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Elastic engineering

A dedicated engineering team that works like yours and stays.

Rackspace Elastic Engineering is our cloud delivery team: a dedicated pod of architects and engineers embedded with your team in weekly sprints, moving your cloud priorities forward across build, migrate, modernize, secure and operate. The same people every month, with capacity that flexes as your needs change. 

Talk to an advisorExplore Enterprise AI Cloud

Project teams leave when the statement of work ends. Support queues wait for something to break. Your roadmap needs a team that does neither. 

Cloud work is continuous: the next migration wave, the next pipeline, the next security control, the next cost review. Most organizations are short of the engineers to keep up, and the traditional choices are a fixed-scope project or a reactive support contract. Elastic Engineering is built for the work in between. 

Outcomes

What a dedicated pod changes 

Progress every week: 

Work is planned, delivered and demonstrated to your stakeholders in one-week sprints, so momentum is visible and course corrections happen early 

Knowledge that compounds: 

The same pod works with you month after month, learning your environment, your constraints and your business, so each sprint starts further ahead 

Capacity that flexes:

Hours-based tiers scale up or down monthly as priorities shift, without renegotiating scope or losing the team 

Every pod's experience, applied to yours:

Accelerators, patterns and automation built across all Rackspace pods are available to your engagement from day one 

How the pod works

A delivery framework built on weekly sprints

Every engagement runs on the Rackspace Engagement Delivery Framework, an agile method designed for visibility and accountability.

INTRO 

Long-range planning: 

Your goals are broken into achievable work items and a prioritized backlog of user stories, reviewed with your team before each sprint. 

PLAN 

Knowledge that compounds: 

The same pod works with you month after month, learning your environment, your constraints and your business, so each sprint starts further ahead 

SPRINT 

One-week iterations: 

The pod carries out analysis, design, engineering, deployment and testing inside the sprint, with a daily standup to surface blockers. 

DEMO 

Every pod's experience, applied to yours:

Show the work: Each sprint closes with a demonstration to your stakeholders and sign-off against agreed acceptance criteria. 

ADJUST 

Reprioritize freely: 

As your priorities change, so does the pod's focus. Status reports and backlog reviews keep everyone aligned on what comes next. 

The pod 

Nine experts, one unit 

Each pod combines leadership, architecture and hands-on engineering so it can take a priority from design through delivery without handing it to another team.

Engagement manager (1):

Owns the pod's success, runs planning, standups and sprint reviews.

Lead cloud architect (1):

Owns technical direction and team performance. 

Cloud architect (1): 

Turns requirements into architecture, reviews code and quality.

Senior cloud engineers (3):

Specialized expertise, reusable patterns and best practices. 

Cloud engineers (3):

Hands-on DevOps and automation across cloud infrastructure. 

What pods deliver 

The full range of cloud work, from one team 

Build and migrate:

Architecture design, landing zones and migration waves across public and private cloud. 

Modernize:

Containers, Kubernetes, serverless and application refactoring, prioritized by business impact. 

Automate:

Infrastructure as code, CI/CD pipelines and self-service platform capabilities. See Platform Automation → 

Secure: 

Security architecture, compliance alignment and vulnerability management through security-specialized pods. 

Data:

Data platforms, pipelines and operations through data-specialized pods, building the foundation analytics and AI depend on. 

Optimize:

Reliability improvements and cost optimization carried through to implementation. See FinOps → 

Human plus AI delivery 

Engineers who build on automation, so your hours go further

Pods work on the same AI operations platform and reusable automation library that Rackspace managed environments run on, so routine work is automated and engineering time goes to design, judgment and the problems specific to your business. For AI workloads moving into production, Rackspace Forward Deployed Engineers carry the same embedded model into Enterprise AI Cloud. 

Industries

Trusted expertise for industries where the stakes are the highest

Healthcare

Epic and clinical platforms kept available, patient data protected, and a governed foundation ready to move AI from pilot to the point of care.

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Financial services

Core banking and payments modernized with proven recovery, data control and the audit evidence regulators expect, so AI can follow safely.

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Public sector

Sovereign, accredited cloud for citizen services, run by cleared teams, with the control to modernize today and adopt AI when you’re ready.

Learn More

Explore Industries

For technology support, our Rackspace team brought excellent AI experience. And they worked well with our internal engineers to execute the project and help us achieve our goals.

Sudipto Das

VP of Engineering, Convera

FAQ

Frequently asked questions

Rackspace Elastic Engineering is a cloud delivery service that gives an organization a dedicated pod of Rackspace architects and engineers who work alongside its team in weekly sprints. The pod builds, migrates, modernizes, automates, secures and optimizes cloud environments across AWS, Microsoft Azure, Google Cloud and Rackspace Private Cloud, accessed through monthly hours-based tiers. 

Nine people: an engagement manager, a lead cloud architect, a cloud architect, three senior cloud engineers and three cloud engineers. The same pod stays with the customer for the life of the engagement. 

Through hours-based tiers purchased monthly. Customers scale their tier up or down as priorities change and keep working with the same pod regardless of tier.

Managed services operate an environment day to day against defined service levels. Elastic Engineering delivers forward-looking engineering work, such as migrations, modernization, automation and security projects, in sprints alongside the customer's team. Many customers use both, with the pod building what managed services then run.

Both embed Rackspace engineers in the customer’s environment. Elastic Engineering pods deliver cloud work; Forward Deployed Engineers deliver AI workloads into production on Enterprise AI Cloud, trained on the AI platforms in the Rackspace stack. 

Yes. In addition to cloud pods, Rackspace offers Elastic Engineering pods for security, data, ERP and Microsoft 365, each with the same engagement model and specialist skills for that domain.

Yes. Pods deliver for healthcare, financial services and public sector organizations, producing compliance evidence as part of the work and planning changes around clinical, trading and service hours.

Put a pod on your roadmap.

Talk to a Rackspace Elastic Engineering expert about the work waiting on your team and what a dedicated pod could clear this quarter.