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Tag: Cloud Computing

  • How to Optimize Your Cloud Operations

    How to Optimize Your Cloud Operations

    Taking a holistic approach to cloud optimization and application modernization can help keep cloud spend in check

    There’s a fine line between cloud spend and cloud sprawl. Most companies today are using cloud technologies to power their most important products and services, communications and collaboration, but it’s easy to cross the line from spending smartly on cloud services to spending unnecessarily.

    Gaining control of cloud operations and cloud spend should be a goal for every organization, big or small. The good news is, it’s not as tough as you think. With a few smart moves, every company can become a cloud operations optimizer. Below are a few tips.

    3 Tips for Cloud Optimization

    Gain Complete Visibility Into Your Data

    It’s all about gaining a comprehensive view of all your data, pulling correct metrics, ensuring tagging best practices are followed and analyzing/interpreting what is going on. Many of the cloud optimization tools out there don’t pull the necessary information (actual RAM usage, for example) to accurately make meaningful recommendations.

    Compute resource data is only part of it; having a deep financial understanding around when to make RI/Savings Plans purchases and EDP/EA negotiation are just as important. You don’t want to pay for too much coverage or too little, and ideally you don’t want to make those decisions before you know your environment has been optimized.

    Know your Applications

    Cloud providers offer multiple financial methods of procuring resources such as savings plans, reserved instances, spot resources, EDP/EA plans, etc. Knowing how your users are interacting with your applications is key to understanding which financial option will make the most sense and achieving maximum savings.

    For example, a client has an application that is very spikey in utilization and is only accessed at certain hours during the workweek. Purchasing a Compute or EC2 savings plan or reserved instances may not be as cost-effective as applying auto-parking policies or utilizing spot resources (or a combination of both), since the application doesn’t need to be on all of the time.

    Non-Traditional Cloud Services

    Frequently, clients migrating to the cloud will simply perform a 1-for-1 migration and carry with it the traditional three-tier architecture (web/app/database). Getting out of that mentality can be a struggle for many clients, but having awareness of what is going on in the cloud environment at the application layer can help formulate a strategy for that over time. It can also help transition that mentality away from traditional architecture into more cloud-native services (containers/serverless, for example), which can provide cost savings and improved performance and open the door to more advanced services that can be taken advantage of in the future, such as machine learning and AI.

    Mistakes to Avoid

    Too often, companies believe that their cloud environment is already optimized. A typical cloud provider rolls out approximately 20 to 30 new features and updates per week. Multiply that by three for the top cloud platform providers (AWS, Azure and Google Cloud), and you have a daunting challenge of keeping up with everything. This takes the client away from doing their most important job: running their business.

    Companies also have a tendency to not think about optimization or application modernization when deciding to move to the cloud. A lot of clients will simply look at their compute requirements that are being utilized in their data center and build the exact same thing in the public cloud. While this will get them to the cloud more quickly in most cases, there tends to be a lot of waste when performing this method. The sooner you can start thinking about optimizing, the better.

    And, finally, too many companies take a traditional data center operations mentality to the cloud. The cloud continues to offer more and more advanced services that can greatly benefit a business.

    Conclusion

    Taking a holistic approach to optimization and application modernization leaves no stone unturned, typically generates enough savings to pay for itself, and, once implemented on a regular basis, will ensure that application performance meets demand. This is especially effective for clients with large cloud spend and dynamic environments.

    The best way to optimize cloud operations and spend is by engaging a managed services provider (MSP) and realizing that there is no single tool that can provide the type of analysis most companies need. Optimization requires both in-depth technical and cloud financial knowledge. It also requires collaboration between the MSP and all of a company’s business units to gain an understanding of their needs and application usage. Once all the data has been collected and interviews performed, recommendations can be delivered. It’s then up to the client, in collaboration with the MSP, to implement those recommendations to achieve true optimization and ultimately realize cost savings.

  • Means and Production

    Means and Production

  • The 4 Stages of Distributed Computing

    The 4 Stages of Distributed Computing

  • Report: Cloud Expertise Now Superior to University Degree

    Report: Cloud Expertise Now Superior to University Degree

    According to a report by online learning platform A Cloud Guru, 90% of IT leaders expect to expand their cloud services usage over the next one to three years, yet only 56% have an actionable plan to upskill their workforce.

    The recently released “State of Cloud Learning Report” revealed interesting trends in cloud adoption and cloud learning statistics. The study frames cloud expertise as a top asset and reveals changing cloud service providers (CSPs) alliances, among other insights.

    Below, we cover the top findings from the report. I also chatted with Katie Bullard, president at A Cloud Guru, to dig deeper into critical takeaways.

    The Report

    A Cloud Guru (ACG) is an extensive educational platform hosting cloud training and certification programs. Earlier this year, ACG questioned its user base on cloud learning and cloud adoption patterns. The “State of Cloud Learning” report surveyed 6,000 cloud learning administrators 20,000 individual leaners.

    Cloud Certification > Degree

    Amid an increasingly remote economy and developer drought, demand for skilled cloud professionals is rising rapidly. According to the report, 82% of hiring managers say cloud certifications make a candidate more attractive and 87% of hiring managers value hands-on experience and certifications over a university degree. “Gaining cloud expertise is a top skill for anyone entering the tech industry,” Bullard said.

    It appears cloud expertise is directly correlated to career advancement, regardless of whether candidates possess a traditional degree. Eighty percent of individuals surveyed realize a higher salary as a direct result of cloud certification, and 52% say cloud certifications expanded their career opportunities.

    Cloud Acceleration

    The cloud is ramping up, as is the need for cloud specialists. Seventy-one percent of leaders surveyed have seen cloud adoption speed  their time to value for new products and features. Yet, 80% view a knowledge gap as a top barrier to cloud success. Deployment and orchestration and IT security are leading barriers to cloud success at 40% of institutions.

    Cloud agility requires niche skillsets. More often than not, we see those skills cultivated with on the job training. Eighty percent of cloud leaders reported it’s easier to upscale existing talent than to hire new roles. Training benefits both parties, as 94% of employees are likely to stay longer at companies that invest in skills development.

    “They can’t solve by just hiring,” noted Bullard. “They must also upscale the current team they have.” As CSPs change so rapidly, continuous cloud education is an ongoing need.

    Azure Popularity Skyrockets

    Azure learning is up nearly 800% year-over-year on ACG—an order of magnitude far outpacing 50%–100% for AWS and Google Cloud. The report surmises that this spike in interest could reflect Microsoft’s massive investment in Azure’s marketing in recent years.

    Among the three top cloud service providers (AWS, Azure and GCP), AWS still holds dominance. Analyzing the use of its eLearning courses, the ACG report found 76.6% of total view time related to AWS during August 2020.

    However, current training doesn’t correlate to which cloud is most desired. Interestingly, when questioned on their desired cloud expertise, respondents ranked the top three providers equally, each at around 50%. Other CSP incumbents Oracle, IBM and Alibaba have also grown in interest.

    The Future Is Multi-Cloud

    According to the ACG study, 70% of respondents are currently utilizing multiple cloud platforms. The report contends there is tremendous interest in AWS, yet alternative CSPs such as Azure “may provide a unique benefit to some companies.” From arctic code vaults to underwater data centers, Microsoft indeed is innovating, which could influence the future CSP hegemony.

    “It’s not that companies are moving away from AWS to Azure,” Bullard noted. A company may port a portion of its load to another cloud “for efficiency benefits, to make the platform fundamentally stronger, or to innovate faster with multiple solutions.”

    Hottest Cloud Skills

    Besides CSP training, cloud adjacent skills such as container orchestration, infrastructure-as-code and CI/CD tooling have risen with the need for agile deployment. Highlighting the current top cloud skills, DevOps-related technologies including Kubernetes, Terraform, Docker and Ansible are among the top 10 most searched terms on ACG.

    “DevOps, as a skill, is still relatively new,” Bullard said. No longer a dedicated side team, DevOps has become integral to the entire development process. “No matter if you’re on a DevOps team or not, it’s becoming integrated into everything a developer is doing,” she noted.

    Final Thoughts on Cloud Andragogy

    Analyzing the statistics from a cloud learning platform provides a unique window into current cloud implementations and future adoption. In summary, the ACG report demonstrates that:

    • eLearning for cloud technology makes candidates more attractive in the job market.
    • For many hiring managers, cloud certifications are more important than traditional college degrees.
    • Although AWS holds the most significant market share, interest in Azure has grown substantially.
    • Organizations are finding benefits in multi-cloud environments.
    • DevOps skills are emerging as necessary to keep pace.

    “We’re in a transformational point in time,” noted Bullard. “The cloud market is accelerating, education is accelerating and people are rethinking the way they approach training.”

    With COVID-19 forcing a remote economy, online learning is far more pervasive. Now more than ever, companies must consider how they strategically scale teams and how they scale on-the-job technology training for cloud and DevOps. Because, if the goal is always to be evolving, then adults need school, too!

  • The Rise of the Cloud Economist: The Other CFO

    The Rise of the Cloud Economist: The Other CFO

    The new Cloud Economist job title wrangles runaway cloud costs

    Have you ever forgotten about a subscription? Maybe it was that Amazon Fresh upgrade you never used, charging you monthly payments. Or, your phone carrier slyly tacked on a feature and it went unnoticed for years. All these charges may seem insignificant, but they mount up over time.

    The same is true for cloud IT tools. Many Ops engineers know all too well the surprising bills that accompany cloud infrastructure. While cloud prices may start low, they often rise unexpectedly with hidden server costs, data replication charges, escalating API fees and other fun add-on expenses.

    Conversely, remaining at a low service tier could cause latency and a loss of revenue. Drowning in a sea of hybrid trends and feeling pressure to deploy at lightning speed, it can be difficult to keep track of which cloud models actually advance business objectives.

    Some believe an entirely new role is needed to rectify the gap between cloud and business repercussions—a Cloud Financial Officer, or the Other CFO (OCFO). An OCFO could act as a Cloud Economist, a tech-savvy ambassador who both understands the financial implications of a cloud strategy and optimizes service tiers to their necessary levels.

    I recently chatted with Leon Adato, Head Geek at SolarWinds, on how businesses could better drive cloud cost optimizations. Like a determined accountant sent in to save a struggling city (h/t to Ben Wyatt in Parks and Recreation), the OCFO may be the star companies need to slash the budget and balance the cloud checkbook.

    Why Do We Need a Cloud Economist?

    According to the “Flexera 2020 State of the Cloud Report,” 74% of companies report their annual cloud spending exceeds $1.2 million each year. At 20% of companies, it’s more than $12 million. As cloud spending skyrockets, balancing these expenses becomes business-critical.

    Yet, forecasting cloud costs is tricky. Unexpected complexities often arise with the cloud, skewing initial cost projections. Maintaining cloud oversight becomes especially complex as COVID–19 accelerates more cloud adoption across the board. Budgets are shrinking, and some companies are undertaking extreme measures to remain lean.

    Simultaneously, the ones that advocate for new technology don’t always consider cost implications. “Three clicks and you’re done means a DevOps engineer in the driver’s seat may not be aware of the cost considerations,” said Adato. In recent years, SaaS companies have stressed easy onboarding and developer experience as a top priority. The staying power of developers to adopt new tools is arguably at an all-time high. But while it’s important to improve developer workflows, developers don’t necessarily have business acumen. “Finance is a lexicon of itself,” noted Adato.

    Thus, some view a Cloud Economist role as necessary for translation across divisions. “IT divisions shouldn’t be encountering sticker shock when they view their cloud infrastructure bills,” he said. “We need IT folks to be able to pay attention to cloud costs in a meaningful way.”

    What Does a Cloud Economist Do?

    A Cloud Economist is an expert that specializes in cloud-spending and cloud cost optimizations. Such a role could help teams realize the efficiency benefits of cloud-native architecture while keeping costs lean.

    This job title truly requires “hands for code and a head for money,” described Adato. He laid out three simple goals of a Cloud Economist:

    1. Increase revenue.
    2. Decrease cost.
    3. Remove risk.

    A Cloud Economist understands the technical underpinnings behind cloud tools and how they support each other within a cloud-native ecosystem. They also appreciate maintenance realities, asking tough questions such as: Will it take 200 code pushes per day to support this microservices integration pipeline? How will server costs change as bandwidth scales? Which plan is most optimized for our needs?

    Specific Cloud Economist Duties

    A Cloud Economist must manage runaway costs associated with cloud adoption. They see the bigger picture and understand the repercussions behind cloud technologies. In terms of specific duties, the role may wear many hats.

    For example, a Cloud Economist may encourage a CSP migration, such as from AWS to GCP. Or, they may foresee the implications of future feature introduction, such as limitations across geographic zones, and advise IT teams accordingly.

    An avid Cloud Economist should also interface with monitoring and testing teams. “API testing before launch can mean the difference between a $25 cloud database bill and a $30k bill,” wrote Rapid API’s Chris McCallister in a separate blog post.

    Other Cloud Economist duties could include:

    • Logging and forecasting rising cloud costs.
    • Becoming Terms of Service (ToS) experts.
    • Avoiding costly data replications.
    • Upgrading servers.
    • Discontinuing unused instances and features.
    • Ensuring elasticity of applications.
    • Database scalability.
    • Increasing CPU power or data loads.
    • Optimizing subscription plans.
    • Considering implications behind feature updates.
    • Limiting the intake of new cloud tooling.
    • Acting as an ambassador between a company and CSPs.

    Traditional IT, or information services, as it was originally called, “has been able to avoid the need to integrate with business,” said Adato. That will likely change drastically as cloud costs escalate and thousands of very small charges amount to “death from a thousand cuts.” It appears that any business size, from startup to enterprise, could benefit from more cloud expense forethought.

    Inherently, DevOps is a cultural movement, not a technical movement, Adato noted. Assigning a Cloud Economist encourages specialization and de-siloing between disciplines, freeing up DevOps engineers to work on projects that matter to them. The role of a Cloud Economist “offloads responsibility that has always been there that may have been ignored,” he said.

    Avoid Ice Town With a Cloud Accountant

    Software architects are often sold on the idea that cloud infrastructure is a cheaper alternative to on-premises. “That statement is false,” Adato said. As an organization cloud evolves out of freemium tiers, where it began cost-wise is often far from where it ends up.

    To navigate the opaque cloud, “we need someone that has fluency and familiarity with tech, understands the platform, understands how code is updated and maintained, and can right-size the cloud platform,” said Adato. Cloud-native certainly has its benefits, but if runaway cloud costs aren’t wrangled, they could equate to revenue loss.

    As author Bob Lewis wrote: “There’s no such thing as an IT project.” We don’t do technology for the sake of doing technology. Rather, we do it in service to the business. A Cloud Economist could help ensure technology answers the business call, not vice versa.

    As of now, the OCFO is mostly a theoretical title; it could materialize as an internal team member or contract hire. Regardless, such a role could advocate for the business and keep operational overhead as lean as possible.

    In general, it may require a dash of hard realism to learn how to avoid plunging the books into a debt-ridden Ice Town.

  • Cloud Foundry Foundation Updates CLI to Extend DevOps Processes

    Cloud Foundry Foundation Updates CLI to Extend DevOps Processes

    The Cloud Foundry Foundation (CFF) today released an update to its command-line interface (CLI) that will enable DevOps teams to build more granular and complex workflows spanning multiple processes across the open source platform-as-a-service (PaaS) environment.

    Announced at the Cloud Foundry North American Summit, version 7 of the Cloud Foundry CLI employs updates to the application programming interfaces (APIs) exposed via the Cloud Foundry PaaS to invoke package, droplet, build and process control resources while adding resources such as sidecars, manifests and deployments.

    The updates to the CLI and associated APIs will make it possible to enable rolling application deployments, run multiple processes within the same container and add metadata to objects.

    Chip Childers, executive director of the CFF, said most of the organizations that have adopted the Cloud Foundry PaaS are already fairly advanced when it comes to implementing best DevOps practices. The latest version of the CLI will make it possible to tighten DevOps feedback loops within the PaaS environment.

    In general, CFF is positioning the Cloud Foundry PaaS environment as a common framework for building and deploying applications on traditional virtual machines and Kubernetes clusters. The CFF has launched an incubation project, dubbed KubeCF, that enables a virtual instance of the Cloud Foundry runtime to be deployed on Kubernetes. At the same time, the CFF has made available Project Eirini, another incubation project that enables the Cloud Foundry scheduler to be replaced by Kubernetes, and Project Quarks, which allows the CF Application Runtime to be packaged using containers.

    The CFF has also launched Cloud Foundry for Kubernetes (cf-for-k8s), a more ambitious effort to replace the underpinnings of the PaaS environment with a Kubernetes foundation. That initiative should result in Cloud Foundry requiring much less IT infrastructure to be deployed. The CFF has also committed to embracing other cloud-native technologies such as the Istio service mesh.

    As part of that effort, the Bosh framework that the CFF created to automate the deployment of its PaaS will also eventually be replaced by a framework optimized for Kubernetes environments.

    Childers said it’s now clear Kubernetes will mature to the level required to support an enterprise-class application development environment. The opportunity now is for IT vendors such as VMware, SUSE and others to deliver an application development environment that makes developers more efficient than any other on cloud-native infrastructure, said Childers.

    For example, VMware today is making available a public beta of the VMware Tanzu application service for Kubernetes based on the cf-for-k8s project.

    Contributors to the CFF project are clearly trying to make up for lost time. Rival PaaS environments such as Red Hat OpenShift have long been integrated with Kubernetes. The CFF community, however, is betting more enterprise IT organizations will embrace Kubernetes once they discover various distributions of a PaaS environment they already rely on is available on that platform.

    Whatever the path chosen, the one thing that is clear is the Cloud Foundry PaaS is about to become a lot more accessible to organizations that, no matter how great the developer experience, previously balked at its overall size.

  • Why the Success of Edge Computing Relies on a Linux Legacy

    Why the Success of Edge Computing Relies on a Linux Legacy

    At this point you’ve certainly heard rumblings of the promises of edge computing and may wonder if it’s right for your organization and how to assess its viability. The way we think about edge is as a decentralized extension, or evolution, of cloud computing, enabling many of the same technologies and applications to be leveraged in areas/locations that weren’t possible before.

    I believe that the promise of edge computing and the opportunity it unlocks is valuable enough to be a major driver in our industry over the next decade. Here’s how to think about implementing edge computing in your organization. 

    Getting Started

    Since edge is an evolving space, the exploration of edge computing should start as soon as possible, and we’d recommend a phased implementation approach to help deal with change as it comes. 

    Many of the companies we work with who delayed their cloud initiatives found that it contributed to their falling behind from a technology standpoint. Given the choice, it’s better to deal with some sharp edges — no pun intended — than to fall behind your competitors in reaping the benefits.

    Edge requires careful life cycle analysis at the beginning of the journey, rather than an afterthought. The decentralized nature of edge computing raises the stakes and amplifies any potential problems you would have in other computing scenarios. So as you begin, keep in mind issues such as adaptable infrastructure, security and life cycling between hardware and software.

    The Value of Adaptability, Linux and Open Source

    Twenty-five years ago, innovation was a slow, laborious, bug-filled crawl — with any advances crippled by proprietary technology. The breakthrough that paved the way for the continuous, rapid pace of innovation possible today was Linux.

    We need to heed the lessons from the early days around private cloud adoption and, more recently, Linux containers with regards to adaptability. Many man-hours were lost in slash-and-burn style rebuilding of infrastructures. The logistics at the edge make it impractical to have the same learn-as-we-go freedom we had inside the datacenter. 

    As we’re likely to see edge computing evolving quickly, the only adaptable architectures will be the ones that can avoid a total tear-down. Adaptable architectures will also be well-positioned to take advantage of the newer capabilities as they become available. 

    Remember, Linux has a strong history in the embedded world and is well adept at tackling a number of the historic challenges in this space. The more immediate impact is being felt at the distribution level. Our distributions, for example, have objectives around minimization and we expect to see more low-level enablement work on the security side for edge happening in the near future.

    For edge computing to reach its full potential, we need to be completely driven by open source and open standards. What we’ve learned from previous technology waves is that while most proprietary technologies have their merits, they miss out on the multipliers that can come from a thriving community.

    Final Considerations

    Security is a longer topic on it’s own, but given that we’re giving up many of the security barriers that are easy to take for granted in the datacenter and cloud (physical access, networking perimeter, security groups/policy, etc.), we are going to rely more and more on lower-level hardware and operating system security.

    No company wants to risk a common vulnerability across a hundred thousand nodes. This makes it our job to keep enterprise deployments from following the pattern of some consumer-grade devices that are long out of software maintenance.

    For edge computing innovation, we need to be thinking more about how we create sustainable solutions and technologies given how many deployments will require a longer life cycle and are more tightly bound to hardware and equipment refreshes. The path of innovation leads from Linux to and through the network edge. Companies that follow this approach will be better positioned to leverage the promise and power of the edge while avoiding fragmentation and lock-in.

  • Harness Enables DevOps Teams to Rein in Cloud Costs

    Harness Enables DevOps Teams to Rein in Cloud Costs

    Harness today unfurled its Continuous Efficiency application, which enables DevOps teams employing its continuous delivery platform delivered as a service to monitor the cost of deploying applications on a public cloud.

    Company CEO Jyoti Bansal said cloud costs are spiraling out of control within many IT organizations because DevOps teams lack visibility into the true cost of deploying an application on not just one cloud versus another but also specific tiers of services made available by cloud service providers.

    Continuous Efficiency provides DevOps teams with granular cost breakdowns by cloud provider, cloud service, application, microservice and environment, as well as by Kubernetes cluster, namespace, workload, node and pod.

    Bansal said that capability is crucial for organizations looking to identify underutilized resources that they today typically only become aware of when a monthly bill is presented by the cloud service provider. Even then, it’s too late for the DevOps teams to proactively optimize the cloud environment to minimize costs.

    In fact, it’s currently too difficult to correlate the monthly bill presented by a cloud service provider with specific application services that might have been consuming that infrastructure, he noted, adding Continuous Efficiency is specifically designed for DevOps teams rather than the finance team.

    In the wake of the economic downturn brought on by the COVID-19 pandemic, DevOps teams are under more pressure than ever to reduce cloud costs, said Bansal. Not only has the cloud become the single largest expense for DevOps teams, but also IT leaders are being required to better predict costs at a time when organizations are unsure how much revenue they are able to generate from one month to next. The days when DevOps teams could view the cloud as essentially a free resource are now over, he noted.

    Beta customers who tested Continuous Efficiency have been able to realize as much as $500,000 in annualized savings on their cloud costs, Bansal added.

    Harness is leveraging its continuous delivery service to auto-discover cloud costs without requiring IT teams to manually tag cloud resources. As a CD platform accessed as a service, Harness is able to aggregate all that data in real-time on behalf of its customers. The Harness platform supports Amazon Web Service (AWS), Microsoft Azure and Google Cloud Platform, including the Kubernetes based services provided by those services.

    Much like the rest of the IT environment, Bansal said responsibility for managing cloud costs will increasingly shift left toward DevOps teams. As one of the primary consumers of those services, it’s typically DevOps teams who have the most variable consumption of cloud services. All too often, it turns out that costs are being incurred because developers have reserved instances of virtual machines on a public cloud for sake of convenience but are not actually using. When many organizations are deeply concerned about cash flow, tolerance for that behavior is quickly dropping to near zero.

    Rightsizing of cloud computing environments has, of course, been inevitable. The thing that has changed is the current economic climate has transformed rightsizing from being merely the desired goal into an absolute requirement.

  • How to Secure the Intangible — Cloud Native Security in the New Age

    How to Secure the Intangible — Cloud Native Security in the New Age

    People don’t want to buy a quarter-inch drill. They want a quarter-inch hole.

    Companies aren’t interested in managing IT; they’re more interested in results. They want to deliver software quickly and focus on their core product or service. This is where the concept of cloud native computing comes in—and why securing it has become critical. 

    Traditionally, companies had many servers and resources. Today we’re moving toward a simpler reality. Developers are focusing on what’s needed to deploy business logic, regardless of what it’s deployed on. That’s why it’s particularly appealing to move to software without the server and the added complex management of IT overhead. 

    If a company can push its offerings without hardware, patch management, storage and so forth, and it can do it more affordably and faster, it’s a great win. 

    The Paradigm Change

    2012 was the golden age of IT, where admins ruled the world and developers got in line. Moving from that era to 2016, we come to the age of the cloud, where developers were kings.

    For many years, the IT department led—and perhaps stifled—innovation within organizations. Developers’ paths for innovation were limited to the area which they had control, i.e., the application layer. Anything beyond that was the IT department’s call. This included hosting, load balancing, database management and whether to adopt virtualization or advanced networking technologies.

    With the emergence of NFV and cloud computing, that changed. There has been a continuous erosion of the abstraction layers that developers were faced with in the past. In 2020, developers are the masters of their own destiny, pushing their organization toward innovation. All of this is possible not only due to virtualization and cloud computing, but also to the relative simplicity of a developer setting up a full application stack on their own laptop.

    In many organizations, the CTO focus has moved from an infrastructure orientation to an application focus. Developers are the new golden children of these organizations. They hold the keys to increasing company profits.

    What Cloud Native Brings to the Table

    There are many numbers being thrown around about the efficiency of cloud native. Whether it’s 300% reduction in deployment time or a mere 30%, the reality is that the time savings are huge. Many developers will never see a traditional data center again in their lives. In fact, new applications are developed as microservices or at the very least as containers, simply because they’re faster.

    There’s no going back. This new approach enables developers to invest in scalable solutions without making companies preallocate unnecessarily large sums of money. Both applications and infrastructure can scale up or down quickly, using the right amount of resources to provide the best service. 

    Businesses that are seasonal or peak-oriented gain a lot from the movement to cloud native architecture. Users also stand to gain from the move, as they receive the best service possible, without downtime. Everyone comes out on top.

    A Look at the Future

    This movement to broader use of cloud native architectures is a trend that will continue to grow over time.

    By 2025, VMs and bare metal will be as anachronistic as mainframe and token ring networks are today. In fact, most medium-to-large organizations already have some kind of a migration project from VMs to containers in progress. Many developers don’t need to spin up VMs anymore, since they can have a whole application stack running on their laptop using containers. When they are done, they simply lift and shift it to staging and production environments.

    In addition, on-premises and cloud environments are becoming a single entity rather than two separate infrastructures. People used to think that the entire data center was going to move to managed clouds for economical reasons. Today, however, most deployments are becoming hybrid. Organizations are opting to keep some of their on-prem systems (mostly legacy applications that cannot be easily moved to the cloud). IT administrators are starting to think about the deployment in the cloud as an extension of the on-prem data center rather than a separate network that needs to be managed.

    This trend will most likely continue, making it all the more important to understand the changing expectations around how to secure the hybrid network environment. The rate of change for cloud native environments is monumentally faster than on-prem, initiating code in milliseconds.

    Most legacy solutions weren’t built to cope with ephemeral networks and compute entities that go up and down within seconds, one million times a day. So, what’s the best way to future-proof risk management in this ever-changing environment? There is no singular answer, but in general prevailing advice suggests you consider the long view, exploring the options best suited for your approach and then look at each through a one, three and five year lens. 

    Cloud Native Security

    When thinking about the future of security, the basics stay the same and the threat modeling concepts stay the same. However, there are a number of security issues to consider, including policies, permissions and authorizations. As networks are converging, the security tools are as well. Looking forward, only solutions that can provide a genuine single pane of glass to control your digital estate will have a real impact on security.

    When looking at solutions to help apply security to cloud native architectures, ask the following questions:

    • Can I improve visibility in my cloud service? Applications may be deployed over multiple cloud instances and on servers in different sites, and even different regions, making it more difficult to define clear security boundaries. The right tool can help you to understand the scope and layout of your cloud resources, particularly if it automatically discovers applications on your cloud deployment and maps the data flows between them, making it easy to understand applications that you have running in the cloud and how they interact with one another.
    • Can I achieve a single view of multiple environments? The tools used to apply security need to adapt to be able to control hybrid networks across on-prem and multicloud organizations. For example, if your architecture requires policies to be deployed to the edge, how is it managing convergence? Numerous network solutions are barely aware of layer 7 process level, let alone containers. 
    • Can I set and maintain policies across these environments? Consider how solutions address network policies and understand potential challenges from both a technical and procedural point of view. Securing application traffic within cloud native architectures or between applications and external networks is a good start, but in the cloud, it’s necessary to implement micro-segmentation so you can define policies at the application level. By defining which applications are allowed to interact and the types of interactions that are permitted at a granular level, it’s possible to provide the level of security necessary for applications operating in the cloud. Look for tools that provide automatic policy recommendations that can be effectively applied on any cloud infrastructure, streamlining your organization’s security policy for deployments.
    • Can I future proof my cloud native security posture? When planning your future roadmap, think about what your network is going to look like. What type of workloads and network constructs are going to be used? Make sure the security vendors you select provide full coverage for your roadmap.

    When implemented correctly, modern micro-segmentation techniques can offer a simple way to secure a cloud native environment, including solving the unique challenges of containers and providing the ability to create dynamic application policies down to process level. Look for tools that provide a single view and foundational visibility, automatically discovering all network flows and dependencies. This allows your business to take advantage of the best of serverless computing without increasing risk or complexity for security.

  • Is Your Infrastructure Ready for Edge Computing?

    Is Your Infrastructure Ready for Edge Computing?

    Like many IT innovations, edge computing began with engineers as a natural extension of technology to address a growing need. The concept isn’t new; distributed computing has been around for decades. But, at the same time standards began to converge and edge hardware started making the rounds at trade shows, the hype machine saw an opportunity. It amplified edge’s considerable promise in reducing latency, offering software-defined deployment, decreasing cloud networking costs and more. But as is too often the case, the bold feature bullets ignored the production concerns businesses must address, including edge computing’s rough spots and the additional operations complexity it adds.

    Of course, edge computing will survive a little overexcited promotion, just like many of the once improbable technologies before it. People used to say, “What? Abstract all my data center applications away from the hardware as virtual servers? Impossible!” A decade later, we can’t imagine how we’d deliver traditional enterprise services, cloud computing, online retail, media streaming and everything else in between without exactly this. Virtualization survived its awkward hype adolescence, and edge computing will, too. The needs edge computing addresses are only growing.

    Thanks to engineers and operations teams, the edge distributed model is moving toward practical use. It’s proving itself capable of meeting requirements for new levels of network performance through reduced latency, scalability and, more importantly, manageability. For some businesses, it’s even reducing costs over the long haul.

    Not All Data Is Created Equal

    With the proliferation of connected devices and a growing focus on 5G-enabled technology, tech pros should set aside their natural reluctance to wade through the edge hype and consider it a genuine possibility. Its adoption is following the rise of emerging technologies and the applications taking best advantage of it: 5G, augmented reality, autonomous vehicles, IoT and smart manufacturing. These environments require not only low upstream latency, but high-performance compute and timely result data. Light only travels so fast, pushing infrastructure closer and closer to consumers for faster, more seamless processing in the form of brand-differentiating user experiences.