Jumpstart Your Journey to the Cloud
Getting to the Cloud
This interactive guide delivers practical insights to help accelerate, secure and optimize your cloud adoption process. In the chapters below, InterVision shares expertise gained through a decade of cloud experience and hundreds of migration projects. Read on for actionable advice that will empower your cloud journey.
- What Does It Mean to Be Cloud First?
- The 6 Common Strategies of Cloud Migration
- How to Build the Right Cloud Architecture
- Balancing Speed and Security in the Cloud
- Disaster Recovery in the Cloud
- Establishing Cloud Governance for Fast, Reliable Deployments
- Best Practices for Data Analytics in the Cloud
- Leveraging Artificial Intelligence in the Cloud
Chapter 1: What Does It Mean to Be Cloud First?
“Cloud first” has become an overused and over-hyped phrase in the tech industry. What does it really mean? Furthermore, how does this concept translate to from business strategy to reality? No matter your unique business posture, goals and needs, cloud can have an enabling role in achieving an IT vision. But in order to reach this state, it’s important to understand fully the ins and outs of cloud.
“The definition for the cloud can seem murky, but essentially, it’s a term used to describe a global network of servers, each with a unique function. The cloud is not a physical entity, but instead is a vast network of remote servers around the globe which are hooked together and meant to operate as a single ecosystem. […] Instead of accessing files and data from a local or personal computer, you are accessing them online from any Internet-capable device.”
What is the cloud?
In this digitalized world, it’s software that creates infrastructure. The cloud is the latest innovation that’s a part of this focus on digitalization. Cloud engineers use code to virtualize and automate applications and datasets on remote servers, giving them the ability to function in dynamic, highly accessible, and secure postures. They call this resulting IT environment “cloud.”
Some will ridicule cloud by saying it’s “just a server” in a special location, and to some extent they won’t be wrong since infrastructure plays a role in defining what cloud is, but it’s also about what “cloud infrastructure” entails, how it allows access from anywhere in the world to make iterations. As a result, the cloud becomes a bundle of Infrastructure as a Service, Platform as a Service, Infrastructure as Code and more—all rolled into one.
There are different cloud postures too, given your company’s intended goals and IT stance.
- Hosted – Infrastructure as a Service (IaaS) usually in a smaller, private datacenter for focused attention, often with hybridity to virtualize physical systems.
- Multi-Tenant – Leverages multiple hosted or public cloud environments, either for redundancy or specific priorities.
- Private – A cloud environment segregated from other cloud environments, often for increased security reasons.
- Public – A cloud environment managed by a major provider such as AWS, Azure or Google, where companies have individualized environments, but shared features, tools and infrastructure for cost efficiencies.
Defining Cloud First, and Misuse of the Term
When some think of “cloud first,” they think that anything they select as upgrades or newly provisioned tech must be in the cloud, whereas this might not be true. This leads to a misuse as “cloud only.”
“Cloud first” is considering the cloud before any other possible solution, either when optimizing IT spend or launching new projects. When you opt not to use the cloud for a project, there will be a good reason for not doing so. It’s about looking at your priorities for cloud and making sure to accommodate those priorities moving forward.
Triggers for Going to the Cloud
- Shutting down a datacenter
- Lease coming up
- Existing hardware aging out
- Sudden growth of capacity needs
- Real or perceived competitive pressure
- Merger or acquisition
- Improve security and reduce cost
- Cloud-first directive
- New cloud native application deployment
- Big data analytics / artificial intelligence
- Seasonal or fluctuating workloads
- No current IT disaster recovery in place
Where Does SaaS Fit In?
Most companies now use some sort of cloud, even if they aren’t aware that they are. Software as a Service (SaaS) platforms have gained immense popularity in streamlining business projects. The important point about SaaS is that the IT department must be aware, to check that such use fits within company governance policies. Too often, a business unit may be using a SaaS application, sharing data around to accomplish sensitive projects, and the business isn’t aware they are putting themselves at a potential risk of data exposure. SaaS, in some ways, can become a cloud silo. For companies utilizing lots of datasets for analytics projects, SaaS presents an additional hurdle in collecting and integrating the data needed for these projects.
Signs You Are Ready for a Cloud First Strategy
It’s best to verify your IT readiness before making the jump to cloud. Some signs that your company is ready to embrace a cloud first strategy are the following:
- You have executive-level support for going to the cloud
- You have a datacenter lease expiration coming up
- You have a big Capex expenditure and you want to consider Opex in its place
- You have a group within your organization that is experimenting and getting technology certifications
- You have change advocates in IT that are chomping at the bit
Chapter 2: The 6 Common Strategies of Cloud Migration
Once your organization has determined the cloud as a good fit for your strategic goals, migrating workloads to the cloud becomes the responsibility of IT. However, there is more than one way to get to the cloud.
There are six common strategies of cloud migration that many companies use in moving their assets to a cloud environment. Here are a few reasons one might choose one path over another, or a blended selection of paths:
Rehost – (“lift and shift”)
Rehost involves moving existing physical and virtual servers into a compatible Infrastructure as a Service (IaaS) solution. Rehosting increases the speed of migration while reducing the risk.
- Servers running packaged software
- Applications without an active roadmap
- When you need to move fast
- Motivated to avoid Capex on aging hardware
Replatform – (clean up a little)
Replatform involves changing the operating system or database engine. This allows you to use cloud native features to optimize aspects of the workload and services that are close to existing infrastructure without requiring code change.
- Changing the OS and database engine
- Upgrading to the latest release of an application
- Upgrading the OS
- Upgrading the database
Rearchitect – (replace / move to SaaS)
Rearchitect involves replacing the application with a SaaS product. In this migration option, you rebuild the application architecture to eliminate dependency on custom hardware or proprietary technology platforms. You also benefit from a fully managed solution.
- Changing application requirements
- Replacing the application with SaaS offering COTS product
- Purchasing a cloud-compatible license
Refactor – (leverage cloud native features)
Refactor involves examining how the application is architected and developed, utilizing new cloud-native features for performance, scaling and agility. This includes changing the middleware by re-coding application components. Refactoring is flexible in porting and globalization and is adaptive to modern consumer needs.
- Changing application code
- Utilizing cloud native features for performance, scaling and agility
- Adopting serverless and/or containerization
Retain – (keep as-is or revisit later)
Sometimes it doesn’t make sense to move a portion of IT systems to the cloud after all, due to complexity or strategic focus in a different area. In this scenario, retaining such applications should be kept as an option.
- A portion of the IT portfolio is too complex to migrate to the cloud
- Application(s) cannot be virtualized securely
- The core business strategy demands the application not be in the cloud
- Compliance requirements dictate location of specific datasets outside of cloud
Retire – (decommission)
Archiving portions of the IT portfolio that no longer serve the company’s interests or goals is a key strategy of any cloud migration. Not only does it save on IT costs, but it also emphasizes proper organizational security.
- Outdated and not worth keeping in regular rotation
- Applications have already exhausted their usefulness
- IT team’s attention needed on other, core applications
Since a cloud migration lays the foundation for how your IT systems will operate, the benefits and outcomes your organization will see from cloud are directly tied to your migration approach. Depending on the resulting stance you enable in the cloud, applications and data may or may not improve their communications. Therefore, taking a strategic approach to the cloud, rather than a rushed move, is the best for the long-term.
With varying levels of time commitments, cloud migration isn’t a one-size-fits-all move for most organizations. Some IT teams don’t account for the intricacies of refactoring and rearchitecting applications. And too often companies realize these complexities in a post-migration phase, which means taking on technical debt until applications can be enhanced to run in the cloud. For this reason, it’s always better to plan well in advance and do some testing along the way.
Chapter 3: How to Build the Right Cloud Architecture
Cloud architecture is the foundation upon which your IT systems and applications will operate and thus, reap the benefits of cloud. It’s critical that you design and build this architecture with those systems and applications in mind, so that the architecture meets your IT vision and can evolve over time. Organizations have been adopting increasingly complex software applications to achieve business goals, so IT development teams must evolve their software creation practices, deploying applications in a repeatable and reliable manner. Having the right cloud architecture aids in this goal, and designing this architecture takes careful planning and attention to strategic long-term company goals.
Benefits of a strategic-focused cloud architecture approach:
- Assess which cloud platform is right for your business
- Get a detailed due-diligence review of your current infrastructure
- Create a financial and business strategy foundation for migrations
- Assess applications for cloud readiness
- Develop infrastructure low-level designs
- Configure APIs and automation tools
- Improve quality assurance and testing
- Establish a Foundation for Efficient Operations
DevOps designates a set of tools, processes, best practices and corporate management guidelines to make IT organizations more agile and more efficient, fully achieved with the adoption of automation. But sometimes this emphasis on speedy deployments can make security professionals uneasy. To both keep your organization secure and run quickly in the cloud, IT governance must be built into the architecture and deployment process. This expert attention to the security aspects during an application deployment is often called SecOps.
To implement complementary SecOps and DevOps into your organization, focus on achieving the following areas in your cloud environment:
- Infrastructure as code
- Continuous deployment
- Automation (including deployment and testing)
- Monitoring and security
As a result of the SecOps and DevOps folks working together to design a streamlined, yet secure deployment process, your organization will better embrace a culture of innovation in the cloud.
DevOps and SecOps, when established in an organization properly, helps reap the following benefits:
- Speed up software fixes
- Shorten software delivery cycles
- Reduce deployment errors
- Enable automated testing
- Gain continuous integration and monitoring
- Enable automated delivery
- Balancing Speed and Security in the Cloud
- Design Thinking in IT
Chapter 4: Balancing Speed and Security in the Cloud
Since cloud’s emergence to the forefront of modern business, organizations have already grown to expect a certain speed of service equal to or better than what on-premise workloads can deliver. A cybersecurity team’s responsibility is to protect the business against rising threats of data exposure and extended downtime. Maintaining a similar speed of deployment in the cloud while also keeping everything secure is a rightful concern. Here’s how to establish a foundation for both speed and security in the cloud:
Steps to Establish a Foundation for Speed and Security
- Understand your requirements
- Clearly establish governance policies
- Build the cloud environment to fit governance
- Enforce the use of templates
- Perform validation activities
- Automate where possible
To properly build an environment that emphasizes goals of speed and security, it’s key to gather multiple stakeholder perspectives to bolster buy-in and be sure of your long-term strategy. This upfront legwork will save a lot of headache down the road.
The Shared Responsibility Matrix
As with securing any IT solution, it’s important to check that ownership for each stage of a dataset’s journey is accommodated for. The cloud is a little different from a traditional, on-premise infrastructure in that multiple hands touch its daily management and deployment. It’s a matrix with multiple entry points that propel the increased accessibility of cloud, which makes security a more comprehensive process. Thus, the need to clearly delineate and know responsibilities is more immediate than traditional infrastructure approaches.
Areas that need delineation of responsibilities in the cloud:
- DR and Cybersecurity
- Artificial Intelligence/Machine Learning
- Data and Log Management
- Maintenance and Lifecycle of Tools
As it comes to any cybersecurity posture, it’s key to be sure all aspects are covered properly. Anything that falls outside of your specific cloud environment could risk a disruption or data exposure to your business. Whether it be the physical components of hybrid infrastructure upon which the cloud rests, data going into the cloud, testing and maintenance activities or user mistakes; such aspects could permeate into the cloud if not secured adequately.
Consider every responsibility that goes into a healthy cloud environment and whether these responsibilities should be shared among team members or offloaded to an expert third party.
Chapter 5: Disaster Recovery in the Cloud
A Disaster Recovery (DR) plan that aligns with business strategy not only protects your company against the impacts of weather-related downtime, hardware failures, power outages, breaches and other scenarios; it can also empower transformative change as your company encounters new avenues of competition. Additionally, the rise of cloud services has made affordable and reliable DR more attainable than ever.
Gain the following benefits from cloud-based DR:
- Eliminate downtime and minimize disruptions
- Protect critical business data in the cloud
- Manage datasets across the cloud
- Satisfy compliance requirements
- Improve quality assurance and testing
Developing DR Strategy for Cloud
Any good DR plan should center around conducting business process analysis, defining continuity objectives, having continuous conversations with business stakeholders, and identifying steps to minimize the effects of a disaster and maximize uptime. The same steps are also true for implementing a DR plan that encompasses cloud.
Indeed, the accessibility of cloud from anywhere with an internet connection naturally lends itself to accommodate a variety of disaster scenarios to keep an organization running while full recovery takes place. However, to confirm that your DR plan matches with and has been designed for your cloud architecture, your IT team must identify which systems, functions and applications are most critical, which are less critical, and which need the least priority during an outage. Only then can your business adequately assign Recovery Point Objectives (RPOs) and Recovery Time Objectives (RTOs) for each dataset.
Backup and Restore:
In traditional environments, data is typically backed up to tape and sent off-site. However, recovery time will be the longest and the inability to leverage automation in this method leads to increased burdens on the IT staff. Using cloud-based storage is ideal for backup data, as it is designed to provide durability over a given year. Transferring data to and from the cloud is typically done via the network, and it is therefore accessible from any location.
Pilot Light for Simple Recovery:
The most critical core elements of your system are configured and running in the cloud as a “pilot light.” When the time comes for recovery, you can rapidly provision a full-scale production environment around the critical core.
Warm Standby Solution:
A scaled-down version of a fully functional DR environment is always running in the cloud, which decreases recovery time since services are always running, but also saves on IT costs since the environment isn’t actively hot.
By leveraging multiple sites in the cloud as well as on existing on-premise infrastructure in an active-active configuration, an organization can send all traffic to cloud servers in a disaster scenario, which can scale to handle a full production load.
Chapter 6: Establishing Cloud Governance for Fast, Reliable Deployments
Delineating responsibilities and adhering to predetermined policies of IT governance are essential to the ongoing security of an IT environment and thus, business at large. Cloud or not, governance can help translate people, tools and policy into process by guiding the construction, maintenance, and validation of an IT environment. Especially when it comes to cloud, governance protocols help to integrate security into software development and release processes that guide DevOps teams in what they’re supposed to do when launching new applications.
Indeed, properly established cloud governance can help IT teams reduce post-release scrambles and design for security and compliance that also emphasizes speed to match modern business demands. However, achieving this harmony of speed and security involves thinking in terms of people, process, and tools to integrate everything into governance processes.
Considerations When Building Governance Policy in the Cloud
- What automation tools can your business use so that everything isn’t built from scratch?
- If you intend to utilize internal security expertise, then how do you go about creating and/or retaining security experts on your team?
- What security requirements must be adhered to, so that compliance is maintained?
Enforce Compliance with Automation
When it comes to compliance frameworks, whether it’s GDPR, SOC, HIPAA, PCI or another, policy making can be reactive by nature. By the time any change in regulatory requirements are introduced, the change has usually been prompted to curb repeated incidents.
Nevertheless, changes in compliance frameworks must be accounted for in IT environments, so that a business can maintain its regulatory accreditation—but how? Compliance demands flexibility to change that can be at odds with the proactive disposition of cybersecurity professionals.
Using automation for identity access management, encryption assurance, blueprinting of architecture/design, templating of systems and components, software defined networking, and compartmentalized storage can increase the speed of deployment, assist in policy crosschecking to ensure continuous compliance, and aid in the validation of reference architectures. As they say, when you find yourself doing something twice, automate it—extending from production deployment all the way through continuous compliance validation.
Solving for Priorities
There are two competing areas of emphasis, depending on your IT group: speed and security. But neither speed nor security, when viewed in silos, emphasize efficiency. Those connected to DevOps want automation to have a baseline method for blueprints and templates for speedy deployments with common configurations. Conversely, a security team wants monitoring and alerting, resiliency scalability, code validation, and logging baked into the development process. Applying automation wherever possible to internal standards of governance can solve for the needs of both groups—which saves time and money for everyone.
Chapter 7: Best Practices for Data Analytics in the Cloud
Modern business runs off of having access to important information in order to make timely decisions. Having disparate datasets in siloed or sprawling environments can inhibit quick access to information, which is needed for business intelligence and advance analytics. It can create obstacles to making the right decisions not only for ongoing business, but also for the ability of an enterprise to be nimble in the future.
“The number one role of data in business is better targeting. Companies are determined to spend as few advertising dollars as possible for maximum effect. This is why they are gathering data on their existing activities, making changes, and then looking at the data again to discover what they have to do.”
AJ Agrawal, CEO, Alumnify, “Why Data Is Important for Companies and Why Innovation Is On the Way”
To interpret datasets for your business, you must have a fortified way to store and sift through the information. This process of data analytics results in what is commonly called “data intelligence,” the use of data to enhance various aspects of your business including to expand services, improve pricing and make investments. Having a predefined strategy for data use is essential before choosing your data repository option, since your strategy will shape the analytics solution. There’s a lot that will need to correspond. After all, data intelligence can’t enable the business without a strategy to analyze your data and a solution to get you there.
The Evolution of Data in the Workplace
The architecture of business has shifted to accommodate the growing importance of data, with data intelligence now taking a front seat. As your IT team leverages the cloud for innovative projects, it’s paramount to consider the current role of data in your business and what role you’d like it to play in the future. The answers to these questions will help to delineate how and where to store datasets, how and when to analyze it, and how and when to use the information from those datasets.
- Identify / clearly define the problem you want to solve
- Pilot light for problem / data fit
- Understand if the right information (data) is available to solve it
- Data collection / preparation
- Collect the relevant datasets and perform necessary transformations required for the data to be usable
- Pilot light for advance analytics
- Develop machine learning / AI models to provide the required solution
- Production deployment of solution to derive business value
- Identify other opportunities to leverage the solution / enhance the value
Once you have a well-developed process to acquire new data, analyze existing datasets and make educated and iterative decisions based upon that information, you can then apply this strategy to other areas of your business to improve efficiency. At this point, your team is leveraging Artificial Intelligence (AI) to up-level cumbersome tasks and achieve new goals.
Chapter 8: Leveraging Artificial Intelligence in the Cloud
The core element in any cloud environment is data aggregation and management. Data is rightly being described as the Oil of the 21st century. Where there is data, there is an opportunity to generate value from it. With the right data in tow, organizations can build advanced analytics and artificial intelligence (AI) solutions to tackle specific problems.
Typically, the process is to start with business intelligence, since it leads to a better understanding of your underlying data and then proceed to leverage the advanced analytics capabilities. Once you have a good picture of your underlying data, pathways emerge where AI can be applied.
“Everything we love about civilization is a product of intelligence, so amplifying our human intelligence with artificial intelligence has the potential of helping civilization flourish like never before – as long as we manage to keep the technology beneficial.”
Max Tegmark, President, Future of Life Institute
Commonly Recognized Benefits of AI
- Increase revenue
- Lower costs
- Increase efficiency
- Reduce risks
- Better customer/user experience
Artificial Intelligence (AI) is quickly becoming a table stakes measure, and a differentiator for those who are leveraging it already. Since AI is ultimately tailor-fit to the business, organizations that use it are able to minimize errors, bias, and decrease interdependencies. As a result, these companies are able to derive a more complete picture of their business’s health than any competitor would be able to do.
Examples of Businesses Leveraging AI for a Competitive Advantage
Law Firm Optimizes Preparedness:
A law firm uses AI on a data lake environment for a legal case to quickly sift through discovery information for a court case.
When having the right information equals the strength of an argument, AI uses textual analysis to determine relevant case evidence and saves hours of work that law professionals would otherwise have to do.
Banking Firm Protects IT Systems:
A bank uses AI to identify malicious actors in their account databases, sending datasets through a rigorous quality assurance algorithm that determines falsifications and suspicious activity.
A process that took hours has been downsized to seconds, which helps keep the bank’s IT systems and mobile application safe from attacks and exploitation. With AI, bank employees can increase their focus on serving customers and streamlining the banking experience.
Media Company Hires the Best, Faster:
A media & entertainment company uses AI in their Human Resources department to sift through resumes quickly with pre-determined qualifications and personality tests to determine mindsets and cultural alignment with the business. No more shortlists or next rounds.
When the hiring manager pulls the results, they receive only the most qualified candidates to choose from.
A Must-Have to Compete
AI has now grown to the point that if you are not doing it, you are going to be left behind. But the AI journey involves an evolutionary phase with your data. As you sift through the datasets with your business, it may turn out that your data is not as good as you thought it was. It could be insufficient, incomplete or unreliable. The cloud helps to not only recognize how and where data is insufficient; it also gives your IT team a pathway for improvements.
Mastering AI for a Better Business Backbone
The cloud allows you to see these gaps and work towards improving your data, through collection, cleansing and retaining processes. The better you get in this process, the more robust your data will be to perform custom AI solutions. At the end of the day, the one who owns the best datasets wins the battle.
Most organizations have mastered the traditional forms of solutions to bring about these efficiencies. AI brings a dimension that normal human observation of data and patterns cannot match, using machine learning as its underlying technology engine. Take, for example, anomaly detection in a network. It is humanly not possible to look at the millions of transactions happening every minute to discern anomalies. Nor is it possible for traditional rule-based systems to keep up. AI can do all of these things, which makes it a baseline requirement for the coming years.