Imantouch

Technologies

Open source, vendor-neutral, production-proven

We work with technologies that have real communities behind them and a credible operating story at scale. Below is where we spend most of our time — the list moves as the ecosystem does.

Streaming and messaging

  • Apache Kafka

    The default event backbone. Most of our platforms have one.

  • Apache Pulsar

    When multi-tenancy and geo-replication are first-order requirements.

  • Apache Flink

    Stateful stream processing, exactly-once, at real volume.

  • Redpanda

    Kafka protocol without the JVM, where operational simplicity wins.

  • Debezium

    Change data capture from existing databases, without touching the application.

Distributed data stores

  • Apache Cassandra

    Write-heavy workloads that must survive a datacentre going dark.

  • ScyllaDB

    Same data model, fewer nodes, when latency budgets are tight.

  • OpenSearch

    Search and log analytics, and the base of our managed SIEM.

  • PostgreSQL

    Still the right answer more often than the architecture diagram suggests.

  • ClickHouse

    Analytical queries over very large tables, at interactive speed.

Cloud and orchestration

  • Kubernetes

    Any distribution, any cloud, and on bare metal when the economics say so.

  • Terraform

    Infrastructure as code, in modules your team owns and reuses.

  • Helm

    Packaging and release management for what runs in the cluster.

  • Argo CD

    Git as the single source of truth for cluster state.

  • AWS · GCP · Azure

    All three, plus European and on-premise hosting when sovereignty requires it.

Observability

  • Prometheus

    Metrics and alerting, with rules tuned to your failure modes.

  • Grafana

    Dashboards built to answer incident questions, not to look full.

  • OpenTelemetry

    Vendor-neutral instrumentation, so changing backend is not a rewrite.

  • Loki

    Log aggregation whose cost tracks volume rather than a licence.

  • Thanos

    Long-term metric retention and global query across clusters.

AI and machine learning

  • Kubeflow

    Training and pipeline orchestration on the cluster you already run.

  • MLflow

    Experiment tracking and a model registry that outlives the data scientist.

  • Ray

    Distributed training and batch inference without bespoke plumbing.

  • vLLM

    Self-hosted LLM serving, with throughput that makes the GPU bill defensible.

  • Feast

    A feature store when several models start needing the same data.

Security

  • HashiCorp Vault

    Secrets, certificates and dynamic credentials — no passwords in Git.

  • Wazuh

    Host-level detection and file integrity, feeding the SIEM.

  • Falco

    Runtime detection inside the cluster, at the syscall level.

  • Trivy

    Image and dependency scanning, wired into the delivery pipeline.

  • Keycloak

    Single sign-on and access control across the platform.

Not seeing yours? Ask. This is what we run most often, not the limit of what we work with.

Let’s talk about what your platform needs

Tell us what you are building, or what is keeping you up at night. We will tell you plainly whether we are the right team for it.