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概览
Software delivery slows down for predictable reasons: pipelines each team maintains differently, environments that drift, manual approvals that hide risk rather than reduce it, and production systems that are hard to observe. Capable engineers end up spending their time on toil instead of product.
We build delivery platforms that make the right way the easy way. Golden-path templates, reusable pipelines, GitOps deployment, self-service environments and built-in observability give teams autonomy within guardrails, so security, compliance and reliability come from the platform rather than from heroic effort on every release.
业务应用
- 01
Internal developer platforms
Self-service portals and templates, often built on Backstage, that let teams create services, environments and pipelines with security, observability and ownership metadata already configured from the first commit.
- 02
CI/CD standardization
Replacing inconsistent, hand-maintained pipelines with reusable workflows that build, test, scan, sign and deploy artifacts the same way across every repository, maintained centrally and versioned like any other code.
- 03
Kubernetes platform operations
Designing and running Kubernetes clusters with GitOps, policy enforcement, autoscaling, secrets management and tested upgrade procedures that application teams can depend on without needing to become cluster specialists themselves.
- 04
Software supply chain security
Adding dependency scanning, software bills of materials, artifact signing and provenance attestations to pipelines, aligned with frameworks such as SLSA and the NIST Secure Software Development Framework.
工程方法
- 01
Delivery assessment
We measure how code reaches production today, using DORA metrics, pipeline analysis and developer interviews to find where time is lost and where risk accumulates.
- 02
Platform as a product
The platform is run as an internal product with defined users, a roadmap and feedback loops, so capabilities are built because teams need them, not because a tool exists.
- 03
Golden paths
We create opinionated templates for the most common service types, bundling build, test, deployment, observability and security defaults that teams can adopt in a single step.
- 04
GitOps and progressive delivery
Deployments are declared in Git and reconciled by Argo CD or Flux, with canary and blue-green releases governed by automated analysis of production metrics.
- 05
Enablement and measurement
We pair with application teams during adoption, document platform capabilities, and track delivery and reliability metrics to show where the platform helps and where it needs work.
技术与平台
CI/CD and GitOps
- GitHub Actions
- GitLab CI
- Jenkins
- Argo CD
- Flux
- Argo Rollouts
Platform and runtime
- Kubernetes
- Backstage
- Helm
- Crossplane
- Terraform
Security and supply chain
- Sigstore Cosign
- Trivy
- Syft
- OPA Gatekeeper
- HashiCorp Vault
- Snyk
Observability
- OpenTelemetry
- Prometheus
- Grafana
- Loki
- Tempo
文中提及的技术名称均为其各自所有者的商标，并不代表任何合作或背书关系。
交付成果
- Delivery assessment with a DORA baseline and prioritized improvements
- Reusable CI/CD workflows with testing, scanning and artifact signing
- GitOps deployment configuration with progressive delivery
- Golden-path service templates and a developer portal
- Observability stack with service dashboards and alerting standards
- Platform documentation, onboarding guides and ownership model
决策者关心的问题
What is the difference between DevOps and platform engineering?
DevOps describes a culture and set of practices that bring development and operations together. Platform engineering is one way to sustain it at scale: a dedicated team builds shared, self-service tooling so each product team does not have to assemble its own delivery and operations stack. We help with both the practices and the platform.
Do we need Kubernetes?
Not always. Kubernetes suits organizations running many services with varied scaling needs and the capacity to operate it well. Smaller estates are often better served by managed container services or serverless platforms. We recommend the runtime that fits your workload profile and team, and design pipelines that work with either choice.
How do you measure whether the platform is working?
We track DORA measures such as deployment frequency, lead time for changes, change failure rate and recovery time after failed deployments, alongside platform adoption and developer feedback. Baselines are captured before changes begin, so progress or regression is discussed against your own data rather than industry averages.