Category: DevOps in the Cloud

  • VMware Starts to Gain Some Momentum on AWS

    VMware Starts to Gain Some Momentum on AWS

    The number of IT organizations planning to move application workloads to the cloud that today run on VMware appears to be accelerating in the wake of the COVID-19 pandemic.

    A survey of 1,054 IT and business professionals conducted by Faction, a provider of IT services, conducted in June finds more than half (51%) of all respondents are either accelerating their cloud adoption timeline or moving forward as planned. Among respondents considering deploying workloads on VMware Cloud on AWS the percentage is 8 points higher (59%), with scalability cited as the primary driver by more than half of respondents (52%). A quarter of respondents (25%) planning to make that transition said they plan to add or increase workloads on VMware Cloud on AWS in the next 12 months.

    Top use cases among IT organizations currently running VMware Cloud on AWS are data center extension (26%), AWS integrated applications (22%) and cloud migration (18%). Among those considering VMware Cloud on AWS, the top use cases cited are data center extension (25%), disaster recovery (23%) and test & development (17%).

    VMware may also be starting to gain some traction with cloud-native applications based on Kubernetes. The survey finds that while the VMware Tanzu platform is currently being used by only 1% of all respondents, 18% said they plan to adopt Tanzu in the next two years.

    Duan van der Westhuizen, senior vice president for marketing and product at Faction said the survey shows VMware is making clear gains in the cloud. The biggest issue now is a lack of skills among internal IT departments looking to deploy workloads on VMware Cloud on AWS, said van der Westhuizen.

    Of course, there are multiple ways to migrate application workloads to the cloud. Some IT organizations may opt to refactor applications to run natively on the open source virtual machines provided by AWS. Others may decide to encapsulate applications in containers that can then be deployed on top of any virtual machine. Regardless of the approach, the need to make applications available at a time when local data centers are inaccessible has driven many organizations to reconsider their options. One of the options is to do not do anything at all. VMware makes a variety of tools available via software-as-a-service (SaaS) platforms that IT teams can employ to remotely manage workloads running anywhere.

    It’s not clear to what degree workloads are moving to the cloud, given how unevenly vertical industries have been impacted by the economic downturn brought on by the downturn. The survey finds the top four industries considering VMware Cloud on AWS are technology services, financial services, health care and government. Among those organizations for which COVID-19 has paused or canceled cloud migrations, top factors are budget pressures (75%). Staffing shortages and macro-economic uncertainty each tied at 41%, the survey noted.

    Virtual machine platforms from VMware are not going to disappear from the IT landscape anytime soon. However, given the number of options, IT organizations now have at their disposal, it appears less likely VMware will be able to continue its historic dominance over application workloads in the enterprise.

  • 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!

  • Are We There Yet? The Long, Hot Road Trip to the Cloud

    Are We There Yet? The Long, Hot Road Trip to the Cloud

     “If I have to pull this car over, there will be trouble!” Does this sentence evoke childhood memories of summer adventures in the family car? It’s the same sort of dread we get when the IT budget-holder turns around and threatens to pull over on our journey to the cloud or hybrid cloud. The family summer road trip may be filled with great expectations, but the last thing we want is an unforeseen disruption along the way. And migration to the cloud is no different. To continue this analogy, the bumps on the road to avoid are the ones around cost, performance and risk. So, here are some thoughts on how to identify the challenges and navigate to your destination smoothly.

    The Line of Business Needs To Pee (They Think) …

    Or even worse—“we just stopped, why didn’t you go then?!?!” Planning business needs is always a challenge—especially at the speed of change in today’s disruptive markets. The unforeseen impact of the COVID-19 pandemic is one example. We hear it a lot in our industry: “We don’t know which applications are using the most bandwidth and how much they are costing us.” And with 59% of infrastructure managers citing infrastructure cost overruns as their biggest concern, there’s definitely room for immediate improvement. Having clarity into your application topology with a clear map to performance is mission-critical for a successful hybrid cloud journey.

    Because this is such a dynamic process, it needs to be mapped and measured daily, in real-time. But simply automating VMs to workload balance does not give you the clarity needed to understand what and when to move in your hybrid journey. You need the ability to understand why and when things changed so you can effectively plan or resolve the issues. According to Gartner Research, on average, AWS deployments are 40% over-provisioned to meet unexpected capacity and performance issues, which defeats the purpose of moving to the public cloud. “Know before you go” should be a mantra for every hybrid journey manager—and parent managing backseat bladder needs.

    IT Just Hit a Major Pothole and Now Has a Flat Tire

    A flat tire only ruins a trip if you don’t have a spare, the tools and the knowledge required to fix it. For most, the actual solution is to call AAA or in this case, get a third-party systems integrator (SI). Calling an SI to help solve an unforeseen problem is not a bad idea, but it does come with a hefty price tag and a level of dependency that doesn’t mirror the model of moving to a public cloud.

    With the right solutions in place, even a pandemic like COVID-19 should not disrupt your business. Every IT leader should have confidence in their infrastructure systems. That said, it takes time and effort to get there, and no journey worth taking is easy. Having integrated solutions and partners are critical to the hybrid cloud journey. And so is knowing when to fix it yourself and when to call in support to save you millions.

    Too Much Luggage From the DBAs

    Packing the back of the family Ford “Wagon Queen Family Truckster” is a special skill set. It’s like playing Tetris with your family’s luggage. Right-sizing infrastructure capacity while supporting applications is like making sure all the luggage fits in the car and that you still have room to move your feet. Sure, you could buy a bigger car to manage the payload, but the expense doesn’t justify the performance. You need the clarity to act across your private and public cloud infrastructure in a single solution without disruption is required. That level of optimization is a constant to remaining competitive, enabling you to transform your infrastructure from being seen as a cost of business to being recognized as a revenue generator.

    Compliance Just Gave You a Speeding Ticket

    No matter how well-intentioned and on the right side of the law your compliance team is, it can feel like you are being chased by Sheriff Rosco P. Coltrane. And while you don’t mean any harm, the law is the law. In the rush to the cloud, you’re not often asked how you will manage the migration, you’re simply asked how fast you can move—reminiscent of another epic journey: “We’ve got a long way to go and a short time to get there.” Regardless of whether you identify with Smokey or the Bandit, you cannot deny that Sheriff Buford T. Justice (aka, Compliance/Security Officer) will slow you down. So, work early and often with your compliance team to ensure that where you store your data and who has access to your data always remains in compliance.

    Leadership Just Ran Out of Gas on the Migration Budget …

    … and now they want to know when the cost of running applications is best on-premises versus across the public clouds? Don’t break out your abacus just yet. Cost is all about transparency to the needs of the application infrastructure. Too many enterprises are finding that the rush to the cloud was expensive and not well-planned and are shifting critical apps back to the private infrastructure. But you need to go beyond just resourcing noisy neighbors with VM automation. A long-term solution is to optimize the application performance with an integrated APM and infrastructure solution. A more immediate and tactical solution is to leverage a hybrid infrastructure platform that works across multiple on-premises vendors and public cloud vendors to give you the cost analysis you need.

    Application Managers Are Fighting Over the Music  

    On-premises versus public cloud, VMs versus containers, AWS versus Google versus Azure. Where should those applications be running and how can they migrate them? These may seem like the most trivial of issues to be concerned about, but DevOps, architects and managers have deep loyalties way beyond rational factors such as cost, performance and control. Having the ability to manage and plan cost across a multi-vendor hybrid infrastructure to maintain your performance SLAs is critical. Don’t let blind loyalty or the loudest voice control your path. Your hybrid optimization platform should afford you real-time planning and cloud brokerage to ensure you are optimized for cost and performance.

    Your Early Talent Team Has Been Doing the Same TikTok Dance in the Backseat for the Past 8 Hours

    Hearing the same story about why the journey is behind schedule or the same ask for more budget to meet performance SLAs, or even a repeated request to deviate from the existing road map, can wear you down or dilute your focus. It’s important to have a multi-department/cross-functional plan and mapped roles and to measure performance. Keeping the entire team (multiple owners of the “cloud” in a large enterprise) engaged and on the same plan to avoid going into a loop of burned resources and nerves.

    Are We There Yet?

    As with most family trips to magical destinations, the road to a successful cloud migration is fraught with unexpected disruptions—but a good plan can avoid most common challenges. So, no matter what stage you might be at in your hybrid cloud journey, we hope you will reach out to us before you feel the need to pull over when the going gets tough.

    Hope you are all happy and healthy. Please, during this increased time of need, remember to give back to your community as you can.

  • Safeguarding Secrets Within the Pipeline

    Safeguarding Secrets Within the Pipeline

    How can an organization write source code to use secrets without directly referencing them and risking them being leaked to the public?

    2020 closes out a decade full of countless code leaks, a topic we talk about quite often. In fact, just recently, Intel became the latest victim after 20GB worth of internal documents were leaked and uploaded to a public sharing site.

    Intel finds itself in good company as it joins a long list of 2020 victims whose confidential source code has involuntarily gone public.

    Many, if not most, of these victims share one common fatal flaw: They hard-coded secrets (logins, tokens, etc.), then published their source code to a trusted cloud computing service platform such as an online Git repository.

    It would be naive to lay blame solely on the platform, however. It has long been a reliable rule of thumb that anything you put online—gated or not—is always at some level of risk. With this in mind, one should never, under any circumstances, include secrets in their source code. Stealing source code is damaging enough; the keys to your kingdom should not be included.

    That’s easier said than done, of course. How do you write source code to use secrets without directly referencing them? In this blog, we’ll show you an overview of how you can utilize your continuous integration and delivery tools to inject secrets into your code at build/runtime without actually including them in the code itself, thus placing a veil between your code and your secrets.

    Injecting Secrets

    One method for publishing source code reliant on secrets without actually including the secrets in the code is to use placeholders within the source code which, at build time, are replaced with the actual values needed.

    Microsoft Partner Technology Strategist Primoz Kocevar details such a method in his Medium post. The general idea is that secret variables are provided to a Docker image so that no secrets are found within the source code itself.

    An environment variable, set up beforehand, stores the secret. This variable is defined in a Docker file, which is used to create an image. During the build phase, secrets are then passed via the Docker image through the variables specified in the source code. Once complete, the application and image can be deployed.

    If you happen to run your images on Kubernetes, you can also leverage its own feature for securely storing secrets. This method allows you some additional options, such as using a Kubernetes environment variable or ConfigMap within a Kubernetes pod to store secrets for injection at build time.

    By the way, this approach to secret injection is by no means exclusive to Docker or Kubernetes. Though we highlight them here as specific examples, the same method can be employed via virtually any similar solution you rely on for deploying pods or containers.

    Injecting secrets via clever use of environment variables and configuration files in your microservices platform of choice is certainly a viable option, but we don’t think it’s the best option. Consider that this approach requires one image per each secret.  This can get cumbersome fast if you have a development environment with one secret and a production environment with another secret, each requiring different images.

    Leveraging Your CI/CD Tools

    First, a quick primer for the uninitiated: Continuous integration (CI) and continuous delivery (CD) tools and practices are an essential part of the larger software supply chain. Continuous processes are those that enable developers to publish code changes easily and frequently without degrading the product’s reliability.

    Continuous integration tools and practices establish uniform processes for creating, testing and building source code, integrating with any required external systems along the way. Continuous delivery covers the activities that follow, streamlining and automating the delivery of source code to infrastructure, especially when multiple multiple environments are involved.

    Many CI/CD tools provide their own built-in solutions for securing sensitive data. You can leverage these features when storing secrets until it’s time to inject them during the build.

    For example, Jenkins provides its own credentials store and its own automatically encrypted Secret field type. (A word of caution: This alone doesn’t prevent a user from accidentally printing a secret in the console log.)

    Another CI tool, CircleCI, offers a number of options for protecting secrets, such as secret masking to prevent secrets from appearing in terminal output and contexts, which limit access to certain variables to only specific user groups.

    There are, of course, as many additional options as there are tools available.

    We can leverage such features to enhance our previous example: secrets stored in your CI/CD tool can then be injected into our Docker run command (or your platform’s equivalent command) during deployment. In other words, your CI/CD tool of choice injects secrets into the image, which in turn injects the secrets into the corresponding source code’s variables. This method ensures our secrets never appear in the actual source code.

    A word of caution: Even utilizing this approach, your secrets are still only as safe as the tool you use to secure them. The Bleeping Computer article we linked earlier in this post points out how weakly configured tools themselves pose a threat: “The leaks have been collected by Tillie Kottmann, a developer and reverse engineer, from various sources and from their own hunting for misconfigured DevOps tools that offer access to source code” (emphasis ours).

    It’s important to stress the universal rule that there is no such thing as perfect security. Consider that encrypting your secrets within one of these tools offers little protection if access to those tools is not sufficiently restrictive. We recommend cautiously limiting who is granted what level of user access to each tool, applying the least privilege principle.

    Protection Post-Deployment

    Now that we have built and deployed our secret-free code, what’s next?

    If we were to stop here, we would have overlooked the fact that any developer who has access to our containers can see our secrets. The downside to utilizing a microservice infrastructure is that there are many opportunities for security gaps to appear between all the moving parts, from the moment the first line of code is written to when it all goes live, which can easily go unnoticed.

    Containers and pods need to communicate with each other and other endpoints, thus an attacker can leverage this by compromising one container or pod then moving laterally to others, rendering any secrets stored within ripe for the taking. The bigger your distributed infrastructure, the more difficult this is to prevent, because of the inevitable complexity of security policies required to do so.

    Thankfully, many tools offer options such as built-in network/firewall policies between containers/pods and endpoints, an option to encrypt data at rest or a mechanism for enforcing the least privilege principle, such as via restricted security groups.

    Some tools may also allow you to configure a Key Management Service (KMS) provider to encrypt your secrets. A KMS provider employs an envelope encryption scheme for data stored within etcd. The added benefit to this approach is that the decryption key is stored remotely on the KMS as opposed to on the same host.

    Conclusion

    Regardless of what tools you have in play along your development pipeline, secrets must always exist outside of the source code and should be (securely) injected into the code as it passes through the pipeline.

    Wherever secrets ultimately live, be it in a remote storage location, a container or pod or within a CI/CD tool, they must always be encrypted and never stored in plaintext.

    Finally, all the obfuscation and encryption in the world will not protect secrets from a lackadaisical user access policy. The least privilege principle should always be in play and user security groups should be strictly managed to control who has access to the systems responsible for securing your secrets.

    All that said, mistakes still happen, and none of the tools discussed here perfectly ensure that no developer will nonetheless accidentally hard-code secrets into your source code. It is with that in mind that we advise adding another layer of security by automatically monitoring your source code repositories for secrets.

  • Tricentis Extends Testing Reach to ServiceNow Applications

    Tricentis Extends Testing Reach to ServiceNow Applications

    Tricentis has extended the reach of its portfolio of testing tools to now include software-as-a-service (SaaS) applications from ServiceNow.

    Martin Klaus, vice president of product marketing for Tricentis, said testing has become a larger issue because in addition to patch updates ServiceNow is now on a cadence to deliver to two major updates to its platform a year.

    More IT organizations are now leveraging the ServiceNow platform to build and deploy custom applications. Rather than build an entire application from the ground up, many organizations are accelerating digital business application deployments by extending functionality already provided by a SaaS application provider. All the updates regularly made to those applications create a testing automation challenge that can be addressed using Tricentis Test Automation for ServiceNow, said Klaus.

    Deployed natively on the ServiceNow platform, Tricentis Test Automation for ServiceNow provides access to capabilities such as point-and-click recording, real-time playback of tests and automatic test case creation, he said. The goal is to speed up the testing process for ServiceNow applications by running hundreds of tests generated by machine learning algorithms in seconds versus what previously would have required days to complete, Klaus added.

    At present, there are more than 6,200 enterprise customers running ServiceNow applications, many of which are employing DevOps processes to build and extend ServiceNow applications. ServiceNow has also extended its DevOps focus via alliances with providers of DevOps platforms.

    The bulk of the use cases for ServiceNow involve IT service management (ITSM). However, ServiceNow as of late has been expanding its focus on digital business applications by, among other things, adding additional workflows applications, including a workplace contact tracing application aimed at human resources (HR) teams.

    The more ServiceNow applications an organization adds, the more complex the testing challenge becomes, especially as workflows start to extend across SaaS applications from different providers. For example, it’s not uncommon for organizations to build and deploy custom applications spanning ServiceNow and SAP platforms, said Klaus. Tricentis provides a set of testing tools that can be applied across both multiple SaaS application platforms as well as the custom applications a DevOps teams builds and deploys on their own, he noted.

    As organizations depend more on digital business applications, disruptions caused by updates to the underlying software components upon which a workflow depends becomes a bigger issue. In many cases, it’s not employee productivity that is affected. Organizations are now driving revenue through digital business applications that can’t be generated if the application isn’t available. As a result, there’s a growing focus on testing updates to digital business applications.

    It’s hard to say to what degree SaaS application platforms will become part of a larger DevOps pantheon. However, the number of applications being built and deployed using low-code/no-code tools that extend these platforms has increased. There might even come a day soon when the backlog for deploying these applications becomes a bigger issue than it is today. In the meantime, it’s clear many DevOps teams are going to have to expand their definition of what constitutes a deployment platform.

  • How Serverless Technologies Can Achieve Optimal DevOps Practices

    How Serverless Technologies Can Achieve Optimal DevOps Practices

    Growing competition and increased customer expectations drive the speed of development. Adopting DevOps, meanwhile, can be a challenge, as it includes adjusting practices and new infrastructure. However, although engineering resources may be slim, serverless offers new solutions to tackle the DevOps challenge. From improved IoT devices to cost-effective machine learning applications, the serverless ecosystem is helping promote DevOps adoption.

    Why Is Serverless Beneficial for DevOps?

    DevOps accelerates development while stabilizing downtime, giving enterprises a competitive edge, a quicker product maturity in terms of features and capabilities and an improved customer experience. Although the benefits are appealing, DevOps adoption is expensive and time-consuming. Serverless can combat the barriers and support the implementation of DevOps solutions, at lower cost and with greater returns.

    Serverless technologies provide a pay-as-you-go model, allowing enterprises to pay for the resources used. For instance, with AWS Lambda, users pay based on the number and duration of invocations, potentially lowering costs. Functions as a service (FaaS) could become more expensive than containers, depending on the traffic experience. The higher and more consistent the traffic, the higher the costs of serverless tools, and these costs can rise higher than container costs.

    Since serverless technology is auto-scalable and fully managed, it allows teams to focus on the business logic that the DevOps infrastructure was actually built for, instead of spending countless hours maintaining the DevOps architecture.

    Availability and Performance Monitoring

    FaaS services such as AWS Lambda or Azure Functions are comparatively easy to spin up, auto-scalable and cost-effective. The functions can make API calls to your service, and API calls can be made by the user via the front-end interface. These periodic checks ensure your services are available continuously and any failures incurred in the production environment can be captured by monitoring tools to inform you of any performance degradations. The alerts from the monitoring tools can be consolidated by incident management SaaS tools.

    FaaS functions can be used for automatic availability and performance checks. However, serverless event buses communicate alerts as invocations of the FaaS functions throughout the DevOps infrastructure, lowering the overall cost from the pay-as-you-go model and auto scalability of FaaS functions.

    ChatOps Improve the DevOps Process

    Developed at GitHub, ChatOps is a conversation-driven development that allows users to type commands in a chat tool to kick off the CI/CD process through custom scripts and plugins. The operation of the scripts requires backend support, which is where serverless technologies can support.

    FaaS functions give DevOps engineers the ability to simply write the script to perform the intended operations and upload it to the function while ensuring that the chat tool can invoke it. This removes arduous container orchestration and networking setup. Furthermore, costs are only incurred when the FaaS function is invoked via the chatbot, not on an hourly basis.

    Serverless Enhances the CI/CD Process for Continuous Deployment

    Similar to ChatOps, serverless can be used to enhance the CI/CD process, but unlike ChatOps serverless can automate the entire process by merging pull requests to deploy in production. This is also known as GitOps.

    Conceived by Weaveworks, GitOps is a methodology for Kubernetes cluster management and application delivery. By leveraging Kubernetes’ convergence properties, continuous delivery is triggered by git push. GitOps allows Kubernetes cluster management and application delivery by using Git as a single source of truth for declarative infrastructure and applications. With Git at the center of delivery pipelines, developers can accelerate pull requests and simplify application deployments and operations tasks to Kubernetes.

    GitOps provides a “source of truth” for the infrastructure and application code to further increase the velocity of development teams. The workflow that makes this possible starts with CI tools to push docker images to hosting tools. Then cloud functions copy the configs and helm charts from the master storage bucket to master git repo. Finally, GitOps operators update the cluster according to the config charts and pull helm charts by the Lambda function.

    By copying the helm charts, FaaS functions can be used to the master git repo. The FaaS functions are easy to set up and cost-effective, which means DevOps engineers can focus on other parts of the GitOps infrastructure and achieve low costs in the process.

    The Road to DevOps is Challenging, But Serverless Can Help

    Serverless can relieve the complexity of DevOps adoption through its pay-as-you-go, auto-scalability and fully managed services, enabling a more efficient and cost-effective implementation of DevOps infrastructures. Serverless technologies can be used across the DevOps stack from development and testing to CI/CD and incident management, it operates at optimal cost and is highly effective in development velocity and code reliability.

  • Survey: Cloud Security, DevOps Emerging as Enterprise Priorities

    Survey: Cloud Security, DevOps Emerging as Enterprise Priorities

    A survey published today by 2nd Watch, a provider of IT services, finds that in the wake of the COVID-19 pandemic, cloud security and DevOps have emerged as the top two priorities for large enterprise IT organizations.

    The survey queried more than 100 IT directors working at companies with at least $500 million in annual sales and IT budgets of at least $50 million per year, Three-quarters of respondents (75%) said they are prioritizing cloud security, followed by cloud-native culture change, also known as DevOps, (60%) and conferencing/collaboration (51%).

    Chris Garvey, executive vice president of product for 2nd Watch, said the report shows that not only are more large enterprises accelerating cloud adoption, but the projects being launched are also more strategic to the business.

    The survey finds 60% of respondents said they are prioritizing projects with potentially large payoffs over cost-conscious projects. Nearly half (47%) said now is the time to position their company for the long haul, while 39% said they are accelerating the use of the cloud to deliver digital products. As part of those efforts, more than a third (34%) said they are accelerating the migration of applications to the cloud.

    A total of 93% of respondents use at least two cloud platforms, with Microsoft Azure being the most widely employed.

    Cloud computing platforms, however, are not without their challenges. Most respondents (82%) said they’ve experienced cloud-related challenges, with 77% reporting those issues have caused them to alter their cloud strategies. Nearly half (46%) said experiencing cloud security-related challenges, while 48% said cloud computing turned out to be more expensive than initially anticipated.

    The top challenges identified are providing remote workers access to corporate systems (63%), providing remote worker support (57%) and conferencing/collaboration systems that haven’t worked as expected (47%). Half said they are accelerating the use of the cloud to support remote employees, with 58% expecting at least half of their company’s employees will become full-time remote workers in 2021.

    Overall, nearly two-thirds (64%) said their IT related budgets have stayed the same or grown since COVID-19 began, and 59% said their cloud budgets would increase over the next 12 months. A total of 80%, however, acknowledged they are concerned COVID-19 will continue to impact their IT strategy and only half (50%) said they were confident in their organization’s ability to adjust.

    Primary areas of focus over the next 12 months include databases (42%), internet of things (39%), data warehousing (35%), artificial intelligence/machine learning (34%) and data lakes (26%).

    Garvey said large enterprises are clearly looking to take advantage of their deeper pockets to accelerate digital transformation initiatives at a time when smaller rivals may not be able to invest. However, because the pandemic has impacted some verticals more adversely than others, the level of digital business transformation occurring across different vertical sectors is uneven, he noted.

    It may be a while before the winners and losers are identified in the wake of the pandemic. However, it’s clear large organizations are betting on IT now more than ever to differentiate themselves. As large organizations assess the damage from the pandemic, it’s likely that the future of many of these companies will depend on the degree to which they can adopt a wide array of not just emerging technology platforms, but also the processes required to master them.

  • How API Testing Can Save You Thousands

    How API Testing Can Save You Thousands

    API testing before launch can mean the difference between a $25 cloud database bill and a $30k bill

    Usage-based billing is a popular payment model in cloud-based SaaS platforms. The idea is that you only pay for the amount of data your project uses, which is great for companies that have finite metrics on their usage amount.

    It’s like getting a glass of water from your kitchen sink. Every time you open the faucet, you know your water bill will go up a few cents (actually much less than that, but for example). So let’s say the water faucet is the cloud platform and the glass represents your API requests.

    One of the ways organizations rack up exorbitant usage-based bills is from critical mistakes in the API request code. For example, your neighbor asks for a glass of water and you fill 10 glasses, or you forget to turn the faucet off after you fill the glass. This is very similar to what can happen in usage-based billing on SaaS platforms, especially for cloud-based API requests.

    An Expensive Example of Data Requests Gone Wrong

    A crowdfunding app in Colombia known as Vaki was shocked to receive a $30,000 USD bill from Google Firebase, due to some pretty simple mistakes. The company had rushed its product to launch, then noticed the app was running incredibly slowly after a version merge.

    Vaki had two choices: either take down the website or try to debug the app in a race against the money-clock. The company chose the latter option and discovered that its API was coded in such a way that with every visitor to their site, it needed to call every document of payments to see the number of supporters of a campaign or the total collected, on every page of the app.

    In other words, the company sent more than 40 billion requests to Firestore in less than 48 hours—an immensely costly mistake, although Vaki managed to work it out with Google in the end. One problem is that Vaki worked on the code while the site was already live, when any of these tools for API testing may have helped the company find the problem before launch.

    It is very important that tech teams debug every request to servers before release. Analyze if the number of requests and data transfer make sense and if your company will support the costs of the host with a big load of traffic. Otherwise, you will just catch loops or un-optimum requests with a huge bill or with your site down.

    API Learnings From Mistakes

    While cloud-based databases such as Amazon, Google Cloud and Microsoft Azure provide a pay-per-hour model, Firebase bills based on a 100k-250k read/write/delete requests to the database. So technically if you stay within this range, your bill shouldn’t amount to more than $25.

    But this also means you need to have perfect code with no mistakes or loops. Vaki was reading every document entry in a certain collection to calculate the total collected and support values for each time a user looked at a particular view.

    In other words, if a crowdfunding campaign had 100 donations, the app would call to the database once, but the reading would equate to 100 reads twice, which means a total of 200 read requests.

    Obviously, when you hit something like 2 million views on a campaign, the read requests to the database will very quickly exceed the billions. And to Google’s credit, this isn’t a get-money schemed it cooked up because it’s very easy to stay within the target metrics.

    In Vaki’s case, it was a simple human error in the data structure that wasn’t optimized for efficiency, and eventually, the company would’ve run into other problems, such as maxed out database connections.

    How to Keep Usage-billing to a Minimum

    Hosting apps today are fairly cheap, but databases can quickly grow out of control if they aren’t optimized efficiently. When it comes to traffic flow between the different parts of your application, read and write requests are the most frequent occurrence in the entire flow.

    So even though the front end may be fast to boot, it’s your backend that needs to be checked, especially as serverless architectures don’t typically offer backend data sessions. So as the backend requires more space and processing power, your overall bill increases.

    There are a few key takeaways from all this. One is that you’ll need to re-think your approach to how your data will have an impact on the total number of reads and writes, and how much processing power is required, which basically means optimizing your code for efficiency and long-term stability.

    The other takeaway is the importance of testing your API before launch, so that you can catch the sort of flaws that Vaki experienced before the product actually goes live.

  • VMware Expands Reach of IT Management Portfolio

    VMware Expands Reach of IT Management Portfolio

    VMware today announced a bevy of updates to its portfolio of IT management tools that is now at the heart of its overall approach to both DevOps and AIOps.

    VMware vRealize Operations 8.2 and VMware vRealize Operations Cloud, the on-premises and software-as-a-service (SaaS) editions of the same IT automation platform, provide deeper support for Kubernetes distributions, including the VMware Tanzu Kubernetes Grid, as well as tighter integration with application performance management (APM) platforms from AppDynamics, Datadog and Dynatrace.

    VMware is also providing tighter integration with its VMware vRealize Network Insight to bridge the divide between IT and network operations and tools to better monitor instances of VMware software running on the Amazon Web Services (AWS) public cloud.

    Enhancements to the capacity and cost management tools that VMware makes available as part of the platform include more visibility into daily virtual machine (VM) costs, enhanced metering capabilities and support for non-VMware vRealize Automation workloads.

    At the same time, VMware is making updates to VMware vRealize Automation and VMware vRealize Automation Cloud. The latest updates to the VMware automation platform add support for VMware Cloud Templates, a way to manage infrastructure as code that is compatible with configurations created using Terraform tools.

    Other enhancements include self-service provisioning of Kubernetes namespaces via the service catalog, including support for VMware vSphere with Kubernetes, as well as more granular role-based access controls and application programming interfaces through which policies for VMware NSX network virtualization software can be applied.

    Updates to VMware vRealize Log Insight and vRealize Log Insight Cloud add enhanced Kubernetes support, deeper integration with VMware Cloud on AWS and other usability enhancements.

    Finally, VMware is streamlining the onboarding process for VMware Skyline, a predictive analytics tool the company makes available as an extension of its operations management portfolio.

    Ken Lee, senior director of product marketing for VMware, said VMware vRealize Cloud Management portfolio is evolving in a way that makes it accessible to both traditional IT administrators and DevOps teams. Each function in the platform can be invoked via a graphical user interface or application programming interface (API), he said.

    At the same time, VMware is infusing machine learning algorithms across the portfolio to enable AIOps, eliminating the need for IT organizations to acquire a separate IT management platform to employ AIOps or embrace best DevOps practices, he said.

    While the number of IT organizations that employ virtual machine software from VMware numbers in the hundreds of thousands, the number of organizations employing its IT operations platform is still measured in the hundreds. The company clearly enjoys the inside track in terms of relationships with those customers. However, it’s clear that the number of IT organizations relying on tools other than those provided by VMware to manage their environments is significant.

    As IT organizations look to modernize those IT environments, however, there is clearly an opportunity for VMware to gain additional traction. The challenge is the race to embed AI and DevOps practices into IT operations platforms is already quite heated.

  • 3 Key Issues With Hybrid Cloud Transformation

    3 Key Issues With Hybrid Cloud Transformation

    The cloud has fractured. Nowadays, it is nearly impossible to scale a cloud-agnostic digital transformation initiative. The reality is that most enterprises adopt a hybrid cloud arrangement. Whether designed strategically or throughout years of competing vendors and technology influences, hybrid cloud environments, and the problems therein, seem a mainstay for modern IT.

    Many digital transformation efforts are culminating in hybrid cloud scenarios. 451 Research recently found 72% of enterprises are already using more than one cloud vendor. As one can surmise, competing standards and inconsistencies among cloud tooling can cause headaches for developers, security teams and potentially even end users.

    3 Common Cloud Transformation Problems

    I recently met with Jeff Kukowski, CEO, and Grant Ho, CMO at CloudBolt Software, to identify issues within today’s cloud transformations. According to CloudBolt, custom coding, governance concerns and cybersecurity incompatibilities are among the top problems that hold back cloud transformation (or make it very costly). Below, we’ll see what strategies they recommend to solve these problems.

    1. Custom Coding

    In 2020, a software-defined approach seems the obvious preferred choice for most IT professionals. Yet, custom code is still a significant struggle for hybrid clouds. The Standish Group research shows 19% of projects will be canceled before they ever get completed. Further results indicate 52% of projects will cost 189% of their original estimates. Custom code decreases reusability and creates redundancy.

    2. Lack of Governance

    With many disparate cloud applications, it can be difficult to set standards. There is not much control. This free-for-all can directly impact the business. Lack of visibility into resources, a related concern, could cost a business significant expenses. Citing a recent Gartner study, ParkMyCloud estimates that companies waste $8.8 billion on idle cloud resources each year.

    3. No Role-Based Security Policies

    Gartner found that 33% of enterprise security attacks are happening from people using resources in the cloud and not necessarily putting the proper governance and security parameters in place. Without role-based access control (RBAC) and a standards-based way to apply RBAC across all your resources, hackers can more easily penetrate a hybrid cloud.

    How Hybrid Cloud Affects DevOps

    These above problems are quite broad, but they reflect a culmination of many roadblocks along the development pipeline. In terms of DevOps, juggling the ever-growing variety of hybrid cloud tools could easily stunt deployment velocity.

    Kukowski described how cloud IT faces a plethora of tooling styles. They include on-premises tooling, serverless, infrastructure as code, Terraform, Kubernetes and backup as a service. “Greater than 70% of organizations are not only multi-cloud, but they are multi-tool,” he estimated.

    Naturally, supporting nuances between them becomes tricky. Not only must you recognize governance and security inconsistencies between platforms, but you must maintain them “into Day 2,” he said.

    Solution: Policy-Based Automation

    With hybrid cloud tooling now a reality for most enterprises, managing them becomes the next logical step. Solutions primarily revolve around better automation to increase self-service capabilities. For Kukowski, the answers lie in automated governance, heightened tooling visibility and implementing enterprisewide security policy services to automate security compliance and decrease custom coding.

    One way to achieve these benefits is by utilizing a Cloud Management Platform (CMP). Gartner’s 2020 Magic Quadrant for Cloud Management Platforms includes CMPs from CloudBolt, Embotics, Flexera (formerly RightScale), HyperGrid, Morpheus Data, Scalr, and VMware with vRealize Automation Cloud plus CloudHealth. A CMP layer could help automate self-service IT, assisting engineers to do their work with governance and security capabilities in place.

    Using a CMP, companies could eliminate custom coding for things such as access control. Such increased visibility could, for example, significantly decrease AWS server cost by reducing unused deployments. A CMP can benefit CI/CD too. Home Depot, for example, uses a CMP to greatly improve efficiency, decreasing infrastructure deployment time from weeks to hours.

    “Who is authorized to perform that action, on that K8s container, local VM, or cloud machine? We need visibility into that,” Kukowski said. “What is it doing? When is it running? Who has visibility to shut it down?” He recognizes that deep industry expertise is required to abstract complexity and standardize governance across all these situations.

    Streamlining the Polymorphic Cloud

    Saturated within an overabundance of cloud tooling, it’s easy to lose sight of your enterprise’s IT policies. Without global DevSecOps standards, security for hybrid cloud becomes risky.

    Enterprises with multi-tool environments are also at risk of wasting development time and effort. “We want to make sure the market does not repeat the problems of the past,” Kukowski noted. “Why custom code the fundamentals that operate your business?”

    Instead, companies should seek to reduce redundancy and eliminate custom code for each point to point integration. However, abstracting such complexity involves porting governance standards across all environments—a challenging feat for internal teams.

    The solution could lie in utilizing an external CMP layer. Such a layer could offer a software-defined approach to eliminate custom coding, offering policy-based security controls that consider the organization’s needs.