Built on top of rich distributed tracing data, metrics, and logs, the platform provides a unified view of telemetry data making it the quickest way to know what’s changed in system and service health
SAN FRANCISCO, April 2, 2020 — Lightstep, the leading provider of observability software for organizations adopting microservices and serverless, today announced the release of its best-in-class observability solution to help developers better understand the health of systems and services. This includes integrating new metrics capabilities into their platform, enabling developers to have a one-stop shop for all their observability needs. New analysis features provide developers with the fastest and most effective way to investigate errors, understand service health issues, and predict the impact of new deployments.
As companies’ reliance on performant and reliable software increases, developers are facing the brunt of the burden. Every second of downtime can be detrimental to an organization’s bottom line, and the need for developers to adopt tools that can mitigate these lapses is greater than ever.
The next evolution of Lightstep’s distributed tracing tool is an observability platform that provides automatic and rich analysis. Lightstep’s powerful capabilities help developers develop, deploy, and debug new service releases, regardless of the deployment methodology used (for example, canaries, blue/green deploys). Developers will then be able to identify and resolve the cause of performance degradations faster than any other tool on the market. The error and latency analysis feature simplifies the investigation of a service’s errors and latency by quickly highlighting the source of the problem and how it propagates through the call stack. It also helps developers understand what may have caused the error with a list of data-driven hypotheses.
And with new capabilities around runtime metrics, the solution accurately correlates metrics with problems in service performance. By making runtime metrics accessible with zero additional configuration and providing side-by-side visibility of performance metrics, developers are able to quickly identify if problems in their runtime (e.g. increased garbage collection, CPU, or memory) are causing service degradations.
“At our core, Lightstep is a company of developers, so we know first-hand the stress placed on DevOps teams to execute seamless deployments every time, and how it is only continuing to grow as tech stacks get more complex,” said Daniel Spoonhower, CTO, Lightstep. “With our new observability solution, developers can analyze errors in real time, at any point in the deployment, and have all the tools and data they need in one unified view – that integrate effortlessly into their existing workflows.”
With current market offerings, data that developers need quick access to is fragmented across many tools, making it difficult to swiftly understand what has changed in the performance of their services. Lightstep’s platform gives users a single place to answer real observability problems in real-time. These new updates include:
- Minimize the guessing: see insights based on metrics, traces, and logs all in one place, and at the right time
- Regression analysis: automatically see what is contributing the most to your errors, latency, and throughput
- Deployment monitoring: automatically see how different versions of your service are performing, and quickly diagnose regressions
- Seamless onboarding: guided onboarding across almost any language in order to enable immediate insights
“The Service Health feature, with regression analysis built-in, is exactly how I, as a performance engineer, would approach a regression. Out of the box, we can pinpoint not only when and where a regression first occurred, but also what caused the regression. All we had to do was show Service Health to the service owner for them to understand performance, distilled into three simple charts on a single tab. Unbeatable,” said Ian Thompson, Senior Software Engineer, Skyscanner.
About Lightstep
Lightstep enables teams to detect and resolve regressions quickly, regardless of system scale or complexity. We integrate seamlessly into daily workflows, whether you are proactively optimizing performance or investigating a root cause so you can quickly get back to building features.
