Operations | Monitoring | ITSM | DevOps | Cloud

Agentic AI is coming to financial services. Elastic provides the data foundation and tools to make it work. In a recent talk at Stanford University, Jamie Dimon, chairman and CEO of JPMorganChase, addressed the firm’s use of AI and ended with mentioning that agentic AI was the next frontier of AI at the firm, inferring it wasn’t ready to be deployed yet. Let’s break down why that may be the case and what the financial services industry can do to become more comfortable with agentic AI.

There are many vendors, Honeycomb included, where actions on the application can emit a web request that goes to another service for coordination or tracking purposes. Many vendors have pre-built integrations, but some have a fallback that says “Custom Webhook” or similar. If you’re looking to create a full picture of your request flow, you would want these other services to show up in your trace waterfall.

This is the fourth blog in our Azure Monitoring series, and this time, we’re digging into cost efficiency. Azure makes it easy to scale, but just as easy to overspend. Idle VMs, forgotten disks, and silent data transfer fees add up fast. The result is budget overruns that catch teams off guard and force reactive cuts. This blog breaks down the Azure metrics that actually help you reduce waste, improve visibility, and keep cloud spend aligned with business priorities. Missed our earlier posts?

This is the ninth post in our Azure Monitoring series, and it’s all about taking control of your cloud costs without losing visibility. We’ll unpack why Azure bills tend to spiral, where native tools fall short, and what it really takes to cut spend while keeping performance on point. You’ll walk away with practical ways to spot waste early, act fast, and stay ahead of surprise invoices. Missed the earlier posts? You can catch up anytime.