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Products

Self-Managed InfluxDB

InfluxDB 3 Enterprise
InfluxDB 3 Core (OSS)

Fully Managed InfluxDB

InfluxDB Cloud Serverless
InfluxDB Cloud Dedicated
Amazon Timestream for InfluxDB

Telegraf

Telegraf Enterprise NEW
Telegraf (OSS)

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Platform Overview
Client Libraries
Explore All Integrations
Telegraf configurations

New Release

Managing Telegraf at scale just got easier

Telegraf Enterprise is now generally available

Learn More
Use Cases

Use Cases

Network & Infrastructure Monitoring
IoT Analytics & Predictive Maintenance
Machine Learning & AI
Satellite Telemetry Monitoring
Battery Energy Storage Systems
Modern Data Historian

Industries

Manufacturing & IIoT
Aerospace
Energy & Utilities
Financial Services
Telecommunications

LeoLabs secures Low Earth Orbit with InfluxDB to track 25,000+ objects. See how

Seadrill saved $55M in asset lifecycle costs by shifting to condition-based maintenance with InfluxDB. See how

Eutelsat OneWeb enabled real-time telemetry across 600+ LEO satellites with 1M points ingested per second. See how

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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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