Helios
| Autor: | Terry Kim, Steve Suh, Sinduja Ramanujam, Lev Novik, Tomas Talius, Rahul Potharaju, Vidip Acharya, Andrew Fogarty, Raghu Ramakrishnan, Apoorve Dave, Wentao Wu |
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| Rok vydání: | 2020 |
| Předmět: |
Database
Computer science business.industry media_common.quotation_subject Search engine indexing General Engineering Hyperscale 020206 networking & telecommunications Cloud computing 02 engineering and technology HeliOS STREAMS computer.software_genre Data model Index (publishing) Debugging 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Use case business computer media_common |
| Zdroj: | Proceedings of the VLDB Endowment. 13:3231-3244 |
| ISSN: | 2150-8097 |
| DOI: | 10.14778/3415478.3415547 |
| Popis: | Helios is a distributed, highly-scalable system used at Microsoft for flexible ingestion, indexing, and aggregation of large streams of real-time data that is designed to plug into relational engines. The system collects close to a quadrillion events indexing approximately 16 trillion search keys per day from hundreds of thousands of machines across tens of data centers around the world. Helios use cases within Microsoft include debugging/diagnostics in both public and government clouds, workload characterization, cluster health monitoring, deriving business insights and performing impact analysis of incidents in other large-scale systems such as Azure Data Lake and Cosmos. Helios also serves as a reference blueprint for other large-scale systems within Microsoft. We present the simple data model behind Helios, which offers great flexibility and control over costs, and enables the system to asynchronously index massive streams of data. We also present our experiences in building and operating Helios over the last five years at Microsoft. |
| Databáze: | OpenAIRE |
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