Meeseeks-Final-Edit

Efec8ffb04df3ef79fc75bf37bd9a2c1?s=47 Gaurav
October 29, 2019

 Meeseeks-Final-Edit

Efec8ffb04df3ef79fc75bf37bd9a2c1?s=128

Gaurav

October 29, 2019
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    • Graph of services across Flipkart. • Understands dependencies between

    services. • Enable org-wide scenarios like BCP • Rich querying on service topologies. • Intelligent cluster-recognition.
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    • Enrichment of the data • Builds real-time service topology

    of Flipkart network. • Intelligent data-store cluster recognition. • Store in a graph DB.
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    • Identify the services running on VMs using port scan.

    • Cluster data-stores on the basis of services running on VMs and network topology. • We cluster Hadoop, MySql, ElasticSearch, Redis, Aerospike, MongoDB and many more.
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    Meeseeks Overlays • “Overlays” sprinkle additional information on the base

    service-graph layer. • Overlay definition - a set of possible annotations over the graph nodes and edges • Meeseeks provides APIs to ◦ Create / register custom overlay ◦ Annotate the base Meeseeks graph with custom overlay data ◦ Query based on the annotations
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    Meeseeks Overlays’ Example • Data DR overlay ◦ Trigger an

    event to the Backup/DR infrastructure ◦ Validate schedules configured for recovery point objective etc. • BCP overlay ◦ Tag services with a certain “criticality level” and a recovery time objective for the same in case of a disaster ◦ Tag edges as “essential”, “optional” etc. ◦ Detect anomalies.
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    Iftop • Couldn’t capture all the data packets, hence loss

    of information. • Compute resource consumption on each baremetal. Conntrack • Once deployed, no easy way to rollback without impacting the host machine. • Compute and memory resource consumption on baremetal.