Web scraping is fragile, slow, and legally risky — not ideal for startups that need reliable data pipelines for their MVPs. Golang, combined with libraries like gopacket, allows you to capture and process raw network packets directly, giving you speed, scalability, and control without depending on third-party HTML structures. In this guide, we’ll explore why Golang is perfect for this job, walk through a complete packet capture workflow, and show how you can turn it into a scalable MVP feature for analytics, monitoring, or security use cases.
If you’ve ever built a startup MVP that relies on external data, you’ve probably thought about web scraping.
At first glance, scraping seems like a quick hack:
The problem? It doesn’t scale.
Here’s why:
When you’re in the build fast, prove value phase of your startup, you need a data pipeline that is:
That’s where network packet capture comes in — and why we recommend Golang for building it.
Network packet capture works at a lower level than scraping. Instead of asking a browser to load a page, you read the raw packets traveling over your network interface.
Benefits:
For startups building MVPs in fintech, IoT, SaaS monitoring, or security, packet capture lets you build advanced features faster and with more reliability than scraping.
At Zenithive, we’ve built MVP backends using many languages — Python, Node.js, Java — but Golang consistently delivers better performance for packet capture systems.
Here’s why Golang works so well:
We’ll walk through building a minimal but real-world-ready packet capture system in Go.
Our MVP will:
You’ll need:
go get github.com/google/gopacket
go get github.com/google/gopacket/pcap
Also, make sure libpcap is installed:
sudo apt-get install libpcap-dev # Ubuntu/Debian
brew install libpcap # macOS
package main
console.log( 'Code is Poetry' );import (
"fmt"
"log"
"time"
"github.com/google/gopacket"
"github.com/google/gopacket/pcap"
)
func main() {
device := "eth0" // Change this to your interface
snapshotLen := int32(1024)
promiscuous := false
timeout := 30 * time.Second
=
handle, err := pcap.OpenLive(device, snapshotLen, promiscuous, timeout)
if err != nil {
log.Fatal(err)
}
defer handle.Close()
packetSource := gopacket.NewPacketSource(handle, handle.LinkType())
for packet := range packetSource.Packets() {
fmt.Println("Captured packet:", packet)
}
}
Run with:
sudo go run main.go
You’ll start seeing packet info in your terminal.
Let’s say your MVP only needs TCP traffic:
filter := “tcp”
err = handle.SetBPFFilter(filter)
if err != nil {
log.Fatal(err)
}
fmt.Println(“Now capturing only TCP packets…”)
This uses BPF (Berkeley Packet Filter) syntax, so you can also filter for udp, port 80, or combinations.
for packet := range packetSource.Packets() {
networkLayer := packet.NetworkLayer()
transportLayer := packet.TransportLayer()
if networkLayer != nil && transportLayer != nil {
fmt.Printf("[%s] %s → %s | Protocol: %s\n",
time.Now().Format("15:04:05"),
networkLayer.NetworkFlow().Src(),
networkLayer.NetworkFlow().Dst(),
transportLayer.LayerType(),
)
}
}
This turns raw packets into readable insights like:
[14:32:10] 192.168.1.5 → 142.250.182.78 | Protocol: TCP
You can integrate with:
Example: storing in PostgreSQL
// Pseudo-code: insert packet details into DB
db.Exec(“INSERT INTO packets (src_ip, dst_ip, protocol, timestamp) VALUES ($1, $2, $3, $4)”,
srcIP, dstIP, protocol, time.Now())
Scaling This into a Real MVP
Once you have packet capture working, you can expand it into full MVP features:
Capture and analyze packets to detect unusual patterns — e.g., DDoS attempts or unauthorized access.
Track when devices go offline or start sending unusual amounts of data.
Measure response times, dropped packets, and network jitter for your app.
Store packet logs to meet industry regulations in finance or healthcare.
For startups, the safe rule is: capture only your own app’s traffic or traffic from systems you control.
Q: Can this run in the cloud?
Yes. Deploy it on your cloud VM or Kubernetes node to monitor container traffic.
Q: How much traffic can Golang handle?
With goroutines and buffered channels, millions of packets/sec are possible.
Q: Can I use this for encrypted traffic?
You can capture encrypted packets, but you won’t read payloads without the keys. You can still use metadata for analysis.
At Zenithive, we help startups build Golang-powered MVP backends that are battle-ready — whether you need packet capture, data analytics pipelines, or full-stack deployment. If your MVP needs to capture and process data without the fragility of scraping, let’s talk.
