Home/Technologies
Technologies

The stack we build and run our own products on.

The languages, frameworks, cloud, data and AI technologies behind ObelusLabs and our client work. Where we have written up how we use one, its name links to the details.

Example architectureEvent-driven, AI-native
ClientsEdgeServicesAIEventsDataPlatformWebNext.jsMobile appSwiftPartner APIOpenAPICDN & API gatewayOrdersJavaCatalogueGoPayments.NETSearchPythonAgentMCPClaudeOpenAIpgvectorKafkaEvent streamOrders DBPostgreSQLCacheRedisSearch indexElasticsearchWarehouseSnowflakeKubernetesAWSAzureGoogle CloudOpenTelemetry
Application engineering

Languages, frameworks and the systems we connect to.

Back end
JavaSpring BootC#.NETEntity Framework CoreSignalRPythonDjangoFastAPINode.jsNestJSPrismaSocket.IOGo
Front end (web & desktop)
TypeScriptReactReduxNext.jsAngularVue.jsNuxtTailwind CSSStorybookElectron
Content management (CMS)
APIs & integration
GraphQLgRPCOpenAPISwaggern8nSAP
Cloud & infrastructure

Cloud, data stores and the tooling around them.

Cloud
Containers & infrastructure as code
DockerKubernetesHelmTerraformPulumiAnsibleNginx
CI/CD
GitHub ActionsGitLab CIJenkinsArgo CD
Databases
PostgreSQLMySQLSQL ServerOracleMongoDBRedisCosmos DBDynamoDBCassandraElasticsearchFirebase
Testing
PlaywrightCypressJestVitestPyTestAppiumk6
Security
SonarQubeSnykSemgrepTrivyVault
Observability
OpenTelemetryPrometheusGrafanaSentryDatadog
Data & AI

Data pipelines, analytics and AI.

Messaging & streaming
KafkaRabbitMQDebeziumFlinkKinesis
Data platforms & BI
SnowflakeBigQueryDatabricksRedshiftdbtAirflowPower BILooker
AI models & platforms
OpenAIClaudeGoogle GeminiLlamaMistralAmazon BedrockAzure AI FoundryVertex AISageMakerHugging FaceOllamavLLM
AI agents & orchestration
MCPLangChainLangGraphLlamaIndexCrewAISemantic KernelOpenAI Agents SDKClaude Agent SDKVercel AI SDK
Evaluation & MLOps
LangfuseLangSmithMLflowWeights & Biases
ML frameworks
PyTorchTensorFlowscikit-learn
FAQ

Frequently asked questions

Usually, yes. The technologies above are the ones we build and run most; most enterprise estates also contain technologies we have modernised rather than chosen. Tell us what you run and we will say honestly whether it is a fit.
No. We are financially neutral across AWS, Azure and Google Cloud, and the recommendation follows your existing agreements, identity estate and data gravity — not ours.
We add a technology when we have used it in production work, for our own products or for clients, and remove it when we no longer do.
Yes — Staff Augmentation places specialists into your team, and you interview and approve every profile. For a whole roadmap, a Dedicated Team brings the delivery system with it.
They are our default way of working. Their scope, budgets and service-level targets are agreed with you, according to your needs and budget.
How we work

Practices that come with the stack.

These four practices are our default way of working. How far each one goes in your project is agreed with you, according to your needs and budget.

01

CI/CD

Automated pipelines with quality gates: every merge is built, tested and scanned before it reaches a staging environment.

02

Observability

OpenTelemetry, Prometheus and Grafana, with service levels agreed with you. Traces, metrics and logs are wired in early, and the runbook is part of the handover.

03

Security in CI

SAST/DAST scanning, secrets management and audit trails. Dependencies are pinned and scanned, and secrets live in a vault.

04

Performance budgets

Core Web Vitals budgets and load testing before release, against targets set together with you.

Engineers who build and run this stack.

Tell us the technologies and the experience level you need. We propose a named team, or place specialists into yours.

✓ No pitch deck✓ AI-native engineer on the call✓ Written follow-up