<img height="1" width="1" style="display:none;" alt="" src="https://px.ads.linkedin.com/collect/?pid=4958233&amp;fmt=gif">
 

Cloud migration services, data centre exits and cloud consulting



Endava has worked on many large-scale cloud migration and adoption projects across a wide set of industries. We believe this knowledge has given us a proven methodology that helps clients get to the cloud faster, more securely and whilst upskilling staff.
 
We have a comprehensive set of documentation that can be used to create an effective plan to migrate applications from an on-premises infrastructure to Google Cloud Platform. This Cloud Adoption Framework (CAF) is a detailed set of requirements covering all areas of cloud adoption, with a strong focus on automation, governance and security.
 
We will work with your teams to create a single plan of action, the Cloud Migration Roadmap, without the paralysis of endless discovery phases and audits. We start quickly and iterate using an agile methodology, but with a clear final state in mind that optimises your ability to deliver technology.
 
Our cloud migration discovery process touches on all aspects of successful digital transformation, such as business, people or process change. We have a set of prescribed and fully automated patterns for accelerated platform buildouts, virtual machine (VM) migrations or day-2 operations – all with enterprise security-first design.

Our discovery and assessment process will help you understand your current inventory of applications, categorise and map them according to cloud migration best practices as well as deploy automated tooling for dependency analysis and insight into the migration risk per application. Our team will also work with all involved business and IT stakeholders, performing interviews and completing questionnaires to better plan and execute your cloud migration.


Infrastructure services, landing zone and implementing the framework



Endava partners with you to upskill your teams on the best way to implement Google Cloud. We have worked with clients both large and small in many different industries, and we have amalgamated that knowledge into our migration approach so that you can enjoy the benefits and see maximum progress.
 
We take an automation-first approach where we deliver the landing zone environment using IaC (Infrastructure as Code). Typically, this means Terraform deployed using pipelines. We use our comprehensive set of CAF requirements to implement your environment with automated code-based accelerators. Our infrastructure services support your organisation with the following core areas: cloud foundations, organisational structure and resources deployment, authentication, authorisation and secrets, networking, logging, financial operating, operating model, billing and many more.
 
We typically build landing zones with Google’s Cloud Foundation Toolkit, implementing best practice design and security from the start. There are many key requirements to get right at the start of the programme, and the aim is to deliver an infrastructure that can be deployed using self-service tools and that follows ITIL (Information Technology Infrastructure Library) best practices.


Multi-cloud PaaS, application deployments, DevOps and application development services



Beyond a ‘lift and shift’ of applications onto IaaS (Infrastructure as a Service), we believe the biggest benefits of migrating to the cloud are the increase in velocity when it comes to innovation and the ability to scale up and down with demand.
 
The acceleration of application deployment is the product of a mature DevOps team combined with a robust 24/7 PaaS (Platform as a Service) infrastructure.
 
Endava specialises in multi- and hybrid-cloud infrastructure using Kubernetes, Anthos and serverless technology. We provide reference designs built in code that have been used on multiple projects, including advanced deployment patterns for both infrastructure and application code.
 
We can help you to build and manage cloud business applications using industry standards and best practices.


Cloud management, security and training services



Operating technology in the public cloud opens the opportunity for a paradigm shift away from on-premises ways of working. Empowering development teams via self-service and self-governance, whilst creating overarching governance and security guardrails to stop dangerous deployments, is a key requirement to get right. Simply transferring an on-premises operating model to the cloud has already resulted in many cloud migration failures.
 
Having a cloud operating model from the get-go is a must, and having one that can be automated via code will transform the way technology is delivered to users and clients. The journey to the cloud requires new ways of working and thinking, and these experiences must be embedded into the new model to make those improvements stick.
 
We can partner with you to deploy your cloud operating model, and we can provide the full support structure via our ‘Managed by Endava’ offering. Our support goes beyond a traditional service model to deliver automation, continuous improvement, comprehensive security plans and patterns, rightsizing and improved developer productivity.
 
Cloud operating models and any cloud project can be supported with structured training delivered by highly skilled professionals.

 

 

Data analytics and machine learning services

 

 

Endava can draw on a depth of experience in data analytics, machine learning (ML) and artificial intelligence (AI) projects. Our professional data engineers, machine learning engineers, AI/ML and data architects support clients in their projects and help them to achieve their business objectives. We have demonstrated success stories in building data solutions, helping customers to turn data analysis into business insights, use sophisticated machine learning models for speech data analysis, image recognition applications and more, to support AI and finally to implement machine learning operation models.

We provide direct offerings using the following products among others:
• Analytics: BigQuery, Dataflow, Dataproc, Datalab, Pub/Sub,
• Machine learning and Google Cloud AI: TensorFlow, Cloud AI, Natural Language API, Speech API, Translation API, Video Intelligence API, Vision API,
• Operations: MLOps
• and much more.