As we start to think we are now all “cloud-enabled”, with most organizations having migrated workloads to the Cloud, a recent IBM-commissioned study by McKinsey & Company reveals that most companies are only 20 percent of the way into their Cloud journeys. The simple workloads are in (or have been in) the process of migration, but 80 percent of workloads are still on premises. The study went on to state that unique workload needs, multiple clouds and vendors and lack of relevant skills are the three major issues in moving that 80 percent chunk to the Cloud.
Big Data is necessitating new architectural solutions in the Cloud, or the “unique” workload. The reality is that no one large vendor’s set of offerings is appropriate for all scenarios and for a variety of reasons. One organization might simply have to deploy a risk mitigation strategy and avoid housing all data with one public cloud; two or more clouds across a division or more appears to cover their risk from a breach or other issue resulting from reliance on a single vendor. Secondly, all organizational divisions may not be on the same path; this means one division could have worked with a vendor that seemed to fit their needs, while another division utilized a different set of standards in vendor selection and/or combined with a private cloud infrastructure. This is the reality in most organizations today. Different parts of a business may have different criteria that were established at different times yet require some form of convergence or ability to manage Clouds for their customer base.
The reality is that many service partners don’t have all the requisite software engineering skills to navigate this open source, multi-tool solution set of the future. Partners are focusing on serving their customers and have their vertical domain expertise to solve challenges by leveraging cloud infrastructure. They need easy to use tools and frameworks that allow them to experiment and innovate with things like Blockchain, AI toolsets, etc, out of the box. IBM has chatbots that can be literally created in a day, alleviating the need for complex programming skills. There are solutions to optimize storage and compute, databases, analytics, security, AI and IoT. In the AI bucket, there are text to speech, visual recognition, machine learning, language translation, semantic tone analyzer and automation of AI across its lifecycle. These offerings have been created to allow the service provider to immediately deploy a variety of new interesting use cases without hardcore coding skills. The message is to experiment and innovate now – the need for digital agility is so key to business today to avoid rapid disruptions in the market with emerging, newer business models. For the savvy and technical business line manager, there are developer tools that have starter kits, DevOps insights for all types of teams and technical depth to begin the journey.
An important thing to remember is that one needs to think about the developer’s needs and how to design an environment that meets all the criteria for an effective cloud infrastructure that can serve the business today, yet scale and adapt for tomorrow’s needs. This is why IBM and others are creating distinctive tools and containers that are loosely coupled and that can be used and shifted to any changing architecture.
If your company is building cloud solutions for customers, this offer is for you. Access 12K free IBM Cloud Credits and build with any of the 130+ services and APIs available.