DNS and CrateDB Integration

Input and output integration overview

The DNS plugin enables users to monitor and gather statistics on DNS query times, facilitating performance analysis of DNS resolutions.

The CrateDB plugin facilitates the writing of metrics to a CrateDB database, leveraging its PostgreSQL-compatible protocol to ensure a seamless experience for users.

Integration details

DNS

This plugin gathers DNS query times in milliseconds, utilizing the capabilities of DNS queries similar to the Dig command. It provides a means to monitor and analyze DNS performance by measuring the response time from specified DNS servers, allowing network administrators and engineers to ensure optimal DNS resolution times. The plugin can be configured to target specific servers and customize the types of records queried, encompassing various DNS features such as resolving domain names to IP addresses, or retrieving details from specific records as needed, while also clearly reporting on the success or failure of each query, alongside relevant metadata.

CrateDB

This plugin writes to CrateDB via its PostgreSQL protocol, allowing for metrics to be efficiently stored in a scalable database. CrateDB is designed for high-speed analytics, supporting time-series data and complicated queries, making it ideal for applications that require fast ingestion and analysis of large datasets. By utilizing the PostgreSQL protocol, the CrateDB output plugin ensures compatibility with existing PostgreSQL client libraries and tools, enabling a smooth integration for users who are already familiar with PostgreSQL’s ecosystem. The plugin provides options such as automatic table creation, connection parameters, and query timeouts, offering flexibility in how metrics are handled and stored within the database.

Configuration

DNS

[[inputs.dns_query]]
  servers = ["8.8.8.8"]

  # network = "udp"

  # domains = ["."]

  # record_type = "A"

  # port = 53

  # timeout = "2s"

  # include_fields = []
  

CrateDB

[[outputs.cratedb]]
  ## Connection parameters for accessing the database see
  ##   https://pkg.go.dev/github.com/jackc/pgx/v4#ParseConfig
  ## for available options
  url = "postgres://user:password@localhost/schema?sslmode=disable"

  ## Timeout for all CrateDB queries.
  # timeout = "5s"

  ## Name of the table to store metrics in.
  # table = "metrics"

  ## If true, and the metrics table does not exist, create it automatically.
  # table_create = false

  ## The character(s) to replace any '.' in an object key with
  # key_separator = "_"

Input and output integration examples

DNS

1. Monitor DNS Performance for Multiple Servers: By deploying the DNS plugin, a user can simultaneously monitor the performance of different DNS servers, such as Google DNS and Cloudflare DNS, by specifying them in the servers array. This scenario enables comparisons of response times and reliability across different DNS providers, assisting in selecting the best option based on empirical data.

2. Analyze Query Times for High-Traffic Domains: Integrate the plugin to measure response times specifically for high-traffic domains relevant to an organization’s operations, such as internal services or customer-facing sites. By focusing on performance metrics for these domains, organizations can proactively address latency issues, ensuring service reliability and improving user experiences.

3. Alerting on DNS Timeouts: Utilize the plugin in combination with alerting systems to notify administrators whenever a DNS query exceeds a defined timeout threshold. This setup can help in proactive troubleshooting of networking issues or server misconfigurations, fostering a rapid response to potential downtime scenarios.

4. Gather Historical Data for Performance Trends: Use the plugin to collect historical data on DNS query times over extended periods. This data can be used to analyze trends and patterns in DNS performance, enabling better capacity planning, identifying periodic issues, and justifying infrastructure upgrades or changes to DNS architectures.

CrateDB

1. Real-Time Analytics for IoT Devices: Collect and store metrics from thousands of IoT devices. By setting up a dynamic metrics table for each device, users can perform real-time analytics on the collected data, enabling quick insights into device performance, patterns, and potential failures. This setup benefits from CrateDB’s ability to handle high-throughput data ingestion while providing the necessary analytics capabilities to derive actionable insights.

2. Website Performance Monitoring: Track key performance metrics from web applications, such as request latency and user activity. By storing metrics in CrateDB, teams can leverage the power of SQL-like queries to analyze traffic patterns, user engagement, and server performance over time, leading to optimized application performance and enhanced user experiences.

3. Financial Transaction Analysis: Manage large volumes of financial transaction data for real-time fraud detection and analysis. With CrateDB’s scalable infrastructure, users can store, query, and analyze transaction metrics efficiently, allowing for the detection of anomalies and illicit activities based on transaction patterns and trends.

Feedback

Thank you for being part of our community! If you have any general feedback or found any bugs on these pages, we welcome and encourage your input. Please submit your feedback in the InfluxDB community Slack.