tokoserver
Managed event streaming

Apache Kafka

Move every event to the systems that need it, as it happens.

Build a durable event backbone for services, analytics, and data platforms without taking on the full operational weight of Kafka. Tokoserver gives your team a managed foundation for producing, retaining, and consuming event streams.

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Live architecture
Event producers
Apps, services, and devices
Apache Kafka
Healthy
Real-time analytics
Microservices
Data platforms
Managed by tokoserver Operational

Product capabilities

A dependable backbone for event-driven systems.

Connect producers and consumers through persistent streams, then grow throughput by partitioning work across your applications.

Managed Kafka foundation

Start with a prepared Kafka service instead of spending your first sprint assembling and maintaining brokers.

Partitioned throughput

Distribute event traffic across partitions so busy streams can scale with growing producer and consumer workloads.

Replicated event data

Use Kafka replication to keep event logs available when individual infrastructure components have a problem.

Consumer-group workflows

Let multiple consumers share stream processing work while independent applications read at their own pace.

Operational visibility

Observe service health and the flow of event workloads so teams can respond before backlogs affect users.

Private cloud networking

Connect producers and consumers over Tokoserver private networks to reduce public-facing infrastructure.

From zero to ready

Your first stream, end to end.

Create a service, define how events are organized, then connect every producer and consumer that needs the stream.

Open the console
  1. 01

    Create your Kafka service

    Choose a configuration that fits the volume and retention needs of your first workloads.

  2. 02

    Define topics and partitions

    Organize event streams by domain and select partitioning that can spread processing work.

  3. 03

    Connect producers

    Publish events from applications, backend services, devices, or data integration jobs.

  4. 04

    Add consumer applications

    Process the stream in real time for analytics, workflows, synchronization, and downstream storage.

Operational confidence

Decouple systems without losing the story between them.

Kafka lets producers move forward without waiting for every downstream system, while consumers can process durable streams at the pace their workload allows.

Durable streams
Retain events for later consumers
Independent pace
Producers and consumers stay decoupled
Parallel work
Partitions distribute processing

Ideal for

Event-driven microservicesReal-time analyticsApplication activity streamsData synchronizationIoT event collectionLog and metric pipelines

Build your stack

Works better together

PostgreSQL

Pair event streams with a managed relational system of record for application data.

Object Storage

Land event exports and long-lived datasets in S3-compatible object storage.

Ready when you are

Put Apache Kafka to work.

Create your account, configure your service, and start building on Indonesian cloud infrastructure.

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