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Join the Boston Elastic User Group and Gigamon on Tuesday, September 29 at The Foundry for an evening exploring two timely technical topics: building long-term memory for AI agents with Elastic and using Elastic and Gigamon to identify bottlenecks and accelerate root-cause analysis.

Connect with fellow engineers and practitioners while gaining practical insights into AI, observability, and troubleshooting. Pizza and refreshments will be provided. πŸ•

⚑️ Interested in giving a talk? ⚑️
Are you interested presenting on your Elastic use case? We welcome 5-10 minute lightning talks, 45-minute deep dives, and everything in between. If you're interested, please send an email to meetups@elastic.co

πŸ“… Date and Time:
Tuesday, September 29th, from 5:30-7:30 pm EDT

πŸ“Location:
The Foundary - 101 Rogers St, Cambridge, MA 02142
We will be in Shop 6

πŸ“Agenda:

  • 5:30 pm: Doors open; say hi and eat some food.
  • 6:00 pm: Building long-term agent memory in Elastic - Susan Chang (Principal Data Scientist at Elastic)
  • 6:30 pm: Finding the Bottleneck: Root-Cause Analysis with Elastic and Gigamon - (Gigamon)
  • 7:30 pm: Event ends

πŸ’­ Talk Abstracts:
Finding the Bottleneck: Root-Cause Analysis with Elastic and Gigamon - (Gigamon)
Modern applications fail across complex service chains, but observability data alone may not reveal where latency begins. In this technical session, Gigamon and Elastic show how network-derived intelligence and application metadata can enrich Elastic Observability. Learn to map client-to-app dependencies, separate network, application, HTTP, and DNS latency, and isolate degraded service edges across hybrid cloud and Kubernetes. Leave with a practical framework for faster, evidence-based root-cause analysis and clearer ownership across network, platform, SRE, and application teams.

Building long-term agent memory in Elastic - Susan Chang (Principal Data Scientist at Elastic)
Details coming soon!

Related topics

Events in Cambridge, MA
Elasticsearch
Kubernetes
Elastic Stack
Observability

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