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Resource augmentationAWS + AzureClient story

SaaS company

An on-demand cloud engineering team for a growing SaaS company

Four AWS, Azure, DevOps and cloud support engineers worked as an extension of a fast-growing SaaS team for 12 months, used as the workload needed.

Told by the DevOps TechLab delivery teamSoftware & SaaS3 min read

The client

A high-growth SaaS and software company running several cloud environments and customer workloads on AWS and Azure. The client is not named at its request.

The challenge

  • The company was growing fast and needed more engineering capacity.
  • It was managing several cloud environments and customer workloads at once.
  • It needed people quickly, without a large increase in permanent headcount.

The team we placed

  • Engineers4
  • Length12 months
  • ModelFlexible
  • SkillsAWS + Azure + DevOps + Cloud support
  • AWS Cloud Engineer
  • Azure Cloud Engineer
  • DevOps Engineer
  • Cloud Support Engineer

What the team handled

  • AWS and Azure cloud infrastructure
  • DevOps and CI/CD
  • Production deployments
  • Cloud monitoring
  • Infrastructure troubleshooting
  • Application environment support
  • Backup and recovery support
  • Performance optimisation
  • Technical incident resolution

How the engagement worked

DevOps TechLab deployed a flexible four-member cloud engineering team that worked as an extension of the client’s engineering team. The engagement was built around the client’s workload, so engineers were used as needed.

The result

  • Rapid access to specialised cloud talent.

  • Increased development and infrastructure capacity.

  • Faster delivery of cloud and DevOps initiatives.

  • Improved production support.

  • Reduced recruitment and onboarding overhead.

  • Flexible engineering capacity without a long-term headcount commitment.

Need engineers like these?

Tell us the skills you need and for how long. We’ll talk it through and suggest a team.

How resource augmentation works →
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Every month you wait, the bill grows, the audit gets harder and the AI project waits another quarter.

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