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Tag: cloud migration

  • Why App Dependency Mapping Is Critical for Cloud Migration

    Why App Dependency Mapping Is Critical for Cloud Migration

    Software dependencies are a crucial part of efficient, component-based programming. At the same time, they can be a hurdle for fast-paced agile development teams, because they can make it more difficult to deploy, update and migrate software applications. Many applications have dozens or hundreds of dependencies, each with its own transitive dependencies, making the problem worse.

    Dependencies are components that provide required functionality that a main component depends on. They can be incorporated into code using package managers like npm or Maven, Git-based code repositories like GitHub and container image registries like Docker Hub. 

    Application dependency mapping involves discovering and identifying dependencies and interactions between application components, their dependencies and underlying infrastructure. Creating a map of application dependencies is an essential part of gaining visibility over complex application structures and understanding the impact of deploying them in different environments.

    Why Application Dependencies Are Critical for Cloud Migration

    Application dependency mapping ensures you have identified all the components you must migrate to the cloud. You may not need to migrate all components to the cloud, but you do need to ensure all dependencies are identified and migrated together. Otherwise, your application may suffer performance issues because important dependencies remain on-premises.

    For example, if you move an application server to the cloud but keep the application’s database on-premises, your application will experience severe performance degradation and may also cause related applications to fail. Once a dependency is disrupted, all related applications suffer. Therefore, when migrating applications to the cloud, you must include all associated dependencies. 

    How Application Dependency Mapping Tools Can Help

    Application dependency mapping can help you avoid poor application performance and service outages. It is a critical component of the migration process, but is also difficult without automated tools. Application dependency mapping tools check an application and help with the following:

    • Modeling all inter-server relationships 
    • Identifying inbound and outbound connection latency
    • Determining the necessary TCP ports
    • Detecting running processes 
    • Application performance monitoring over time

    Cloud vendors offer specific application dependency mapping tools developed for their environments. For example, Amazon Web Services (AWS), Google Cloud and Microsoft Azure offer proprietary tools to help manage this process. However, these tools are tied to each provider, which means you should use the vendor tool that matches your chosen target cloud environment.

    Alternatively, you can use open source tools that provide similar services but are vendor agnostic. Use these tools if you want an assessment that is not specific to a single cloud vendor environment.

    Mapping Application Dependencies to Prepare for Cloud Migration

    An application consists of a hierarchy of dependent APIs and tools. The hierarchy starts with the application’s interfaces and then goes down through platform tools. Dependency management helps identify combinations of related versions and ensures that the development team recognizes new application dependencies when changes occur.

    Versioning application components

    The first step in this process involves versioning application components. If you intend to deploy a specific software component independently, you need to assign a version number for every revision and then track the dependency chain for this version. 

    This technique ensures you know the specific platform tool versions associated with each application version. If you need to roll back, you know what additional components you need to roll back to ensure version compatibility.

    Changing platform components

    This technique requires changing some platform components, such as middleware, which also requires synchronizing each application’s platform version. You should start from the top of the application dependency chain.

    Each application is designed to use specific operating system and middleware features, expecting “version Y or later” of the tools. As a result, you must validate each tool with a specified version against the tool’s dependencies and continue validating each of these dependencies until you reach the bottom of the dependency chain.

    However, some application dependencies are not as obvious and explicit as others. You may encounter problems if you expect to run a guest operating system in a virtual machine (VM) on a hypervisor platform in a different source. 

    You may also encounter issues if a cloud stack release, like OpenStack, requires a certain scripting language version. You can mitigate this issue by testing every dependency chain against the standard middleware and operating system combination, ensuring that all dependencies are recognized.

    Rebuild the dependency tree

    Once you are ready to move to the cloud, you need to supplement the dependency tree for applications and include all the references to the cloud provider’s APIs and features. Make sure to determine how the provider notifies of changes to tools and APIs and prepare to validate new dependencies these changes can create.

    For a multi-cloud or hybrid deployment, you must compare cloud dependency trees across all the components and applications planned to migrate beyond a cloud platform boundary. Note that having a different dependency tree for each provider can result in problems when scaling or failing over between providers’ platforms. You can avoid this by synchronizing components in advance.

    You should also rebuild your dependency trees whenever you change software platform components. A basic update could undo all the mapping and work you have done, and you can easily overlook a change to a small middleware component. You can mitigate this by setting up a life cycle management process to ensure dependency problems do not arise when incompatible elements are introduced. 

    Conclusion

    In this article, I explained the basics of application dependency mapping, and showed how application dependency tools can make cloud migrations safer and easier:

    • Versioning application components—Understanding what version your application expects for all dependent components.
    • Changing platform components—Determining the impact of switching out certain platform components. 
    • Rebuild the dependency tree—Use the map of your existing dependency tree to rebuild a matching dependency tree in the cloud environment.

    I hope this will help you evaluate the use of dependency mapping and make your next migration a success.

  • A Guide to Cloud Migration Trends and Strategies

    A Guide to Cloud Migration Trends and Strategies

    For several years, we have witnessed widescale cloud adoption as a software infrastructure growth and maintenance strategy. Spending on cloud application services (SaaS) continues to grow as monolithic applications are replaced by microservices-based apps and monoliths become relics of the past. In 2021 alone, companies spent $410.9 billion on public cloud services, and Gartner expects this number to rise by 20.4% in 2022 to reach $494.7 billion. But as this movement continues to evolve, engineering leaders preparing their cloud migration strategy must be up to speed on the latest key trends.

    Is Migrating to the Cloud Cost-Effective?

    For companies migrating to the cloud now, the process is no longer a simple transition from on-premises to remotely hosted servers. Cloud service providers now offer a wide variety of options, and companies run the risk of overspending in the cloud marketplace.

    A lack of clarity of their business and product needs or submission to shiny object syndrome can drive companies to spend on non-essential services, especially during migration. It is easy to fall into this trap; companies only realize it after they have committed and try to undo the damage by reversing the process.

    Although many public cloud providers offer pay-as-you-go pricing, companies often purchase more services than they use. When companies are unclear about their objectives, such expenditure is more extravagant than the utility. This awareness of cloud spending has encouraged companies to take stock of their needs and expenses, and when they do not add up, to consider partly shifting back to on-premises.

    But Isn’t On-Premises a Thing of the Past?

    Not yet, but gone are the days of mindlessly unloading entire infrastructures into the cloud. Increasingly, companies are aware of the costs of pulling their data from the cloud.

    For many, security and control concerns motivate them to keep data on-premises. The public cloud has its benefits, but private storage has its place, too, especially for some components of your software. All in all, on-premises is here to stay, as companies continue to acknowledge and appreciate its value despite their reliance on public cloud environments.

    Why Do Companies Choose Cloud Migration in 2022?

    Cloud technologies can potentially deliver faster and better-performing experiences to end users, while innovations are giving rise to new services that cloud vendors can capitalize on. Various use cases are surfacing as companies understand the cloud better and see its potential. They are pushing the boundaries on how they can use the cloud, and cloud service providers are keeping track of the changing nature of the demand.

    For example, cloud-based gaming platforms like Amazon Luna are seeing significant growth. The cloud is also of great value to artificial intelligence and machine learning efforts, and these are often intertwined.

    The Great Resignation phenomenon also drives some companies towards the cloud. Although some knowledge is needed when moving to the cloud, cloud services offer automation and require less employee supervision in the long term.

    The COVID-19 pandemic has also been a catalyst for accelerating cloud adoption, making resiliency a priority. Companies can stay afloat in an emergency if their workloads are moved to the cloud. It comes at a cost, sure, but allows companies to outsource time-consuming responsibilities and focus resources elsewhere. While this was most significant in 2020 and 2021, this logic remains relevant.

    Cloud computing is also helping companies improve performance, efficiency and scalability. In addition to AI, the cloud will be instrumental in the development of more powerful augmented and virtual reality apps.

    Approaches Defining Cloud Migration Today

    The possibility of these approaches or facilities also motivates companies to migrate to the cloud:

    Containerization: The process of compiling and storing a service, along with its dependencies, in a container. Due to their small size, multiple containerized applications can run on a server, allowing for easier and cheaper shipping of the service. According to CNCF’s 2021 Annual Survey, containerization is now a mainstream practice, and Kubernetes, for instance, is a heavyweight in this domain, with 96% of companies employing or evaluating it.

    Security: In Q1 of 2022 alone, 90% of data breaches had their origins in cyberattacks. Mindful of this alarming trend, companies are factoring security concerns into their cloud adoption strategies. We are also witnessing a shift in businesses’ approach to security via DevSecOps: Incorporating security as a continuous practice from the beginning of the software development life cycle instead of relegating it to the back-burner until the last moment. Additionally, frameworks like secure access service edge (SASE) and customized cloud disaster recovery strategies are becoming essential elements of cloud adoption.

    Sustainability: Sustainability is becoming a key component in most business models. Companies are eager to adopt practices and models that reduce their carbon footprint. This impetus is also emerging from business partners and investors who are beginning to employ sustainability as a critical factor when deciding which companies to work with. When a cloud migration is planned carefully, chances are that you will retire certain services in your infrastructure and make decisions about what to migrate and what to retain. By optimizing your migration strategy, you are likely to only run and pay for the services you need, ensuring that your energy expenditure is under control.

    Edge computing: Edge computing, a $176 billion market in 2022, emphasizes the importance of building data centers locally; i.e., closer to where they are needed for storage and computational purposes. It solves any bandwidth and latency issues. Improved security is another added benefit of this practice. Edge computing has a bright future as it attempts to compensate for some of the pitfalls of using centralized servers in the cloud.

    Cloud-native applications: Cloud-native applications are easier to work with on the cloud, as they are designed and built on the cloud itself, not rearchitected to ensure compatibility with cloud services. When compatibility is not a concern, they can leverage various benefits offered by cloud services. As a result, scalability, flexibility and resilience are built into these applications. With cloud adoption, companies are increasingly in favor of cloud-native applications. This subsequently informs their migration strategy as they decide which services to retire, rearchitect or build anew once the actual migration is complete.

    How Does the Hybrid Cloud Fit In?

    Hybrid computing is on the rise as it leverages the public and the private cloud to deliver maximum benefit to companies with little to no compromise. The public cloud offers scalability, flexibility and speed, while the private cloud provides cost-effectiveness, security and compliance with regulations. While sensitive data can rest on the private cloud, frequently accessed data can be stored in public servers like AWS and Google Cloud. Investing in a hybrid cloud strategy from the point of migration itself can go a long way in giving companies access to the best of both worlds.

    Similar to a hybrid cloud environment, a multi-cloud strategy where companies distribute workloads across multiple clouds put some control into the company’s hands and ensures additional flexibility. By working across cloud services, companies can pick and choose which services are most compatible with their application’s components. These can include services offered by different cloud providers.

    Cloud Providers Seeing Growth, and What They are Doing Differently

    Serverless cloud environments: Cloud vendors like Amazon, Microsoft and IBM are pushing serverless cloud services. Although these continue to rely on servers (despite the name), companies don’t rent servers or pay fixed charges. Instead, the storage and bandwidth infrastructure scales with the software as and when it requires it. Companies do not need to concern themselves with technicalities and can focus on innovation and improving their existing applications. An added advantage is the provision of safe testing environments that encourage developers to tinker with cloud services and develop solutions for potential failures or outages. Serverless cloud solutions are also beneficial for smaller companies that need not invest large amounts of capital to ensure growth.

    Partnerships: To meet the soaring demand for cloud services, partnerships among cloud providers are also on the rise. By partnering with other service providers, companies can offer more services by leveraging the resources and reputations of one another while strengthening their competitive edge in the cloud market.

    Industry optimization: Cloud adoption is not limited to software companies. Businesses across industries like healthcare, finance and retail are migrating their infrastructures to the cloud. This variety in demand has encouraged providers to customize their services to meet the specific requirements of each industry. Often, these include regulatory compliance needs in these sectors.

    The cloud is only getting bigger and better. You can develop a well-curated transition strategy with the knowledge of current cloud migration trends. Additionally, identifying your requirements at an early stage will go a long way in leveraging the cloud to your advantage.

  • Moving From Lift-and-Shift to Cloud-Native

    Moving From Lift-and-Shift to Cloud-Native

    Analyst firm Forrester recently predicted that 2022 “will see big organizations move decisively away from lift-and-shift approaches to the cloud, embracing cloud-native technologies instead.”

    According to Gartner, more than 85% of enterprises “will embrace a cloud-first principle by 2025 and will not be able to fully execute on their digital strategies without the use of cloud-native architectures and technologies.”

    As the Gartner analysts put it, “cloud-native platforms improve on the traditional lift-and-shift approach to cloud, which fails to take advantage of the benefits of cloud and adds complexity to maintenance.”

    What’s happening here? Is lift-and-shift–long seen as a relatively quick and inexpensive way to migrate existing workloads to the cloud–really going the way of the dinosaur? Has the cloud-native future really arrived?

    I think the true answer is somewhere in the middle right now. Yes, many companies have adopted a cloud-first strategy, turning to the cloud as an assumed starting point for most or all of their application needs. But many others still have a mix of on-premises infrastructure and public cloud infrastructure with opportunistic lifting-and-shifting from one to the other rather than a holistic cloud-native model.

    Lift-and-shift has been and remains a perfectly natural and effective step in many organizations’ cloud journeys. All you do is redirect a copy of an application from an on-premises data center to the cloud–no need to redesign the app’s architecture or code.

    This method offers a fast and efficient way to leverage the cloud’s benefits: The ability to focus IT dollars on operational (rent) rather than capital (own) expense and take advantage of the extensible computing power, storage and other services in the cloud.

    In contrast with lifting and shifting, a cloud-native approach takes longer and is more labor-intensive because it takes many moving parts to redesign the entire app ecosystem. The payoff comes later with lower total cost of ownership and more flexible, responsive infrastructure.

    If many companies are still lifting-and-shifting, why are the analysts so bullish that it is on its way out? Because lift-and-shift isn’t as simple and inexpensive as it looks. It essentially defers the eventual re-engineering to cloud-native and yet still requires an investment in capacity, people, money and time.

    First, despite lift-and-shift’s promise as an easy way to migrate existing applications to the cloud, it is common for organizations, no matter how much they plan, to hit some technical roadblocks in the execution. An app that worked a certain way in the legacy environment might not work exactly the same way in the cloud, and these details must be worked out.

    Second, companies are often caught off guard by cloud “sticker shock”–the unpleasant billing surprises that occur when workloads exceed the capacity agreed on with the cloud provider.

    Third, while lift-and-shift is a way to advance on the cloud path, it’s not the ultimate destination.

    The Cloud Native Computing Foundation defines cloud-native technologies as empowering 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.”

    That’s a much bigger vision than the intermediary steps that lift-and-shift entails.

    What should companies still engaged in a lot of lifting-and-shifting be doing to prepare for their cloud-first future?

    1. Containerize like crazy. Virtualization was a game-changer because it allowed companies to abstract away hardware and run multiple virtual machines (VMs) on a single piece of hardware. This allowed a move in best practices toward a VM-per-function. Process containers, made famous by Docker and Kubernetes, are a logical extension of this concept: Stripping out redundant pieces of an operating system so that each logical unit contains only what is needed for the function it is designed to achieve. That, combined with a more deliberate approach to separating application and data, is the secret sauce of a cloud-native enterprise. Container adoption has been growing rapidly in enterprises–Gartner has predicted that containers will be the “default choice for 75% of new customer enterprise applications” by 2024. This trend bodes well for the move away from lift-and-shift to cloud-native and brings organizations closer to “write once, deploy anywhere” as each of the major cloud platforms and many on-premises tools provide mechanisms to run containers as first-class citizens.

    2. Consider the skills equation and where you want to focus your efforts. Every company embarking on a cloud-native strategy needs to carefully examine to what extent they’ll need architects and other skilled pros to carry it out. They need to think about what makes sense in terms of hiring people in-house, outsourcing to third-party experts and leveraging public cloud offerings such as serverless computing that reduce labor requirements.  It may be more sensible, for example, to focus on migrating application development to containers but rely on public cloud container platforms, low-ops Kubernetes or managed data center Kubernetes services rather than trying to build that competence in parallel.

    3. Rely heavily on automation. One of the advantages of containers encapsulating everything they need is that it makes it easier to build, test and deploy them as part of a CI/CD pipeline. Given they are also normally easier to scale horizontally, it is possible to automate how the application will scale to respond to external factors. Taking a model-driven approach to cloud-native applications can help DevOps teams and developers understand the conceptual pieces and relationships between complex software deployments while automating some of the details and life cycle management. Monitoring microservices brings its own set of challenges, so it is important to ensure that the observability tools you are using were designed to be effective with cloud-native applications. Cloud-native can bring great scalability benefits, but only with sufficient automation to limit friction in the cloud-first journey.

    4. Have a strong update strategy. Moving to containers distributes your software provenance and update problem across a much greater number of pieces; containers are not normally updated but instead are replaced with an updated version. This changes your traditional update approach. It is more important than ever that the pieces you are putting into those containers at build-time have a good software provenance and update story.

    5. Think holistically. Ruthlessly evaluate what apps can be cloud-native and which should remain in the data center and then consider the true benefits of hybrid cloud. Some organizations get caught up in thinking they need to move everything to the cloud wholesale. Maybe cloud-native isn’t right for everything.

    The industry-wide transition from lift-and-shift to cloud-native is accelerating. By keeping these five points in mind, companies can feel confident they’re moving forward, too. 

  • Is Your Future in SaaS? Yes, Except …

    Is Your Future in SaaS? Yes, Except …

    The growth of SaaS—including IaaS—was phenomenal when it came and it has become somewhat pervasive. Today, there are SaaS tools in use at just about every business, large or small. From sales to marketing to customer management, there is a SaaS tool that does it affordably and well. For now. The same is true of cloud vendors. Cloud prices are kept low by two mechanisms—volume and profit. Volume; much like the theory that mass transit is cheaper, by putting many customers on a single server reduces cloud vendors’ operating expenses and thus reduces what the cloud vendor must charge to make a profit.

    But as costs rise and growth slows in the current environment, it is important that your IT department, as a customer, pays attention to the cost/benefit equation of all SaaS offerings. Some will remain beneficial because of the work they offload, even as prices increase for your organization. Others, you’ll see, will quickly outgrow the value they bring as costs rise and there is a third class that just isn’t worth it—maybe it never was and you haven’t bothered to pay attention.

    Look for those items. So that this is less vague, here’s an example: A company I am involved with has been paying for a SaaS service that simply emulates an on-site functionality. The organization could (and previously did) drop a couple of boxes in and achieve largely the same result. Recently, we looked more closely at items like this and found that, in this particular case, (though not in most SaaS cases the org is using) the cost of dropping two boxes in and letting them do the job was cheaper (assuming those boxes were upgraded/replaced every other year) than continuing with the SaaS solution at the current monthly price. So much cheaper, in fact, that a contractor could be hired to deal with any issues that came up with the physical boxes and the only increased work for IT would be maintenance updates to keep the system secure. If, instead of appliances, the solution consisted of two Windows or Linux boxes, even that maintenance cost would be minimized.

    Service will be the same or better—the devices are right there if a change is needed—and there will be one less link in the chain of tools/vendors for attackers (the physical solutions would be on a private subnet, SaaS cannot be). Assuming the solution is a quality product, there really is no downside here. And yet, for several years this company has used the SaaS solution. These are the low-hanging fruit that people will point at and call “retrenchment” or whatever. Ignore them. Do what’s best for your org—be it SaaS or local—and make that decision on a per-tool/per-project basis.

    And keep kicking it. You’re building apps and infrastructure that keep the company running. Don’t hesitate to take pride in what your team(s) have built and don’t hesitate to cut costs on things that don’t matter so you have more funds for things that do. And once again, thank you—from all the employees in your organization that don’t realize they should say thanks.

  • IBM Shifts Mainframe App Testing to the Cloud

    IBM Shifts Mainframe App Testing to the Cloud

    IBM this week revealed it has added the ability to set up testing environments on the IBM Cloud for z/OS mainframe applications.

    In addition, on March 15, IBM will make available an IBM Z and cloud modernization stack to make it simpler to modernize mainframe applications by adding application programming interfaces (APIs) using a cloud-native set of DevOps tools that run in a Kubernetes environment.

    Tarun Chopra, vice president for the IBM Z Hybrid Cloud, said IBM Z as-a-service on IBM Cloud for development and test eliminates the need to dedicate mainframe capacity to an application testing environment. Instead, mainframe application testing can now occur in the IBM Cloud, he added.

    Currently available as a closed experimental today, IBM plans to make IBM Wazi as-a-Service (Wazi aaS) for z/OS generally available in the second half of this year. That offering will enable DevOps teams to self-provision an instance of a z/OS virtual server on a secure private space running on IBM Cloud.

    That hybrid approach means application testing no longer disrupts mission-critical applications running in production environments on a mainframe, added Chopra. The overall time required to gain access to a z/OS development and test environments will drop from days or weeks to six minutes or less, he said.

    At the same time, it will become easier to modernize mainframe applications by making them more accessible to other applications via a set of secure APIs. Many organizations today increase their technical debt by duplicating functions that already exist within mainframe environments simply because those functions are not easily accessible to developers. The IBM Z and cloud modernization stack makes it simpler to modernize mainframe applications to drive a digital business transformation initiative without increasing the overall technical debt an organization needs to service, noted Chopra.

    While many workloads over the years have been migrated off mainframes or simply retired, the applications that run on z/OS today are still among the most mission-critical that organizations run. A recent IBM Institute for Business Value study found 71% of respondents said mainframe-based applications are still central to their business strategy. Four out of five respondents also noted they needed to modernize those applications, as well.

    Modernizing mainframe applications is a less complicated endeavor than migrating them. The challenge is that building, deploying, maintaining and securing all the APIs required to do so represents a significant amount of effort. IBM said it is committed to simplifying the mainframe app modernization process.

    One way or another, mainframe applications are becoming part of the larger distributed computing environment. Most organizations that have invested in mainframe applications continue to run them in on-premises environments because of the unique transaction processing capabilities a mainframe provides. Mainframe applications that have been migrated to the cloud generally run more slowly than they did when running natively on a mainframe. There may still be circumstances where migrating a mainframe application to the cloud makes sense as part of a larger IT strategy. However, like every other application being accessed over a wide area network (WAN) there will always be performance tradeoffs to consider.

  • Enabling Cloud Adoption in the Government

    Enabling Cloud Adoption in the Government

    In 2022, federal agencies are estimated to spend $7.8 billion on cloud computing. While this spending on cloud computing is necessary, it’s imperative that the government uses its allotted funding appropriately to leverage the cloud’s full potential and avoid common pitfalls.

    Avoiding Common Cloud Adoption Pitfalls

    I’ve frequently witnessed government agencies get locked into a cloud reseller that doesn’t give them the full capabilities offered by AWS, Google Cloud or Microsoft Azure. Most people outside of the federal market don’t realize that the government does not buy cloud directly from the cloud providers—apart from some very large contracts like the upcoming JEDI replacement contract vehicle, JWCC. They buy through a network of reseller partners that offer volume discounts and try to bundle managed services to help with cloud management.

    This approach gives the reseller, not the customer, the power to hold the keys to their kingdom—and can make it difficult for the customer to easily switch between cloud providers in the event of poor performance, lack of access or billing transparency. The federal government would benefit from keeping a small, but purposeful, cloud project management office (PMO) in-house. Thus ensuring that root access is available to all the accounts, subscriptions and projects to provide freedom to the agency to more easily change partners as their cloud maturity evolves.

    I’ve also seen government customers unfocused on the holistic end-user experience of actually using the cloud. The result is fragmented collections of different systems, processes and steps that cause engineers to be frustrated and inefficient. Customers must transform the end-to-end cloud provisioning process so that self–service is paramount and existing technology investments are seamlessly and transparently integrated to the end-user. When done correctly, innovation will be the byproduct, because focus can go towards developing the next generation of mission systems and tools—rather than trying to determine how to get a cloud account to begin a project.

    Three Steps Government Agencies Can Take to Get Value from Cloud Infrastructure

    Challenges exist, but there are proven steps the government can take to get the most value from their cloud infrastructure.

    • Define purpose: First and foremost, understand the purpose the cloud infrastructure intends to serve. Are you looking to reengineer cloud architecture, become more cost-efficient, or transform the innovation potential within your organization by introducing new services that can take you farther, faster? Understanding this purpose and your goals will go a long way towards success.
    • Quantify ROI: To get the best return on your investment, understand what resources are already available and which are necessary for your operations. To fully take advantage of the cloud, it is important to make sure basic costs are under control, such as ensuring AWS EC2 or Azure VM instances are not overprovisioned or underutilized. It’s equally important to make sure you take advantage of reserved capacity reservations for your predictable workloads; these can save you 30% or more. Last but not least, keep a focus on fully leveraging technology solutions to help bring all the pieces together in an integrated user-friendly experience across cloud providers.
    • Consider the outsourcing approach: Bringing in cloud resellers and contractors can provide guidance to your organization and help you make better choices. Just like building or renovating a house, agencies need general contractor-type companies that can help to manage and orchestrate the process of migrating to the cloud and all of its moving pieces. These contractors can also help to locate the various specialists required to get the job done for each unique situation. Long term, having a small, efficient cloud PMO is something every agency should strive to have in-house; however, given the demand for cloud engineering talent, the near-term focus should be to ensure flexibility into engagements with partners, so that they don’t hold back the potential of the organization.

    As digital transformation and cloud migration continue, it’s important for the government to stay on pace with its adoption. As of now, most agencies are still relying on manual steps to validate controls and get Authorizations to Operate (ATOs) approved. Making the simple swaps to more automated processes, learning how to leverage cloud resources to their full ability, and outsourcing operations to contractors can make acceleration easy.  There has never been a greater need for cloud enablement. The time to scale up is now.

  • Debunking 6 Stubborn Public Cloud Myths

    Debunking 6 Stubborn Public Cloud Myths

    A lot of enterprises migrate to the public cloud because they see everyone else doing it. And while you should stay up on the latest and greatest innovations—which often happen in the cloud—you need to be aware of the realities and understand different migration strategies. You need to know why you’re moving to the cloud. What’s your goal? And what outcomes are you seeking? Make sure you know what you’re getting your enterprise into before moving forward in your journey. Here are six stubborn myths that persist about the public cloud and the realities you’re facing.

    1. Cloud Technology is not a Project, it’s a Constant

    Be aware that while there is a starting point to becoming more cloud-native—the migration—there is no stopping point. The migration occurs, but the transformation, development, innovation and optimization is never over.

    There are endless applications and tools to consider; your organization will evolve over time, technology changes regularly and user preferences change even faster. Fueled by your new operating system, cloud computing puts you into continuous motion. While continuous motion is positive for outcomes, you need to be ready to ride the wave regardless of where it goes. Once you get on, success requires that you stay there.

    2. Flex-Agility is Necessary to Survival

    Flexibility + agility = flex-agility, and you need it in the cloud. Flex-agility enables enterprises to adapt to the risks and unknowns occurring in the world. The pandemic continues to highlight the need for flex-agility in business. Organizations further along in their cloud journeys were able to quickly establish remote workforces, adjust customer interactions, communicate completely and effectively and, ultimately, continue running. While the pandemic was unprecedented, more commonly, flex-agility is necessary in natural disasters like floods, hurricanes and tornadoes; after a ransomware or phishing attack; or when an employee’s device is lost, stolen or destroyed.

    3. You Still Have to Move Faster Than the Competition

    Gaining or maintaining your competitive edge in the cloud has a lot to do with speed. Whether it’s the dog-eat-dog nature of your industry, macroeconomics or a political environment, these are the things that speed up innovation. You might not have any control over these factors, but they’re shaping the way consumers interact with brands. Again, when you think about how digital transformation evolved during the pandemic, you saw winning businesses move the fastest. The cloud is an amazing opportunity to meet all the demands of your environment but if you’re not looking forward, forecasting trends and moving faster than the competition, you could fall behind.

    4. People are Riskier than Technology

    In many ways, technology is the easiest part of an enterprise cloud strategy. It’s people that introduce much of the risk involved. You may have a great strategy with clean processes and tactics, but if the execution is poor, the business can’t succeed. A recent survey revealed that 85% of organizations report deficits in cloud expertise, with the top three areas being cloud platforms, cloud-native engineering and security. While business owners acknowledge the importance of these skills, they’re still struggling to attract the caliber of talent necessary.

    In addition to partnering with cloud service experts to ensure a capable team, organizations are also reinventing their technical culture to work more like a startup. This can incentivize the cloud-capable with hybrid work environments, an emphasis on collaboration, use of the agile framework and fostering innovation.

    5. Cost-Savings is Not the Best Reason to Migrate

    Buy-in from executives is key for any enterprise transitioning to the cloud. Budget and resources are necessary to continue moving forward, but the business value of a cloud transformation isn’t entirely about cost savings. Really, it’s about repurposing dollars to achieve other things. At the end of the day, companies are focused on getting customers, keeping customers and growing customers, and that’s what the cloud helps to support.

    By innovating products and services in a cloud environment, an organization is able to give customers new experiences, sell them new things and delight them with helpful customer service and a solid user experience. The cloud isn’t a cost center, it’s a business enabler, and that’s what leadership needs to hear.

    6. Cloud Migration Isn’t Always the Right Answer

    Many enterprises believe that the process of moving to the cloud will solve all of their problems. Unfortunately, the cloud is just the most popular technology operating system platform available today. Sure, it can help you reach your goals with easy-to-use functionality, automated tools and modern business solutions, but it takes effort to use and apply those resources for success.

    For most organizations, moving to the cloud is the right answer, but it could be the wrong time. The organization might not know how it wants to use cloud functionality. Maybe outcomes haven’t been identified yet, the business strategy doesn’t have buy-in from leadership or technicians aren’t aware of the potential opportunities. Another issue stalling migration is internal expertise (or lack thereof). If your technicians aren’t cloud-savvy enough to handle all the moving parts, bring on a collaborative cloud advisor to ensure success.

  • The Role of APIs in Mainframe Modernization

    The Role of APIs in Mainframe Modernization

    Mainframes are historically clunky systems. They are incredibly secure and can process impressive calculations, yet they are complex to manage and challenging to extract data from. This reality is at odds with modern cloud-native infrastructure, which emphasizes distributed computing and portable microservices. So, how can existing mainframes adapt to this connected, data-driven economy?

    I recently met with Dr. Alex Heublein, president at Adaptigent, to talk about the state of legacy modernization. According to Heublein, many mainframes are here to stay for the foreseeable future. However, enterprises are continuing to get value from these systems by adding an integration layer on top of them. By using a REST API layer on top of a mainframe, enterprises could finally open up these systems. This could facilitate bidirectional communication with newer cloud-native services, enable phase migration and edge closer to real-time processing.

    State of Mainframe Modernization

    The software industry changes every day. “Nothing in the tech field is permanent,” said Heublein, yet some legacy technologies will persist into the foreseeable future. In terms of mainframe adoption, Heublein sees a couple of categories of users. First are the large financial services organizations, such as large banks and insurance companies, which are considerably invested in their mainframe architectures and which will likely continue to rely on mainframe environments for their policy management and core infrastructure. “I think there’s a lot of good reasons for that,” explained Heublein. “If you want to process billions of transactions a day, [mainframe] is still a good option.”

    That said, regulations and market pressures are influencing a global movement toward open banking. For example, PSD2 mandates open banking in Europe and industry consortiums like Financial Data Exchange (FDX) are directing it in the U.S. market. These initiatives are encouraging financial services to transform their legacy environments and spurring cloud migration, especially for applications that aren’t mission-critical.

    Heublein pointed out a few different patterns in enterprise mainframe modernization. One approach is that enterprises are rewriting or re-architecting old COBOL applications and keeping them on-premises. Or they are porting and re-platforming the application; moving a COBOL app to a Windows or Linux system, for example. Finally, some are shifting straight to the cloud. For solutions that don’t need to be on the mainframe, enterprises may shift toward cloud-native to free up capacity.

    APIs Enable Legacy Modernization

    Distributed cloud technology is helping businesses scale to the right level. Yet, it’s difficult to jump off the mainframe entirely, noted Heublein. “Very rarely can you take all your stuff and move it all at once,” he said. “It’s a tough pill to swallow.” It’s especially difficult to move core banking infrastructure to a distributed environment—an instant shift could introduce security risks. For this reason, he recommended a ‘phase migration’ approach in which individual components are slowly migrated. For example, an insurance provider may shift their claims engine, policy engine and ratings engine to the cloud one at a time.

    As a result of phase migration, however, engineers must simultaneously support both on-premises and cloud-based applications. They must also ensure bidirectional communication so that these systems can exchange data. This is where a REST API transactional layer is necessary, Heublein explained. Such a layer could enable bidirectional communication between the mainframe and cloud-native applications, abstracting complexity when calling out to the modern world, or intercepting cloud data and filtering it into a format mainframe technologies can process.

    To increase developer usability, abstracting complexity from the mainframe integration process will be the key to building out connectivity. This could involve a codeless development approach with a COBOL sub-routine to call external systems, Heublein said. Automatic restructuring of data will be necessary to enable fluent bidirectional communication, too.

    Four Business Drivers of Mainframe Integration

    So what is the end result of putting an integration layer on top of mainframe systems? According to Heublein, there are four key business benefits of using such an abstraction layer:

    1. Orchestration: Software ecosystems often need to make multiple calls to different applications to collect and transform data. Yet, mainframe environments are very complex and challenging to integrate with. More usable integration fabric for mainframe systems could enable better orchestration of workflows in a developer-friendly manner. By using a REST interface, all apps could be calling the same interface, thus greatly simplifying orchestration between disparate services.
    2. Sustained Adaptability: The world is rapidly accelerating, and enterprises need to maintain and modify these APIs very quickly. Organizations require “sustained adaptability” to adapt and survive in the digital world, said Heublein. Mainframe systems, however, were not designed for the 21st century. Thus, low-code integration layers are critical to empowering rapid development.
    3. Data Transformation: Data is powerful for the business. Data is not only a commodity in and of itself but also is required for AI and machine learning. However, mainframes have a completely different way of encoding data. Thus, there is a need to transform this data into a modern format that businesses can consume. An integration layer between these systems can deliver an improved data consumption model.
    4. Real-Time Processing: You may think online payments happen in real-time; however, payment apps like Venmo are really just an abstraction layer over bank transactions, which may clear as little as twice a day. In short, mainframes are not great at real-time processing. However, more usable integrations to this infrastructure could enable user-facing applications to interact more closely to real-time.

    Another concern is security. Opening up mainframe environments that house core financial infrastructure must be done with extreme care—especially as API attacks remain the number-one rising threat in the software landscape. All organizations building out new integrations will require a secure layer from an outbound standpoint. Heublein said this often involves placing an API management layer or gateway in front of the integration layer. This system enables authorization and functions like a firewall between the internal and external world. It can also enable logging and prevent denial of service attacks, he explained.

    Improving Agility for Legacy Systems

    Legacy systems are entrenched in older technology and carry lots of technical debt, forcing operations to move at a slower pace. Maintainers are also culturally a bit different than the newer breed of cloud-native engineers. “Mainframe people are not … fast,” said Heublein.

    DevOps folks want to build, test and promote projects to production very quickly and, arguably, this agility is necessary to satisfy rising digital innovation demands. Improving integration capabilities for on-premises systems could enable businesses to better utilize preexisting investments while also improving agility.

    Low-code/no-code capabilities could also increase collaboration potential, Heublein added, which could bridge the gap between on-premises engineers and fast-moving business folks. When adopting low-code/no-code tools for mainframe integration, he cautioned against general-purpose citizen developer frameworks. Whereas universal integration layers can work well for many situations, he stressed that a very specific boundary box is best for building APIs for mission-critical applications.

    How is your organization approaching modernization for legacy systems? Let us know in the comments below!

  • Avoiding Budget Overruns During Cloud Migration

    Avoiding Budget Overruns During Cloud Migration

    Many organizations have already started their migrations to the cloud, or soon plan to. It makes sense: The cloud is an attractive option for multiple reasons, including its potential for cost savings, scalability and support of continuous application development.

    However, benefits aside, it can be very easy for enterprises to lose financial control of a cloud migration. The potential for costly mistakes when shifting to the cloud is significant, and organizations often end up getting hit with surprising bills that ultimately stop them in their tracks. In fact, in a 2020 survey, 94% of participants claim that it is a challenge for them to take full advantage of public cloud resources, with 40% citing the need to control cloud costs as their biggest obstacle.

    These financial mistakes are typically made due to the pay-per-use model of cloud services and the growing cloud skills gap. Too often, IT team members are forced to work in cloud environments they are not proficient in, and as new features are released every week, it’s almost impossible for these individuals to keep up. One recent study claimed that 90% of enterprises found that their cloud skills gap doubled over a three-year period.

    The Two Different Types of Cloud Migrations

    There are two types of cloud migrations that typically occur, a lift and shift, or a replatform/rearchitecture migration. The lift and shift method is fast and relatively easy, but it doesn’t enable organizations to truly optimize their cloud usage. The rearchitecture method is the most popular as it gives an organization the opportunity to fix any outstanding issues by harnessing the benefits of cloud-native technologies and services.

    However, once a rearchitecting migration begins, organizations often find it takes significantly more time, effort and resources to complete than they originally thought. This can become a real challenge, especially when facing critical deadlines or experiencing major events like the COVID-19 pandemic or the wild weather events experienced around the globe.

    Understanding and Assessing Performance

    For both types of cloud migrations, understanding and assessing performance and underlying architecture is an ongoing task, as cloud providers are always releasing new or improved services or lowering prices. To make sure they’re achieving the best performance and building a resilient architecture, application developers and IT teams must always be looking for ways to improve their applications. Within the cloud, this is typically focused on four key areas: Networking, computing, storage and application architecture.

    From a network perspective, understanding where data is being used and where data is being accessed is critical and can help organizations cut costs exponentially. For example, cloud providers often have costly data ingress and egress charges, so assessing how best to access and use data when necessary can help a company navigate those charges.

    Regarding computing, there are multiple resources that can help manage system load, make tweaks to computing infrastructure and find performance and cost benefits. For instance, leveraging the data and metrics from native cloud reporting tools can help organizations understand and predict demand, and taking advantage of services like auto-scaling enables them to scale up or down appropriately depending on the changes in application use and demand.

    On the storage front, cloud providers offer a number of ways to save money and boost performance. From the release of GP3 volumes to tiered long-term storage options based on the frequency of access, storage is an easy way to find cloud savings opportunities. Additionally, cloud providers will usually make recommendations and set up tiering policies to help move data automatically into colder and deeper storage.

    As cloud providers continue adding new services, looking at your application architecture is essential to innovation and cost savings—especially when including labor and effort—and truly achieving the promise of the cloud.

    Solving Common Costly Mistakes

    While there are numerous examples of common financial mistakes companies make when managing cloud instances, lack of visibility and understanding are the leading pain points for the developers who stand up and maintain their organization’s architecture. With the demand for cloud so high and with their attention directed elsewhere, developers and engineers often take the mentality of “If it isn’t broke, don’t fix it.” This hampers the company’s ability to assess and optimize their cloud operations. They don’t have time to consistently review their applications for ways to save money or even know how much their decisions cost.

    This ubiquitous issue can be solved by bringing greater visibility into the cloud migration and management process and aligning real-time finances directly with established corporate budgets. In addition, organizations struggling with the cloud services’ pay-per-use model should take the necessary steps—whether internally or with a third-party vendor—to ensure cloud resource and service use is being effectively monitored. This makes it easier for developers to understand where and how their actions affect the financial posture of the organization before their boss comes knocking on the door.

    If enterprises provide the resources necessary for IT teams to become more knowledgeable about how their applications are being used within the cloud and address the cloud skills gap in their workforce, they will be able to prevent cost overruns, experience cost savings and take back control of their budgets. This can take a variety of forms, but enterprises need to establish continual training programs to ensure team members are up-to-date on the latest cloud features and services, as well as leverage tools and automation to reduce manual intervention. Providing this critical visibility throughout a cloud migration can often mean the difference between a successful, on-budget migration and one that is stalled and costly.

  • The Next Phase of Pandemic Tech Transformation

    The Next Phase of Pandemic Tech Transformation

    Last spring, we were inundated with headlines, tweets and Medium posts applauding the rapid digital transformation that businesses were going through—almost overnight—due to the pandemic and the shift to remote work. It made for an interesting feel-good narrative at the time, but it didn’t paint the full picture. Companies were thrown into the deep end; many barely staying afloat by implementing quick-fix, surface-level changes that they assumed would only be needed for a short time. Turns out, the “transformation” touted was just the tip of the iceberg.

    More than a year later, the workforce is still in flux. The reality is, some form of distributed, hybrid work is likely here to stay. Employees will continue to expect remote options and customers will want seamless, digital ways to interact with businesses, pandemic or not.

    As a result, companies must move past the temporary, band-aid solutions of last year and make those sweeping changes permanent. It’s time to move forward with true, sustainable change: Technical, experiential and, most importantly, cultural. Every company will need to become a modern technology company capable of delivering first-class digital solutions to customers, partners and employees—or risk becoming obsolete.

    Transactional Vs. Transformational Change

    The good news is just about every company understands the value of leveraging technology. A recent 2021 State of the CIO survey found that 82% of CIOs said they implemented new technologies, new IT strategies and/or new methodologies over the past year. The issue is how companies go about their technology deployments.

    People talk about digital transformation all the time, but it’s been used so much that it has become an unhelpful misnomer. More often than not, the change that companies are implementing isn’t truly transformational, but rather transactional or just slightly incremental.

    When companies have a transactional mindset, the focus is on immediate, simple and predictable changes. The purpose—or, more importantly, the outcome—is simply to continue business-as-usual. This is reminiscent of many companies last year turning to technology just to keep the lights on. A transformational mindset, on the other hand, aims to disrupt this business-as-usual and fundamentally change the paradigm in how the company operates through ways of working, use of technology and culture. It’s purposeful, aiming to solve business problems holistically and spur long-term growth.

    To be successful in today’s climate and to gain a competitive edge with customers, companies must strive to be transformation-focused.

    How to Move Toward True Transformation

    Here are three examples of how companies can shift from a transactional mindset to a transformational mindset.

    Cloud Migration vs. Modernization

    Often, when companies talk about their use of cloud, they tout that they’ve “moved to the cloud.” But all too often, it’s treated as a one-time event; a destination to reach and a box to check. At the outset of the pandemic, we saw so many organizations quickly mobilize to shore up their digital strategies and ensure they were thinking about the limitations of doing business in a virtual context, but their cloud strategies didn’t evolve to rethink these paradigms, as well. They simply accelerated their migration strategies to get out of their physical data centers and into the cloud.

    The opportunity to leverage the cloud is so much bigger than that. It can unlock greater efficiency, flexibility and growth and underpin new digital experiences and revenue opportunities—exactly the kind of strategies most companies envision. For example, health care leader InnoCare was struggling with outdated clinic management software. Instead of just moving the old bits to their cloud provider, they adopted a broader digital strategy to modernize their delivery capabilities and reimagine both the patient and clinician experience, setting new industry standards in the process. This is what we refer to as modernization and it is what leads to transformation.

    Software Engineering vs. Product Engineering

    With the rapid growth of software, it’s no surprise that software engineers are in high demand. The U.S. Bureau of Labor Statistics projects that software engineering job openings will grow 22% through 2029. And while software engineers will play an irreplaceable role in helping build innovative solutions, transformational-focused companies know to bring more people under the tent. By combining software engineers with other cross-functional experts who bring a different level of artistry, design and audience understanding, the end result is a more engaging, customer-centric product that evolves and grows over the entirety of its useful lifespan.

    This is exactly what fitness giant Nautilus did. They brought together a team of engineers, data scientists and machine learning experts to help bridge the gap between their equipment manufacturing prowess and their digital experience and software development goals. Collectively, they produced a total platform that integrated hardware, software and data to create a dynamic workout regimen that impressed users and fended off competitors.

    Moving Beyond Proof-of-Concept to Long-Term ROI

    A proof-of-concept (POC) is a rite of passage in the tech world. It’s how a company or team demonstrates that their idea is feasible and can work in a real-world application. But POCs alone are insufficient; they are transaction-minded and don’t focus on achieving lasting business outcomes or generating deeper ROI. Rather, they mostly focus on technical feasibility. The key to upleveling toward transformation is by focusing on the processes, not just the end product. When testing features in a real-world setting, make sure that you’re proactively measuring not just that they work—but that they contribute to business imperatives, meet customer expectations and strategic outcomes. And if they don’t, go back to the drawing board and optimize with those higher-level goals in mind.

    Culture is Key

    As you can see, the difference between a transactional and transformational mindset is more about culture than technology. A culture of innovation and modern ways of working leads to transformation that fundamentally shifts the way technology is conceptualized and created. It isn’t solely about gaining efficiencies or cutting costs—instead, the focus is on making the lives of customers, employees and everyday users better. Transformation-focused companies believe in the promise of technology advancements, but they believe that it also can make operations smoother, customer relationships more meaningful and increase revenue when implemented with the right combination of skills, disciplines and organizational buy-in over time. It’s those companies who will thrive in this new era.