Making Application Monitoring Simple and Powerful
How it Works
Optimizing and making your applications more reliable is simpler than ever. Just include the Yokaranda open source library or use a small footprint API to upload time series data points and KPIs.
The cloud-based platform correlates millions of time series within a single instance and across instances and proactively alerts upon deviation from normal application behavior.
Yokaranda provides a clear indication of the components that cause the abnormal behavior, allowing operation teams to quickly focus on and fix the problem.
Monitor your Application Performance
Analyze millions of time series to identify deviation from normal behaviour and avoid incorrect decisions
Prioritize Most Critical Issues
Focus on the immediate issues that require a fix
Drill Down to the Root Cause of the Problem
Identify the common parameters in the time series that lead to biased decisions
Proactively Identify and Fix Issues before Users are Impacted
Highlight application instances that share the same parameters as those that made wrong decisions and advise on required fix
Multi Series Analysis
Scalability to millions
As a Data Scientist I work in a dynamic environment, I need to focus on creation of models, I need to track their behavior, and be able to experiment with the latest versions of state of art libraries. By using Yokaranda I can seamlessly track the behavior of my models, detect anomalies, identify impacts of changing libraries versions, and compare the behavior of different models.
As a team we develop complex AI solutions, due to the nature of AI, the behavior of deployed solutions evolves over time, so creating simple thresholds is not enough to verify that everything is working as planned. Often, we develop ¨lightweight¨ solutions, especially when they are used in IoT and consumer devices, we need a solution with minimal footprint to track them. Yokaranda is a lifesaver for us, using it poses no restriction in the way we develop our solutions, no heavy SDKs, no methodology restrictions. Yokaranda has a minimal footprint, it provides open source libraries, so no obscure side effects, we are in control. Yokaranda continues to learn our solutions evolving behavior even after they are deployed, providing us trustable alerts and insights when most needed.
As a startup we need to concentrate on our core innovation, we need to seamlessly integrate tools that will permit us to detect changes in the behavior of the solutions we develop, we need to be able to compare the behavior of different releases, we need to identify unexpected behaviors. Integrating Yokaranda is straightforward, it permits us to focus on our work, we do not need to invest resources in creating monitoring tools, we can easily identify when something is not working as expected.
As an enterprise we deploy large numbers of miscellaneous AI and ML based solutions, that scales from tens to millions. We need visibility, we need to be able to track all our solutions regardless of the technology used to create them, to verify their proper behavior, to track changes in the operational environment of each instance, and to get insights based on holistic analysis. Yokaranda helps us be more productive in developing enterprise ready AI/ML applications. It allows us to analyze each deployment individually and the whole population together, to have the needed visibility and insights, to be proactive and to detect problematic trends and issues before users are impacted. It helps us streamline development, reduce R&D costs and improve customer satisfaction.
Gadi Solotorevsky, Ph.D., Yokaranda Founder and CEO – “I believe that AI/ML will soon become a key technology impacting both our personal lives and business activities. The potential of AI/ML is huge and will become a core technology across all vertical markets, including Consumer Electronics, Healthcare, FinTech, Telecom, Manufacturing and Automotive. The common challenge of large enterprises and fast-growing start-ups is to maximize the benefits of the AI/ML technology and minimize the business risks associated with it. I believe that Yokaranda is best positioned to help the developer community achieve this goal and become successful”. Gadi Solotorevsky, holds a Ph.D. in Artificial Intelligence from Ben-Gurion University, is a Distinguished Fellow of the TM Forum and the former CTO of cVidya, a market leader in Revenue Assurance and Fraud Management, acquired by Amdocs (NASDAQ: DOX). Dr. Solotorevsky is the inventor of several patents in the areas of AI/ML, Big Data and User Anonymity.
Application Performance Management (APM) solutions have become, during the past two decades, a mandatory component in business and mission critical applications, ensuring the imperatives of application performance and end-user experience KPIs.
While legacy applications rely on fixed algorithms and performance baselines, AI/ML applications behaviour and base lines are dynamic and complex. The challenge is not only to define dynamic baselines, but to identify if the change in application behaviour is a result of a change in application usage or a flaw in one of its components that requires a fix.
Yokaranda patent pending platform is revolutionizing the AI/ML market with a modern and holistic APM solution that meets the dynamic nature and behaviour of AI/ML applications. By correlating deviations in application behaviour across thousands of instances, Yokaranda proactively alerts on performance issues and identifies the root cause of the problem, before it impacts the business.