U.S. Federal Agencies Spot Emerging Cloud Trends for 2022

Myles Brown | Monday, August 15, 2022

U.S. Federal Agencies Spot Emerging Cloud Trends for 2022

Federal agencies are moving toward cloud-based IT data centers and have increased their budgets to do so. Cloud spending is increasing. Federal spending alone has been expected to rise from $6.6 billion in fiscal 2020 to $8.5 billion in 2023, according to Bloomberg Government. Much of the spend centers around hybrid and multicloud environments, cloud native technologies and cloud analytics. No matter your role in IT, these trends affect you and your organization.

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The use of public cloud at U.S. Federal Agencies has been on the rise since the 2019 Federal Cloud Computing Strategy – Cloud Smart was introduced to embrace “best practices from both the federal government and the private sector, ensuring agencies have capability to leverage leading solutions to better serve agency mission, drive improved citizen services and increase cyber security.”

Laid out by the Office of the Federal Chief Information Officer, Cloud Smart was designed to drive savings, improve security, and deliver mission-serving solutions faster, as well as improve the ability of agencies to purchase cloud solutions through repeatable practices and sharing knowledge. This has resulted in a much broader cloud adoption among all types of federal agencies.

According to government market intelligence leader Deltek, federal spending on cloud computing reached $10.8B in Fiscal Year 2021, up from $9.2B in FY 2020 and $7.6B in 2019. Figure 1 shows the growth of cloud spending across civilian, defense, and independent agencies.

 

Figure 1 Federal spending on cloud computing

This upward trend appears to be increasing in FY 2022. The CIO for the Department of Defense, Officer John Sherman, said that the Joint Warfighting Cloud Capability contract will be awarded in December 2022 and will be worth upward of $9B, according to the U.S. Department of Defense. The contract will be a multicloud effort that involves the four biggest public cloud providers: AWS, Microsoft, Google, and Oracle. This brings us to our first trend.

Trend #1: Hybrid and Multicloud

IT organizations, both in the public and private sector, are embracing hybrid and multicloud architectures. A hybrid architecture combines the use of both a public and a private cloud. Organizations often use a public cloud to address issues in their private data centers, such as those having to do with scale or high availability. Since it doesn’t usually make sense to scrap all the expensive infrastructure organizations already have, many agencies run some workloads in their private cloud in their own data centers and run other workloads in their public cloud provider of choice. With this approach, IT infrastructure teams need two different sets of ways to procure and manage those infrastructures unless they use some sort of platform or framework, such as VMware Cloud, that allows workloads to be managed across both infrastructures under one pane of glass.

Many organizations already use VMware to manage their private cloud. According to the Flexera 2022 State of the Cloud Report, 31% of organizations use VMware vSphere to manage their private cloud. For such organizations, it can be a simple transition to use VMware Cloud to run the same kinds of workloads you’re running in your private cloud in any of the popular cloud providers without having to learn a lot of new tools and architectures.

For those agencies that embrace public cloud, questions remain: which public cloud provider should they use, and should they choose just one? Increasingly, we are seeing multicloud architectures as an option. Running workloads in multiple public cloud provides some interesting trade-offs. But first, let’s define what we mean by multicloud. Many organizations find themselves running different workloads in different clouds for a variety of reasons. For example, an agency may mainly use AWS but may also use commercial off-the-shelf software (COTS) that only runs on Microsoft Azure. Does that really mean they are multicloud? Most people would say no. So, too, if an organization uses AWS as well as Microsoft Office 365 (a Software as a Service cloud product), most IT professionals would not consider that as multicloud. So, when we talk about multicloud, we mean that an organization is actively running its own apps in multiple public cloud providers. In Figure 2, you can see how organizations are using multicloud architectures.  


Figure 2 Percentage of organizations using specific multicloud architectures

Multicloud environments allow organizations to use the best-of-breed services from each provider, avoid vendor lock-in, improve resilience and risk management, and shop for the best prices to run workloads wherever it’s cheapest. The biggest perceived drawback is having to learn multiple cloud tools and behaviors. Other drawbacks include decreased bargaining power and increased security needs. If you are spreading your workloads across multiple cloud vendors, then you won’t be able to take advantage of some of the volume discounts that you might otherwise be able to use. Also, your surface area is increased from a security perspective. The more infrastructure you have to deal with, the more of a security burden.

Let’s take a closer look at some of these trade-offs. If you intend to run different workloads in different clouds, then you can pick the best cloud provider for each app to take advantage of the best-of-breed services and cheapest pricing. This will mean that your teams will need to know all of the cloud providers well and each individual app will be locked-in to that vendor. If your intention is to create cloud-agnostic workloads that can be deployed to any cloud, then you’ll need to pick the lowest common denominator in terms of services that you choose. In effect, you would only be using the basic services of virtual machines, networking, and storage, and you’d have to ignore all the bells and whistles each vendor provides.

However, if you use a platform or framework like VMware Cloud or OpenShift, you can get high-level services that extend to all the public cloud service providers. However, these tools also come with some complexity and cost. One of the ways to decrease the burden of moving workloads between clouds is to embrace cloud native architectures, which brings us to our next trend.

Trend #2: Cloud Native Technologies

Agencies tend to start off using a public cloud by migrating some non-mission critical workloads into virtual machines from their public cloud vendor of choice. This is often referred to as a lift-and-shift. However, traditional applications lack the ability to take full advantage of all the cloud benefits. Cloud native technologies, which are easily deployed and managed in the cloud, give you these benefits: speed to market, scalability, high availability and enhanced security. There is a vendor-neutral organization that sets standards for such cloud native applications, the Cloud Native Computing Foundation (CNCF). Its mission is to make cloud native computing ubiquitous. CNCF provides the following definition for cloud native:

“Cloud native technologies empower organizations to build and run scalable applications in modern, dynamic environments such as public, private, and hybrid clouds. Containers, service meshes, microservices, immutable infrastructure, and declarative APIs exemplify this approach.

“These techniques enable loosely coupled systems that are resilient, manageable, and observable. Combined with robust automation, they allow engineers to make high-impact changes frequently and predictably with minimal toil.”

A major tenet of cloud native is that applications should be decomposed into a collection of small, loosely coupled, independent services. These microservices form an architecture where each service is fine-grained and communicates through lightweight protocols. There are two main implementations of microservices that have become popular in the cloud. One way to implement a single microservice is by encapsulating it in a container like Docker. The other option is through cloud-powered serverless functions.

Container usage has been increasing since Docker was first introduced in 2013. Lately, it has become very popular in IT organizations of all sizes. In the Flexera 2022 State of the Cloud Report, 40% of all respondents stated that “Progressing on a cloud-first strategy” was a top initiative for 2022, while 35% said that a top initiative was to “Expand use of containers.” Docker is no longer the only game in town when it comes to running and orchestrating containers. The most popular containerization framework is Kubernetes, an open source orchestrator that can run in on-premises data centers or in any cloud. In fact, the cloud vendors have special services for running Kubernetes like Amazon Elastic Kubernetes Service (EKS), Azure Kubernetes Service (AKS), and Google Kubernetes Engine (GKE). The popularity of these tools is shown below in Figure 3.


Figure 3 Percentage of container tools used by respondents

Another way to implement a microservices architecture that fits within the CNCF definitions is with serverless functions. These are sometimes referred to as Function-as-a-Service, or FaaS, offerings from the cloud vendors. In the Flexera report, 36% of respondents were currently using FaaS in production, with an additional 29% experimenting with FaaS.

Trend #3: Cloud Analytics, Machine Learning & AI

As federal agencies move more of their workloads to the cloud, they find that more and more of their data is available in one centralized place. In the private sector, companies are now using much of the data they have collected over years on their customers to make data-driven decisions. Federal agencies also have big data and can use it to make better decisions. The cloud is well-suited for performing all kinds of analytics on that data, saving agencies time and money.

Three Main Types of Analytics

Let’s look at the three main types of analytics.

The first type, Descriptive Analytics, has been around for decades. It asks the question, “What has happened?” To answer this question, agencies have been collecting data in data warehouses for many years and then building reports and dashboards using Business Intelligence (BI) tools like Tableau, IBM Cognos, or Power BI. Although a move to the cloud doesn’t much affect Descriptive Analytics, many organizations are upgrading their legacy data warehouse appliance to a newer cloud-powered data warehouse service from the major cloud providers, which can handle large amounts of data due to their seemingly limitless scale. Upgrading to a major cloud provider is not the only option. Some organizations are moving to cloud-based data warehouses that have their own analytical tools, such as Snowflake or Databricks.

Predictive Analytics asks the question, “What could the future outcome be based on previous trends and patterns?” These educated guesses of future outcomes are predicted using statistical and machine learning algorithms. In the past, these machine learning algorithms were the purview of a very small set of data scientists, which were in short supply. But as machine learning has grown, data science has become a popular IT specialty. Additionally, there are increasingly more machine learning-driven features incorporated into cloud services by the public cloud vendors. It may very well be that at some point in the near future, machine learning will be just another skill in every developer’s tool belt.

The final type of analytics is Prescriptive Analytics, which answers the question, “What should an organization do?” Prescriptive Analytics deals with optimizations to achieve the best outcomes. By simulating the future under a set of assumptions, Prescriptive Analytics will analyze various scenarios and find the optimal path to take. This is the most complex type of analytics and involves heavy-duty machine learning and data science.

How to Stay on Top of These Trends

These three major cloud trends at U.S. Federal agencies mean that IT teams are needing a lot more than just training from a single cloud vendor. With multicloud, cloud native, and cloud analytics, there are a number of vendors involved, as well as dozens of possible open source technologies in use for a given project. In order to keep abreast of all these technologies, it’s important to partner with an IT training company that offers a wide range of cloud training. At ExitCertified, we have offer vendor-authorized classes from companies such as AWS, VMware, IBM, Microsoft, Google Cloud, and Oracle, as well as open source training that you need on Containers and Cloud Native and analytics. Having worked with the U.S. Federal Government for more than 12 years, ExitCertified has a government purchase portal and pre-negotiated pricing for both GSA and SEWP contracts, making it easy for federal agencies to obtain IT training.

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