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Latest News Releases InfluxData Launches New “Metrics First” Approach to Log Analysis Enhancing Observability and Enabling Faster Problem Resolution

InfluxData Launches New “Metrics First” Approach to Log Analysis Enhancing Observability and Enabling Faster Problem Resolution

By: Deborah Schalm on June 14, 2018 1 Comment

Company Delivers High-Speed Ingestion and Parsing via Syslog and New Log Visualization to Speed Correlation of Application, Infrastructure and Business Metrics with Log Data

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LONDON (InfluxDays London 2018) — June 14, 2018 — InfluxData, the modern Open Source Platform built specifically for metrics, events and other time series data that empowers developers to build next-generation monitoring, analytics and IoT applications, today at InfluxDays London 2018 released new capabilities targeted at speeding the visualization and analysis of structured application and system events captured via log files. Now by correlating business, server and application metrics with structured logs, InfluxData provides faster and more precise problem investigation and root-cause analysis capabilities.

AWS Builder Community Hub

This release expands the functionality of the InfluxData platform with support for high-speed parsing and ingestion using the syslog protocol, custom log parsing, and pre-built log visualization components. InfluxData believes in a “metrics first” approach that provides developers and operators with the means to easily ingest, correlate, and visualize all time series data, including data from infrastructure metrics (applications, databases, systems, containers), business metrics and now log events.

Each log message represents an event in time and the same metadata that accompanies metrics can be used to pinpoint the valuable contextual information contained within those files. By starting with metrics and their associated metadata, operators and developers can rapidly understand where and how to interrogate the large volumes of event data contained within logs without performing expensive search queries. This reduces much of the guesswork and prior knowledge required to sift through log data that is typically present when using logs as the initial and primary source of anomaly detection.

“Providing powerful visualizations and integrations allowing the correlation of business, system and infrastructure metrics with log data has been something our hundreds of thousands of community members have been asking for,” said Paul Dix, InfluxData Founder and CTO. “We are excited to release these capabilities in the platform and see this solution as a more natural and complete way to approach log data, ensuring faster time to awesome for developers building next-generation monitoring and real-time analytics applications.”

With InfluxData, users can uniquely capture metadata at the collection point, allowing the developer to map elements across systems and supplement additional information when and where required, providing consistency and richness to the logs being transmitted via the syslog protocol. It provides an improved workflow for log visualization within the same environment where they have constructed metrics dashboards, which allows a developer to easily analyze the captured log events for a specific time interval and narrow data down by the important metadata elements, such as host, application, subsystem, and more. Starting the problem investigation at the specific time interval and with a specific set of metadata highlighted by captured metrics reduces process noise and allows developers to identify the root cause faster.

Read more about the new solution details here: https://www.influxdata.com/blog/influxdata-log-release/

InfluxData’s InfluxDB Database is the overwhelming leader among Time Series Database management systems, according to DB-Engines’ latest results published earlier this quarter. Its unique features enable customers to quickly build:

  • Monitoring, alerting and notification applications supporting their DevOps initiatives
  • IoT applications supporting millions of events per second, providing new business value around predictive maintenance and real-time alerting and control
  • Real-time analytics applications that are focused on streaming data and anomaly detection

InfluxData has rapidly built its developer and customer base across industries – including manufacturing, financial services, energy, and telecommunications – by delivering the fastest growing Open Source Platform that enables customers to derive better business insights, data-driven real-time actions, and a consolidated single view of their entire infrastructure – from applications to microservices, and from systems to sensors. More than 420 customers, including Cisco Systems, Coupa Software, IBM, Houghton Mifflin Harcourt, Nordstrom, and Tesla, have selected InfluxData as their modern data platform for metrics and events. InfluxData is pioneering the shift to time series in a modern metrics and events platform, and is making it possible for customers to become data-driven and take on digital transformation initiatives.

Availability

InfluxData’s new logging functionality is available today for download and is available as part of the Chronograf, InfluxDB and Telegraf projects. For more information, see:

https://www.influxdata.com/blog/influxdata-log-release/.

About InfluxData

InfluxData, the creator of InfluxDB, delivers a modern Open Source Platform built from the ground up for analyzing metrics and events (time series data) for DevOps and IoT applications. Whether the data comes from humans, sensors, or machines, InfluxData empowers developers to build next-generation monitoring, analytics, and IoT applications faster, easier, and to scale delivering real business value quickly. Based in San Francisco, InfluxData’s more than 420 customers include Cisco, eBay, IBM and Siemens. Visit https://www.influxdata.com/. Twitter: @influxdb.

###

InfluxData, InfluxCloud and InfluxDB are all trademarked by InfluxData. All other trademarks are the property of their respective owners.

 

Filed Under: Latest News Releases Tagged With: Influxdata

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