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DNS-collector captures DNS telemetry from DNStap, live traffic, or log files, processes it, and routes it to outputs such as JSON, PCAP, Fluentd, or MQTT. Choose a format and destination based on what the receiving system can parse—and check buffering and outage behavior before relying on a pipeline for continuous delivery.
What does DNS-collector do?
DNS-collector is software for capturing, processing, and routing DNS telemetry. Its documented inputs include DNStap, live capture, and log files; it can then emit records in several formats or forward them to a destination. The project README describes the tool and lists supported DNS servers including BIND, PowerDNS, and Unbound.
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Which DNS-collector output format should I choose?
Start with the consumer: how it parses records, what you need to inspect later, and whether readable output is more important than retaining structured or packet-level data. The project’s output-format documentation describes these options:
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|---|---|---|
| Text | Human-readable output with customizable rendering. | Text-oriented output can replace non-UTF-8 characters. |
| Nested JSON | Consumers that natively support nested objects. | DNS-collector documentation claims nested JSON generation in Go is about 3.4 times faster than flat JSON generation; this is an encoding comparison, not an end-to-end pipeline benchmark. |
| Flat JSON | Indexing and analytics systems such as Elasticsearch, Loki, OpenSearch, ClickHouse, or Grafana. | Flattening changes the representation of structured fields and lists; check how the destination parses those fields. |
| Jinja templates | Custom rendered output. | Choose it when the consumer needs a tailored representation. |
| PCAP | Wireshark, traffic analysis, and network troubleshooting. | The documented capture maps DoH, DoT, and DoQ to UDP port numbers without encryption; do not assume it is a byte-for-byte record of encrypted application payloads. |
| DNStap | Forwarding to another DNStap-compatible consumer. | Check that the receiving system supports the format. |
Preserve binary or unusual field values
DNS textual fields such as qname and rdata are processed as UTF-8 strings. The format guide warns that non-UTF-8 characters—including raw binary values in TXT records—may be replaced in Text or JSON output. If the original bytes matter, configure the Data Extractor transformer’s base64-fields or hex-fields options so the values survive in encoded form.
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How should I think about performance and buffers?
The project’s pipeline buffering guide documents these defaults under global.worker:
| Setting | Documented default | What it controls |
|---|---|---|
buffer-size |
512 batches | Capacity for buffered batches. |
batch-size |
64 messages | Number of messages grouped in a batch. |
flush-interval-ms |
10 ms | How often buffered data is flushed. |
Batching is intended to reduce channel contention, context switching, and allocations. The guide claims a 40% speedup versus unbatched processing for its batch-size 64 description; that is a project documentation claim, not an independent measurement. Its buffer-sizing suggestions are recommendations, not guarantees for every workload. Larger buffers can help absorb bursts, but they do not fix a sink that remains too slow to keep up.
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Likewise, the documentation’s roughly 3.4× nested-versus-flat JSON figure concerns generation, not the complete path to a disk or network destination. End-to-end throughput can be limited by disk I/O and network latency, so treat encoding comparisons as one factor rather than a capacity promise.
Why is DNS-collector dropping packets?
A warning that a logger buffer is full alongside packet drops indicates buffer exhaustion. The logger or destination may be unable to accept records quickly enough. Check the sink’s latency and ingestion rate as well as collector settings.
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- Inspect the collector and destination logs for buffer-full warnings, disconnects, or delayed ingestion.
- If bursts exceed available buffering, consider increasing
buffer-size; the project guide gives 1024 and 2048 as example values. - If the destination can accept more concurrent work, scale logger workers and tune sink-side batch ingestion.
- Review the logger-specific outage and retry behavior before assuming that a larger in-memory buffer makes delivery durable.
When file output is delayed
Review the file logger’s configured mode, batching, flush interval, rotation, and optional compression. Its file-output documentation says compression runs asynchronously after rotation and only one compression task runs at a time. Check disk capacity and whether post-rotation compression is queuing work alongside the collector’s flush behavior.
When text fields look corrupted
If a value is replaced or unexpectedly altered in Text or JSON, check whether it contains non-UTF-8 or binary data. Use the Data Extractor’s base64 or hex field options when preserving original bytes is required.
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How do Fluentd and MQTT behave during an outage?
Do not assume every logger retries or buffers in the same way. The official Fluentd logger guide documents memory-only buffering: when the connection is unavailable, messages are dropped; during reconnection, incoming messages are discarded and buffering is paused. This is not disk-persistent delivery.
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How do I choose an integration?
DNS-collector documentation spans DNS servers, analytics destinations, and message systems. The README lists BIND, PowerDNS, and Unbound; the format guide names Elasticsearch, Loki, OpenSearch, ClickHouse, and Grafana; dedicated logger guides cover Fluentd and MQTT.
- Consumer fit: Check whether the destination handles nested or flat records, needs indexed fields or dashboards, or requires packet-analysis data.
- Backpressure and outages: Establish buffer capacity, persistence behavior, message dropping, and retry policy for the specific logger.
- Latency and batching: Balance flush interval and batch size against the destination’s ingestion behavior and the latency your use case can tolerate.
- Security and deployment: Verify the chosen logger’s TLS settings and any certificate, trust-root, or client-authentication requirements.
Logger behavior and exact settings can differ by integration and version. Consult the current logger-specific documentation for the version you deploy before applying configuration values.
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