SAN MATEO, Calif., September 17, 2019 – SignalFx, the leader in real-time monitoring and observability for cloud infrastructure and microservices, today announced a series of platform updates to SignalFx Microservices APM™ that provide AI-driven problem detection and alerting on trace latency and error metrics. The new enhancements enable DevOps and site reliability engineering (SRE) teams to use SignalFx’s Microservices APM to not only troubleshoot, but also monitor microservices through distributed tracing in a single solution. Combined with Splunk’s market-leading log analytics, these capabilities further enhance the industry’s first enterprise-grade end-to-end observability platform.
With the continued adoption of cloud-native technologies such as containers and microservices, applications are becoming increasingly complex to monitor. Distributed tracing has become a critical part of modern monitoring and observability strategies, helping DevOps teams understand how requests are being handled end-to-end by an application’s set of microservices. SignalFx Microservices APM is the industry’s only Application Performance Monitoring (APM) solution that metricizes traces and spans, and applies streaming analytics to those metrics. With our NoSample™ tail-based approach that observes and analyzes 100% of all transactions, alerts from SignalFx are more accurate than any other APM solution in the market.
Mark43, a cloud-based public safety software company providing solutions for dispatch, records, evidence, and analytics, relies on SignalFx Microservices APM for real-time monitoring and proactive alerting. “With SignalFx Microservices APM, we can see all the traces and spans for an API call and fix underperforming APIs, all of which helps us improve performance and maintain high availability of our platform,” said Kevin Heins, DevOps Technical Lead at Mark43. “Performance improvements that previously took a team of five almost an hour can now be done by one engineer in a matter of minutes. SignalFx helps us ensure that public safety officers who depend on Mark43 to perform their critical work can do so without any service disruption or degradation. This quality of real-time performance is critical to protecting real lives.”
The latest release of SignalFx Microservices APM includes:
- Real-Time, AI-Driven Application Alerts — Leveraging the industry-leading capabilities of SignalFx’s NoSample tail-based sampling, trace and span metricization, and SignalFlow® streaming analytics engine, Microservices APM now supports real-time alerts based on AI-driven problem detection on trace latency and error rate metrics. These self-configuring alerts learn and trigger on behavior changes, and remove the guesswork and back-and-forth associated with manual configuration. This helps DevOps and SRE teams detect sudden spikes and historical anomalies in services and endpoints, significantly reducing mean time to detect (MTTD) and mean time to resolution (MTTR).
- Enhanced Service Maps — Dynamic service maps have been enhanced with automatic detection of inferred services, such as databases, message queues, caches, and other third-party web services. This provides a clearer and more accurate picture of service dependencies by making otherwise untraceable services visible. Combined with existing service performance and alert status details in the service map, users can easily visualize, correlate, and pinpoint potential issues in complex microservices environments.
- Database Query Metrics — SignalFx Microservices APM now has the ability with the addition of database query metrics to provide insight into the performance of databases and their impact on end-to-end transactions. This gives DevOps and SRE teams the ability to monitor, alert, and more quickly investigate database-related issues.
- New Auto-Instrumentation Options — Go and Kotlin are now supported with auto-instrumentation, a process that automatically identifies frameworks and libraries, and instruments them to capture trace spans. Along with existing auto-instrumentation support for Java, Python, Ruby, and Node.js, as well as open-standards support for OpenTracing, OpenCensus, Jaeger, and Zipkin, SignalFx is one of the leaders in offering a wide selection of instrumentation options and helping our customers avoid vendor lock-in.
“The value of distributed tracing extends beyond simple troubleshooting and root cause analysis when incidents occur,” said Arijit Mukherji, CTO, SignalFx. “Traditional APM tools are not suited for modern application environments. Since our Microservices APM supports open instrumentation, observes every single transaction, and leverages advanced statistics and algorithms for analytics, we are able to offer the industry’s most unique monitoring and alerting capabilities. No other APM solution can do this.”
Read more at the SignalFx blog: SignalFx Microservices APM Now Delivers Unified, AI-Driven Application Monitoring and Troubleshooting.
SignalFx, the only real-time cloud monitoring platform for infrastructure, microservices, and applications, collects and analyzes metrics and traces across every component in your cloud environment. Built on a massively scalable streaming architecture, SignalFx applies advanced analytics and data-science-directed troubleshooting to let operators find the root cause of issues in seconds. SignalFx is trusted by leading enterprises across most every industry sector. SignalFx is backed by Andreessen Horowitz, Charles River Ventures, General Catalyst, and Tiger Global Management.
In August 2019, SignalFx announced a definitive agreement to be acquired by Splunk. The combination of SignalFx and Splunk will give IT and developers a data platform that allows them to monitor and observe data in real-time, no matter the infrastructure or data volume, helping them cut costs, boost revenue, and improve the customer experience.
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