Real-Time Application Development

Real-time software for events users must see and act on now

We build real-time application features for live operations, collaboration, tracking, alerts, and state synchronisation. The work starts by defining freshness, ordering, delivery, reconnection, permissions, scale, and degraded behaviour, then choosing WebSocket, server-sent events, webhooks, queues, or simpler polling. Real-time delivery reduces delay; it does not make upstream data correct.

See our work

Bring the problem, the current workflow, or the existing code. We reply with a practical next step within one business day.

The brief

Start with what is not working.

Good software decisions begin with the constraint, not a list of features or a preferred technology.

01

Users refresh dashboards or wait for scheduled jobs while an operational event is already changing what they should do?

02

A WebSocket prototype works with a few users but cannot explain ordering, missed events, reconnects, fan-out, backpressure, or recovery?

Plain answer

Real-time application development delivers events to users or systems within an agreed freshness window using WebSocket, server-sent events, webhooks, queues, or streams. RaftLabs defines ordering, delivery, reconnect, recovery, security, and load behaviour before building. A focused workflow starts at $20,000 and commonly takes 8 to 12 weeks.

The dashboard was live until the network blinked.

After reconnect, some users saw a stale snapshot, others received events twice, and nobody knew whether the red status meant a fresh incident or an old message.

Real-time engineering is mostly about what happens between updates.

Real time is a contract about delay and failure

The label means little without a freshness window. A collaboration cursor may tolerate hundreds of milliseconds. An operational dashboard may tolerate seconds. A background status update may need only a minute. The architecture should match the decision a delayed event could change.

This page remains distinct from general custom software development because it addresses persistent connections, event semantics, state synchronisation, recovery, and load. It also sets a boundary: device connectivity management belongs on the IoT connectivity platform page, while a normal request-response application belongs with web development.

A live workflow with explicit service limits

Event contract first
1
Freshness, order, delivery, identity, recovery, permissions, and ownership
Indicative delivery weeks
8-12
After producers, consumers, environments, and test data are ready
Starting investment
$20K
Fixed after concurrency, protocol, infrastructure, and test scope are known

Performance claims require a configuration and workload. We report observed behaviour for the tested environment, traffic model, regions, payloads, dependencies, and failure cases. Product owners still decide the acceptable delay, loss, duplicate, stale state, and degraded experience.

Use real-time engineering when delay changes a user action.

Prefer refresh, polling, or scheduled processing when a slower path is simpler and adequate.

A fit
01

Users collaborate, monitor, track, dispatch, trade, communicate, or respond to events inside a defined freshness window.

02

The team can identify event producers, consumers, ownership, recovery rules, expected concurrency, and degraded behaviour.

03

Persistent connections, event fan-out, replay, or synchronisation are material product or operational requirements.

Not a fit
01

The data changes rarely and a refresh button, short polling interval, or scheduled job meets the user need.

02

Upstream data is unreliable and the proposed live interface would only display wrong information sooner.

03

The requirement is described as zero latency, infinite scale, perfect delivery, or exactly once without a bounded business definition.

System scope

What one live workflow may include

  • 01

    Event and state model

    Define event names, schemas, identifiers, producers, consumers, sequence, timestamps, snapshots, retention, compatibility, and ownership. Separate facts from commands and transient presence from durable business state.
  • 02

    Transport and fan-out

    Choose WebSocket, SSE, webhook, queue, stream, or polling by direction and tolerance. Implement authentication, subscriptions, brokers, partitions, routing, heartbeats, quotas, and backpressure around measured needs.
  • 03

    Client synchronisation and experience

    Handle optimistic updates, conflicts, presence, stale indicators, offline state, reconnect, missed-event recovery, permissions, and device or browser lifecycle. Where shared editing needs CRDT or operational transformation, it is scoped explicitly.
  • 04

    Reliability and operations

    Add idempotency, acknowledgements, retry, dead-letter handling, replay, reconciliation, dashboards, alerts, tracing, capacity tests, deploy strategy, incident runbooks, and service limits.

Choose the update model

PatternUse it when
Refresh or pollingSimple request-response updatesChanges are infrequent and small delays or redundant requests are acceptable.
Server-sent eventsOne-way server updates over HTTPBrowsers mainly receive a stream and do not need bidirectional messages.
WebSocketLong-lived bidirectional connectionInteractive messaging, collaboration, presence, or low-delay commands justify connection state.
Queue or event streamDurable backend distributionServices need buffering, replay, independent consumption, and operational decoupling.

Degraded behaviour belongs in the product design

When a connection drops, a spinner is not a recovery plan. The interface should tell users when data was last confirmed, whether a request is queued, which edits conflicted, and what can still be trusted. Reconnect storms after an outage need jitter and capacity protection. Slow consumers need batching, dropping, resync, or disconnection rules.

Event-driven backends also need business reconciliation. A message acknowledgement can confirm transport without proving the downstream state is correct. For money, inventory, entitlement, or other important workflows, periodic comparison with the system of record may matter more than an elegant delivery claim.

Delivery

From event contract to observable live workflow

Four phases make the timing, recovery, and operating model testable.

  1. Phase 1
    01

    Define events and user tolerance

    Map producers, consumers, payloads, identity, freshness, ordering, duplicates, permissions, concurrency, disconnection, degraded behaviour, and business ownership.

  2. Phase 2
    02

    Prove protocol and capacity

    Choose polling, SSE, WebSocket, webhooks, queues, or streams through a thin path; test fan-out, reconnect, backpressure, latency, and cost assumptions.

  3. Phase 3
    03

    Build workflow and recovery

    Implement event contracts, state synchronisation, product UI, acknowledgements, retries, idempotency, replay, observability, security, and failure handling.

  4. Phase 4
    04

    Load test release and hand over

    Exercise realistic traffic and faults, stage rollout, verify service objectives, document runbooks and limits, and transfer or support operations.

Constraints

What the architecture record must settle

Delivery semantics
Define where at-most-once, at-least-once, deduplication, ordering, idempotency, replay, and reconciliation apply.
Connection lifecycle
Cover authentication refresh, heartbeats, sleep, network changes, proxies, timeouts, reconnect backoff, resume, and stale-state display.
Capacity and dependency
Record traffic model, burst, payload, regions, brokers, storage, downstream limits, quotas, load-test environment, and headroom.
Operations
Set service objectives, dashboards, alerts, deploy and rollback, incident roles, support hours, retention, privacy, security, and cost ownership.

Scope and price

A focused real-time workflow starts at $20,000.

Start with one event family, producer, consumer experience, service target, recovery path, and operating owner.

The proposal separates engineering from cloud, broker, network, observability, vendor, on-call, and support costs.

Starting investment

Starts at $20,000

A focused release commonly takes 8 to 12 weeks. Collaboration, durable replay, several regions, large connection counts, device fleets, or regulated data add scope.

Tested assumptions

Capacity results name the environment and workload rather than becoming an unqualified scale promise.

Visible degraded state

Reconnect, stale data, retries, and recovery are designed as product behaviour, not hidden implementation details.

Choose the wider platform path

Common questions

Not necessarily. Polling may be enough for infrequent changes. Server-sent events suit server-to-client streams. Webhooks notify other systems. WebSocket supports bidirectional, long-lived interaction. Queues and streams distribute backend events. A product may use several. We choose from freshness, direction, connection count, browser or mobile behaviour, intermediaries, delivery semantics, team skills, infrastructure, and cost.

Distributed systems rarely offer a useful universal exactly-once guarantee. We define the required boundary, then use identifiers, sequence data, idempotent consumers, acknowledgements, retries, durable storage, replay, deduplication, and reconciliation as needed. Ordering may be global, per entity, or unnecessary. The product must specify what a duplicate, delay, omission, or reorder means to the workflow.

Clients resume from a known cursor, sequence, timestamp, or state version where the architecture supports it. The server may replay retained events or return a fresh snapshot followed by changes. We test suspended mobile apps, expired credentials, network switching, long disconnects, deploys, partial outages, and retention gaps. The interface shows stale or reconnecting state rather than pretending it is current.

We model realistic connection ramps, active versus idle users, message sizes, event bursts, subscriptions, regions, authentication, fan-out, slow consumers, reconnect storms, and downstream limits. Load tests run against an agreed environment with observable client and server measures. Results apply to that configuration and scenario; they are not a permanent guarantee against different traffic or dependencies.

A focused workflow starts at $20,000 and commonly takes 8 to 12 weeks. Collaboration algorithms, several regions, durable replay, high concurrency, device networks, strict latency, regulated data, or complex legacy integration add scope. The proposal separates engineering from cloud, broker, network, monitoring, third-party, on-call, and ongoing support costs.

Work with us

Which event reaches the user too late?

Bring the producers, consumers, payloads, current delay, freshness target, concurrency, network conditions, ordering needs, recovery rules, and operating owner.

  • Scope and cost agreed before work starts. No surprises. No obligation.
  • Working prototype within 3 weeks of kickoff.
  • Pay by milestone. You see progress before each invoice.
  • 60-day post-launch warranty. Bug fixes, UI tweaks, and deployment support. No retainer.
  • All conversations are NDA-protected.