Deliver and enhance software applications faster, with practices and tooling that allow you to streamline innovation, reduce risk and strengthen governance.
Many organisations struggle with slow, error-prone software release cycles, caused by disconnected teams and cumbersome manual processes. The results are delayed project timelines, higher costs, and difficulties in meeting service quality expectations.
DevOps is a working culture founded on seamless cooperation between the Development and Operations teams. It involves a set of practices and tooling that automate the safe deployment, auditability, and maintenance of software. Machine Learning Operations (MLOps) is an evolution of DevOps to facilitate and de-risk the deployment and management of machine learning models, enabling organisations to harness AI at scale.
It’s not straightforward to adopt DevOps or MLOps. Both ways of working depend on your most valuable resource: your people. As such, any change programme needs to encompass your technology, your business processes and your engineering teams.
Scott Logic has extensive experience in helping organisations undertake DevOps and MLOps transformations in even the most complex environments: from the deeply technical, such as creating MLOps pipelines for citizen data at DWP; to the more people-focused, such as providing DevOps coaching for teams at Rabobank.
Our expert consultants work with you to understand your adoption progress to date and your aspirations towards maturity. We then support you in creating a smooth flow of tasks through all of the different processes and stages, such as business story creation, coding, testing, and production. We create fast and tight feedback mechanisms to help you ensure that issues are identified and addressed early on.
Our processes are constantly evolving and there is no final stage of improvement. Regular experimentation is vital to adapt to new technologies, challenges and stakeholder expectations.
We believe that quality checks must be built into every stage to prevent work from repeatedly returning to earlier phases. Through automation, we create a seamless flow that reduces delays and improves the overall efficiency of our development process.
We promote a one-team approach, working with you and your stakeholders as a single, cohesive unit with shared goals, responsibilities, risks and deadlines. This allows us to shift tasks “left” in the process so that tool support and service standards are introduced early, reducing post-development activity.
Find out how we have helped clients like you with tailored support to tackle technology challenges and achieve business goals.
We supported DWP Digital to build production-ready pipelines and develop the Machine Learning Operations (MLOps) capability of its data science team so that it could rapidly iterate ML models in a safe environment, with the aim of safeguarding citizens.
How we worked with this international financial services provider as part of its transformation to DevOps, developing a solid model that would improve performance and build a more cohesive culture of collaboration and communication.
While our approach is always tailored to your needs, we have a range of tried-and-tested solutions that speed up delivery and drive a successful outcome.
We work closely with your teams to foster collaboration, address bottlenecks and iron out inconsistencies, embedding these improvements into the workflow for immediate results in the speed and quality of delivery.
We automate manual tasks and embed quality checks throughout the development lifecycle, thereby accelerating delivery times, reducing errors, and improving the quality and reliability of your services.
We employ MLOps techniques and create robust AI pipelines to allow iterative quality improvements to be made to machine learning models so that you can move them from prototype to production with confidence.
This paper by Bartosz Jedrzejewski, Paolo Barile and Rob Griffiths introduces the core concepts behind DevOps, considers the unique challenges it poses, and suggests how organisations can embrace a DevOps mindset and culture.
Graham Odds examines why public sector organisations are struggling to move AI from prototype to production and shares insights that point towards how government organisations can harness AI with greater confidence.
Graham Odds
With organisations still getting to grips with how and where to deploy AI, James Heward summarises the distinct capabilities required for AI/ML projects and the capability models that are out there.
James Heward
Continuous Testing includes the ability to run a repeatable so that CI/CD pipeline can provide rapid that will not impact the product negatively. Callum Akehurst-Ryan explains how to achieve continuous confidence in software through Continuous Testing.
Callum Akehurst-Ryan
Find out how we can help your organisation foster a culture of DevOps and MLOps so that you can streamline innovation, reduce risk and strengthen governance.
