Operations | Monitoring | ITSM | DevOps | Cloud

Starting the journey for Elasticsearch monitoring is crucial to get the right visibility and transparency over its behavior. Elasticsearch is the most used search and analytics engine. It provides both scalability and redundancy to provide a high-availability search. As of 2023, more than sixty thousand companies of all sizes and backgrounds are using it as their search solution to track a diverse range of data, like analytics, logging, or business information.

This article will focus on the metrics side of Azure Functions and features offered by the Azure Portal and then talk about the value of Serverless360. Then about the product that provides beyond the primary feature set in the Azure Portal, which will help you improve the day-to-day operations of your Azure solution. There are many different ways you can manage and operate Azure Functions and features like Application Insights which can also help you with Azure Functions.

Event-driven architecture is an efficient and effective way to process random, high-volume events in software. Real-time monitoring of event-driven system architecture has become increasingly important as more and more applications and services move toward this architecture.

With the arrival of Grafana 9.5, we’re excited to introduce Grafana support bundles — a tool to help debug your Grafana instance faster and more easily. Support bundles provide a simple way to gather and share information about your Grafana instance, and this feature is available across all tiers in Grafana Cloud as well as in Grafana OSS and Grafana Enterprise.

BugSplat's new auto-grouping feature is a powerful way to automatically group crashes in a way that's meaningful to your team. Normally, crashes are grouped by the top of the call stack. But sometimes this grouping isn't ideal. For example, if the top of your call stack is KERNELBASE!RaiseException (a Windows OS function) you'd probably prefer the crashes were grouped by a different stack frame. That's what BugSplat's auto-grouping feature does!

Elasticsearch is used for a wide variety of data types — one of these is metrics. With the introduction of Metricbeat many years ago and later our APM Agents, the metric use case has become more popular. Over the years, Elasticsearch has made many improvements on how to handle things like metrics aggregations and sparse documents. At the same time, TSVB visualizations were introduced to make visualizing metrics easier.

Users are complaining about slow load times and you’ve thrown logs, traces, and metrics — heck, the entire kitchen sink of performance monitoring — at your application, but you still can’t figure out the source of the bottleneck. Maybe you missed adding instrumentation to something in the critical path, or you’re simply testing in an environment vastly different from the ones your users are experiencing in production.