Full Stack Observability

Monitoring tells you when something is wrong, while observability enables you to understand why. Tuuring provides a holistic view on the full workload stack by collecting, normalizing and analyzing wide-spread data and translate this into actionable and meaningful performance information.

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Our customers

Testimonials

Read why our customers chose the Tuuring platform to optimize their workload performance.

After realizing that the aim for optimal business integration would result in a massive increase in transaction data, CZ chose the Tuuring platform as their end-to-end performance analytics solution.

CZ group

Tuuring provided the answer to the question of whether end-user experience would remain sufficient after combining and integrating two very large financial applications.

Nationale Nederlanden

Upgrading a mainstream ERP application with a sensitive performance baseline could lead to delays and possible degradation of end-user experience. The Tuuring platform provided the performance baseline and much more insights during and after the go-live.

LUMC

Observability

The platform collects essential performance data from a combination of sources for applications, workspaces and (cloud) infrastructures. This data is consolidated into the Tuuring data lake which enables artificial intelligence baselines and anomaly detection for an entire chain rather than a part of it enabling full-stack observability

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1

Combine performance data from applications, workspaces and (cloud) infrastructures

The platform collects essential performance data from a combination of sources for applications, workspaces and (cloud) infrastructures. This data is consolidated into the Tuuring data lake which enables artificial intelligence baselines and anomaly detection for an entire chain rather than a part of it.
2

Breaches silos by collecting data from a wide spectrum of performance data sources

The data collected focus on anything that is performance-related, such as: user, application, workspace and infrastructure platforms and solutions. This includes generic and proprietary APM solutions, business-related data such as actual transactions and orders to enable actual business impact analysis and optimization
3

Create AI-based performance baselines for historical, real-time and predictive analysis

The integrated machine learning engine creates performance baselines from collected datasets to create historical overviews, real-time trends and future performance predictions. Analyzed data and results are visualized in out-of-the-box and custom-made dashboards. These dashboards can be published and broadcasted to all types of displays.
4

Optimize the performance of complex application chains

Based on changes in metrics, baselines and analysis alerts can be generated to be shown within the software but also sent to third-party ITSM tools, supporting faster times to resolve issues and improve root cause analysis.

How we collect data

Data collection is done through our dedicated and proprietary connectors that ensure robust and consistent data flow. The connectors are developed to use supported data extraction mechanisms available for the intended solution. The connectors are maintained to stay up to date with the latest changes by the vendor, assuring data collection and integrity with future releases. We collect data from almost every monitoring environment.