If you haven’t learned it yet, multicloud deployment is not something you can improvise. Now, companies that didn’t make solid plans in the first place need real solutions.
According to a SAS-sponsored report titled “ A Silver Lining from Every Cloud,” most decision-makers in businesses in the UK and Ireland face challenges from having data across multiple clouds (also known as multicloud).
The report focuses on the difficulties that companies encounter when relying on various public and private cloud platforms to store their business data and run applications. The most common complaints are low accuracy, high costs and low speed. In other words, multicloud isn’t making things better.
The report surveyed more than 200 data, analytics and cloud services decision-makers at companies with more than 3,000 employees. I have a hunch the responses would be comparable to other markets in Europe, the US and Asia.
Note: Keep in mind that bias may exist when the company sponsoring a report sells a solution to the problems listed in the report.
Resort to trickery
The report indicates that, on average, organizations operate across three private clouds. Nearly half (42%) rely on at least two public cloud providers. These are hosts for business applications, analytics, and business data.
Companies reported issues such as multiple answers to the same question depending on where the cloud data resides (64%), high costs (64%), and latency in gaining insights from the data (60%). It is not good.
Those leveraging the data have found tricks to get around the limitations. A popular trick is to extract regular snapshots of data into a common database. Additionally, 70% use different analytics platforms in each cloud and need to consolidate responses, which often results in erroneous data and wasted time. People need to learn what they can and cannot trust, and then create microsystems around the dysfunctional data to do their jobs.
The result of all this trickery is a set of data platforms that need to be better integrated. All of these problems, inconveniences, and workarounds are likely caused by the lack of a plan before data was migrated to cloud platforms. Most of this should be expected, as we have been dealing with a lack of proper planning for years.
It’s not rocket science
The solution to these problems is not to scrap a complex cloud deployment. In fact, considering the advantages that multicloud can bring (cost savings and ability to leverage best-of-breed solutions), it is generally the right choice. What gets companies in trouble is the lack of a real plan that indicates where and how they will store, protect, access, manage, and use all business data, regardless of where it resides. Don’t just send inventory data to a single cloud platform and expect efficiencies.
We are only considering data complexity here; There are also other issues, including accessing application functions or services and securing all systems across all platforms. Data is typically where companies see problems first, but other issues will also need to be addressed.
A solid plan tells a complete data access story and includes data virtualization services that can make complex data deployments more usable by users and business applications. It also enables data security and compliance using a software layer that can reduce complexity with abstraction and automation. Simple data storage is just a small part of the solution you need to consider.
Businesses are likely to continue to struggle with complex and inefficient data usage, including security, governance, and compliance. This will drive necessary changes after the fact, including a reassessment of data integration, data security, and data connectivity solutions.
Unfortunately, this will be like changing the tires on a truck while it is running on the road. The process will be disruptive, risky, and cost twice as much. We need to be much more proactive about technology planning, starting now.
Multicloud deployment of consistent infrastructure across AWS, GCP, Azure, and more
Moving to the cloud is no small feat, especially for enterprise-scale infrastructure. And imagine the complications when you need to deploy to more than one cloud. Multicloud deployment is sometimes characterized by slow, error-prone workloads, lack of consistency, and inflexibility that hold users back.
In this blog, we will provide clear definitions, use cases, benefits, challenges, and factors to consider for multicloud deployment. Then we’ll wrap up by describing how scalable multi-cloud automation makes everything much smoother.
What is multicloud deployment? Definition + Examples
Multicloud deployment occurs when an organization deploys resources such as infrastructure, platform, or software across multiple public and private cloud providers such as Amazon AWS, Microsoft Azure, Google Cloud, and others.
There are three basic types of cloud-delivered resources:
- Infrastructure as a Service (IaaS): IaaS includes basic infrastructure building blocks that you would find in a data center, such as virtual machines (VMs), storage, and network function virtualization (NFV).
- Platform as a Service (PaaS): PaaS is when the cloud provides the middleware needed to develop and manage applications. This includes things like database services, content delivery and web services, artificial intelligence and machine learning (AI/ML) services, and inter-application messaging.
- Software as a Service (SaaS): SaaS is the delivery of a fully usable application. Netflix, SalesForce, Concur, and countless other applications are SaaS.
The benefits of multicloud deployment
Organizations do multicloud deployment because cross-cloud deployment offers role choices, specific strengths, and cost savings.
No single cloud provider does everything an organization might need to do in the cloud. If one tool does some of the things you need while another does the rest (or a combination), multi-cloud deployment may be the only way to operate in the cloud.
Having to choose between one tool and another can make cloud deployment impossible or unrealistic, especially for larger organizations with more complex or diverse infrastructure (such as information technology in government, for example).
Additionally, some cloud providers may be better known for specific services than others. Amazon Web Services (AWS), for example, is the most established cloud platform on the market, so it has a larger user base and a reputation for reliability. If you need search integrated into your infrastructure, Google Cloud Platform (GCP) is king – it uses the same infrastructure as Google Search and YouTube.
Another benefit of multicloud deployment is its ability to help control cloud computing costs. AWS, Azure, and Google have their own pricing structure, which is a deciding factor for some deployments. But prices and billing increments for cloud services like storage change frequently. Multi-cloud deployment allows you to diversify the tools you use so that your entire cloud deployment isn’t locked into a pricing structure you can’t afford – or simply don’t want.
The challenges of multicloud deployment
Obviously, deployment on cloud platforms is not without some difficulty. Some of the common issues organizations face when moving to multi-cloud deployment include:
Teams with a lack of experience:
Each cloud (and each service those clouds provide) requires specialized skills to manage.
Rewriting for each cloud:
Just as cloud management is specialized, each cloud has its own APIs and integration methods.
Managing several different environments and dealing with multiple vendors can be quite complicated.
Comparing and managing costs:
Organizations using multiple clouds are not looking at price by choice. They often balance the cost of individual services (such as input/output cost) against the overall cost of using the tool. This can make budget and affordability a concern when deploying to clouds.
Security and risk management:
Ensuring security in different cloud environments and during transit between clouds is fundamental for any organization.
As you may have noticed, the main problem with multicloud deployment is that there is not much standardization between cloud services. Each cloud does things a little differently. There may be some similar constructs among certain types of PaaS cloud offerings (such as SQL-based databases), but even so, there are dozens of specialized database services that may be better for different use cases.
This lack of standardization really becomes apparent when configuring and maintaining individual clouds. Infrastructure as Code (IaC) tools like Terraform can be used to help reduce configuration complexity, but this speed increase can still prevent organizations from efficiently using multiple cloud providers at the same time.
Multi-Cloud Automation Use Cases + Benefits
Almost anything can be automated in a cloud environment. This includes tasks that are critical to building and maintaining infrastructure. This also means you can automate application lifecycle management (ALM), from server/service provisioning to security, management, scaling, remediation, and destruction.
Automation in a cloud environment is focused on the timeless issues of reliability, availability, and scalability (RAS). With automation, it is easier to ensure environments are consistent, maintain them in their proper state, and maintain self-healing systems.
There are many use cases for automation in a multi-cloud environment. For example, automation facilitates the development of microservices architectures, like Kubernetes, that reduce single points of failure. It also allows you to scale services up and down as needed, quickly deploying new systems and eliminating unnecessary ones.
How automation supports a multi-cloud strategy
Making the decision to deploy to multiple clouds (or making changes to your current multicloud deployment) can have a huge impact on your development and operations. That’s where automation shines: it can actually make managing complex multi-cloud environments easier.
Deploying across multiple environments almost always creates a skill gap. Remember how different each cloud provider can be? When team members become subject matter experts on one platform, the techniques and nuances they learn may not transfer to another cloud deployment. Automation can help your team bridge the skills gap by allowing different subject matter experts to develop reusable resources for others to leverage.
Automation can also minimize differences between environments. Providing a consistent abstraction layer that connects individual cloud providers, creates a more even playing field across clouds for your team to utilize. This means that users do not need to be familiar with the differences between environments to use them properly. For example, you can write a Terraform configuration set that allows users to deploy the same set of services to AWS or GCP simply by passing in a single configuration option.
But multi-cloud automation does more than fix and prevent cloud deployment issues. By addressing the above friction points, it offers architects and engineers new ways to develop environments. This leads to better, more resilient infrastructure across all platforms.
Introduction to Multi-Cloud Automation
Finally, any automation and configuration management tool you use for multicloud deployment shouldn’t care about the location of the deployment. Puppet stands out because it doesn’t care if your operating systems are physical, virtual, local, in the cloud, or on multiple clouds at the same time.
Puppet is one of the pioneers in using abstractions to manage configurations. The reusable components in Puppet are written by experts in individual technologies to be leveraged by users without specialized cloud skills. In other words, Puppet users get specialized features without having to become experts.
The art of multicloud deployment in your organization
Enabling users to get the most out of their cloud applications can be a technical challenge. Discover how to design and deliver the next generation of applications.
As cloud adoption has steadily increased, it has become increasingly risky for organizations to host all of their applications and data on one cloud provider. Risk can be mitigated through multicloud deployment, which distributes resources across multiple cloud providers.
Pros of multicloud deployment
One of the key benefits of a multicloud deployment approach is that it ensures that mission-critical services are not disrupted when a cloud provider experiences an outage. This resilience is crucial for systems and applications that need to support end users 24 hours a day.
Today’s business needs are constantly changing. Multicloud deployments enable organizations to remain flexible and agile in the face of constant and rapid change. It also allows organizations to satisfy different data needs and ensure data is available.
Organizational IT compliance requirements around the areas of privacy and data sovereignty often vary. When dealing with data that involves stringent data security measures, multicloud deployments allow organizations to store sensitive data in a hardened private cloud and control how public cloud environments query it.
Avoiding vendor lock-in
Multicloud deployments provide companies with a way to not be tied to one provider, as the alignment between a provider and an enterprise can change over time. Misalignment can result in increased costs and ineffective service delivery. Additionally, switching providers as a result of this misalignment can be expensive and time-consuming. Multicloud environments limit organizations’ exposure to vendor lock-in.
Multicloud deployments can provide an organization with the means to optimize the costs of cloud technologies and the reliability of workloads. Because cloud providers vary in offering and cost, organizations can choose which providers cost-effectively align with their strategic initiatives.
Cons of multicloud deployment
A single cloud provider can present a steep learning curve for teams as a result of the processes and systems that IT teams need to learn, as well as the familiarity with the services that these providers present. Now consider the impact of adopting more providers. It can be challenging to ensure teams remain competent in all environments.
Overall, cost proves to be a challenge for multicloud deployments. Extra cost is generated from the additional traffic and management layer between cloud environments. Unnecessary expenses can arise when organizations fail to understand cost differences between cloud providers.
Additionally, the cost of hiring and training staff for all cloud environments and the cost of unused resources that can go unnoticed in complex cloud environments show that costs can easily spiral out of control without proper management and monitoring.
Considerations for multicloud deployment
There are a number of considerations that need to be made for a successful multicloud deployment. This includes infrastructure, operations, and applications.
A multicloud deployment plan should be specific about the target infrastructure based on the current and future needs of various stakeholders. The plan must also take into account the impact of advanced technologies such as software-defined infrastructure, virtualization, and more.
The deployment plan needs to consider a multicloud deployment that supports these advanced infrastructure technologies in complex hybrid and multicloud environments. It is also crucial to determine how necessary data format conversions will be performed when moving data across public cloud and on-premises environments. This consideration still applies to data transit between different cloud providers.
It is also important to determine whether a potential multicloud deployment supports infrastructure self-provisioning as much as possible. This includes infrastructure as code (IAC) models, particularly because cloud providers’ IAC tools are vendor-specific and often difficult to manage in multicloud environments.
Finally, data stored in containerized environments needs to be managed and protected correctly. Containerized environments benefit multicloud environments by running code the same way regardless of the deployment infrastructure.
A multicloud deployment plan must address a range of operational issues. There must be an understanding of the impact of the deployment on the IT landscape and where new roles may need to be established.
For example, business relationship management functions may need to be introduced to ensure that business needs and IT services work in alignment. These roles must also be created with access control and multicloud security in mind.
One of the biggest challenges affecting multicloud deployments is cost management. As a result, the deployment plan must incorporate a cost management process to handle current and future right-sizing.
It should also be easy to move data from one cloud to another when needed. Users need to consider multicloud deployment tools that address data replication, synchronization, and multicloud data transfer in a cost-effective manner.
Organizations should also consider multicloud deployment tools that manage and deploy the entire data structure from a unified dashboard to provide transparency across the entire spectrum of multicloud end users. This transparency must also cover billing and pricing models for these end users.
To effectively deploy multicloud applications, teams must evaluate which applications and workloads are best suited for specific cloud platforms. This can be determined by the availability of specialized computing, how simple it is to integrate a cloud provider’s services and resources with other cloud environments, and the geographic locations of the provider’s data centers.
Protecting and securing data must be a priority, as data security is one of the main challenges for multicloud deployments. Deployment of multicloud applications must be augmented by effective authorization and authentication capabilities to protect data.
Encryption of data at rest and data in transit is one of the approaches that can be taken to protect data. Additionally, this data needs to be protected from corruption and loss and should be considered in a multicloud deployment plan.
Additionally, standardization and coordination of development stacks across clouds must be considered to ensure consistent and interchangeable deployments across multiple clouds. Considering continuous integration and delivery solutions for multicloud environments can facilitate the move to multicloud environments and make the deployment of multicloud applications more consistent and manageable.
Top Multicloud Deployment Tools
Flexera Cloud Management Platform
Flexera is a cloud management tool with a wide range of discovery, operational monitoring, management, governance, template-based provisioning, orchestration and automation, and cost optimization across multicloud environments and bare-metal and virtual servers. It is suitable for, but not limited to, small and medium-sized businesses that need a powerful orchestration engine and workflow automation capabilities.
VMware multicloud solutions give organizations the ability to easily migrate to the cloud without having to recode their applications. They enable them to modernize their infrastructure and operate consistently across multicloud, data center, and edge environments. VMware offers several multicloud products, including VMware Cloud Foundation, Tanzu, Cloud on AWS, vRealize Cloud Management, CloudHealth by VMware Suite, and more.
Azure Arc extends the Azure platform to enable users to build applications and services that can run flexibly across multicloud environments, at the edge, and in data centers. Arc runs on new and legacy hardware, embedded systems, IoT and Kubernetes devices, and virtualization platforms.
Nutanix Cloud Manager Cost Governance
Formerly known as Nutanix Beam, Nutanix Cloud Manager Cost Governance is a cloud management platform that offers organizations visibility into cloud consumption patterns and provides solutions for cost management and security optimization. Nutanix Cloud Manager Cost Governance also simplifies and boosts multicloud governance. Cloud teams looking for insights into their spend will find great value in this tool.
Mist is an open-source multicloud management platform aiming to simplify multicloud and provide a unified interface for multicloud management. Mist supports all relevant infrastructure technologies such as private and public clouds, containers, bare-metal servers, and hypervisors.
Deciding whether to move to multicloud
Organizations should keep an eye on multicloud if they are looking for options that single providers do not offer. If you like flexibility, resiliency, and control over applications and data, consider multicloud deployment. However, because multicloud deployments are large-scale transformative undertakings for any enterprise, the deployment plan must be executed in an agile manner.
Hybrid and multi-cloud deployment scenarios
As cloud strategies gradually transition to cloud-only initiatives, many IT teams feel pressure to move all, or at least most, of their workloads to the cloud as legacy on-premises infrastructure slowly becomes harder to use for modern applications. Seeking to avoid vendor lock-in, keep sensitive data secure, and increase organizational agility, more and more companies are adopting hybrid and multi-cloud strategies. In fact, hybrid IT is increasingly seen as a long-term strategic project for many companies. Consider the following:
According to the IDG Cloud Computing study, 42% of organizations currently rely on multi-cloud environments.
A recent Forrester presentation revealed that 74% of companies describe their cloud strategies as “hybrid” or “multi-cloud” today.
Gartner confirms these numbers, projecting that 75% of midsize and large organizations will adopt hybrid and multicloud IT strategies by 2024.
Hybrid cloud strategies are undoubtedly powerful, but there are several types of hybrid and multi-cloud deployment scenarios that organizations should consider based on their application needs and how they want to configure their IT infrastructure.
Hybrid cloud deployment scenarios
Hybrid cloud environments incorporate infrastructure from multiple platforms and data centers. In most cases, this involves running infrastructure on-premises while also using resources hosted by a cloud service provider such as Google Cloud Platform.
Here are three of the most common hybrid cloud deployment scenarios:
- Lifecycle Partition
Lifecycle partitioning is the process of moving parts of the application development lifecycle to the cloud while the remainder remains on-premises. The most popular example of this hybrid cloud deployment scenario occurs when applications are developed and tested in the cloud, but then moved on-premises for production deployment.
- Application partitioning
Application partitioning occurs when parts of a production application run in the cloud while other parts run on-premises. For example, the Sony PlayStation runs databases for individual games in the cloud, but handles user authentication on-premises.
- Application scope
Application spanning occurs when the same application runs on-premises and in the cloud. A common use case for this hybrid cloud deployment scenario is when it is much faster and easier to provision new infrastructure from a cloud provider to meet spikes in demand than to scale on-premises resources. A good example of application breadth is Best Buy actively running its entire online store application across multiple cloud regions and multiple on-premises data centers to allow it to quickly adjust to spikes in demand, such as during the holiday season.
Multicloud deployment scenarios
Multi-cloud infrastructure involves a combination of on-premises, hosted, and cloud services spread across internal data centers and multiple private and public clouds. Simply put, multi-cloud environments allow you to choose the right cloud for each specific job because you are using more than one cloud offering at the same time.
DataStax customers often think of multi-cloud strategies as future-proofing exercises. Most of the time, companies want to make architectural decisions today that allow them to migrate to or leverage other public clouds in the future, taking their data wherever it is.
Multi-cloud strategies are gaining more momentum as organizations try to unlock best-in-class capabilities from different cloud providers.
There are two common multicloud deployment scenarios:
when a service or product runs on more than one cloud service provider infrastructure and potentially on-premises as well.
when data is integrated or exchanged between cloud service providers as part of a logic app deployment.
Multicloud deployment involves taking any of the above deployment scenarios and deploying them across multiple clouds, not just one. Sometimes this is done to avoid vendor lock-in. But most of the time, this is to gain access to specific cloud functionality, moving each workload to the most beneficial environment.
Is your company ready to move to a hybrid or multi-cloud environment?
There’s a reason why hybrid cloud and multicloud adoption is increasing: These environments offer organizations the cost savings, agility, scalability, and availability that modern applications demand.
While moving applications to the cloud is easy, managing all the associated data can be complicated without the right approach. After all, there are several issues to consider when it comes to the success of your hybrid cloud journey, including data silos, ongoing scalability, and availability.
To achieve this, organizations need to have a well-thought-out strategy before migrating to hybrid or multicloud environments. By doing your due diligence and keeping these critical design principles in mind as you begin to architect, you can overcome these challenges and unlock the true promise of the cloud – delighting your customers and bolstering your bottom line along the way.
You can also count on the help of a specialist.