Originally published on The Doppler
How to get past obstacles and avoid roadblocks stalling your cloud journey.
Cloud transformations are often referred to as “journeys,” with starting points and reasonably well-defined destinations. They begin with assessments, plans, foundational initiatives and workload migrations. The journeys do not officially have an endpoint, but successful ones do eventually arrive at a place where organizations fully embrace automation, and follow a right mix approach, where cloud is a viable option in their active portfolio.
Somewhere along this continuum, between adopting and scaling, cloud journeys can take some interesting, sometimes awkward, sometimes inspirational turns. It is when the rubber hits the road and organizations begin to truly start leveraging the power of the cloud that they gain the most confidence and speed.
But if organizations are not careful, this stretch can introduce any number of issues, causing the team to lose their way, make mistakes and miss both internally – and externally – imposed deadlines. They can lose focus on the overall transformation plan – and on the stakeholders responsible for executing on portions of the plan. This is an important part of the journey that organizations must navigate through.
How do you know if you are on the right track to success? What are the signs that you are stuck, and struggling to make progress? What does success look like at this point in your cloud journey? And what can you do to make sure you stay pointed in the right direction?
One way you can check your organization’s progress is to evaluate the current state of your cloud adoption initiative according to four basic criteria: innovation, economics, data gravity and the establishment of a DevOps culture. Are you meeting your objectives in these four areas? Are you following best practices and pushing each area to the point where you can safely say that you can see your desired destination? Let us take a closer look at how each of these measures applies.
DevOps: Embrace the Cultural Change
To effectively leverage cloud capabilities, successful organizations undertake initiatives to make their cultures more agile. This involves extensive work in the three classic dimensions of IT – technology, process and people. A lot of this work should begin as a cloud project gets off the ground. During these early stages, how the three dimensions of IT will need to change is driven by the alignment of the overall business strategy with the current level of adoption of the tenets of DevOps: automation, continuous improvement, iteration and fast feedback loops. More mature cloud projects should be pushing these factors ahead, and already witnessing cultural changes aligned with accelerated delivery throughput.
On the technology front, organizations typically start by picking an initial set of tools to support automation and/or DevOps itself. This list of tools grows to support security, testing, monitoring and aspects of the continuous integration/continuous delivery (CI/CD) pipeline. In addition, teams must choose between cloud native and best-of-breed tooling. Once your enterprise begins to gain leverage with the cloud, integrating and optimizing these tools across the organization is essential. It is also critical to consider if the tools are functioning at a high level. Have you filled out your whole technology stack? Is your organization appropriately skilled to leverage these tools?
In terms of process, many companies will start creating DevOps capabilities in certain units or departments, but not consider how these capabilities need to be developed and integrated throughout the entire organization. Companies often begin their value stream mapping in the development organization, followed by the infrastructure organization, but often get stuck there. As they look to generate greater value out of the cloud, they need to drive further alignment with their DevOps procedures across the organization. Value stream mapping, or lean analysis, should be expanded to include governance and operational functions, with a focus on continually optimizing throughput. For example, ensuring that a standard DevOps deployment flow (and toolchain) is available for use across the organization, for all SDLC environment types, helps support this key cultural transformation.
Furthermore, enterprises that typically operated in an ITIL-based data center environment now have to be updated to operate with more agility. You must determine the optimal mix of ITIL and Agile processes, in order to balance the operational guardrails with the deployment throughput expected. Deeper analysis of governance processes commonly reaps the most added throughput. For example, the adoption or expansion of “standard” change requests can address a common hurdle for production deployments. It will take years to reach the optimal mix, so this will need to be continually re-evaluated throughout the cloud adoption lifecycle.
Organizations looking to drive value in the cloud often fall behind in terms of equipping their people to operate in the new environments. The cloud requires different skill sets and a new array of tools. Most importantly, the cloud also requires a different attitude: a drive for continuous improvement. Have you assembled the right kind of team that embraces this culture of continuous improvement instead of a “hero culture” that requires individual members to make acrobatic saves to keep your project on track? Have you identified which skills exist inside the organization, and which ones will have to be brought in as new hires or from third parties? Have you found cloud evangelists in your organization, willing to embrace cloud and learn the new skills required? Have you rewarded, acknowledged or otherwise developed incentives to drive the new behaviors? Have you created new roles and set up cross-functional teams? Have you assessed which workers can adapt to new roles? Have you set up targeted training sessions for existing workers and those brought in from the outside?
Data Gravity: Are Data and Cloud Getting Along?
Organizations tend to be well into their cloud transformation journeys before they recognize the importance of tying together a universal view into their data. It is not uncommon for organizations to have one initiative underway that looks at how they can make better use of data and analytics, and a separate initiative for cloud transformation. Ideally organizations will have both as fully-fledged initiatives, developed as if they were joined at the hip. If not, you are just creating more data sprawl by spreading it out to different places in the cloud. And if you do not have a data initiative at all, we strongly recommend you get started!
The first step to an integrated, holistic data/cloud strategy should be to assess, tag and map all your data assets. Getting all these resources aligned helps the organization do a better job of migrating applications strategically and securely. This really should be done early on, as the organization gets its cloud project off the ground. In reality, it often is not tackled until the project is well under way, when organizations should be seeing value, rather than scrambling to get assets to work together.
If you are in this predicament, push hard to catch up. Full knowledge of your data is critical to the long-term success of your cloud project, and it is foundational for innovation, if this data is expected to power those initiatives. Cloud service providers and cloud-friendly third parties offer many tools to help with this. By integrating data, creating an overarching metadata layer and data catalog and migrating data from older systems to cloud-native resources, organizations can gain better value from their data, and operate with greater agility.
Economics: Optimize Your Costs in the Cloud
Most organizations that commit to a cloud transformation ultimately want to save money. Cost optimization, after all, is a defining benefit for cloud over on-premises computing (once you have a plan for overcoming the cloud adoption agility bubble). But costs do not magically fall out of the overall IT equation just from using the cloud. Clients typically build and deploy workloads to gain experience in how those workloads perform in the cloud for real vs. their hypotheses. After having tested this, organizations have to institute cost controls and manage the costs of cloud usage. The cloud cost control work needs to be done early in your cloud journey to reach your stated financial goals.
Determine the appropriate metrics, and leverage cost optimization tools to gain more visibility into overall cloud spending. Tools offered by technology providers such CloudHealth and Cloudability, or our own Continuous Cost Control managed service, include dashboards that show which cloud resources are being used, how much they cost, when usage peaks and how different cloud providers charge for their services.
Along the cost optimization continuum, organizations need to establish solid procedures for stakeholders to do a better job of managing costs. For example, if cloud instances are not rightsized based on their utilization metrics, automating this optimization process will yield returns. Advanced capabilities enable organizations to set triggers to automate decommissioning based on certain factors. If workloads are no longer needed–say, for a model validation that is complete–codifying, communicating and automating proper hygiene of your cloud estate is essential to managing costs. Later in the continuum of economic management, firms are aligning the automation of resource decommissioning to how they flow through their SDLC environments
As organizations work their way through their cloud transformations, they not only need to start dialing up the functionality of these cost-management tools, but also should consider revisiting their architecture by considering serverless compute. Firms should consider tools that can model scenarios, run cost projections, set more complicated triggers incorporating multiple factors and even anticipate certain situations. Automation capabilities are advanced enough that once properly configured, these cost-control solutions can be sustained with minimal ongoing oversight.
Innovation: The Indispensable Element
Occasionally, we see clients who have established their initial cloud implementation(s), but continue to struggle to leverage the cloud as an innovation platform. Innovation delivery via the cloud is dependent on holistic maturity across the several domains required for transformation, and is not just a matter of deploying solutions faster. Organizations need to commit to a culture of innovation, establish a strategy across the transformation domains of DevOps, security, applications and operations.
Take, for example, automated compliance and security. Each is critical for a cloud capability to enable innovation. Confidence that new deployments are compliant and secure at the moment of creation allows firms to test hypotheses and measure customer experience knowing the deployment is continuously checked. Cloud native architectures leveraging microservices, containers and orchestration provide firms with the flexibility required to test new solutions that impact customers. Combining these capabilities with DevOps allows firms to quickly deploy and retire functions based on the results of the customer experience.
It is the holistic enablement of the innovation value chain that provides differentiation. As you move through your journey, are you encountering blockers that prevent innovation in your cloud implementation? Have you completed an assessment across the multiple domains mentioned above, and created a roadmap to enablement?
True innovation in the cloud represents more than creating resources faster than you could by ordering and provisioning on premises. Software delivery changes are achieved through a mature, interconnected automation framework, and tight collaboration with business units, operations, information security and application development personnel. Enabling changes in the culture and in software delivery provides the catalyst for innovation.
Conclusion
Cloud transformation journeys do not always follow straight lines. They wind their way through different paths, and as with any major new technology implementation, it is not uncommon to get nudged off course from time to time. If you are worried that your cloud project is not generating the value it should, it probably is not. The good news: there are ways to get back on track. As you move further into your cloud transformation journey, try to fine-tune your platforms to align with the goals you set for your transformation and your overall corporate strategy. We hope these recommendations will help you get back on track, and keep your cloud project moving forward.
