Wavefront has added distributed tracing support, making it the first and only platform for microservices observability that combines a “3-dimensional” view into metrics, histograms, and traces at cloud-scale, over 1,000,000 data points per second. The combined view of metrics, histograms, and traces is essential to maintaining production microservices, and a leapfrog over the blind spots of legacy APM tools. Starting today, SREs, developers, and DevOps teams can enroll in our public beta.
Get a Fully OpenTracing/OpenCensus Compliant Solution with Lightweight Agentless Instrumentation
Key functional differentiators of Wavefront’s Distributed Tracing include the following:
- Single platform unifying metrics, histograms, and traces, eliminates context switching that reduces MTTR for microservices
- Cloud-scale tracing solution, capable of handling millions of metrics, histograms, and traces per second needed to support high-growth, production cloud applications
- Built-in support for all popular frameworks and languages provides instant visibility into the health of your microservices
- Combined lightweight agentless instrumentation, a single open source library for collecting metrics, histogram, and traces. Unlike the bulky agents of traditional APM vendors, the Wavefront Observability SDK has negligible production impact.
- Full OpenTracing/OpenCensus Compliance. Wavefront provides a fully OpenTracing/OpenCensus compliant solution with a drop-in replacement for Zipkin and Jaeger for instant scalability and enhanced retention.
Wavefront Distributed Tracing differentiators
Traditional Monitoring vs. Modern Observability
Developers and engineering organizations are moving away from old, monolithic application architectures and adopting modern microservices-based distributed application architectures. Traditional monitoring tools built for monoliths, fail to provide the required visibility into these modern architectures. Here are some of the main differentiators of a modern observability platform when compared to traditional monitoring tools such as APM tools.
Traditional monitoring versus modern observability
Wavefront Makes Microservices Observability Easy: With Out-of-the-box Metrics, Histograms and Traces Visibility
One of the common concerns of implementing distributed tracing is that it requires high-level of instrumentation added to the production codebase, and the tools used to search and visualize trace data can be complex to set up, hard to maintain and challenging to use productively. Wavefront makes it easy for SREs and developers to monitor modern microservices-based applications – with the built-in support for key health metrics and distributed tracing for common languages and frameworks. With minimal code change, developers can now visualize, monitor and analyze key health performance metrics and distributed traces of Java, Python and .Net applications built on common frameworks such as Dropwizard and gRPC.
Wavefront dashboard showing key health metrics and TopK charts of an application
And speaking of easy, our pricing is very transparent and easy to understand. Everything including metrics, histograms, and traces is measured in points per second, making it easier for customers to order, consume and track their usage. For any questions on pricing, please contact our sales team.
Reduce Microservices Troubleshooting Time with Traces Context and Spans Detail
While troubleshooting microservices, once you have the overall context from key health metrics and Top-K charts you then need to drill into details regarding where the transaction is failing and visualize erroneous or extended transaction flows. In Wavefront, you can easily search for traces containing the selected service or API and quickly view which ones had errors or longer response time. Additionally, you can filter the trace search to show traces containing spans from a given cluster and shard. This ability to get both key health metrics and trace details in one platform enables DevOps teams, including developers and SREs, to troubleshoot issues quickly and lower MTTR.
Wavefront summary trace view showing traces with errors
Optimize Microservices Performance with Visibility into Bottleneck Spans
In a microservices based architecture, each request might be fulfilled by multiple microservices. The inability to visualize performance bottlenecks in each iteration of a request across different services makes it impossible for developers to pinpoint services that are performing sub-optimally and understand the corresponding call context. Using Wavefront, you can click into the filtered traces in the traces summary view (shown above) and view the corresponding span details (as shown below). The critical path in each trace is highlighted across different services, so you can easily narrow down the services that are taking the longest time. Furthermore, span tags associated with each span can be directly viewed in the traces detailed view. Custom span tags can also be easily added and viewed in the traces detailed view.
Traces and spans detailed view with critical path
Summary
Wavefront has added support for distributed tracing to its cloud-native monitoring and analytics platform, making it the first and only platform that combines metrics, histograms, and traces at cloud-scale, over 1,000,000 data points per second. With built-in health metrics, Top-K charts, traces summary view, and corresponding span details, teams across SREs, development, and DevOps can easily tame their modern distributed systems, resulting in faster MTTR and better customer experience.
Don’t get left behind in a blind spot with traditional APM tools, enroll here to get access to Wavefront Distributed Tracing today. For more product details, please checkout the demo and refer to the documentation.
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The post Wavefront Introduces 3D Microservices Observability™: The First Cloud-Scale Platform to Unify Metrics, Histograms and Tracing appeared first on Wavefront by VMware.
