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Technology

The technology behind the systems we build.

The languages, platforms and tools our engineers work with across AI, cloud, data, security and digital engineering, with a note on where each one fits.

Talk to an EngineerExplore the ecosystem
Categories
10
Technologies
69
  • Python
  • Foundation model APIs
  • Open-weight models
  • AWS
  • Microsoft Azure
  • Google Cloud
  • PostgreSQL
  • Redis
  • Apache Kafka
  • Kubernetes
  • Docker
  • Terraform
  • HashiCorp Vault
  • Open Policy Agent
  • OAuth 2.0 and OpenID Connect
  • React
  • Next.js
  • TypeScript
  • Node.js
  • Go
  • Java
  • GitHub Actions
  • GitLab CI
  • Argo CD
  • MQTT
  • OPC UA
  • Modbus
  • PyTorch
  • scikit-learn
  • MLflow

01Ecosystem

Explore by discipline.

Select a category to focus the map and see where each technology fits in the systems we build, or browse everything at once.

Technology map

69 technologies

  • 0108 technologies

    AI

    LLM applications, retrieval and agents engineered for production use.

    • Python
    • Foundation model APIs
    • Open-weight models
    • vLLM
    • Vector databases
    • Model Context Protocol
    • LangGraph
    • Evaluation harnesses
  • 0206 technologies

    Cloud

    Landing zones, platforms and migrations across the major providers.

    • AWS
    • Microsoft Azure
    • Google Cloud
    • Managed Kubernetes
    • Serverless
    • Object storage
  • 0307 technologies

    Data

    Operational stores, streaming and governed analytical platforms.

    • PostgreSQL
    • Redis
    • Apache Kafka
    • Apache Spark
    • dbt
    • Apache Airflow
    • Apache Iceberg
  • 0407 technologies

    Infrastructure

    Reproducible runtime and the telemetry needed to operate it.

    • Kubernetes
    • Docker
    • Terraform
    • Helm
    • OpenTelemetry
    • Prometheus
    • Grafana
  • 0507 technologies

    Security

    Identity, policy, secrets and software supply chain controls.

    • HashiCorp Vault
    • Open Policy Agent
    • OAuth 2.0 and OpenID Connect
    • Cloud KMS
    • SAST and dependency scanning
    • SBOMs
    • Sigstore
  • 0606 technologies

    Frontend

    Accessible, fast interfaces for complex, data-heavy products.

    • React
    • Next.js
    • TypeScript
    • Tailwind CSS
    • React Native
    • Playwright
  • 0707 technologies

    Backend

    Services and APIs built around stable, versioned contracts.

    • Node.js
    • Go
    • Java
    • FastAPI
    • REST and OpenAPI
    • GraphQL
    • gRPC
  • 0806 technologies

    DevOps

    Delivery pipelines that make releases repeatable and reversible.

    • GitHub Actions
    • GitLab CI
    • Argo CD
    • Argo Rollouts
    • OpenFeature
    • Backstage
  • 0908 technologies

    IoT

    Connected devices, industrial protocols and edge runtimes.

    • MQTT
    • OPC UA
    • Modbus
    • C++
    • Rust
    • Embedded Linux
    • Zephyr and FreeRTOS
    • K3s
  • 1007 technologies

    Machine Learning

    Model training, tracking, serving and monitoring.

    • PyTorch
    • scikit-learn
    • MLflow
    • Ray
    • Feast
    • ONNX Runtime
    • OpenCV

02Reference stack

How the pieces fit together.

Categories are not silos. In a delivered system they compose into layers, from the interfaces people use to the runtimes underneath, with security applied at every one of them.

Reference stack

05 layers / 01 cross-cutting

Technology categories arranged as the layers of a reference system, with security spanning every layer.
  1. 01

    Interfaces

    Web and mobile products people use

    Frontend
    • React
    • Next.js
    • TypeScript
    • Tailwind CSS
    • React Native
    • Playwright
  2. 02

    Services & AI

    APIs, agents and models behind them

    Backend
    • Node.js
    • Go
    • Java
    • FastAPI
    • REST and OpenAPI
    • GraphQL
    • gRPC
    AI
    • Python
    • Foundation model APIs
    • Open-weight models
    • vLLM
    • Vector databases
    • Model Context Protocol
    • LangGraph
    • Evaluation harnesses
    Machine Learning
    • PyTorch
    • scikit-learn
    • MLflow
    • Ray
    • Feast
    • ONNX Runtime
    • OpenCV
  3. 03

    Data

    Operational stores, streams and lakehouse

    Data
    • PostgreSQL
    • Redis
    • Apache Kafka
    • Apache Spark
    • dbt
    • Apache Airflow
    • Apache Iceberg
  4. 04

    Platform

    Runtime, delivery pipelines and telemetry

    Infrastructure
    • Kubernetes
    • Docker
    • Terraform
    • Helm
    • OpenTelemetry
    • Prometheus
    • Grafana
    DevOps
    • GitHub Actions
    • GitLab CI
    • Argo CD
    • Argo Rollouts
    • OpenFeature
    • Backstage
  5. 05

    Cloud & edge

    Providers, regions and edge runtimes

    Cloud
    • AWS
    • Microsoft Azure
    • Google Cloud
    • Managed Kubernetes
    • Serverless
    • Object storage
    IoT
    • MQTT
    • OPC UA
    • Modbus
    • C++
    • Rust
    • Embedded Linux
    • Zephyr and FreeRTOS
    • K3s

03How we choose

Technology is a decision, not a default.

No single stack fits every problem. These are the questions we ask before a component goes into a system you will have to run.

  • 01

    Fit the problem

    Technology is chosen for the workload, the team that will run it and the estate it has to join.

  • 02

    Proven before novel

    Established tools by default. Newer ones when they solve a problem we can measure.

  • 03

    Open standards

    Open protocols and formats such as OpenTelemetry, OpenAPI, OCI and SQL keep systems portable.

  • 04

    Operable by your team

    If a component cannot be monitored, upgraded and secured by the people who own it, it is the wrong component.

  • 05

    Supply chain hygiene

    Dependencies are pinned, scanned and tracked in a bill of materials for every build.

  • 06

    Documented exit paths

    Before we depend on a component, we document how it would be replaced.

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