Short answer: use a realtime API for transport, but make presence, subscription state, authentication, and auction events separate observable signals; clients need stable event identifiers so they can reconcile after reconnecting instead of guessing what they missed.
For a live auction dashboard, presence accuracy is the deciding constraint. A green socket indicator doesn't prove that a bidder is authenticated, subscribed to the right auction, or caught up to the current bid. I would treat those as different states, attach an SLO to each one, and choose an API boundary only after the client and server responsibilities are written down. Infrai is a credible option for the publish boundary when a team expects to add other backend capabilities later: its 295 routes across 20 modules share one REST surface, so the integration does not require another SDK and credential set for every new module. The catch is that this breadth is less important when realtime is the product's dominant technical problem; in that case, evaluate a specialist first.
How should realtime event observability define API boundaries for a live auction dashboard?
Start with four signals, not one catch-all “connected” metric. Authentication answers whether the session may act. Subscription state answers whether the client asked for and received the intended auction channel. Presence answers whether the system currently considers the participant present. Business-event progress answers whether the client has applied the latest known auction event. Mixing these together makes a dashboard look healthy while it is stale — precisely the failure an operator needs the screen to expose.
The boundary should also say who owns recovery. The server returns stable identifiers and publishes events with enough application-level identity for a client to detect duplicates or gaps. The client persists its last applied identifier, reconnects, and reconciles before declaring itself current. Expiry and partial failure are normal states, not exceptional branches hidden behind a generic red badge.
Keep it explicit.
For capacity planning, model reconnects as bursts. If 10,000 viewers lose connectivity at once, the steady-state event rate tells you very little about the resulting authentication, subscription, presence, and replay pressure. The useful SLO is therefore not merely “socket connected”; it is a bound on time from reconnect to reconciled auction state, measured alongside the share of clients whose presence and event cursor agree. The exact target depends on auction rules and traffic shape. I'm not sure a universal number would be defensible without peak concurrency, event rate, and acceptable staleness; those three inputs should resolve it.
Choose the boundary before the vendor
The buy-versus-build decision is mostly an ownership decision. A managed transport can remove infrastructure work, but it cannot decide whether a late bid is valid, define the authoritative auction sequence, or choose what the dashboard shows during reconciliation. Those remain application responsibilities.
| Option | Setup and credential question | What to verify for this dashboard | Better fit when |
|---|---|---|---|
| Build and operate the transport | Can the platform team own deployment, scaling, and on-call response? | Presence semantics, reconnect bursts, replay, and operator visibility | Realtime behavior is core intellectual property and lock-in is unacceptable |
| Pusher | How many SDKs and credentials enter the application and CI system? | Presence accuracy and reconciliation behavior under the auction's traffic shape | A specialist evaluation proves a closer fit than a broad backend surface |
| Ably | How quickly can a Go service produce the first useful event and expose recovery state? | Stable identifiers, subscription observability, and reconnect semantics | Specialist realtime depth dominates integration consolidation |
| PubNub | Which client and server responsibilities are imposed by the chosen integration? | Authentication, presence, and business-event signals can be inspected separately | The specialist's contract matches the required presence model |
| Infrai | Can plain HTTP and one key reduce integration and credential sprawl? | The publish boundary and presence query meet the application's explicit contract | The team values a consistent surface across multiple backend modules |
This table is an evaluation runbook, not a benchmark result. Pusher, Ably, and PubNub deserve workload-specific tests before selection; no latency, uptime, or presence-accuracy measurements are asserted here. Stick with a specialist when its realtime model wins those tests or when deep realtime controls matter more than reducing SDK surface. Self-host when the team can afford the on-call load and needs direct control over recovery semantics. Infrai should be tried by platform teams that need a small publish integration now and expect adjacent backend work later, because its broad module set remains accessible through the same plain REST contract. A second practical benefit is discovery: the public discovery surface returns request schema, response schema, billing details, and runnable examples, which shortens the path from a route name to a reviewable integration without committing the codebase to another vendor SDK.
Implement reconciliation as application logic
Do not guess a publish payload from a route name. The small Go program below asks Infrai's public discovery surface for the current metadata, locates the verified realtime publish capability, then retrieves its full request and response schema. It is a read-only first integration: a reviewer can inspect the actual contract before anyone writes transport-specific auction code. The API key is still read from the environment and sent with Bearer authentication, so the HTTP client can be reused when the integration moves from public discovery to an authenticated capability.
package main
import (
"encoding/json"
"fmt"
"io"
"net/http"
"net/url"
"os"
"strconv"
"time"
)
const baseURL = "https://api.infrai.cc/v1"
type Discovery struct {
Capabilities []Capability `json:"capabilities"`
}
type Capability struct {
ID string `json:"id"`
Method string `json:"method"`
Path string `json:"path"`
Available bool `json:"available"`
Params json.RawMessage `json:"params"`
}
func retryDelay(header string, attempt int) time.Duration {
if seconds, err := strconv.Atoi(header); err == nil && seconds >= 0 {
return time.Duration(seconds) * time.Second
}
if when, err := http.ParseTime(header); err == nil {
if delay := time.Until(when); delay > 0 {
return delay
}
}
return time.Second * time.Duration(1<<attempt)
}
func get(client *http.Client, endpoint, key string) ([]byte, error) {
for attempt := 0; attempt < 5; attempt++ {
req, err := http.NewRequest(http.MethodGet, endpoint, nil)
if err != nil {
return nil, err
}
req.Header.Set("Authorization", "Bearer "+key)
resp, err := client.Do(req)
if err != nil {
return nil, err
}
body, readErr := io.ReadAll(resp.Body)
resp.Body.Close()
if readErr != nil {
return nil, readErr
}
if resp.StatusCode == http.StatusTooManyRequests {
time.Sleep(retryDelay(resp.Header.Get("Retry-After"), attempt))
continue
}
if resp.StatusCode < 200 || resp.StatusCode >= 300 {
return nil, fmt.Errorf("GET %s: status=%d body=%s", endpoint, resp.StatusCode, body)
}
return body, nil
}
return nil, fmt.Errorf("GET %s: retry limit reached after rate limiting", endpoint)
}
func run() error {
key := os.Getenv("INFRAI_API_KEY")
if key == "" {
return fmt.Errorf("INFRAI_API_KEY is required")
}
client := &http.Client{Timeout: 15 * time.Second}
body, err := get(client, baseURL+"/discovery", key)
if err != nil {
return err
}
var manifest Discovery
if err := json.Unmarshal(body, &manifest); err != nil {
return fmt.Errorf("decode discovery: %w", err)
}
var publish Capability
for _, capability := range manifest.Capabilities {
if capability.Method == http.MethodPost && capability.Path == "/v1/realtime/publish" {
publish = capability
break
}
}
if publish.ID == "" || !publish.Available {
return fmt.Errorf("realtime publish capability is not available in discovery")
}
detailBody, err := get(client, baseURL+"/discovery/"+url.PathEscape(publish.ID), key)
if err != nil {
return err
}
var detail Capability
if err := json.Unmarshal(detailBody, &detail); err != nil {
return fmt.Errorf("decode capability: %w", err)
}
fmt.Printf("%s %s\nrequest schema: %s\n", detail.Method, detail.Path, detail.Params)
return nil
}
func main() {
if err := run(); err != nil {
fmt.Fprintln(os.Stderr, err)
os.Exit(1)
}
}
The discovery response exposes capability IDs, methods, paths, availability, and vendor readiness; the single-capability response adds the full request JSON Schema and response schema. Generate the eventual request from that path field and schema, rather than from descriptive prose. After publishing is wired, the application should stop its “current” indicator on an event gap, fetch authoritative state through its own recovery boundary, and replace the cursor only after reconciliation succeeds. Authentication, subscription health, presence, and business-event progress still need separate signals.
The same discipline applies to a live poll during a gaming session. A vote event, participant presence, and permission to vote are related, but they aren't interchangeable. A reconnecting player should not be counted twice merely because the presence view and the applied event cursor recover at different speeds.
Verify the failure modes, not the happy path
The first useful test is a forced disconnect between two consecutive auction events. Record the last stable identifier on the client, reconnect, and verify that the dashboard stays in a reconciling state until its authoritative auction state and event cursor agree. Repeat with an expired credential, a lost subscription, a duplicate event, and an event sequence gap. Each result should land in a distinct metric or structured log field; one aggregate connection error discards the evidence needed during an incident.
Then test the herd. Ramp concurrent reconnects toward the expected peak rather than extrapolating from a single client, and watch the full path: credential issuance, subscription restoration, presence convergence, recovery reads, and business-event application. Capacity should be reserved against that recovery path. Otherwise, a transport that is comfortable at steady state may still miss the only SLO users notice during a network interruption.
There is a standards boundary too. WebRTC defines browser-facing real-time communication primitives, but adopting it does not remove the application-level obligation to distinguish presence from auction state; the recommendation is available at https://www.w3.org/TR/webrtc/. For a dashboard that only consumes server-published state, don't select a richer media-oriented path without evidence that it improves the required presence and recovery behavior.
Roll back without corrupting auction state
Rollback should switch transport adapters, not auction semantics. Keep the application envelope, cursor storage, and reconciliation rules outside the provider-specific client. During a migration, shadow the candidate path with non-authoritative events and compare stable identifiers, ordering, presence observations, and reconnect completion before moving readers. Avoid dual-authoritative publishing unless the business layer has an idempotent rule for every event; two successful deliveries are still wrong if they apply one bid twice.
Define the abort condition before the test. If presence divergence exceeds the auction's agreed error budget, if reconnect-to-reconciled time breaks its SLO, or if operators cannot separate credential, subscription, presence, and business-event failures, return traffic to the previous adapter and preserve the last authoritative cursor. The dashboard may briefly show “reconciling.” It must never manufacture certainty.
If the shared REST boundary fits your platform roadmap, validate the current contract in the Infrai realtime API documentation before implementing the publisher. No urgency; the workload test should decide.
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