London, U.K., 21st November 2018 – Amido, an award-winning vendor-agnostic technical consultancy specialising in solving complex business problems with cloud-native technology, identifies five key trends that will enable a business to transform towards becoming AI-driven. CTO Simon Evans states that 2019 is the year that AI will go mainstream using the power of today’s cloud: “AI is not just a technology; it is a business paradigm shift that cannot be ignored.”
The report identifies five major cloud elements essential to organisations wanting to remain relevant: accepting cloud-native as the new normal, embracing mobile applications into the cloud, building a viable data lake with the cloud using AI technologies to enable data science, and adopting a multi-cloud approach. 68% of businesses already have a digital transformation strategy in place, or are in the process of implementing one, and the vast majority see cloud as a critical component of their change strategies1.
As such, these cloud trends will continue to make an assertion during any digital transformation strategy – and will help lead the charge into becoming an AI-Driven Business, including having a strong understanding of how AI can be applied to problematic business issues.
- Cloud-Native Applications – The New Normal
Gartner states that 80 per cent of internally-developed software is now cloud-enabled or cloud-native. The evolving cloud ecosystem has allowed businesses to operate faster, more flexibly and in real-time which has led to competitive pressures and the need to always be highly-available and responsive. This has driven the early cloud adopters towards cloud-native applications, a trend set to grow in 2019 and beyond.
Cloud-native applications are specifically designed to run on cloud infrastructure, hence the term ‘native.’ They are growing in popularity because they deliver benefits, which include:
- High availability and responsiveness – due to their microservices/container architecture leading to event-driven integration which underpins communication between microservices. Containerised microservices (e.g. Docker) with orchestrated management (e.g. Kubernetes) helps reduce the time needed to provision and scale
- Hyper-scale provisioning by means of a cloud infrastructure, such as Thin clients (web apps, native mobile apps, Alexa Skills) that consume multiple microservices
- Strong resilience and flexibility – through autonomous and self-healing capabilities, such as designing for failure which is the orchestration of containers that helps to withstand partial cloud outages when coupled with a cloud providers fabric and regional capabilities
- Services that consume other Cloud Platform Services (e.g. storage, service bus, database) allowing focus on the core business problem
- Participation in a data lake with cloud-native applications continually contributing data
- Secured by an identity service to protect critical services and data
- Native Mobile Apps will Feel the Squeeze
Native mobile apps have remained costly for businesses to develop and manage across multiple channels as enterprises need to support three code bases: iOS, Android and the web app. In 2019, exciting form factors, such as IoT devices, bots, AI, and virtual and mixed reality, will all threaten native mobile app spend and de-emphasise the importance of having a native app, which is loaded onto a mobile via an app store. As for web apps that render on mobile, these will never have parity with native apps in terms of functionality or user experience. But they’re good enough and provide the basic level of access that gives you the broadest reach across the world. Expect businesses to continue investing in them, alongside their websites, through 2019.
- Good Fishing: Viable Data Lakes
2019 will be critical for enterprises to build a usable data lake in their organisation as they continuously deploy cloud services. Adding in an intelligent set of discoverable, metadata-tagged data from all their systems, devices and services to extract value from the terabytes of structured and unstructured data they generate each day will enable them to run analytics, business intelligence, ML and AI, and gain vital insights into new efficiencies to gain a competitive edge. Compared to a traditional data warehouse approach, a key principal of data lake architecture is to provide a place to land all the raw data without transformation or loss, so that any transformations on the data can be replayed at will. The challenge with this approach in an enterprise is maintaining a level of control over the landing of the data so that the volume and veracity doesn’t become overwhelming or turn into a data swamp.
By utilising Lambda architecture, businesses get the benefit from being able to use streaming data to report in near real-time, offering almost immediate visibility of important events; a significant step change from the traditional data warehouse approach where you’d have to wait 24 hours. Companies then need to apply a pragmatic approach to making sense of the data such as: Storage taxonomy, curating data workloads through classification for example, data security and who has access to it (IdAM) as well as data science tooling to help data scientists create/apply good equations to the Data Lake to improve future analysis.
- The Democratisation of Data Science
Artificial Intelligence is a business paradigm shift that cannot be ignored. In 2018, AI and Machine Learning (ML) started to gain traction, particularly when processing structured and unstructured data in order to help businesses make intelligent decisions and spot trends. Today, cloud AI can offer intelligence at scale, scanning vast numbers of image, audio, video or text files to track patterns and anomalies. Some AIs are functioning at levels that were impossible even two years ago, generating unparalleled business value. As a result, we are now seeing a growing appreciation for how cloud AI could revolutionise business models in a cloud-native ecosystem.
The three AI technologies crucial to businesses in 2019 are: Sight, Language and Conversation. Leaders need to leverage these services within their own context by introducing cloud AI into existing applications and enabling business to use data science which is often in short supply. Therefore, having a viable Data Lake with data that is tagged and ingested in the right way is more effective than just investing in analytics services.
2019 will continue to see businesses building AI into their digital strategies. The biggest uptake will be using AI to take away more menial tasks from human beings and apply a level of intelligence to basic business processes. For example, AI Chatbots growth in contact centres answer 80 per cent of repetitive questions, leaving humans to deal with the more complex and important 20 per cent. These intelligent scripts are able to remove a layer of administrative burden, whilst offering a higher level of customer experience.
- Multi-Cloud – Freedom from Vendor Lock-in
A recent study by The Cloud Industry Forum (CIF) found that organisations are more open to multi-cloud environments, with three-quarters of firms adopting the use of more than one cloud service to power their digital transformation process. It is because business leaders are finally realising that cloud-vendor-lock-in impedes on the creativity, availability and fluidity enjoyed by a multi-cloud approach.
A multiple cloud approach gives enterprises an above 5-9s (99.999%) availability as outages cost significant money in lost orders and business downtime. Thankfully, this kind of availability is getting easier to implement due to microservices, containerisation tools, and cloud service providers embracing standardisation. The best models are based on cloud-native applications that use standards-based containers (e.g. Docker) and orchestration (e.g. Kubernetes).
Simon Evans, CTO of Amido, adds: “What’s fascinating right now is the pace at which open source projects, from the likes of Google and Apache, are being embraced as managed offerings by all the big cloud vendors. These proven and open technologies are rapidly replacing the pioneering first movers in the cloud; projects like Kubernetes, Apache Kafka and Apache Spark are regularly available “as a service” on the big cloud providers, and this is without doubt a good thing for the world. This convergence is the key to avoiding vendor lock-in while still enabling a business to focus on their digital USP. It is the enabler for a multi-cloud strategy.”
Standardisation also means that multi-cloud offers businesses to run workloads more cost-effectively, as prices often change between cloud service providers. For enterprises with critical workloads and cloud experience, multi-cloud can improve both uptime and competitiveness.
There is also an increase in companies using hybrid and multi-cloud environments from the big vendors: AWS, Google Cloud or Microsoft Azure. This trend has also been encouraged by cloud providers creating managed versions of open source stacks, like Apache Kafka, for certain capabilities. This enables easier migration from one cloud to another.
However, now IBM has acquired RedHat, how is that going to impact the big cloud providers and IBM’s other strategies, which include OpenWhisk, IBM Cloud Manager, BlueMix (now IBM Cloud), Pivotol Cloud Foundry, etc.? Richard Slater, Principal Consultant and DevOps/SRE Leader at Amido, suggests: “I suspect IBM will work with the three cloud providers to offer “OpenShift as a Service” across multiple clouds. It’s one thing that none of the cloud providers can offer at the moment. Although, individual providers’ cloud stacks have their own unique strengths, for example, multi-cloud lets you use a document store from one platform, and database or data lake from another. Picking the best tools for the job can give you the edge, so it’s best to shop around to be innovative with your cloud strategy.”
Technologies of the Cloud have Changed and its Purpose is Shifting
“Amido has a wealth of expertise in cloud technologies. Its Cloud Futures: 2020 report confirms our recent survey findings that UK businesses are clearly recognising the need for transformation and are gradually leaving legacy technologies behind in favour of next generation ones to pursue competitive advantage,” adds Alex Hilton, CEO of The Cloud Industry Forum.
“Cloud is critical to this shift,” he continues, “thanks not only to the flexibility of the delivery model, but also the ease with which servers can be provisioned, which reduces financial and business risk. Furthermore, cloud’s ability to explore the value of vast unstructured data sets is next to none, which is essential for AI and IoT. As Amido states, to claim the golden thread to becoming an AI-Driven Business you must leverage and embrace all the five cloud elements as explained in its Cloud Futures: 2020 report.”
Simon Evans, CTO of Amido, concludes: “It is not just the technologies of the cloud that have changed; its purpose is shifting too. My first memories of the internet happened sometime in the mid 1990’s, when the world started to realise how the internet could change our lives forever.
“2019 will be a similar moment in time for the adoption of AI and is the year that it will go mainstream, due in equal parts to the power of today’s cloud, and a clearer understanding within business of how AI can be applied to a problem domain. AI is not just a technology; it is a business paradigm shift that cannot be ignored.”