Since 2003, we’ve re-architected our hosting systems four times to meet the needs of our rapidly growing systems and member base. At the same time, we’ve gone from less than a hundred services in 2009 to thousands of services and hundreds of thousands of service instances today. However, we achieved that scale at the price of wasted hardware and people hours. It...
Search results for "autoalerts"
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- Topics:
- infrastructure,
- LPS
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Co-authors: Krishnan Raman and Joey Salacup Editor's note: This blog has been updated. Monitoring big data pipelines often equates to waiting for a long-running batch job to complete and observing the status of the execution. The status can result in “Failed” or “Successful” or even “Incomplete.” From there, it’s the team’s job to understand the impact and...
- Topics:
- infrastructure,
- Gobblin,
- tools,
- Kafka,
- Data
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Couchbase is a highly scalable, distributed data store that plays a critical role in LinkedIn’s caching systems. Couchbase was first adopted at LinkedIn in 2012, and it now handles over 10 million queries per second with over 200 clusters in our production, staging, and corporate environments. Couchbase’s replication mechanisms and high performance have enabled...
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To maintain the high network availability needed to serve all LinkedIn applications, we need to monitor and analyse both network...
- Topics:
- Network Performance,
- monitoring,
- InFlow
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Coauthor: Tim Crofts The LinkedIn site has been available to the public over IPv6 since 2014, and our employees have been able to...
- Topics:
- data center,
- IPv6,
- Network Performance
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At LinkedIn, we use a log-centric system called Apache Kafka to move tons of data around. If you're not familiar with Kafka, you can...