The most valuable software and applications in the modern world aren’t just those that offer speed, automation, and efficiency. Instead, the most successful and beneficial are the ones that provide visibility, and security across applications. As modern software infrastructure becomes more complex and with changing business requirements, observability that offers some degree of control is precious. Distributed tracing helps companies to tackle the challenges of observability by tracking requests as they move from frontend to backend and all the way inbetween. In this blog post, we will discuss the top 5 distributed tracing startups to watch in 2022.
What is Distributed tracing?
Tracing is a fundamental step in software engineering to gather information about an application’s behavior. But traditional tracing isn’t efficient when troubleshooting applications built on a distributed architecture. Since microservices scale independently, multiple iterations of a single service running across different locations, servers, and environments is standard. However, multiple iterations lead to a complex web through which a request must travel. Companies can’t track these requests with traditional techniques that are designed for a single service application.
Unlike traditional techniques, Distributed tracing offers an excellent solution to track requests through each service or module and provide an end-to-end narrative account of that request. Analysts, SREs, developers, and others can observe each function iteration, enabling them to monitor performance by seeing which instance of that function is causing the app to slow down or fail and how to resolve it.
Distributed Tracing Startups to Watch in 2022
1. Chronosphere
Chronosphere is a cloud-native monitoring platform that raised $200 million, a Series C, increasing the company’s value to over $1 billion. It was co-founded by two former Uber engineers — Rob Skillington and Martin Mao in 2020. The company offers a three-step solution: Know, Triage, and Understand — the three phases of observability. Chronosphere’s multi-million dollar Annual Recurring Revenue grew by 9x so far in 2021. Chronosphere comes with a wide range of interesting features such as Query Builder, SysAdmin mode, Alert monitors, and Comparison mode.
It started supporting root cause capabilities and distributed tracing within the past year. With distributed tracing capabilities, customers can safely scale to any environment, make data-backed decisions, and get a contextual understanding of metrics and traces. Chronosphere has also partnered with PagerDuty and GKE Autopilot to strengthen the alert system and triage, respectively.
2. Lumigo
Lumigo offers end-to-end debugging and observability through automated distributed tracing. Customers can easily navigate containerized and serverless environments with lighting speed. They have a no-code distributed tracing that automatically correlates metrics, logs, and traces into a visual map. Customers can also easily remove data silos to reduce downtime, improve user experience, and cut cloud costs at the moment of activation. Other features of Lumigo are visual debugging, dynamic dashboards and widgets, and custom-built, serverless smart alerts.
Start with a 14-day free trial and move to a Free, Standard, Plus, or Custom plan. Each plan has unlimited users, but the number of traces differs — 150K, 1M, and 5M for Free, Standard, and Plus plans.
3. Arize
Arize is the first and only full-stack model performance monitoring and ML observability platform. The AI company recently introduced the next-generation ML observability platform at the Arize:Observe 2022 summit. It solves troubleshooting bottlenecks and pain points experienced by thousands of ML engineers. The next-generation Arize platform can detect issues as they emerge, troubleshoot the cause, and improve overall performance.
4. SigNoz
SigNoz is an open-source performance monitoring tool that helps businesses to monitor applications and troubleshoot problems. It uses distributed tracing to observe and gain visibility into a software stack. With SigNoz, you can monitor application metrics such as requests per second, latency, error rates, etc. You can also track user requests across services and set alerts on metrics. SigNoz also helps to find the root cause of the concern by going to the exact traces causing the problem. SigNoz uses OpenTelemetry, an open-source observability solution, to collect data. Therefore, SigNoz also supports all the frameworks supported by OpenTelemetry.
5. CloudAEye
CloudAEye is an AI-Powered Observability solution that offers distributed tracing solution for microservices-based architecture. It provides ML and AI-based intelligent operations management for Cloud services with an objective to improve time-to-market. The ML based incident management solution provides frictionless management of an incident, contextual awareness, and root-cause analysis. This reduces MTTD (mean time to detect) and MTTR (mean time to repair).
The company offers various other services such as Anomaly Detection, Automated Root-cause Analysis, Proactive Monitoring, Automated Context, and Centralized Logging. CloudAEye helps to improve end-user satisfaction and application uptime. It also reduced noise and alert fatigue and offers real-time actionable insights.
Conclusion
A distributed tracing tool helps organizations receive continuous insights on the overall health of their deployed software and applications. In the modern cloud-native world, maintaining your application’s or software’s observability is essential to have a competitive edge. These were some of the top observability startups that offer distributed tracing. Do keep an eye on them as activity in the distributed tracing space heats up.
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