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Logz.io Launches App 360, Revolutionizing Application Performance Monitoring

Logz.io Launches App 360, Revolutionizing Application Performance Monitoring

App 360 is an easy-to-implement, cost-effective alternative to traditional APM that helps engineers surface issues sooner and debug their services faster.

Logz.io provider of Open 360, the industry’s most easy-to-use, cost-efficient observability platform  announced the launch of App 360, a new, observability-based approach to Application Performance Management (APM). App 360, the newest addition to the Logz.io Open 360 observability platform, delivers all the functionality needed for core APM use cases in an observability solution that is simpler to use and less expensive than traditional APM solutions yet provides full visibility into application health and performance.

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APM is broadly defined as tools and systems to monitor and manage the performance and availability in software applications.

“App 360 takes everything that’s wrong with traditional APM and flips it on its head,” said Asaf Yigal, co-founder and CTO of Logz.io. “Whereas traditional APM is heavy, hard to implement, expensive, shackled by vendor lock-in and slow to bring business value, App 360 is exactly the opposite. App 360 is tailor-made for the microservices and Kubernetes era and offers a high-performance observability approach that is easy to set up, easy to use, and less costly than traditional APM solutions.”

App 360 is a centralized interface for visualizing and investigating application performance. Built for distributed microservices architectures running on Kubernetes and other modern environments, App 360 combines logs, metrics and traces from applications, infrastructure and Kubernetes into a single picture. App 360 enables stakeholders to see the right signals and correlate all the relevant information to truly understand their environment, from individual applications all the way down to the CPU level. With App 360, customers can avoid siloed telemetry and quickly achieve full application observability so they can answer difficult questions about the current state of their environments — at a fraction of the cost of other platforms.

“Engineers can now get APM capabilities without APM headaches through a modern, observability-centric technology that doesn’t take forever to implement and gives engineers just what they need to surface and resolve issues rapidly,” Yigal continued.

*Key Benefits of App 360: Essential APM Made Easy and Cost-Effective*
One of App 360’s major benefits is that it is exceptionally easy to use. Logz.io’s OpenTelemetry-based agent enables automatic service discovery, one-click application instrumentation, and data collection for logs, metrics and traces. From there, the most critical application telemetry data and insights are automatically highlighted within App 360 — making the current state of service performance obvious.

App 360 helps engineers surface issues sooner and debug their services faster. Logz.io’s Service Map and Service List provide a bird’s eye view of performance across microservices architectures. Telemetry data is automatically tagged and organized by microservices so when a problem occurs, it is immediately obvious which services are affected. From there, App 360 provides straightforward paths to investigate problems by correlating the relevant logs, metrics and traces needed to isolate the root cause of the issue.

Another key differentiator from traditional approaches is that every element of the Open 360 platform is optimized for maximum data and cost efficiency. From the platform’s unique Data Optimization Hub to multi-tiered storage, including Cold Tier on Amazon S3, organizations choosing Open 360 with new App 360 capabilities will appreciate significant savings over legacy APMs.

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*Key Components of App 360*
App 360 combines numerous Open 360 capabilities to deliver an innovative approach to APM, including:

  • Service Overview: Unifies the essential telemetry data from your infrastructure and applications in a single data analysis interface — all while requiring minimal configuration. Service Overview makes it easy to spot high-level performance trends across your microservices and get fast insights into the current state of your microservices performance in a single place.
  • Distributed Tracing: While Service Overview helps you isolate application performance issues across your entire infrastructure and all applications, Distributed Tracing helps you drill down into individual application transaction flows to diagnose the root cause of issues such as bottlenecks and failures.
  • Service Map: This updated visualization of topology highlights the data flow, dependencies and critical performance metrics across your microservices architecture. Service Map makes it easy to gather critical troubleshooting context as you investigate production issues.
  • Service List: The Service list dashboard centralizes all of your running services, allowing you quickly to detect if and when issues occur. You can use the dashboard to investigate the different services, operations and logs inside each one.
  • Easy Connect: Go from zero to full observability in minutes. With Easy Connect, service discovery, application instrumentation and data collection is entirely automated. After deploying the Telemetry Collector — Logz.io’s OpenTelemetry-based agent — on a Kubernetes cluster, Easy Connect will discover every service in your cluster and provide the option to instrument each one.
  • Deployments: This new capability can view and track the deployments of a user’s service within Open 360 dashboards. Users gain visibility into when services were deployed, which versions are running and any associated deployment notes to better troubleshoot production incidents.
  • Data Optimization Hub: This telemetry data pipeline capability provides a single place to identify, remove or manipulate unneeded observability data to easily reduce costs. Many Logz.io customers remove as much as 50% of their data, saving significantly on observability costs while also limiting data complexity.

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