Technology ecosystem

The engineering stack behind dependable cloud platforms.

VexEagle selects technologies around architecture, workload behaviour, operational requirements, and team capability—not a one-size-fits-all toolset.

Discuss Your Stack Explore Technologies

Cloud platforms

Cloud capabilities assembled around the system you need to run.

AWS, Microsoft Azure, and Google Cloud offer powerful building blocks. The useful choice is the one that fits the workload, operating model, and product direction.

01

AWS

Flexible application, data, networking, and operations foundations for teams building cloud-native systems.

EC2ECS / EKSLambdaS3RDSElastiCacheCloudFrontRoute 53IAMVPCCloudWatchWAFALB / NLBEFSSES
02

Microsoft Azure

Platform choices that connect application delivery, identity, governance, and operational visibility.

Virtual MachinesAKSApp ServiceAzure FunctionsAzure StorageAzure SQLAzure MonitorVirtual NetworkKey Vault
03

Google Cloud

Cloud-native services selected around application runtime, managed data, and team operating requirements.

Compute EngineGKECloud RunCloud StorageCloud SQLCloud MonitoringVPCIAM

Containers & orchestration

Package consistently. Run with the right level of orchestration.

Docker, Kubernetes, Amazon ECS, Amazon EKS, Azure AKS, and Google GKE serve different runtime and operational needs. We use them to create clearer deployment, scaling, and service-management paths.

Explore Docker & Kubernetes consulting
01Application
02Container
03Registry
04Orchestration
05Load balancing
06Autoscaling
07Observability
ContainerizationImage optimizationContainer securityService deploymentCluster architectureIngress & load balancingAutoscalingResource managementRolling deploymentsHealth checksSecrets & configurationObservability
01Design
02Code
03Review
04Plan
05Apply
06Validate

Infrastructure as Code & automation

Infrastructure changes should be visible before they reach production.

Terraform, Ansible, AWS CloudFormation, Shell/Bash, and Python can turn environment decisions into version-controlled, repeatable workflows with reusable modules and more deliberate change controls.

Explore Infrastructure as Code

CI/CD & release engineering

Release engineering that gives change a safer path to production.

Jenkins, GitHub Actions, GitLab CI/CD, and AWS CodePipeline can support a measured progression from commit to verification.

01Commit
02Build
03Test
04Security
05Package
06Deploy
07Verify
Branch & release workflowsArtifact & container handlingEnvironment promotionDeployment strategies & rollbackApproval gates & secret handlingPipeline monitoring

Observability

Signals that explain behaviour, not just dashboards.

Amazon CloudWatch, Prometheus, and Grafana help teams connect metrics, logs, alerts, and operational response to the way an application actually behaves in production.

Explore Cloud Monitoring
ApplicationsContainersServersDatabases
TelemetryMonitoringAlertingResponse
LinuxUbuntuNginxApache

Systems & web infrastructure

Production engineering below the application layer.

Linux administration, reverse proxies, TLS, service management, process tuning, access controls, logging, patching, and load-balancer integration all shape the reliability of an application runtime.

Explore Server Management

Data & caching

Data infrastructure decisions that respect production realities.

MySQL, PostgreSQL, MongoDB, Redis, and Valkey are considered as part of the application architecture—not as isolated boxes to deploy.

01

MySQL

Relational workload patterns, backups, access, and operational visibility.

02

PostgreSQL

Managed or self-managed choices, recovery, performance, and connectivity.

03

MongoDB

Document-oriented workloads with appropriate scaling, access, and monitoring decisions.

04

Redis / Valkey

Caching architecture, availability, memory behaviour, and secure application integration.

Security layer

Controls that span the stack, rather than one isolated tool.

Security becomes more effective when identity, network, compute, data, delivery, and operational visibility are designed together.

01

Identity

IAM, least privilege, and secrets management.

02

Network

Private networking, security groups, controlled exposure, and TLS.

03

Compute

Hardened runtime configuration and permissions.

04

Containers

Image controls, runtime choices, and service boundaries.

05

Data

Encryption, backup, recovery, and access patterns.

06

Delivery

CI/CD controls, reviews, and credential handling.

07

Observability

Logging, auditability, and security-relevant signals.

How we choose technology

Fashion is not an architecture decision.

Not every application needs Kubernetes. Not every workload needs serverless. Not every infrastructure problem requires another tool.

01

Workload fit

Does the technology fit the application runtime and traffic profile?

02

Operational complexity

Can the team realistically operate and improve it?

03

Scalability

Can it support the next stage of product growth?

04

Security

Does it support appropriate control boundaries?

05

Cost

Does the operational value justify the cost?

06

Team capability

Will the engineering team be able to maintain it?

07

Ecosystem

Does it connect cleanly to the existing stack?

How the stack comes together

Example architecture patterns.

These are illustrative technology combinations, not customer case studies or prescribed blueprints.

Example architecture pattern

01

SaaS platform

GitHub→CI/CD→Docker→ECS / EKS→RDS→Redis→CloudWatch

Example architecture pattern

02

Kubernetes platform

Git→Pipeline→Registry→Kubernetes→Ingress→Services→Pods→Prometheus / Grafana

Example architecture pattern

03

Lean cloud application

GitHub Actions→Docker→Managed compute→Managed database→Object storage→Monitoring

Tools into outcomes

Technology is the means. Services solve the engineering problem.

TerraformInfrastructure as CodeKubernetesDocker & KubernetesJenkinsCI/CD EngineeringCloudWatchCloud MonitoringAWSAWS Cloud ServicesPrometheus / GrafanaCloud Monitoring

Questions, answered

Technology FAQ

The right answer depends on your product, current environment, and what the team needs to own after the work is complete.

Do you only work with AWS?

No. VexEagle works across AWS, Microsoft Azure, and Google Cloud, choosing services based on workload, operations, integration, and team requirements.

Can VexEagle work with our existing technology stack?

Yes. Existing architecture and delivery tooling are an important part of the discovery process. The goal is to improve what is useful and change only what needs to change.

Do we need Kubernetes?

Not every application needs Kubernetes. Containers, managed compute, ECS, serverless, or virtual machines can all be appropriate depending on the workload and operational model.

Can you migrate our existing Jenkins pipelines?

Yes. Existing pipelines can be reviewed, strengthened, or moved to another CI/CD platform when there is a clear technical and operational reason to do so.

Can you manage both cloud and self-managed infrastructure?

Yes. The relevant scope can include cloud platforms, Linux servers, web infrastructure, containers, and the operational interfaces between them.

Can you introduce Terraform into an existing environment?

Yes. A gradual Infrastructure as Code approach can begin with selected environments or modules, with state, reviews, and ownership designed before broad adoption.

Do you support environments that use multiple cloud providers?

Yes. Multi-cloud environments need especially clear boundaries, identity patterns, observability, and cost ownership. The right design depends on why multiple providers are in use.

Can you work with technologies not listed on this page?

This page represents common tools and platforms. A technical conversation can determine whether a specific technology fits the engagement and operating model.

Already have a stack?

Let's make it work better.

VexEagle can work with the environment you have today or help design the next one around clearer technical and operational decisions.

Discuss Your Stack Explore Services
Chat on WhatsApp