Distributed-systems analyzer

See every request, decrypted, across your whole stack.▌

Spider captures traffic at the kernel with eBPF and AF_PACKET, decrypts it, and reconstructs it into one correlated trace, so troubleshooting your distributed system stops being guesswork.

Try the live demo See pricing Explore the docs site →

◆ eBPF capture · no code changes · HTTP · gRPC · Redis · PostgreSQL · Kafka

Spider Analyzer communication grid: protocols correlated into one timeline
0 code changes × 5 wire protocols → 1 correlated timeline

What Spider does

Built to end the guesswork

[ tls ]

Decrypt without the guesswork

eBPF uprobes lift TLS keys straight from OpenSSL and goTLS secrets from Go binaries, so traffic is decrypted with zero code changes.

[ trace ]

One trace, five protocols

HTTP, gRPC, Redis, PostgreSQL and Kafka reconstructed into a single timeline, correlated end to end.

[ map ]

Automatic cluster map

eBPF traces and resolves every network call in the cluster, so you see what talks to what with no configuration.

[ ebpf ]

Agentless by design

Kernel-level capture. No instrumentation, no libraries, no language lock-in. Deploy probes from the UI in a few clicks.

[ infra ]

Runs on your infra

Helm and Docker, on-prem or SaaS, with IAM and data segregation. Your traffic never leaves your cluster.

[ business ]

Search it in your language

Tags and plugins resolve raw wire data into customers, orders and products, pulled from your own business APIs.

See how →

How it works

Four steps, no instrumentation

  1. 1

    Capture

    eBPF probes sniff traffic in-kernel across your pods. No agents in your code.

  2. 2

    Decrypt

    TLS keys lifted from OpenSSL and Go memory reconstruct the plaintext session.

  3. 3

    Parse

    Protocol parsers rebuild every request and response, correlated end to end.

  4. 4

    Visualize

    Timelines, maps and a searchable trace of what actually happened.

The signature move

From raw wire to business meaning

Five protocols converge into one correlated trace. Then tags and plugins resolve every raw identifier into the customers, orders and products your business actually thinks in.

Every protocol, one trace

HTTPS gRPC Redis PostgreSQL Kafka + more

These five are just the start - more protocols are on the way.

↓
search ▸ clientId:  c-452002 Acme corp 5 matches
time proto contenttemplate clientId orderId
10:24:07 gRPC orderservice.createOrder Create an Order c-452002 Acme corp o-125689 Blue pin - x12 - €149.00
10:24:07 PSQL INSERT INTO ORDERS Save order c-452002 Acme corp o-125689 Blue pin - x12 - €149.00
10:24:08 Redis SET cart.cache.4567 Update cart c-452002 Acme corp o-125689 Blue pin - x12 - €149.00
10:24:08 HTTPS POST /transactions/ Send payment c-452002 Acme corp o-125689 Blue pin - x12 - €149.00
10:24:09 Kafka Produce order.placed Confirm fulfilment c-452002 Acme corp o-125689 Blue pin - x12 - €149.00

◆ resolved live by tags + plugins, against your own business APIs

Ready to see it on real traffic?

Spin up the live demo and watch your protocols correlate into one trace.

Try the live demo Explore the docs site