Insight
Gain real-time insight into the performance of your microservices.
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1.2
Gain real-time insight into the performance of your microservices.
Last updated
Was this helpful?
A service mesh lacks monitoring and visibility. Without mesh operations visibility, SREs and DevOps engineers struggle to find root causes for problems that can happen anywhere: on the network, inside containers, or between services.
Decentralized systems already have reporting challenges that grow exponentially with new services, and cloud environments. To make matters worse, failure to comply with privacy protection policies could bring legal trouble, massive fines, and loss of accreditation.
Digital twins are a cost-effective way to help decision-makers across a number of business use-cases, from technical operations to marketing and sales. They require systems capable of securely replicating, interacting with, and, as necessary, accurately modifying, massive historical data volumes at rapid speed. In addition, human user and customer data is subject to several PII policy compliance requirements that may require the anonymization or the outright removal of key user data immediately upon user request.
Service meshes, microservices, serverless, and containers are key elements of Mesh Application and Service Architecture (MASA) implementation. However, these capabilities present significant service-to-service communication, discovery mechanism, security layer, and audit observability challenges at scale. The volume of data generated by mesh operations coupled with the complexity of hybrid and multi-mesh operations can overwhelm traditional compliance tracking efforts.
Grey Matter's Intelligence 360 helps visualize service health, data-flows, and microservice interactions so you can solve performance issues fast. Intelligence 360 provides full-scope health observability and contextual awareness for the mesh.
The combination of Fabric orchestration and Intelligence 360 dynamic control lets your team check service health, making changes on the fly fixing an anomaly impacting service performance. Grey Matter also enables granular audit and policy compliance as well as rapid dependency identification, for real-time tracking of aggregate, route, and service level SLOs for Memory Utilization, CPU Utilization, Percentile Latencies, Error Rate, and Request Rate in an easy-to-understand manner.
Grey Matter’s omnidirectional mesh telemetry capture and analysis capabilities enable deep mesh audit and observability without the need for special instrumentation. Grey Matter employs a normalized and repeatable in-depth audit capture of every event on the mesh which can be used to establish a baseline for compliance reporting. Employing Kibana as a third-party dashboard, Grey Matter enables data lineage and provenance oversight via fully observable audit controls for rapid forensic detection and diagnosis of anomalies and intrusions.
Grey Matter supports various containers, microservices, and serverless architectures so you can adopt cloud-native technologies without worry.
Grey Matter records and displays every activity within the mesh for in-depth audit control, policy compliance reporting, rapid forensic detection and diagnosis of anomalies and intrusions. You can cut through the noise to find performance outliers throughout your mesh and pinpoint the root cause of your problem within seconds.
Grey Matter offers distributed tracing to monitor service availability and performance. This data helps teams troubleshoot the mesh and improve mesh performance.
Grey Matter offers in-depth observability and policy compliance management for your complex multi-environment networks. Grey Matter sidecars run alongside each microservice within the mesh, creating a controlled and trusted service edge fleet guided by dynamically established policy guidelines. These services are responsible for managing network requirements such as scaling, access control, policy compliance, audit, and service-to-service intercommunication.
Grey Matter’s omnidirectional mesh telemetry capture and analysis capabilities enable deep mesh audit and observability without the need for special instrumentation. Network micro-segmentation and policy enforcement ensure zero-trust managed security compliance.
Mesh telemetry data powers architecture-wide service level objective (SLO) policy compliance and fine-grained hybrid mesh operational control. With Grey Matter, users can dynamically set SLOs governing each policy action atop the mesh. If one approaches warning or violation, Grey Matter alerts via an intuitive single-pane-of-glass interface for rapid mitigation.
Grey Matter is designed to operate using a zero-trust threat model to ensure each service and transaction running within a Grey Matter enabled hybrid mesh is appropriately protected. This is supported by the normalized and repeatable in-depth audit capture of every event on the mesh which can be used to establish a baseline for compliance reporting. The concept of zero-trust is centered on a belief that enterprises do not automatically trust systems or services inside or outside its perimeters. In the case of Grey Matter, everything attempting to connect is verified before granting access. Every action is recorded and can be played back for forensic analysis.
Grey Matter records and displays the lineage and provenance of every activity conducted by every user on every object atop the mesh throughout its life-cycle. The platform makes this information fully observable and accessible for in-depth audit control, policy compliance reporting, and rapid forensic detection and diagnosis of anomalies and intrusions.
Grey Matter is purposefully designed to capture and analyze the massive volumes of telemetry, user, and operational data generated by mesh operations. With Grey Matter, every piece of network traffic, user activity, or policy-driven system action can be brought together to create digital twins of systems, networks, and even individual users or group for analysis and testing. Because Grey Matter is built with zero-trust control and audit tracing in mind, PII information can be anonymized or selectively removed in keeping with legislative requirements such as the EU General Data Protection Regulation (GDPR).
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