Capture Opportunities and Mitigate Risk with Greymatter Sense-making Models

Generative AI has recently captured the popular imagination with free tools like ChatGPT, Google Bard, and Microsoft Bing Chat among others. While an ongoing debate over the pros and cons of these tools continues, this hardly diminishes their effectiveness in dramatically increasing the productivity of “human in the loop” processes. At Greymatter.io we’ve seized on the technology to help organizations that are struggling to navigate complex cloud, cluster, and hybrid environments. Here’s why and how:

Why organizations need more than signals

The deployment and management of distributed applications architectures is highly complex, requiring a high level of skill that is both difficult to acquire and expensive to maintain. Typically, measurement and observation across multiple clouds, services, and distributed applications is focused on counters, baseline statistics, and possibly analysis of a runtime protocol’s requests/response times in a specific environment. The current state captures common signals of a potential opportunity or a problem. However, it forces you to make sense of these signals piece by piece. In other words, there is no actionable information immediately available. This translates into lost opportunity costs or worse – extended exposure to risk.

To respond to risk and opportunities faster and more effectively, enterprise leaders need to rely more on smart metrics to make coordinated, fact-based decisions and streamline their business models. The Greymatter application networking platform enables organizations to move from traditional observability to actionability with our AI-driven sense-making models.

How Greymatter sense-making models work

Greymatter sense-making models use AI to analyze application, API, and data service metrics for business and forensic purposes. We design our sense-making models with “intentional silence” in mind. Rather than overwhelming the user with the typical flashing dashboard lights and alerts, the Greymatter model diagnoses the situation, highlighting the applications and services with key information. This eliminates much of the time spent gathering and processing raw data, and also offloads the burden for non-technical cross-team members trying to understand traffic or system metrics.

Powered by our Catalog Registry of Apps, APIs, and microservices, our Overwatch dashboard provides users with an aerial view of their distributed environment that reveals valuable contextual information such as health checks, detected anomalies of meshes and services, event timelines, compliance, and configurations at the service level.  Highlighting what matters most, our sense-making models can:

• Infer the health of services and provide specific, explicable, and actionable insights when the health of a service degrades.
• Surface unusual behavior, often in advance of failures.
• Audit user and endpoint behavior to highlight noteworthy activity.
• Observe user requests by user and timeline, making it easier to adjust costs to services most used by customers, or to potentially uncover abnormal user behaviors within their environments.
• Translate user experience metrics into straightforward scorecards for rapid knowledge capture and easier cross-team information sharing and collaboration, saving teams time.

Greymatter helps technical and business teams cut through the clutter and make informed, data-driven decisions. For example, providing the visibility and insights needed to identify and troubleshoot performance issues more quickly, prevent security breaches, optimize resource usages, improve compliance posture, and capture growth opportunities.

At Greymatter.io our goal is to make your life easier with a unified application networking platform that extends service mesh and modern service connectivity with all the additional technologies required to simplify control, security, and visibility across today’s hybrid, multi-cloud environments. Our sense-making models are an example of the innovative solutions we provide to guide customers through the complexity of these environments with ease and confidence, and improve the performance, scalability, and security of their applications while saving costs.

Request a demo to see how we can help you go from observability to actionability for real-time control and security over your operations.

Sources:

[1] Bernard Marr, ‘The 7 Biggest Business Challenges Every Company Is Facing In 2023’, Forbes, November 15, 2022, https://www.forbes.com/sites/bernardmarr/2022/11/15/the-7-biggest-business-challenges-every-company-is-facing-in-2023/?sh=1c96d0575688

[2] Tom Donilon et al., ‘Geopolitical risk dashboard’, BlackRock, February 9, 2023, https://www.blackrock.com/corporate/literature/whitepaper/geopolitical-risk-dashboard-february-2023.pdf

[3] Shakked Noy, Whitney Zhang, “Experimental Evidence on the Productivity Effects of Generative Artificial Intelligence”, MIT, March 2, 2023, https://economics.mit.edu/sites/default/files/inline-files/Noy_Zhang_1.pdf