Observability is a suite of diagnostic tools that give account administrators granular visibility into how data flows through the mParticle platform: from the sources where your data originates, through mParticle’s various internal systems, and finally to your connected third-party outputs.
\nWhether you want to monitor the ingestion of batches containing dozens of events or you need to track down a modification to a single user profile, Observability provides the ability to configure and browse detailed traces of all of your data flows so you can troubleshoot issues with confidence.
\nAs an example, consider you have an ecommerce business and you use the mParticle SDK to ingest real-time website traffic into mParticle. Now imagine that you began to notice intermittent dips in traffic volume at certain times of day – you would want to identify the cause. Are the dips in traffic due to changes in user behavior, or are they just the result of a poorly configured filter or another processing anomaly?
\nBy analyzing traces of your data as it flows through mParticle during the impacted timeframes, you can look for any errors or warnings triggered during processing that could explain a bottleneck or anomaly causing your traffic dips.
\nObservability can be used to help detect and troubleshoot a range of issues, including:
\nThe foundation of Observability is tracing. As data flows through mParticle, it is ingested, processed, and routed to various services or forwarders in discrete steps.
\nA trace in mParticle’s Observability is a detailed record that connects all of these steps on through a single timeline. Think of a trace as a trip report for your data: it shows where it came from, where it went, and any stops it made along the way.
\nTracing is provided by default for all data flowing in your development environment. For production data tracing, Observability lets you configure what data is traced through customizable Trace Configurations. When Observability is used in conjunction with tools like System Alerts and Live Stream, it can help you diagnose and troubleshoot issues with your data pipelines.
\nAll data sent through your mParticle development environment is traced by default, and can be viewed on the Trace Activity page. If you want to trace production data, you can do so by creating a custom trace configuration to gain specific insights.
\nIf a data flow has an active trace configuration, a call made to one of the supported mParticle services initiates a unique trace. Each trace is identified by a Trace ID, which you can use to find and view specific details about the data’s journey in the Observability tool.
\nTraces record information such as which input the data originated from, which outputs the data will be sent to after processing, any rules or filters applied to the data, any user MPID’s related to the trace, the types of events included in the data, error codes, and any data plans that will be used to process the data.
\nIn addition to these details, the trace details page presents a graphic display of the following stages, known as “spans”, that your data happen to flow through:
\nObservability provides end-to-end tracing for all event data, starting from it’s first ingested through via an mParticle platform SDK or server-to-server inputs, to when data is forwarded to any of the real-time event destinations.
\nSpecifically, tracing is available for data processed by the following APIs:
\nYou can also use Observability to trace data ingested from Warehouse Sync pipelines.
\nBy default, data in your development environment is traced automatically. You don’t need to configure anything, and you can immediately begin reviewing trace details for your development data from Live Stream or the Trace Activity page in Observability. To trace your production data, you must first create a trace configuration that specifies which data you want traced.
\nObservability does not currently support tracing for data sent to mParticle’s bulk forwarding event outputs or audience pipelines.
\n\nYou can trace up to 10% of your annual batch volume sent through your production environment at no extra charge.
\nIf you exceed this limit:
\nTraces for development and production data are accessible for up to 14 days.
\nTo learn more about the information provided in a trace and how to create a trace configuration for your production data, continue reading the Observability User Guide.
\nObservability provides detailed information about how data is ingested, processed, and forwarded through mParticle’s CDP. To make the best use of Observability while keeping your cost low, we recommend the following strategies:
\n100% of your development data is traced automatically, at no extra cost to you. This makes Observability a powerful testing and troubleshooting tool that you should use when setting up a new mParticle configuration.
\nBy sending test data through your development environment, you can gain insights into how your platform or feed inputs are functioning; whether your data plans, rules, and filters are behaving as expected; and whether the data you expect to see in your output is successfully being forwarded.
\nEven after deploying a well tested mParticle configuration to process your production data, it’s still possible to encounter issues.
\nmParticle recommends creating a tracing configuration to monitor new configurations with a high sample rate (up to 100%) but for a short period of time (up to one week). This allows you to detect issues quickly.
\nRemember that you can trace up to 10% of your annual batch volume at no extra charge, but if you reach this limit you will be unable to create new trace configurations. If you do reach this limit, you can contact your mParticle account representative to discuss the unique needs of your business and what additional tracing options may be available.
\nOnce a new mParticle configuration has been successfully processing production data for a period of about a week, you can transition to a long-term monitoring approach.
\nmParticle recommends creating long-term tracing configurations (more than one week) with a low sample rate (under 10%). This allows you to still detect and troubleshoot anomalies that may occur in your existing pipelines without causing you to reach your tracing usage limit. If you do begin to approach your limit, your mParticle account representative will contact you.
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