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<i>Department of Computer Sciences Seminar</i></div>
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<b>Raja Sambasivan </b></div>
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<b>Assistant Professor, Computer Science</b></div>
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<b>Tufts University</b></div>
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<b>Wednesday, November 8<span><sup>th</sup> </span></b></div>
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<b><span>11:30am - 12:30pm </span></b></div>
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<b><span>In-Person: John Crerar Library 390</span></b></div>
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and efficiently observing microservices</b></span></div>
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<span style="font-family: "Segoe UI", "Segoe UI Web (West European)", "Segoe UI", -apple-system, BlinkMacSystemFont, Roboto, "Helvetica Neue", sans-serif; font-size: 15px;"><b>Abstract: </b></span></div>
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<div style="font-weight: 400; margin: 0px; color: rgb(0, 0, 0);">The microservices architecture is a commonly used paradigm for building distributed applications. Many small software services, each providing different functionalities, interact to provide high-level
application behaviors. This paradigm has many benefits: it enables fine-grained scaling, it facilitates’ development teams’ independence, and it aligns with the breakdown of Moore’s law, which incentivizes smaller compute units. Unfortunately, it also has
one well-known drawback—understandability or observability. End-to-end behaviors in microservices applications are very challenging to reason about because they result from myriad interactions within and among services. Though there is opportunity for research
to help, a lack of real-world data about microservice deployments depresses opportunities to provide value. </div>
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<div style="font-weight: 400; margin: 0px; color: rgb(0, 0, 0);">In this talk, I will discuss our efforts to characterize a large cloud providers’ microservice deployment. I will also discuss one key challenge our studies revealed—the tension between the desire
for deep observability and immense instrumentation exhaust—and our efforts to address it via a framework that automatically chooses which logging points should be enabled at any time to provide visibility into performance problems. </div>
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<div style="margin: 0px;"><font style="color: rgb(0, 0, 0);"><span style="margin: 0px;"><b>Bio: </b></span></font></div>
<div style="font-weight: 400; margin: 0px;" class="elementToProof">Raja is the Ankur and Mari Sahu Assistant Professor of Computer Science at Tufts University, where he works on debugging and management techniques for cloud-based applications. In prior lives,
he helped worked with the Massachusetts Open Cloud Project, studied routing-protocol evolvability, and worked on (what is now called) distributed tracing.<br>
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Tracey Walton</div>
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Business Assistant </div>
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University of Chicago</div>
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5730 South Ellis JCL 212</div>
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Tywalton615@uchicago.edu</div>
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(773)702-0723</div>
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