Traceability in distributed systems

Trace requests across system boundaries. Correlate and visualize long running business processes.

Trasier is a Data as a Service platform that gives a quick insight into messages exchanged by software services across teams, projects or even companies. It can be used in Software development, bug-, performance-, business- analysis and integration testing.

Gain unknown insights into your data

Data extraction and ingestion for BigData processing and machine learning.Ingest and learn from large amounts of data at high volume.

Error detection

Error detection based on the message type or machine learning algorithms.


We’re all generating huge amounts of data every day. Whether we’re driving our car, ordering pizza or even when carrying our mobile while walking the dog. The challenge of processing and storing has been addressed many times and is widely paraphrased with the term BigData. Often these systems are pieced together by many components communicating with each other. The trend of decoupling applications into smaller microservices is still ongoing, as it gets cheaper and easier to run serverless architectures in the Cloud. However, this flexibility comes with difficult error analysis and traceability in distributed systems. How do we monitor which system was involved when processing a specific request and how long did it take to respond? How do we figure out which service is causing a request to fail and why? How do we know which microservice caused the slow processing of a request?

Microservices typically process multiple transactions per seconds. In case of an error, getting to a root cause of a problem often means digging through thousands of log entries. This is time consuming, inefficient and often we do not find enough information needed for the analysis.

Trasier gives you an inside into your service architecture, message flow and the exchanged data in the order of cause. It tells you what service and what host was involved in serving a request and how long did it take. It automatically recognizes anomalies and errors so that you don't have to waste your time in the analysis.

Build to scale

Injest large amount of data at high volume


Data transmitted and stored encrypted

Easy integration

Java and Go clients available

Open Tracing

Open Tracing compatibility


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