Observability to Actionability: Greymatter’s Sense

Introduction

In 2023, global enterprises are facing threats from inflation and geopolitical tensions [1], cyberattacks, sustainability concerns [2], and the decoupling of global technology. There are key challenges associated with managing large-scale, global microservice architectures that span borders. Platform engineering teams are spending significant time and effort managing operations. At the same time they must also manage the cost of applications, APIs, and data services running in multiple cloud environments. The deployment and management of distributed applications architectures is highly complex. It requires a high level of skill that is both difficult to acquire and expensive to maintain. To respond to these risks and opportunities, enterprise leaders will rely more on smart metrics to make coordinated, fact-based decisions and streamline their business models. Greymatter enables enhanced sense-making backed by AI for improved modeling and decision-making.

A Peek into Greymatter’s Sense-making Models

The Greymatter application networking platform is designed to provide a cloud agnostic platform for enterprise scale organizations. This “platform engineering” approach seeks to remove the friction from developers, simplifying application modernization. Our platform includes fundamental features such as service discovery, traffic routing, and observability. However, Greymatter also includes additional advanced functionality to facilitate deployment, ensure security, validate configuration and present sensible information. All of this leads to smarter, faster, and more informed decision-making.

We recognize that while observability metrics are crucial, they may not suffice. To navigate complex multi-tenant, multi-mesh, multi-cluster or multi-cloud and disconnected environments users need more. Furthermore, they are not adequate to enable AI-driven management, debugging, or application networking control. Today 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. Even more egregiously, systems today do not tell you how to seize growth opportunities or treat problems to mitigate your exposed risk.

AI in Greymatter Sense-making

AI has recently captured the popular imagination, with free tools like ChatGPT and Stable Diffusion. Although these tools occasionally hallucinate, this hardly diminishes their usefulness. Used effectively, they can dramatically increase the productivity of a human in the loop. [3]

Greymatter does this for application networking use-cases such as:

• Analyze application, API, and data service metrics for business and forensic purposes
• Identify key drivers for managing applications, APIs, and data assets
• Recognize critical business impacts across global, distributed applications
• Optimize resource allocation and cost for customer-preferred capabilities
• Review visualizations and scorecards for cross-team monitoring and decision-making.

With Greymatter, you can infer the health of services and provide specific, explicable, and actionable insights when the health of a service degrades. Anomaly detection surfaces unusual behavior, often in advance of failures. Audits break down user and endpoint behavior to highlight noteworthy extrema.

Improving the User Experience

Our sense-making models are designed 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. With Greymatter, mesh administrators can observe user requests by user and timeline. This makes it easier to adjust costs to services most used by customers, or to potentially uncover abnormal user behaviors within their environments. User experience metrics are translated into straightforward scorecards, saving mesh administrators time.  This eliminates much of the time spent gathering and processing raw data. It also unloads unnecessary burdens for non-technical cross-team members trying to understand traffic or system metrics. These capabilities play a vital role in the seamless execution of Day 2 Operations tasks such as: continuous improvement of service quality, cost management, troubleshooting, reliability, and security. 

To sum up, Greymatter streamlines cloud performance and tracking operations by simplifying cloud complexity and reducing noise. With Greymatter, users can avoid mental overload and focus on what matters most. By providing contextual information and highlighting only the most pertinent data, Greymatter helps users cut through the clutter and make informed and data-driven decisions. This, in turn, opens the door to organizational alignments that streamline business goals all the way down to cloud operations. 

Where We are Heading

Drawing on our past success with our sense-making model, we plan to further simplify the complexity that inevitably follows digital transformation and cloud migration. Our roadmap includes an array of insightful features to enhance user experience, such as:

• Overwatch:  An aerial view of the multi-mesh landscape. Our users will gain valuable contextual information such as health checks, detected anomalies of meshes and services, event timelines, compliance, and configurations at the service level. 
• Conversational interface: A “ChatGPT-type” experience featuring an interface that will enable users to ask natural language questions in order to obtain critical information quickly and efficiently without complex querying mechanisms or data offload.
• Scorecards enhancement: Scorecards containing critical security, performance, and business indicators within the application for rapid knowledge capture and easier cross-team information sharing and collaboration.  

Ultimately, our goal is to continue providing innovative solutions to guide customers through complex cloud environments and deployments with ease and confidence.

Conclusion

Investing in appropriate tools during the early stages of cloud migration planning can significantly mitigate the challenges associated with the process of digital transformation. This significantly smoothes out the “pain curve”. With Greymatter, our customers have been able to gain a comprehensive understanding of their application networks. Our sense-making capabilities enable them to exercise control, and enhance their security posture. We remain committed to advancing our unique models to achieve the ultimate user experience for our customers.

Interested in learning more about how Greymatter can help your team? We invite you to try our platform for 30 days!  Contact us or schedule a demo to learn how greymatter.io can help your enterprise control complexity, secure applications and see real-time operations.

Article Authors:

Daniel Cox and Anna Chung

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