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DIDComm Mediator Architecture Documentation

Table of Contents

  1. Introduction
  2. Architecture Constraints
  3. System Scope and Context
  4. Solution Strategy
  5. Building Block View
  6. Runtime View
  7. Deployment View
  8. Cross-cutting Concepts
  9. Architecture Decisions
  10. Quality Requirements
  11. Risks and Technical Debt
  12. Glossary

1. Introduction

1.1 Document Goals

This document outlines the architecture of didcomm-mediator-rs, a Rust-based implementation of a DIDComm v2 mediator. The primary purpose of this mediator is to enable secure, efficient, and reliable routing of DIDComm messages, acting as a critical component in decentralized identity communication. This document serves as a comprehensive guide for stakeholders, architects, and developers, providing the necessary clarity for implementation, integration, and ongoing support of the system.

1.2 Stakeholders

  • Product Owners: Define feature requirements.
  • Developers: Build and maintain the mediator.
  • Operations Team: Deploy and monitor the mediator in production.
  • Compliance Teams: Ensure adherence to privacy and security regulations.
  • DIDComm Users: End-users leveraging decentralized identity systems.

2. Architecture Constraints

2.1 Technical Constraints

  • Rust Programming Language: Ensures high performance and memory safety.
  • Transport Agnosticism: Supports HTTP
  • No External State: Minimal reliance on external systems for scalability.

2.2 Regulatory Constraints

  • Privacy Compliance: Aligns with GDPR and similar regulations.
  • Decentralized Design: Eliminates central authority dependencies.

3. System Scope and Context

3.1 Business Context

The mediator facilitates routing of DIDComm messages for agents unable to maintain direct communication channels. It acts as an intermediary, ensuring reliability and privacy.

3.2 External Components

  • DIDComm Agents: Sending and receiving agents.
  • Transport Protocols: Various transport layers, e.g., HTTP or WebSockets.
  • Cloud Infrastructure: For scalable and fault-tolerant deployments.

3.3 Component Diagram

graph LR
    Agent1[Agent 1] --> Transport1
    Transport1 --> Mediator1
    Mediator1 --> Mediator2
    Mediator2 --> Transport2
    Transport2 --> Agent2[Agent 2]
Loading

4. Solution Strategy

A microservices approach ensures modularity and scalability. didcomm-mediator-rs employs Rust's async capabilities to handle concurrent message routing efficiently.

Key Features:

The didcomm-mediator-rs project implements several essential protocols in the DIDComm v2 ecosystem, as outlined below:

Feature Specification Status
Mediator Coordination Protocol Adopted
Pickup Protocol Adopted
DID Rotation Accepted
Cross-Domain Messaging/Routing Protocol Adopted
Trust Ping Protocol Adopted
Discover Features Protocol Adopted
Out-of-Band Messaging Adopted
Basic Message Protocol Adopted
Acknowledgments (Acks) Adopted
Present Proof Protocol Adopted

5. Building Block View

5.1 Overview

The didcomm-mediator-rs project utilizes a plugin-based architecture, allowing modular and extensible implementation of DIDComm messaging protocols. The architecture is divided into two key plugin layers:

  1. Web Plugin Layer:

    • Enables plug-and-play of web endpoints.
    • Currently used to implement features such as DID Endpoints, out-of-band messaging, and DIDComm messaging.

  2. DIDComm Messaging Plugin Layer:

    • Facilitates incremental addition of DIDComm sub-protocols.
    • Modular implementation ensures support for future protocols without major refactoring.

5.2 Detailed View

Top-Level Architecture

At the core is the Mediator Server*, responsible for hosting the overall application and enabling the plugin system. The main components are:

  1. Dispatcher: Routes incoming requests to the appropriate web plugin.
  2. Web Plugin Layer: Hosts modular implementations for endpoint-specific logic (e.g., DID endpoint generation, out-of-band messaging).
  3. Common DIDComm Processing: Handles general DIDComm request/response processing applicable across sub-protocols.

DIDComm Messaging Plugin Layer

Nested within the DIDComm Messaging endpoint is another plugin system for managing sub-protocols. This includes:

  1. Forward Protocol: Handles message routing across agents.
  2. Pickup Protocol: Manages message retrieval by offline agents.
  3. Mediator Coordination Protocol: Supports agent registration and mediation setup.
  4. Discover features: allows to query the mediator for supported protocols
  5. trust-ping: This protocol is a standard way for agents to test connectivity, responsiveness, and security of a DIDComm channel.
  6. basic message: Sending a basic message to the mediator
  7. Plugin Utilities: Shared utilities that facilitate sub-protocol implementations.

5.3 Building Block Diagram

The following diagram illustrates the layered architecture with the plugin-based system:

graph TD
    MediatorServer[Mediator Server] --> Dispatcher[Dispatcher]
    Dispatcher --> WebPluginLayer[Web Plugin Layer]
    WebPluginLayer --> DIDEndpoint[DID Endpoint]
    WebPluginLayer --> OOBMessaging[Out-of-Band Messaging]
    WebPluginLayer --> DIDCommMessaging[DIDComm Messaging Endpoint]
    DIDCommMessaging --> CommonProcessing[Common DIDComm Processing]
    DIDCommMessaging --> MessagingPlugins[Messaging Plugin Layer]
    MessagingPlugins --> Forward[Forward Protocol]
    MessagingPlugins --> Pickup[Pickup Protocol]
    MessagingPlugins --> Coordination[Mediator Coordination Protocol]
    MessagingPlugins --> Trustping[Trust Ping Protocol]
Loading

5.4 Key Advantages of Plugin Architecture

  1. Modularity: Each protocol or feature can be independently developed, tested, and deployed.
  2. Extensibility: New protocols or endpoints can be added without significant architectural changes.
  3. Scalability: Lightweight plugins ensure efficient handling of additional features and traffic.

6. Runtime View

6.1 Message Flow

  1. Agent sends a message to the mediator.
  2. Mediator stores or forwards the message based on the recipient's status.
  3. Recipient retrieves the message via the pickup protocol.

Sequence Diagram

sequenceDiagram
    Agent1->>Mediator: Send Message
    Mediator->>Storage: Store Message
    Agent2->>Mediator: Pickup Request
    Mediator->>Agent2: Deliver Message
Loading

6.2 Mediator Coordination Flow

The Mediation Coordination Protocol is a component of the DIDComm framework, facilitating secure and efficient message routing between agents. It enables a recipient agent to request a mediator agent to handle message forwarding on its behalf.

Sequence Diagram: Mediation Coordination Protocol

sequenceDiagram
    participant Recipient
    participant Mediator

    Recipient->>Mediator: Mediate Request
    alt Mediator Accepts
        Mediator-->>Recipient: Mediate Grant
        Note right of Mediator: Provides routing information
    else Mediator Denies
        Mediator-->>Recipient: Mediate Deny
        Note right of Mediator: Declines mediation request
    end
    alt Recipient Registers Key
        Recipient->>Mediator: Keylist Update
        Mediator-->>Recipient: Keylist Update Response
    end
Loading

Illustration: Runtime Interaction

  1. Mediate Request: The recipient sends a mediate-request message to the mediator, initiating the mediation process.

  2. Mediator's Response:

    • Grant: If the mediator agrees, it responds with a mediate-grant message, providing necessary routing details.
    • Deny: If the mediator declines, it sends a mediate-deny message.

  3. Key Registration: Upon receiving a grant, the recipient registers its keys with the mediator using a keylist-update message. The mediator acknowledges with a keylist-update-response.

This interaction ensures that messages intended for the recipient are appropriately routed through the mediator, enhancing communication reliability and security.

6.3 Pickup Protocol

The pickup process allows agents to retrieve messages stored by the mediator. The mediator securely holds messages on behalf of the recipient agents, ensuring their safe and timely retrieval. This process is essential to ensuring reliable message delivery, even when the recipient agent is temporarily unavailable.

  1. Message Storage When a message is sent to an agent that is not immediately available to receive it, the mediator stores the message. The message remains encrypted using DIDComm standards to ensure that only the intended recipient can decrypt and read the content. Key aspects include:
  • Encrypted Storage: Messages are stored in an encrypted format, ensuring the mediator has no access to the content.
  • Indexed Storage: Messages are indexed based on the recipient's DID to facilitate efficient lookup and retrieval.
  1. Pickup Request The recipient agent initiates the pickup process by sending a pickup request to the mediator. The request must be signed with the agent’s private key to ensure authenticity and prevent unauthorized access. The pickup request contains:
  • Recipient DID: To identify which messages are being retrieved.
  • Authentication Signature: A cryptographic signature to validate the agent’s identity and access rights.

7. Deployment View

7.1 Deployment Strategy

The deployment of the didcomm-mediator-rs project leverages a scalable, distributed architecture designed for high availability, fault tolerance, and efficient message routing.

7.2 Deployment Model

1. Distributed Deployment with Load Balancer

Use Case: Ideal for production environments requiring high availability and scalability.

  • Multiple mediator instances are deployed behind a load balancer.
  • The load balancer distributes requests evenly across mediators, ensuring efficient utilization of resources.
  • Supports horizontal scaling by adding more mediator instances as needed.

Advantages:

  • High availability: If one mediator instance fails, others continue handling requests.
  • Scalable: New instances can be added to handle increased load.
  • Efficient routing: Load balancer optimizes resource utilization.

Disadvantages:

  • Slightly higher complexity due to additional components (load balancer).

7.3 Deployment Diagram

Below is a component diagram showcasing the deployment with multiple mediators and a load balancer:

alt text

7.4 Deployment Considerations

Cloud Deployment

Infrastructure:

  • Use cloud platforms like AWS, Azure, or GCP.
  • Services like Elastic Load Balancer (AWS), Application Gateway (Azure), or Cloud Load Balancer (GCP) can be employed for load balancing.

Scaling:

  • Leverage auto-scaling groups to dynamically scale mediator instances based on traffic.

Monitoring:

  • Use monitoring tools (e.g., Prometheus, CloudWatch, or Azure Monitor) to track mediator performance, error rates, and resource usage.

On-Premises Deployment

Infrastructure:

  • Deploy mediators on virtual machines or containers (e.g., Docker).
  • Use a software-based load balancer (e.g., HAProxy, NGINX) for request distribution.

Scaling:

  • Add more mediator instances manually to handle increased traffic.

Monitoring:

  • Use tools like Grafana and Prometheus to monitor system health.

7.5 Benefits of Load Balancer in Deployment

  1. Fault Tolerance:

    • Ensures service continuity even if one mediator instance fails.

  2. Scalability:

    • Handles growing traffic by distributing load across multiple instances.

  3. Optimized Resource Utilization:

    • Prevents overloading a single mediator, ensuring consistent performance.

  4. Simplified Maintenance:

    • Instances can be updated or replaced without downtime by redirecting traffic.

This detailed deployment view provides clarity on how the system can be deployed effectively, balancing performance, fault tolerance, and scalability.

8. Cross-cutting Concepts

8.1 Security

The security of didcomm-mediator-rs integrates both application-level security and secure software development lifecycle (SSDLC) practices to ensure robust, private, and resilient operations against potential vulnerabilities and attacks.

8.1.1 End-to-End Encryption

DIDComm itself provides robust end-to-end encryption, ensuring that the mediator operates without access to message contents.

  • Encryption in Transit: Messages are encrypted using DIDComm standards, safeguarding confidentiality during routing.
  • Confidentiality: Only the intended recipient can decrypt and access the message content, ensuring data remains private.

8.1.2 Authentication and Agent Identity Verification

Authentication ensures that only legitimate agents interact with the mediator, preventing unauthorized access and spam.

  1. Authentication During Mediation Coordination:

    • Agents requesting mediation must authenticate using:
      • DID Authentication: Validates that the DID corresponds to the public key.
      • Signed Credentials: Ensures requests are cryptographically signed and verifiable.
      • Trust Frameworks: Optional integration with registries or decentralized credentials to validate agents.

  2. Anti-Spam Measures:

    • Rate Limiting: Restricts the number of requests per agent within a given period.
    • Credential Validation: Verifies agent credentials or DID associations.
    • Reputation Scoring: Maintains agent reputation based on past behaviors.

8.1.3 Authorization for Message Handling

The mediator enforces strict access controls to ensure only authorized agents can send and retrieve messages.

  1. Message Sending:

    • Sender validation ensures:
      • The sender provides a cryptographically signed request.
      • The recipient's DID document lists the mediator as a valid routing endpoint.
      • Access control policies allow communication between the sender and recipient.

  2. Message Pickup:

    • Before delivering stored messages, the mediator ensures:
      • The requesting agent provides a signed pickup request.
      • The private key used for signing matches the public DID associated with the mediator.

8.1.4 Secure Storage and Key Management

Protecting private keys and sensitive data is paramount.

  • Encryption at Rest: Private keys and secrets are encrypted using secure algorithms.
  • Memory Protections: Runtime mechanisms prevent sensitive data from being swapped to disk.
  • Key Management:
    • Secure storage mechanisms like HashiCorp Vault or AWS KMS are used.
    • Keys are rotated periodically to minimize risks.

8.1.5 Traffic Control and Anti-Spam Measures

To ensure efficient operation and prevent abuse:

  • Rate Limiting and Throttling: Prevents overloading by limiting agent requests.
  • Reputation-Based Blocking: Blocks agents with poor reputations based on spam or malicious activity.
  • Audit Trails: Logs all requests for later analysis and forensic investigation.

8.1.6 Secure Logging and Monitoring

Log Handling:

  • Sensitive data (e.g., private keys, Personally Identifiable Information) is redacted from logs.
  • Logs are encrypted at rest and in transit.
  • Access to logs is restricted to authorized personnel.

Monitoring:

  • Tools like Prometheus, Grafana, and ELK Stack are employed to monitor:
    • API response times and error rates.
    • System performance (e.g., memory and CPU utilization).
  • Alerts are configured for anomalies, unauthorized access, and potential attacks.

8.1.7 Secure Software Development Lifecycle (SSDLC)

Incorporating SSDLC practices ensures that vulnerabilities are minimized from inception through deployment.

  1. Static Application Security Testing (SAST):

    • Tools like SonarQube, CodeQL, or Checkmarx are used to scan source code for vulnerabilities.
    • integration of CI/CD pipelines to analyze every commit and pull request.

  2. Dynamic Application Security Testing (DAST):

    • Tools like OWASP ZAP or Burp Suite test the application in running environments.
    • Simulates real-world attack scenarios to identify runtime vulnerabilities.

  3. Dependency Management:

    • Tools like Snyk, OWASP Dependency-Check, or GitHub Dependabot monitor dependencies for vulnerabilities.
    • Enforces strict policies to restrict unverified or malicious modules.
    • Locks dependency versions to prevent accidental updates.

  4. Code and Image Signing:

    • All code artifacts are cryptographically signed to ensure integrity.
    • Container images are signed using tools like Cosign to verify authenticity before deployment.

8.1.8 Continuous Security Assessment

  1. Penetration Testing:

    • Regular penetration testing by internal and external experts to identify and remediate vulnerabilities.

  2. Vulnerability Management:

    • Monitor CVEs and apply patches promptly.
    • Update dependencies and application components regularly.

  3. Incident Response:

    • A defined incident response plan ensures quick detection, isolation, and resolution of security breaches.
    • Logs and audit trails provide forensic support.

8.1.9 Deployment Security

  1. Immutable Infrastructure:

    • Deployments use containerized environments (e.g., Docker, Kubernetes) for consistency.
    • Infrastructure updates are handled via image-based deployments.

  2. Secure CI/CD Pipelines:

    • Pipelines enforce checks for vulnerabilities, code integrity, and dependency security.
    • Deployments use RBAC (Role-Based Access Control) to restrict unauthorized changes.

  3. Load Balancer Security:

    • Load balancers enforce TLS for secure communication.
    • Denial-of-Service (DoS) protections are applied at the load balancer level.

8.1.10 Enhancements for Anti-Spam and Traffic Control

  1. Rate Limiting: Prevents message flooding by enforcing request caps.
  2. Trust-Based Validation: Agents are validated using decentralized identity frameworks.
  3. Agent Reputation: Maintains behavior-based reputation scores to filter malicious agents.

Summary Table

Aspect Practices
End-to-End Encryption Encrypt messages in transit using DIDComm protocols.
Authentication Use DID authentication and signed credentials for agent verification.
Authorization Enforce access control policies for sending and retrieving messages.
Secure Logging Mask sensitive data, encrypt logs, and restrict access.
Monitoring Use tools like Prometheus and Grafana for real-time anomaly detection.
Static Analysis (SAST) Integrate SonarQube or CodeQL into CI/CD pipelines.
Dynamic Analysis (DAST) Test live environments using OWASP ZAP or Burp Suite.
Dependency Management Use Snyk or OWASP Dependency-Check to monitor and secure dependencies.
Code Signing Sign all artifacts and verify container images before deployment.
Incident Response Have a clear plan for detection, containment, and recovery.

This combination integrates application security and SSDLC best practices, providing a comprehensive security framework for didcomm-mediator-rs.

8.2 Performance

  • Concurrency: Async Rust handles high message throughput.
  • Caching: Reduces database queries for frequent operations.

9. Architecture Decisions

9.1 Technology Decisions

  • Rust for Performance:

    • Chosen for its memory safety, high-speed execution, and ability to handle concurrent processes efficiently.
    • Ensures robust and reliable mediation services in a decentralized environment.

  • Transport Agnosticism:

    • Supports various communication protocols (e.g., HTTP, WebSocket, and others).
    • Designed to integrate seamlessly into diverse ecosystems, enhancing interoperability.

  • Cloud-First:

    • Optimized for deployment in modern cloud environments.
    • Employs containerized solutions (e.g., Docker) and orchestration tools (e.g., Kubernetes) for scalability and ease of maintenance.

9.2 Architectural Features

  • DIDComm Protocol Implementation:

    • DIDComm v2 Protocol Compliance: The system adheres to the DIDComm v2 standard as a critical requirement, ensuring all communications are secure, decentralized, and authenticated.
    • Secure Messaging: Supports end-to-end encryption and transport-agnostic messaging as part of the DIDComm v2 protocol implementation.

  • Scalability and Modularity:

    • Architected to handle growing user and message loads without performance bottlenecks.
    • Modular design allows for easy extension of features like advanced message routing or additional protocol support.

  • Secure Message Mediation:

    • Incorporates robust cryptographic mechanisms to protect sensitive data.
    • Ensures confidentiality, integrity, and authenticity in all message exchanges.

9.3 Deployment and Maintenance

  • CI/CD Integration:

    • Automated pipelines for testing, building, and deploying ensure rapid and error-free updates.

  • On-Premise and Hybrid Support:

    • Though optimized for the cloud, the solution is also adaptable for on-premise deployment.
    • Suitable for organizations with strict data sovereignty or privacy requirements.

  • Logging and Monitoring:

    • Designed to include observability features such as detailed logs and performance monitoring.
    • Aids in debugging and enhances operational reliability.

9.4 Future Considerations

  • Additional Protocol Support:

    • Exploring further transport protocols to expand integration capabilities.

  • Dynamic Scaling:

    • Introducing auto-scaling mechanisms to manage resource usage based on real-time demand.

  • Advanced Observability:

    • Adding comprehensive monitoring and analytics dashboards to track system performance and detect anomalies.

10. Quality Requirements

Functional

  • Reliable Message Storage and Delivery: The system must ensure that messages are stored persistently and delivered reliably to the correct recipient, even in the event of system failures. This includes handling retries, acknowledgments, and maintaining message order. The system should support eventual consistency and be able to recover from intermittent network failures, ensuring that no messages are lost during transmission.

  • DID Rotation Support: The system should support Decentralized Identifier (DID) rotation to ensure secure communication can continue uninterrupted when the keys or identifiers change. This includes the ability to handle key rotation, update trust stores, and ensure that the recipient is aware of the new DID information. Rotation must not disrupt communication, ensuring transparency in key changes and maintaining message integrity through appropriate versioning and key management mechanisms.

Non-Functional

  • Scalability: The system must be capable of handling a high number of concurrent connections while maintaining performance and reliability. Scalability can be achieved through load balancing, horizontal scaling across multiple servers, and efficient resource management. Techniques such as data partitioning, caching, and asynchronous processing will ensure that the system can handle increased load without performance degradation.

  • Security: All messages must be routed and stored in an encrypted format to ensure the privacy and integrity of the data. The system should comply with established cryptographic standards, using public-key encryption for message transmission and ensuring that keys are securely managed. Additional measures like integrity checks (e.g., HMAC, digital signatures) must be used to protect data from tampering or unauthorized access. The system must also support end-to-end encryption to ensure that only the intended recipients can decrypt the messages, with mechanisms for key revocation and renewal built-in.

11. Risks and Technical Debt

Risks

  1. Message Pickup Delays Under High Load:

    • Cause: High volume of concurrent requests or uneven workload distribution.
    • Mitigation:
      • Implement rate limiting for individual agents.
      • Introduce adaptive queueing mechanisms to prioritize urgent messages.
      • Optimize message retrieval with indexed storage and caching.

  2. Single Point of Failure in Initial Deployments:

    • Cause: Lack of redundancy during early development or testing phases.
    • Mitigation:
      • Transition to a distributed deployment model with load balancing.
      • Utilize active-passive failover strategies for critical components.

  3. Transport Layer Compatibility Issues:

    • Cause: Incomplete or inconsistent support for diverse transport protocols (e.g., WebSockets, Bluetooth).
    • Mitigation:
      • Expand transport testing suites for edge cases.
      • Adopt a common interface for transport abstraction to reduce inconsistencies.

  4. Encryption Key Management Challenges:

    • Cause: Complexities in securely rotating keys and ensuring backward compatibility.
    • Mitigation:
      • Introduce automated key rotation with DIDComm-compliant mechanisms.
      • Ensure seamless coordination between mediator and agents for key updates.

  5. Potential Data Breach via Misconfigured Logs:

    • Cause: Insufficient log redaction or improper access controls.
    • Mitigation:
      • Enforce log encryption and access policies during development.
      • Integrate log analysis tools that detect and block sensitive data exposure.

Technical Debt

  1. Simplified Transport Layer Abstraction:

    • Impact: Makes it harder to extend mediator functionality to support new or custom transport protocols.
    • Planned Resolution:
      • Refactor to adopt a modular transport interface.
      • Use a factory pattern for transport instantiation.

  2. Basic Observability Tools:

    • Impact: Limited insight into runtime behavior may hinder issue resolution under high traffic.
    • Planned Resolution:
      • Integrate advanced observability solutions like distributed tracing with OpenTelemetry.

  3. Incomplete Protocol Coverage:

    • Impact: Missing implementation of critical protocols (e.g., Discover Features, Present Proof) limits applicability in broader DIDComm ecosystems.
    • Planned Resolution:
      • Prioritize development of high-demand protocols.
      • Define a phased approach to protocol implementation.

  4. Static Resource Allocation:

    • Impact: Inefficient use of resources under variable load conditions.
    • Planned Resolution:
      • Introduce auto-scaling mechanisms in Kubernetes to dynamically allocate resources.

  5. Minimal Failover Testing:

    • Impact: Could lead to prolonged downtime or message loss during unexpected failures.
    • Planned Resolution:
      • Conduct chaos testing to validate failover strategies.
      • Build automated failover and recovery scenarios into CI/CD pipelines.

12. Glossary

Component Definition
Asynchronous Programming A programming model that allows tasks to be performed without blocking the main program flow.
Caching Storing frequently accessed data in temporary storage for faster retrieval.
Cloud-First A strategy where applications are designed to be deployed in the cloud, leveraging cloud services for scalability.
Decentralized Identity (DID) A self-sovereign identity system that allows individuals to own and control their identifiers without depending on a central authority.
DID Decentralized Identifier: A self-sovereign, cryptographically secure identifier independent of centralized authorities.
DIDComm Messaging Protocol for DIDs: A protocol for secure, private communication between entities using DIDs.
DID Rotation Changing a DID’s associated cryptographic keys to enhance security while maintaining continuous communication.
Encryption The process of securing data to prevent unauthorized access, ensuring privacy and data integrity.
Encryption Algorithm A mathematical procedure used to encrypt or decrypt data, ensuring confidentiality and security.
Encryption Key Management The process of handling, storing, and rotating encryption keys to ensure the security of encrypted data.
GDPR General Data Protection Regulation: A regulation in EU law focused on the protection of personal data and privacy of individuals within the EU and EEA.
Horizontal Load Balancing Distributing incoming traffic across multiple servers to prevent overloading a single server.
Horizontal Scaling Increasing capacity by adding more instances of servers or resources.
Kubernetes A container orchestration platform that automates deployment, scaling, and management of applications.
Load Balancing Distributing network traffic across multiple servers to avoid overloading a single resource.
Mediator Message Intermediary: A trusted entity that routes messages between parties in DIDComm, often used to bridge communication gaps.
Message Acknowledgment A process where the recipient confirms receipt of a message, often to ensure reliability in communication.
Message Delivery The reliable transmission of messages from sender to recipient, often involving intermediaries.
Persistent Storage Data storage that retains information beyond the system’s runtime, ensuring data availability across sessions.
Public Key Infrastructure (PKI) A framework for managing digital keys and certificates for secure communication.
Public-Key Cryptography A cryptographic system that uses a pair of keys: a public key for encryption and a private key for decryption.
REST API An architectural style for building web services, using HTTP requests to interact with resources (e.g., GET, POST).
Retry Logic A mechanism that attempts to resend failed operations or messages to ensure reliability in communication.
Rust A systems programming language known for memory safety, concurrency, and performance.
Scalability The system's ability to handle increasing loads by distributing resources or scaling horizontally.
Semantic Versioning (SemVer) A versioning scheme for software that indicates the nature of changes through MAJOR.MINOR.PATCH.
Security Protection of data through encryption, ensuring confidentiality, integrity, and authenticity of messages.
Service Discovery The process of automatically detecting services in a network, allowing components to find and interact with each other dynamically.
SQLite A self-contained, serverless database engine used for lightweight, persistent storage.
TLS (Transport Layer Security) A cryptographic protocol designed to provide secure communication over a computer network.
Transport Agnosticism The capability of a system to support different communication protocols without being reliant on one.
Trust Chain A sequence of certificates that validate the authenticity of a cryptographic key, leading back to a trusted root certificate.
Trust Store A repository of trusted certificates and keys used to verify the authenticity of communication partners.
Vertical Scaling Increasing a system's capacity by adding more resources (e.g., CPU, RAM) to a single server.
WebSocket A communication protocol that provides full-duplex communication channels over a single TCP connection.
Zero-Trust Security A security model that assumes no trust is granted to any entity, even inside the network, and requires continuous verification.