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BUSINESS POSTURE

This project, InfluxDB, is a time-series database designed to handle high write and query loads. It is intended to store and analyze time-stamped data, making it suitable for use cases such as monitoring, IoT sensor data, application performance monitoring, and real-time analytics.

Business Priorities and Goals:

  • Provide a robust, scalable, and performant time-series database solution.
  • Enable users to efficiently store and query large volumes of time-series data.
  • Support real-time data ingestion and analysis.
  • Offer a flexible and user-friendly query language.
  • Provide features for data retention and management.
  • Foster a strong open-source community and ecosystem.
  • Offer commercial offerings and support for enterprise users.

Business Risks:

  • Data loss or corruption due to system failures or software bugs.
  • Performance degradation under high load, impacting real-time data analysis.
  • Security vulnerabilities leading to data breaches or unauthorized access.
  • Operational complexity in managing and scaling the database.
  • Lack of adoption or competition from other time-series database solutions.
  • Dependence on open-source community contributions and maintenance.
  • Compliance with data privacy regulations (e.g., GDPR, HIPAA) if storing sensitive data.
  • Vendor lock-in if users become heavily reliant on specific InfluxDB features.

SECURITY POSTURE

Security Controls:

  • security control: Code reviews are likely performed as part of the development process, although not explicitly stated in the repository. Location: Development process, implicitly assumed.
  • security control: Unit and integration tests are present in the repository, contributing to code quality and potentially catching some security issues. Location: Repository code, test directories.
  • security control: Input validation is expected to be implemented within the database to handle various data types and prevent injection attacks. Location: Database codebase, input processing modules (implicitly assumed).
  • security control: Authentication and authorization mechanisms are implemented to control access to the database and its data. Location: Database codebase, authentication and authorization modules (implicitly assumed).
  • security control: Encryption of data in transit (HTTPS) is likely supported for API access. Location: Deployment documentation, API documentation (implicitly assumed).

Accepted Risks:

  • accepted risk: Reliance on community contributions for identifying and fixing security vulnerabilities.
  • accepted risk: Potential for vulnerabilities in third-party dependencies.
  • accepted risk: Operational security misconfigurations by users deploying and managing InfluxDB.
  • accepted risk: Insider threats from developers or maintainers with access to the codebase.

Recommended Security Controls:

  • security control: Implement automated Static Application Security Testing (SAST) in the CI/CD pipeline to identify potential vulnerabilities in the codebase.
  • security control: Implement automated Dynamic Application Security Testing (DAST) to test the running application for vulnerabilities.
  • security control: Perform regular dependency scanning to identify and update vulnerable third-party libraries.
  • security control: Implement a vulnerability disclosure program to allow security researchers to report vulnerabilities responsibly.
  • security control: Provide security hardening guidelines and best practices for deployment and configuration.
  • security control: Consider implementing encryption at rest for sensitive data stored in the database.
  • security control: Implement robust logging and monitoring of security-related events, such as authentication failures and access violations.

Security Requirements:

  • Authentication:
    • Requirement: The system must authenticate users before granting access to the database.
    • Requirement: Support multiple authentication mechanisms, such as username/password, tokens, and potentially integration with external authentication providers (e.g., LDAP, OAuth).
    • Requirement: Implement strong password policies and enforce password complexity.
  • Authorization:
    • Requirement: The system must implement role-based access control (RBAC) to manage user permissions and restrict access to specific data and operations.
    • Requirement: Authorization should be enforced at multiple levels, including database, measurement, and field level.
    • Requirement: Principle of least privilege should be applied when assigning permissions to users and roles.
  • Input Validation:
    • Requirement: All user inputs, including queries, data points, and configuration parameters, must be validated to prevent injection attacks (e.g., SQL injection, command injection).
    • Requirement: Input validation should be performed on both the client-side and server-side.
    • Requirement: Implement proper encoding and sanitization of user inputs before processing or storing them.
  • Cryptography:
    • Requirement: Sensitive data in transit, such as authentication credentials and data exchanged over the API, must be encrypted using TLS/HTTPS.
    • Requirement: Consider encryption at rest for sensitive data stored in the database to protect against unauthorized access in case of physical media compromise.
    • Requirement: Use strong cryptographic algorithms and libraries for all cryptographic operations.
    • Requirement: Manage cryptographic keys securely and follow key management best practices.

DESIGN

C4 CONTEXT

flowchart LR
    subgraph "Organization"
    U["Monitoring System User"]:::person
    A["Application User"]:::person
    end

    subgraph "InfluxDB System"
    I["InfluxDB"]:::software_system
    end

    subgraph "External Systems"
    M["Monitoring System"]:::software_system
    AP["Application"]:::software_system
    ET["External Time-Series Data Sources"]:::software_system
    V["Visualization Tools (Grafana)"]:::software_system
    end

    U -->> I: Query Data
    A -->> I: Query Data
    M -->> I: Write Metrics
    AP -->> I: Write Application Data
    ET -->> I: Write External Data
    I -->> V: Provide Data for Visualization

    classDef person fill:#ECF2FF,stroke:#9CB4CC,stroke-width:2px
    classDef software_system fill:#DAE5D0,stroke:#8AA081,stroke-width:2px
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Context Diagram Elements:

  • Element:

    • Name: Monitoring System User
    • Type: Person
    • Description: A user who interacts with monitoring systems that utilize InfluxDB to store and analyze metrics. This user typically views dashboards and sets up alerts based on time-series data.
    • Responsibilities: Monitoring system health, analyzing performance trends, setting up alerts, and troubleshooting issues based on data visualized from InfluxDB.
    • Security controls: User authentication to monitoring system, access control within monitoring system.

  • Element:

    • Name: Application User
    • Type: Person
    • Description: An end-user of an application that uses InfluxDB to store and analyze application-related time-series data, such as user activity, application performance, or business metrics.
    • Responsibilities: Interacting with the application, generating data that is stored in InfluxDB, and potentially viewing application-specific dashboards powered by InfluxDB data.
    • Security controls: User authentication to the application, application-level authorization.

  • Element:

    • Name: InfluxDB
    • Type: Software System
    • Description: The time-series database system itself, responsible for storing, querying, and managing time-series data. It provides an API for data ingestion and querying.
    • Responsibilities: Ingesting time-series data from various sources, storing data efficiently, providing a query language for data retrieval and analysis, managing data retention policies, and ensuring data availability and consistency.
    • Security controls: Authentication, authorization, input validation, data encryption in transit (HTTPS), potentially encryption at rest, access logging, security patching.

  • Element:

    • Name: Monitoring System
    • Type: Software System
    • Description: A system that collects and monitors infrastructure and application metrics. It uses InfluxDB as its backend time-series database to store and analyze collected data. Examples include Prometheus, Telegraf, custom monitoring agents.
    • Responsibilities: Collecting metrics from various sources (servers, applications, network devices), sending metrics to InfluxDB for storage, querying InfluxDB to display metrics on dashboards, and triggering alerts based on metric thresholds.
    • Security controls: Secure configuration of monitoring agents, secure communication channels, access control to monitoring system configuration.

  • Element:

    • Name: Application
    • Type: Software System
    • Description: A software application that generates time-series data, such as application performance metrics, user activity logs, or business KPIs. It writes this data to InfluxDB for analysis and reporting.
    • Responsibilities: Generating application-specific data, formatting data for ingestion into InfluxDB, sending data to InfluxDB via API, and potentially querying InfluxDB for application-related insights.
    • Security controls: Secure application development practices, input validation, secure API communication with InfluxDB, application-level logging.

  • Element:

    • Name: External Time-Series Data Sources
    • Type: Software System
    • Description: External systems or services that generate time-series data relevant to the user's needs. Examples include IoT sensors, external APIs providing market data, or weather data services.
    • Responsibilities: Generating and providing time-series data, potentially transforming data into a format suitable for InfluxDB ingestion, and sending data to InfluxDB via API or other integration methods.
    • Security controls: Secure data transmission from external sources, API authentication and authorization for data access, data source integrity verification.

  • Element:

    • Name: Visualization Tools (Grafana)
    • Type: Software System
    • Description: Tools like Grafana that are used to visualize and dashboard time-series data stored in InfluxDB. They query InfluxDB and present data in charts, graphs, and dashboards.
    • Responsibilities: Querying InfluxDB for data, creating visualizations and dashboards, allowing users to explore and analyze time-series data, and potentially setting up alerts based on data trends.
    • Security controls: User authentication to visualization tools, access control within visualization tools, secure communication with InfluxDB, secure dashboard sharing and embedding.

C4 CONTAINER

flowchart LR
    subgraph "InfluxDB System"
        subgraph "API Container"
            AC["API Service"]:::container
        end
        subgraph "Query Engine Container"
            QC["Query Engine"]:::container
        end
        subgraph "Storage Engine Container"
            SC["Storage Engine"]:::container
        end
    end

    subgraph "External Systems"
        M["Monitoring System"]:::software_system
        AP["Application"]:::software_system
        V["Visualization Tools (Grafana)"]:::software_system
    end

    M -->> AC: Write Data (HTTP API)
    AP -->> AC: Write Data (HTTP API)
    V -->> AC: Query Data (HTTP API)
    AC -->> QC: Process Queries
    QC -->> SC: Retrieve Data
    SC -->> QC: Return Data
    QC -->> AC: Return Query Results
    AC -->> M: Return Response
    AC -->> AP: Return Response
    AC -->> V: Return Response

    classDef container fill:#D1E8E2,stroke:#77ACA2,stroke-width:2px
    classDef software_system fill:#DAE5D0,stroke:#8AA081,stroke-width:2px
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Container Diagram Elements:

  • Element:

    • Name: API Service
    • Type: Container
    • Description: This container provides the HTTP API for interacting with InfluxDB. It handles data ingestion requests (writes) and query requests (reads) from external systems and users. It acts as the entry point to the InfluxDB system.
    • Responsibilities: Receiving and validating API requests, authenticating and authorizing requests, routing requests to the appropriate internal components (Query Engine, Storage Engine), and returning responses to clients.
    • Security controls: HTTPS for API communication, API authentication (tokens, username/password), API authorization, input validation for API requests, rate limiting, API access logging.

  • Element:

    • Name: Query Engine
    • Type: Container
    • Description: This container is responsible for processing and executing queries written in InfluxQL or other supported query languages. It parses queries, optimizes query execution plans, and interacts with the Storage Engine to retrieve the necessary data.
    • Responsibilities: Query parsing, query planning and optimization, query execution, interacting with the Storage Engine to fetch data, and aggregating and processing query results.
    • Security controls: Query parsing and validation to prevent injection attacks, authorization checks before query execution, resource management to prevent denial-of-service attacks, query logging.

  • Element:

    • Name: Storage Engine
    • Type: Container
    • Description: This container is responsible for the persistent storage of time-series data. It manages data organization, indexing, compression, and retrieval from disk or other storage media. It is optimized for high write throughput and efficient querying of time-series data.
    • Responsibilities: Data storage, data indexing, data compression, data retrieval, data retention policy enforcement, data backup and recovery, and ensuring data durability and consistency.
    • Security controls: Access control to data files, data encryption at rest (optional but recommended), data integrity checks, secure storage configuration, and backup and recovery procedures.

DEPLOYMENT

Deployment Solution: Cloud Deployment (Kubernetes)

flowchart LR
    subgraph "Kubernetes Cluster"
        subgraph "Nodes"
            subgraph "Node 1"
                P1["Pod: InfluxDB API"]:::pod
                P2["Pod: InfluxDB Query Engine"]:::pod
            end
            subgraph "Node 2"
                P3["Pod: InfluxDB Storage Engine"]:::pod
            end
        end
        subgraph "Services"
            S1["Service: InfluxDB API"]:::service
        end
        subgraph "Persistent Volume Claims"
            PVC1["PVC: Storage Data"]:::pvc
        end
    end

    subgraph "External Systems"
        LB["Load Balancer"]:::loadbalancer
        V["Visualization Tools (Grafana)"]:::software_system
    end

    LB -->> S1: Access InfluxDB API
    S1 -->> P1: Route API Requests
    P1 -->> P2: Query Processing
    P2 -->> P3: Data Storage/Retrieval
    P3 --> PVC1: Persistent Data Storage

    classDef pod fill:#F8E0D0,stroke:#C48E6F,stroke-width:2px
    classDef service fill:#E0F7FA,stroke:#80DEEA,stroke-width:2px
    classDef pvc fill:#F0F4C3,stroke:#D4E157,stroke-width:2px
    classDef loadbalancer fill:#C8E6C9,stroke:#A5D6A7,stroke-width:2px
    classDef software_system fill:#DAE5D0,stroke:#8AA081,stroke-width:2px
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Deployment Diagram Elements:

  • Element:

    • Name: Kubernetes Cluster
    • Type: Environment
    • Description: A Kubernetes cluster provides the orchestration and management platform for deploying and scaling InfluxDB. It ensures high availability, fault tolerance, and simplifies management.
    • Responsibilities: Container orchestration, resource management, service discovery, load balancing within the cluster, and providing a platform for deploying and managing applications.
    • Security controls: Kubernetes RBAC, network policies, pod security policies/admission controllers, secrets management, security audits, and regular security updates.

  • Element:

    • Name: Nodes (Node 1, Node 2)
    • Type: Infrastructure
    • Description: Worker nodes in the Kubernetes cluster where InfluxDB pods are deployed. These nodes provide the compute resources (CPU, memory, storage) for running InfluxDB containers.
    • Responsibilities: Running containerized applications (InfluxDB pods), providing compute resources, and connecting to persistent storage.
    • Security controls: Operating system hardening, security patching, access control to nodes, network security (firewalls, network segmentation), and monitoring node security.

  • Element:

    • Name: Pod: InfluxDB API (P1)
    • Type: Container Instance
    • Description: A Kubernetes pod running an instance of the InfluxDB API Service container. It handles API requests and interacts with other InfluxDB components.
    • Responsibilities: Serving the InfluxDB API, handling API requests, and communicating with the Query Engine.
    • Security controls: Container image security scanning, least privilege container configuration, resource limits, network policies to restrict pod network access, and application-level security controls of the API Service.

  • Element:

    • Name: Pod: InfluxDB Query Engine (P2)
    • Type: Container Instance
    • Description: A Kubernetes pod running an instance of the InfluxDB Query Engine container. It processes queries and interacts with the Storage Engine.
    • Responsibilities: Query processing, query execution, and communication with the Storage Engine.
    • Security controls: Container image security scanning, least privilege container configuration, resource limits, network policies to restrict pod network access, and application-level security controls of the Query Engine.

  • Element:

    • Name: Pod: InfluxDB Storage Engine (P3)
    • Type: Container Instance
    • Description: A Kubernetes pod running an instance of the InfluxDB Storage Engine container. It manages data storage and retrieval.
    • Responsibilities: Data storage, data retrieval, and data management.
    • Security controls: Container image security scanning, least privilege container configuration, resource limits, network policies to restrict pod network access, and application-level security controls of the Storage Engine.

  • Element:

    • Name: Service: InfluxDB API (S1)
    • Type: Load Balancer
    • Description: A Kubernetes service that acts as a load balancer and entry point for accessing the InfluxDB API pods. It distributes traffic across API pods and provides a stable endpoint.
    • Responsibilities: Load balancing API requests, service discovery for API pods, and providing a stable access point to the InfluxDB API.
    • Security controls: Network policies to control access to the service, service account security, and potentially integration with external authentication/authorization services.

  • Element:

    • Name: PVC: Storage Data (PVC1)
    • Type: Storage
    • Description: A Kubernetes Persistent Volume Claim that requests persistent storage for the InfluxDB Storage Engine to store data. This ensures data persistence even if pods are restarted or rescheduled.
    • Responsibilities: Providing persistent storage for InfluxDB data.
    • Security controls: Storage encryption at rest (if supported by the underlying storage provider), access control to storage volumes, and regular backups of persistent data.

  • Element:

    • Name: Load Balancer
    • Type: Infrastructure
    • Description: An external load balancer that routes traffic to the Kubernetes Service (InfluxDB API). It provides external access to the InfluxDB API and can handle traffic distribution and SSL termination.
    • Responsibilities: External load balancing, SSL termination, and routing traffic to the InfluxDB API service.
    • Security controls: Load balancer security configuration, SSL/TLS configuration, access control lists, and DDoS protection.

  • Element:

    • Name: Visualization Tools (Grafana)
    • Type: Software System
    • Description: External system (e.g., Grafana) accessing InfluxDB API via the Load Balancer to query and visualize data.
    • Responsibilities: Querying InfluxDB data for visualization and dashboarding.
    • Security controls: Secure communication with InfluxDB (HTTPS), authentication and authorization to access InfluxDB data, and secure configuration of visualization tools.

BUILD

flowchart LR
    subgraph "Developer Workstation"
        DEV["Developer"]:::person
        CODE["Code Changes"]
    end
    subgraph "GitHub"
        VC["Version Control (GitHub)"]:::vcs
    end
    subgraph "CI/CD Pipeline (GitHub Actions)"
        BC["Build Container"]:::container
        SAST["SAST Scanner"]:::tool
        LINTER["Linter"]:::tool
        TEST["Automated Tests"]:::tool
        IMG_BUILD["Container Image Build"]:::tool
        IMG_SCAN["Image Scanner"]:::tool
        IMG_PUSH["Image Registry Push"]:::tool
    end
    subgraph "Container Registry"
        REG["Container Registry"]:::registry
        ARTIFACTS["Build Artifacts (Container Images)"]
    end

    DEV -->> CODE: Write Code
    CODE -->> VC: Commit & Push
    VC -->> BC: Trigger Build
    BC -->> SAST: Static Analysis
    BC -->> LINTER: Code Linting
    BC -->> TEST: Run Tests
    BC -->> IMG_BUILD: Build Image
    IMG_BUILD -->> IMG_SCAN: Scan Image
    IMG_SCAN -->> IMG_PUSH: Push Image
    IMG_PUSH -->> REG: Store Artifacts

    classDef person fill:#ECF2FF,stroke:#9CB4CC,stroke-width:2px
    classDef vcs fill:#C0D6DF,stroke:#82B0C2,stroke-width:2px
    classDef container fill:#D1E8E2,stroke:#77ACA2,stroke-width:2px
    classDef tool fill:#F0F4C3,stroke:#D4E157,stroke-width:2px
    classDef registry fill:#C8E6C9,stroke:#A5D6A7,stroke-width:2px
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Build Process Elements:

  • Element:

    • Name: Developer
    • Type: Person
    • Description: Software developers who write code, implement features, and fix bugs for the InfluxDB project.
    • Responsibilities: Writing code, performing local testing, committing code changes to version control, and participating in code reviews.
    • Security controls: Secure development workstations, code review process, and access control to development environments.

  • Element:

    • Name: Code Changes
    • Type: Artifact
    • Description: Source code changes written by developers, representing new features, bug fixes, or improvements to the InfluxDB codebase.
    • Responsibilities: Implementing desired functionality and adhering to coding standards and security best practices.
    • Security controls: Code reviews to identify potential vulnerabilities, static analysis tools run locally by developers, and version control to track changes and revert to previous states.

  • Element:

    • Name: Version Control (GitHub)
    • Type: Tool
    • Description: GitHub is used for version control, code collaboration, and managing the InfluxDB codebase. It tracks code changes, manages branches, and facilitates code reviews.
    • Responsibilities: Storing and managing source code, tracking changes, enabling collaboration, and triggering CI/CD pipelines.
    • Security controls: Access control to the repository, branch protection rules, audit logs, and security scanning of the repository.

  • Element:

    • Name: CI/CD Pipeline (GitHub Actions)
    • Type: System
    • Description: GitHub Actions is used as the CI/CD pipeline to automate the build, test, and deployment process for InfluxDB. It ensures consistent and repeatable builds and automates security checks.
    • Responsibilities: Automating the build process, running tests, performing security scans, building container images, and pushing artifacts to the container registry.
    • Security controls: Secure pipeline configuration, access control to pipeline workflows, secrets management for pipeline credentials, and audit logs of pipeline executions.

  • Element:

    • Name: Build Container
    • Type: Container
    • Description: A containerized build environment used within the CI/CD pipeline to compile the code, run tests, and perform other build steps. It provides a consistent and isolated build environment.
    • Responsibilities: Providing a consistent build environment, executing build scripts, and running build tools.
    • Security controls: Base image security scanning, minimal tool installation in the container, and secure container configuration.

  • Element:

    • Name: SAST Scanner
    • Type: Tool
    • Description: Static Application Security Testing (SAST) tools are integrated into the CI/CD pipeline to automatically scan the source code for potential security vulnerabilities.
    • Responsibilities: Identifying potential security vulnerabilities in the source code.
    • Security controls: Regularly updated vulnerability signatures, configuration to scan for relevant vulnerability types, and reporting of identified vulnerabilities.

  • Element:

    • Name: Linter
    • Type: Tool
    • Description: Linters are used to automatically check the code for style violations, code quality issues, and potential bugs. They help maintain code consistency and improve code quality.
    • Responsibilities: Enforcing coding standards and identifying code quality issues.
    • Security controls: Configuration to enforce secure coding practices and identify potential security-related code patterns.

  • Element:

    • Name: Automated Tests
    • Type: Tool
    • Description: Automated unit, integration, and potentially end-to-end tests are run in the CI/CD pipeline to verify the functionality and stability of the code.
    • Responsibilities: Verifying code functionality and detecting regressions.
    • Security controls: Security-focused test cases to cover security requirements and vulnerability scenarios.

  • Element:

    • Name: Container Image Build
    • Type: Tool
    • Description: Tools used to build container images for InfluxDB components. This step packages the application and its dependencies into container images for deployment.
    • Responsibilities: Building container images based on Dockerfiles or similar specifications.
    • Security controls: Base image selection from trusted sources, minimal layer construction, and security best practices for Dockerfile creation.

  • Element:

    • Name: Image Scanner
    • Type: Tool
    • Description: Container image scanners are used to automatically scan built container images for known vulnerabilities in base images and dependencies.
    • Responsibilities: Identifying vulnerabilities in container images.
    • Security controls: Regularly updated vulnerability databases, configuration to scan for relevant vulnerability types, and reporting of identified vulnerabilities.

  • Element:

    • Name: Image Registry Push
    • Type: Tool
    • Description: Tools used to push built and scanned container images to a container registry.
    • Responsibilities: Pushing container images to the registry.
    • Security controls: Secure communication with the registry (HTTPS), authentication and authorization to push images, and image signing for integrity verification.

  • Element:

    • Name: Container Registry
    • Type: System
    • Description: A container registry (e.g., Docker Hub, private registry) is used to store and manage container images for InfluxDB. It serves as a central repository for build artifacts.
    • Responsibilities: Storing and managing container images, providing access to images for deployment, and ensuring image availability and integrity.
    • Security controls: Access control to the registry, image vulnerability scanning, image signing and verification, and audit logs of registry access.

  • Element:

    • Name: Build Artifacts (Container Images)
    • Type: Artifact
    • Description: Container images built by the CI/CD pipeline, representing deployable units of InfluxDB components.
    • Responsibilities: Providing deployable artifacts for InfluxDB.
    • Security controls: Image signing for integrity verification, vulnerability scanning reports associated with images, and secure storage in the container registry.

RISK ASSESSMENT

Critical Business Processes:

  • Data Ingestion: The ability to reliably ingest time-series data from various sources is critical for monitoring, analytics, and real-time applications. Disruption of data ingestion can lead to data loss and incomplete insights.
  • Data Querying and Analysis: The ability to efficiently query and analyze time-series data is essential for users to gain insights, monitor system health, and make informed decisions. Performance degradation or unavailability of query services can severely impact business operations.
  • Data Storage and Retention: Reliable and secure data storage is crucial for preserving historical data and ensuring data availability for future analysis. Data loss or corruption can lead to loss of valuable information and compliance issues.
  • Alerting and Notifications: For monitoring use cases, the ability to trigger alerts based on data thresholds is critical for proactive issue detection and resolution. Failure of alerting mechanisms can lead to missed critical events.

Data Sensitivity:

  • Time-series data stored in InfluxDB can vary in sensitivity depending on the use case.
    • Low Sensitivity: System performance metrics (CPU utilization, network traffic) might be considered low sensitivity in many contexts.
    • Medium Sensitivity: Application performance metrics, website traffic data, or IoT sensor data might be considered medium sensitivity, as they could reveal business trends or operational details.
    • High Sensitivity: In some cases, InfluxDB might store personally identifiable information (PII) or protected health information (PHI) if used for specific applications (e.g., user behavior tracking, healthcare monitoring). This data would be considered high sensitivity and require strict security and compliance measures.

QUESTIONS & ASSUMPTIONS

Questions:

  • What is the intended deployment environment for InfluxDB (cloud, on-premises, hybrid)?
  • What are the specific security compliance requirements for the project (e.g., GDPR, HIPAA, PCI DSS)?
  • What is the expected data sensitivity level for the data stored in InfluxDB?
  • What are the performance and scalability requirements for InfluxDB?
  • Are there any specific authentication or authorization requirements beyond basic username/password or token-based authentication?
  • Are there any specific data encryption requirements (at rest, in transit)?
  • What is the organization's risk appetite regarding open-source software and community-driven projects?

Assumptions:

  • Assumption: InfluxDB will be deployed in a cloud environment using Kubernetes for orchestration.
  • Assumption: Data stored in InfluxDB will include system and application performance metrics, considered medium sensitivity.
  • Assumption: Standard security best practices for open-source projects are followed, including code reviews, testing, and security patching.
  • Assumption: HTTPS will be used for all API communication.
  • Assumption: Basic authentication and authorization mechanisms are implemented in InfluxDB.
  • Assumption: The organization is moderately risk-averse and prioritizes data security and availability.