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INFLUXDB 3 PRODUCTS

Self-Managed

InfluxDB 3 Enterprise NEW
InfluxDB 3 Core (OSS) NEW

Fully Managed

InfluxDB Cloud Serverless
InfluxDB Cloud Dedicated

Telegraf

Telegraf Enterprise NEW
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icon Platform Overview
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icon Explore All Integrations
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Network & Infrastructure Monitoring
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Machine Learning & AI
Modern Data Historian

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Manufacturing & IIoT
Aerospace
Energy & Utilities
Financial Services
Telecommunications
Explore All

Siemens Energy Scales Global BESS Operations

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Application Performance Monitoring (APM) Using the InfluxDB Time Series Platform

Due to the complexity of application environments, root-cause identification has become like searching for a needle in a haystack. Frequent and fragmented deployments, as well as distributed and third-party integrated infrastructure, make a perfect “breeding ground” for issues. Therefore, a solution that goes beyond resource monitoring is needed.

IT and DevOps need a tool with which to detect - in real time - undesired shifts in application performance, systems and network metrics. It is no longer enough to simply point out performance problems like latency, high error rates or no response. It is also necessary to pinpoint where, what or who is causing performance degradation. Also needed is knowing how to expedite remediation and work towards achieving automation of an appropriate response.

This tech paper covers the underlying rationale and practical aspects of application performance monitoring. We discuss APM value propositions (including a broadened scope for application environment monitoring, root cause analysis, and integration with AI/ML frameworks); functionalities (including monitoring user experience, observation of workflow, and alerting); and implementation methods (including synthetic transaction monitoring, real user monitoring, and distributed tracing monitoring). We also discuss the use of open-source APM tools, including performing APM with InfluxDB open source time series platform. Register to download this paper and read it in full.

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