Scalexa — Senior Engineering & AI Solutions
    Empower your content with seamless, scalable solutions, combining cutting-edge technology with captivating design for a truly dynamic presence.

    DevOps Services

    • Design and implementation of scalable, secure cloud architectures on major platforms (AWS, Azure, Google Cloud)
    • Migration of legacy systems to cloud environments for improved efficiency and cost-effectiveness
    • Implementation of multi-cloud and hybrid cloud solutions to optimize performance and reduce vendor lock-in
    • Continuous optimization of cloud resources to balance performance and cost
    • Implementation of CI/CD pipelines for automated testing, building, and deployment
    • Configuration management using tools like Ansible, Puppet, or Chef for consistent environments
    • Container orchestration with Kubernetes for scalable, manageable microservices architecture
    • Infrastructure as Code (IaC) implementation using Terraform or CloudFormation for reproducible, version-controlled infrastructure
    • Design of comprehensive IT solutions aligned with business goals and technical requirements
    • Integration of various systems and technologies to create cohesive, efficient architectures
    • Performance optimization and scalability planning to support business growth
    • Risk assessment and mitigation strategies in solution design
    • Proactive monitoring and management of servers, networks, and applications
    • Implementation of robust backup and disaster recovery solutions
    • Regular system updates and patch management to ensure security and stability
    • Troubleshooting and resolution of complex system issues
    • Configuration and management of network devices (routers, switches, firewalls)
    • Implementation of network security measures, including VPNs and access controls
    • Monitoring and optimization of network performance
    • Troubleshooting of network issues to ensure continuous connectivity
    • Design and implementation of scalable, high-performance network architectures
    • Integration of advanced networking technologies (SD-WAN, MPLS, VoIP)
    • Network virtualization and software-defined networking (SDN) implementations
    • Design of secure network topologies to protect against cyber threats

    Related Case Studies

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    Technologies We Use

    Deep expertise in leading technologies to deliver enterprise-grade solutions

    AWSAzureGCPKubernetesDockerCI/CD PipelinesPostgreSQLMongoDBRedis

    Why Choose Scalexa?

    25+

    Years Experience

    Decades of experience building systems at scale for Fortune 500 companies.

    3x

    Faster Delivery

    Our proven methodologies deliver results faster than traditional approaches.

    100%

    Production-Ready

    Everything we build is enterprise-grade, tested, and ready for scale from day one.

    Frequently Asked Questions

    Platform engineering means building an internal developer platform that abstracts away infrastructure complexity so product teams can ship without becoming SREs. Concretely: self-service environments, golden-path templates, internal docs/portals (Backstage, Port), standardized CI/CD, observability defaults, and security guardrails. Done right, it cuts time-to-production for new services from weeks to hours.

    All three work, but they differ on GPU availability, managed AI services, and pricing. AWS has the broadest service catalog and best startup credits; Azure has the deepest OpenAI integration and is dominant in enterprise (especially regulated industries); GCP has the strongest data analytics stack (BigQuery, Vertex AI) and is competitive on TPU access. For most enterprise AI, the decision should be driven by where your data already lives and which compliance certifications your industry requires — not the cloud vendor's marketing claims.

    A real Azure DevOps engagement covers: pipeline design (YAML-first, multi-stage), Azure Boards configuration with cross-team work tracking, Repos governance (branch policies, required reviews, build validation), Artifacts setup for internal packages, Test Plans integration, and security baselines via Azure Policy and Defender for DevOps. We typically pair Azure DevOps with Terraform for infrastructure and integrate with Azure AD for identity.

    Three deployment patterns we use depending on context: (1) Blue/green — full traffic switch behind a load balancer for stateful services, (2) Canary — gradual traffic shift (1%, 10%, 50%, 100%) with automated rollback on error budget violation, ideal for high-volume services, and (3) Feature flags — code is always deployed but disabled until toggled, ideal for de-risking large changes. We layer all three with progressive delivery tools like Argo Rollouts or Flagger.

    Realistic migration timelines: 4-8 weeks for a single application lift-and-shift, 3-6 months for a multi-service migration with refactoring, and 9-18 months for a full datacenter exit. The biggest accelerators are good infrastructure-as-code discipline on the source side and a willingness to refactor stateful services. The biggest blockers are undocumented dependencies and license-locked vendor software.

    End-to-end means we own the full stack from VPC design to production observability: network architecture, IAM, infrastructure as code (Terraform/Pulumi), Kubernetes or serverless compute, CI/CD pipelines, observability (Datadog, Grafana, OpenTelemetry), cost management (FinOps), and disaster recovery. The goal is a platform your product teams can self-serve on without filing tickets.
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