Transitioning to a New Backend Pipeline and Data Availability

M-Lab data is collected from distributed experiments hosted on servers all over the world, processed in a pipeline, and published for free in both raw and parsed (structured) formats. The back end processing component for this has served us well for many years, but it’s been showing its age recently. As M-Lab collects an increasing amount of data thanks to new partnerships, we have been concerned that it will not be as reliable.

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Traffic Microbursts and their Effect on Internet Measurement

In August 2015, M-Lab was notified of potential degradation of site performance by a measurement partner based on discrepancies compared to results for their own servers. After a full investigation these patterns were found to have been caused by the unique confluence of several specific conditions. Interim remediation measures were taken in early October 2015, and the resolution of the degradation was confirmed by the partner and others. Due to these administrative actions, the episode, which we are calling the “switch discard issue,” has not affected testing conducted in the United States (the region impacted by this problem) since October 11, 2015, and thus measurements after this period are not affected by the incident. M-Lab has also conducted an evaluation of data collected during the time period in which the issue occurred, and has taken steps to remove affected measurements from its dataset. This incident will not affect use of its dataset, past or present, as a result.

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Making it Easier to Use M-Lab Data

In January, M-Lab launched a beta test of new BigQuery tables for M-Lab data. Today, M-Lab is pleased to announce that the beta test was successful. The new, faster-performing tables will be M-Lab’s new standard BigQuery tables.

Before we move on to specifics, when we say faster performing, we mean a lot faster. As in, certain queries that used to take over 2 hours now complete in 8 seconds. That means that playing with the data just became a lot more fun.

To help users dig in to this data as quickly and seamlessly as possible, M-Lab has consolidated all of its data documentation and updated it to show how to take advantage of the new tables.

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Announcing improved performance for M-Lab BigQuery data

Today, M-Lab is happy to announce the public beta of new M-Lab BigQuery tables. These tables provide substantially improved performance and reduce the difficulty of writing BigQuery SQL.

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ISP Interconnection and its Impact on Consumer Internet Performance: Introducing A New M-Lab Consortium Technical Report

Sample graph from this report. We are happy to announce the release of a long-term collaborative research effort using M-Lab’s data to understand how interconnection impacts end-user performance. The report, ISP Interconnection and its Impact on Consumer Internet Performance examines years of network measurement data from across the United States to determine the effects of network interconnection on the Internet performance of customers subscribing to specific access ISPs. Alongside this report, we are also pleased to release the Internet Observatory – a dynamic data visualization tool that will allow consumers, policymakers, and researchers to better understand the impact of ISP relationships on their own Internet access and performance. The Internet Observatory will be updated regularly, allowing future monitoring and comparison against past performance.

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