Latest product release provides out-of-the-box content for powerful cluster computing
SAN MATEO, Calif. – September 14, 2017 – SignalFx, a leader in real-time operational intelligence for data-driven DevOps, today announced its integration with Apache Spark. Spark has become the defacto standard engine for big data processing and advanced analytics. As Databricks is founded by the team that created Spark, many enterprises use Databricks’ cloud-based unified analytics platform to accelerate innovation by unifying their data science and engineering teams with the line of business. SignalFx now adds real-time visibility across infrastructure, clusters, and applications, which is necessary for optimizing performance in today’s rapidly changing world.
As large-scale data processing has moved into a new age of sophistication, Spark provides enterprises with the ability to process massive data in real-time. However, the ephemeral nature of Spark applications means that operating, verifying, and optimizing applications over time are becoming increasingly complex. Distributed systems further exacerbate these challenges as numerous development and operations teams submitting Spark applications need to understand where and how patterns and trends indicate an emerging issue.
“Many Databricks enterprise customers have built large-scale streaming and machine learning applications where performance and scale is essential,” said Michael Hoff, SVP of Business Development and Partners at Databricks. “We’re pleased that SignalFx’s real-time monitoring for Databricks’ Spark-based platform can now provide real-time visibility into these high-performance applications.”
SignalFx provides the most comprehensive, real-time view across Spark clusters and applications, which helps to maximize the performance of analytics and data science at scale. The SignalFx integration with Spark provides monitoring at every level and is complemented by several new built-in dashboards, including cluster overview, master and worker processes, and running jobs. Teams can proactively address performance issues before latency or outages that affect end users.
“Spark and Databricks’ Spark-based platform have become the defacto standards for data science and engineering at many of our enterprise customers.” said Mark Cranney, Chief Commercial Officer of SignalFx. “Our latest integration enables Spark and Databricks admins, data scientists, developers, and operators to gain the real-time visibility required to innovate at high speed.”
More information regarding this release is available on the SignalFx website.
SignalFx is a leader in real-time operational intelligence for data-driven DevOps. The service discovers and collects metrics across every component in the cloud, replacing traditional point tools and providing real-time visibility into today’s dynamic environments. Leveraging the massively scalable SignalFx platform, the SaaS service is optimized for container and microservices based architectures and provides powerful visualization, proactive alerting, and collaborative triage capabilities across organizations of all sizes. SignalFx is used by Fortune 500 enterprises across financial services, apparel, industrials, telecommunications, media, and by web-scale players like Yelp, Hubspot, Acquia, and Kayak. SignalFx is venture-funded by Andreessen Horowitz and Charles River Ventures.