces under Explore in the navigational menu.

In the LOGIQ.AI UI, navigate to Traces under Explore in the navigational menu.

You can also click Analyze and get the full span and logs for the trace for download.

Logiq offers to trace capabilities that allow organizations to track the flow of transactions between distributed services. utilizes distributed tracing to provide a comprehensive view of the entire lifecycle of a request. This helps users to identify and fix problems more efficiently, as they can see exactly where the request is being slowed down or failing.


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