Modern software delivery depends on infrastructure that is reliable, observable, and fast to change. We design and operate cloud infrastructure on AWS, GCP, and Azure — built as code, managed through automation, and monitored to the level of detail that lets you understand exactly what is happening in production at any given moment.
Our DevOps practice covers the full spectrum: CI/CD pipeline design and implementation that gets code from commit to production in minutes rather than days; container orchestration with Kubernetes for teams running microservices at scale; Infrastructure as Code using Terraform and Pulumi that makes your infrastructure reproducible, version-controlled, and safe to change; and cloud cost optimisation that reduces your bill without compromising reliability.
We work as an embedded DevOps partner — either building and handing over infrastructure to your team, or operating as an ongoing managed infrastructure partner. We instrument everything with OpenTelemetry, build dashboards that surface the metrics that matter, and configure alerting that tells you about problems before your users do.
We assess your current infrastructure — architecture, security posture, cost profile, deployment processes, and observability gaps. For new builds, we design the full architecture before provisioning a single resource.
Everything is built as code: no clicking in consoles, no undocumented manual configuration. We establish dev, staging, and production environments with environment parity, and implement a secrets management strategy from the start.
We build deployment pipelines that automate testing, security scanning, image builds, and deployments. The goal is a pipeline where the only human decision is approving a production release — everything else is automated.
We instrument your applications and infrastructure with OpenTelemetry, build Grafana dashboards covering the four golden signals, configure alerting with appropriate thresholds, and run a knowledge-transfer session with your team.
Yes. We have production experience on AWS, GCP, and Azure. Most clients have a primary cloud provider — we are a strong fit for any of the three. For multi-cloud or hybrid-cloud architectures, we design the inter-cloud connectivity and data flow carefully, using cloud-agnostic tooling like Terraform and Kubernetes where it reduces vendor lock-in without sacrificing the managed services that make each platform genuinely useful.
Cloud cost optimisation is a recurring engagement for many of our clients. We start with a cost analysis that breaks down spend by service, environment, and team — usually revealing significant optimisation opportunities quickly. Common wins include right-sizing over-provisioned compute, moving appropriate workloads to spot or preemptible instances, implementing S3/GCS lifecycle policies for storage, consolidating underutilised environments, and purchasing reserved capacity for stable baseline workloads. We have achieved 40–70% cost reductions without changing application behaviour.
Kubernetes is genuinely powerful and genuinely complex. For teams new to it, we focus on getting the fundamentals right before adding complexity: a well-structured cluster with appropriate node pools, resource requests and limits, horizontal pod autoscaling, and health checks. We invest in documentation and training alongside the implementation so your team understands what they are operating, not just that it is running. We also assess whether Kubernetes is actually the right choice — for some workloads, simpler orchestration (AWS ECS, Cloud Run, Fargate) is a better fit.
Secrets in environment variables, .env files, or source control are a security failure mode we take seriously. We implement a secrets management strategy using the appropriate tool for your environment: HashiCorp Vault for complex multi-cloud setups, AWS Secrets Manager or Parameter Store for AWS-native workloads, GCP Secret Manager, or Azure Key Vault. Application code retrieves secrets at runtime from the secrets manager, rotation is automated, and access is controlled by IAM policies with the principle of least privilege.
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