Tag: cloud

  • 4 Ways to Simplify Cloud Performance Monitoring

    4 Ways to Simplify Cloud Performance Monitoring

    Over the past 18 months, technologists across the globe have played a crucial role in the survival of brands and organizations via digital strategies. Across all industries, their skill and dedication have enabled businesses to rapidly launch innovative new digital services to meet huge fluctuations in customer needs and allow entire workforces to operate from home during the pandemic.

    This hasn’t been easy, even as end users’ expectations for seamless digital experiences are on the rise. In fact, the recent 2021 App Attention Index reaffirmed found 76% of consumers’ expectations of digital services have increased in the last year. And an overwhelming 85% noted that applications and digital services have become a critical part of their daily lives. This has placed even greater pressure on the technologists who are responsible for keeping applications and cloud experiences running smoothly.

    Often IT teams are challenged with monitoring companies’ digital services, but they lack the visibility they need to monitor health and performance across an increasingly sprawling IT estate, exacerbated by a seismic shift toward cloud architectures over the last 18 months. IT departments don’t yet have the right tools and data to optimize health and performance in their cloud environments.

    As a result, technologists are constantly addressing the same issues because they can’t easily isolate and identify them, and don’t know where to prioritize their actions. Hiccups can lead to brands losing customers—the same report revealed that over half of consumers indicated that brands have one shot to impress them, and that if their digital service does not perform, they won’t use them again.

    After a year and a half since the start of the pandemic and with adoption of cloud technologies set to accelerate even further over the next few years, it’s time for technologists to get ahead. Here are four things technologists can do to take the stress out of managing performance across the cloud.

    Implement Visibility from the Ground Up

    Having visibility into applications and the underlying cloud infrastructures that support them can be challenging without the right tools, which has contributed to some of the pressure technologists are experiencing. Traditional monitoring has allowed technologists to identify and catch issues in certain areas of an IT stack, but this approach is of little use in dynamic, distributed and software-defined environments where organizations are continually scaling their use of IT and the cloud up and down.

    As a result, the performance of the digital services can be impacted, potentially hurting end-user experience and eroding trust in the brand.

    To keep up with the rising demands from consumers in the digital world, technologists need the ability to monitor the full IT estate, from cloud infrastructures to customer-facing applications through to core infrastructure such as compute, storage and network; including the open web and security. With access to tools like observability platforms, technologists can lessen the burden of individually monitoring the performance of each item supporting the digital service. Instead, they can achieve one holistic view into alerting, root cause and analysis of correlated metrics, events, logging and tracing (MELT) data from the cloud to enable early and easy troubleshooting.

    Consider tools that link infrastructure (compute, storage and network) with the services and applications they execute. When there is an application-level issue, it is easy to take a closer look and identify problematic areas in what makes the application run or the application itself.

    Align IT Performance to Business Results

    After aggregating a full-stack view of applications and the cloud infrastructure behind them, technologists can then link performance data identified by the observability platform with real-time business metrics.

    Linking the two provides technologists with the ability to identify where and how the digital services are impacting the business and end-users. Full-stack observability automatically provides technologists with these linked insights, enabling them to address the areas that matter most.

    Educate Teams

    In addition to having the right tools to help take advantage of the cloud, it is important that an IT team is well-versed in the technology itself. Managing the performance of the cloud is complicated and there is a finite pool of talent available to businesses. Therefore, business leaders should provide appropriate resources to ensure teams are educated and equipped to succeed.

    To support a seamless implementation of cloud infrastructure to support a business’ digital services, business leaders must invest in upskilling their teams or recruit others who are knowledgeable about cloud monitoring.

    This will ease the pressure on existing teams and give technologists the skills and confidence to progress in their careers.

    Leverage Automation

    Even with the best observability solutions in place and teams equipped with the necessary skills, there is still concern that there will be an overwhelming amount of data generated by accelerated digital transformation over the coming years, especially those involved in large-scale public cloud environments. It can become a challenge for technologists to dedicate the level of resources and skills required to manage and optimize performance across the IT estate.

    To avoid these potential circumstances in the future, it’s worth considering how to minimize the impact of a data deluge by reducing an IT department’s reliance on manual interventions to monitor health and performance and resolve issues.

    Two things that will play an increasingly vital role in tracking health and performance across the entire IT estate are automation and AI. This is particularly the case in large-scale public cloud environments, which are fast becoming the biggest headache for some IT teams.

    With AI deployment to identify and fix issues in real-time, technologists can spend less time firefighting thanks to the AI/ML guiding hand. This will lead to increased job satisfaction and fulfillment and a better work-life balance.

  • How to Improve Cloud Management

    How to Improve Cloud Management

    Cloud technology underpins emerging technologies like artificial intelligence (AI), IoT, edge computing and containerization. Organizations must prioritize implementing effective cloud management practices to avoid spiraling costs and potential security and compliance violations.

    The COVID-19 pandemic has vastly accelerated cloud adoption. To support remote work, many businesses have moved workloads from on-premises servers to the public cloud. At the same time, thanks to the proliferation of technologies like AI and machine learning, organizations are generating more data than ever, much of which is also being stored in the cloud. It’s no surprise then, that the explosion in demand for cloud services is showing no sign of slowing down. Gartner predicts that worldwide end-user spending on public cloud services is forecast to grow by 23.1% in 2021 to total $332.3 billion.

    But, it’s not all smooth sailing. As the average organization’s cloud infrastructure grows in complexity and size, it becomes increasingly difficult for teams to manage it effectively. This has significant security, compliance and cost implications. According to Accenture, an astronomical 30% of organizations’ cloud spend is currently wasted.

    So, what can you do to ensure you avoid the most common cloud management pitfalls?

    See the Big Picture

    It’s surprising just how little visibility many businesses—even those with large teams of cloud architects—have into their cloud infrastructure. For instance, one recent survey found that over 25% of IT departments have no idea what their monthly cloud spend actually is.

    Before taking steps to optimize your cloud management practices, it’s crucial that you gain full visibility into your current situation. You need to understand your cost history, audit trail and CPU utilization patterns to identify where you’re overspending.

    Plus, make sure you’re using tagging consistently. A well-defined organization-wide tagging policy is essential, enabling you to accurately visualize expenditure by category. It’s also good practice to set up alerts which are triggered when a user launches instances without tags. This prevents any potential oversights.

    Develop a Change Management Process

    Gone are the days of rigid change management processes handled solely by IT teams. Nowadays, business units can acquire cloud services without even involving IT.

    In the cloud, change management is a series of continuous integrations, deliveries and deployments. Given this fast-moving environment, it’s crucial to implement a robust change management process or risk spiraling costs and potential compliance violations.

    It’s important that your change management process gives you visibility into and control of each infrastructure change without compromising on delivery speed. To achieve this while establishing strong policies and rules, it’s worth considering automation for at least part of the application delivery process. By auto-approving all routine and low-risk changes, you can free up time for your developers to focus on more complex projects.

    In addition, it’s worth integrating your change management process with your DevOps tool stack. You can use collaboration tools like Slack, Teams and/or Jira to ensure everyone has visibility into changes and resolve any issues quickly.

    Continuously Optimize your Cloud Infrastructure

    Unfortunately, when it comes to effective cloud management, your work is never truly done. Conducting a one-off review of your existing cloud infrastructure will only get you so far.

    Many businesses make this mistake and find themselves falling back into their old bad habits a few months down the line. To keep your cloud infrastructure in check, it’s best to continuously track a whole host of factors, including costs, changes, users, permissions and compliance breaches. After all, it’s much easier to solve an issue when you are able to spot it before it gets out of control.

    Now you have an idea of where to start when it comes to improving your cloud management practices. However, manually juggling all of the above considerations is a significant undertaking. It’s prohibitively time-consuming for many organizations whose DevOps teams are already overstretched. This is why a whole host of SaaS-based cloud management tools have sprung up in recent years. These offer unparalleled visibility into changes, resource utilization, costs, security, compliance, performance and more. Yes, they come at a cost. But, most businesses find that the savings such tools enable them to identify significantly exceed any outlays.

  • How to Achieve Cloud Operational Excellence

    How to Achieve Cloud Operational Excellence

    Cloud operational excellence means delivering the right mix of cloud-based services at the optimal cost and quality to support your organization’s mission and strategy. You might be thinking, “Why go to the trouble? Isn’t ‘almost good enough’ sufficient?” It turns out that it matters—a lot. The difference between the top 10% and the bottom 10% in cost per relevant delivery metric can vary by an order of magnitude or more.

    In the mid-1990s, Gartner acquired an IT metrics firm called Real Decisions. They offered benchmarking services so customers could compare their IT efficiency with similar organizations. With hundreds of “Global 2000”-sized customers, their database was rich. Over time, the Real Decisions team refined their catalog of metrics and enriched their data with repeat studies over time, to develop indices of efficiency. 

    Within their user population, the difference in cost per unit of productive work was 11 times better in the top 10% compared with the bottom 10%. That doesn’t mean 11% better, it means 1,000% better. 

    Note that the user base was self-selected. All participants wanted to get objective metrics of performance relevant to their business goals and paid for extensive studies involving questionnaires, financial audits and technical benchmarks. Notably, all participants had cost recovery programs (beyond chargeback) in place. The bottom 10% of this segment is still within the top 10% of the IT industry—and their score is 11 times worse than the best of the best. 

    Which raises the question: What is the industry average for IT efficiency? Is it possible that the hundreds of benchmarking users are all doing IT wrong, and the search for relevant metrics is misguided? I think not. 

    Choosing the Right Metrics

    In 1911, Fredrick W. Taylor published The Principles of Scientific Management, which discussed approaches to optimizing two important variables: Output quality and worker compensation. Taylor recognized that successful firms work collaboratively, with management and workers jointly setting goals and developing methods and tools to achieve both profitability and proportionate compensation. Nowhere in this text—or in any of his recorded speeches or documents—does he say, “If you can’t measure it, you can’t manage it.” He never said that for two reasons: First, he did not believe it; second, it is not true. What he did emphasize was that if you do measure it, you will manage it. That was a warning: Pick the right metrics or you will exert effort pursuing a meaningless goal. 

    Here are some potential cloud performance metrics compiled from several cloud providers and users across various industries, not-for-profits and governmental agencies: 

    • Service Metrics 
      • Reliability – mean time between failure (MTBF)
      • Availability – Uptime, expressed as a meaningful percentage of demand
      • Serviceability – Mean time to repair (MTTR)
    • IT Metrics
      • Capacity 
      • Latency
      • Bandwidth
      • Response time
    • Strategic Metrics  
      • Business agility 
      • Customer engagement 
      • Customer reach 
      • Financial impact 
      • Solution performance 

    The journey to cloud excellence starts with developing the metrics that are most relevant to your business goals. Picking the right metrics with the right scale matters. As a rule of thumb, generally right beats precisely wrong. 

    Sustaining Excellence 

    After you agree on a set of metrics that are both statistically reliable, repeatable, objective and aligned with your firm’s mission, how do you achieve and sustain excellence? 

    In the 1970s, the U.S. Department of Defense bought a lot of custom software. Sometimes it worked well, other times it didn’t. So, the DoD funded research on code quality. It turns out that the key difference between great and mediocre quality code flowed from how the organization managed problems. More specifically, how did the team react to an unexpected event? The spectrum runs from confusion and dismay through fire drill chaos to calm, rational assessment and remediation. That methodology gets baked into the code itself. This study produced the Capability Maturity Model (CMMi), which was created by the Software Engineering Institute at Carnegie Mellon University. 

    The CMMi framework identifies five levels of process maturity. A simplified assessment of an organization’s process maturity level comes down to two questions. First, is there current comprehensive documentation for the process, including how to deal with defects? If the answer is yes, the organization is at level three or higher. If the answer is no, the second question is, “Does anyone know what’s going on?” If the answer is yes, that’s level two; if no, level one. 

    A level one organization has no standard method in place to deal with problems. When something goes wrong, everybody grabs tools and tries to figure out what went wrong and how to fix it. Organizations like this do not spend much on training or analysis. Their focus is continuing to produce whatever they are trying to make. Over time, an individual may develop expertise in diagnosing a component, and when things go wrong, the call goes out to “Get Fred in here!” to troubleshoot the problem. Organizations with pockets of expertise are moving into level two. Most organizations fall within one of these two levels. 

    Organizational transformation is very difficult, and often requires significant changes in the management team, as well as funding different activities. Training and communications skills are crucial to proceeding beyond level two. Management rewards heroes who can shoot the most difficult bugs. They get the big bonus, the promotion, the better office, a parking space near the door. This behavior reinforces the culture of heroes. But moving forward requires the heroes take on a new role.  

    Once the organization creates documentation, it is on the path to level three. Note that these transformations are wrenching. It is not easy to tell the heroes that their greatest value to the organization is now how well they can write or teach. But with proper management attention, it can be done. And the benefits of moving forward are many: 

    • Dramatically fewer crises. Staff could make plans and keep them – no emergencies interrupting a family gathering, a school event, or a get-together with friends. 
    • High quality code. Maintenance tasks became much simpler, and customers experienced improved reliability. The documentation was helpful, and troubleshooting became routine rather than overwhelming. 
    • Reliable planning. In a mature organization, plans hold true because they are based in proven metrics, continuously validated processes and uniformly high competence within the team. Project estimates are accurate because the data stems from reliable, repeatable evidence. 

    Cloud excellence is not a phantom or an unachievable goal. It is the result of clear thinking and sound documentation. Over time, practices improve, skills build. To quote Macklemore, “The greats weren’t great because at birth they could paint, the greats were great because they painted a lot.”  With practice and focus, your organization can achieve cloud excellence.

  • Majority of Organizations Now Adopt Multi-Cloud

    Majority of Organizations Now Adopt Multi-Cloud

    As IT’s digital footprint grows, its cloud footprint is rising both in size and complexity. As a result, most organizations have matured into multi-cloud operators. A multi-cloud approach empowers different divisions with the autonomy to select the right computing environment for their needs. It also enables a lift-and-shift ability to port workloads across cloud service providers (CSPs) when needed. Adopting a multi-cloud model could bring performance benefits, cost savings or better scalability, all while encouraging a more vendor-neutral stance.

    We’re in a multi-cloud world. A recent HashiCorp study found three out of every four organizations are already multi-cloud. This is a staggering increase from just a few years ago when mono-cloud was more accepted, and operators had zombie-like allegiance to AWS. The uptick in multi-cloud signals the maturity of offerings at other CSPs, like Azure and GCP. It also signals differentiation among clouds as each hones in their unique value propositions.

    HashiCorp’s inaugural State of Cloud Strategy Survey offers some very clear results about the state of multi-cloud adoption. Below, I’ll review major takeaways from the report to better understand the state of multi-cloud adoption. To sum it up, large organizations tend to benefit most from multi-cloud adoption, as there are still significant roadblocks to truly reaping a sizable return from a multi-cloud status. Yet, more infrastructure automation may help companies of all sizes respond to multi-cloud complexities.

    The Multi-Cloud Era

    DevOps truly operates in a multi-cloud era. The report revealed 76% of organizations are already multi-cloud; that leaves only one in four companies leveraging a single cloud. And, that trend won’t stop—within two years, 86% predict they will be multi-cloud operators. The study also confirms that the larger a company is, the more likely it will adopt multi-cloud—94% of large enterprises with 5,000 or more employees are multi-cloud.

    So, what’s driving this cloud fragmentation? Well, 34% of respondents cite digital transformation as a top driver for multi-cloud adoption. In the race to meet new digital innovation demands, multi-cloud has emerged as a strategic force. To enact this rapid change, many organizations are investing in a cloud center of excellence (CCoE) to guide cloud transformation efforts. A CCoE is most common within large companies with a cloud budget of $5 million or more.

    Speaking of budgets, cloud spending is going through the roof. In 2020, only half of companies met their projected cloud spend, and 39% of companies overspent their allotted cloud budgets. As I’ve covered before, cloud-native costs are notoriously difficult to identify and trim. Without the proper guardrails to manage spending, surprise data egress fees or hidden server costs can strain the cloud checkbook. As it stands now, 40% of companies lie in the $100,000 to $2 million per year range, and 6% of enterprises are investing $50 million a year or more into multi-cloud. This spending will likely increase in the coming years as cloud reliance expands.

    Enterprises Benefit Most

    So, which clouds are companies using? If we compare cloud adoption, AWS is a clear market leader; 88% of companies use AWS, 74% use Azure and 61% use GCP. AWS’s hegemony is not expected to fade in the next two years. Yet, while AWS usage will remain the same, competing CSPs will experience modest increases. This is likely due to Azure and GCP making gains in geographical zones outside North America, such as Asia-Pacific and Africa.

    In terms of technology used in cloud environments, open source software (OSS) is a popular choice. Cloud-native open source projects, such as Kubernetes, OpenStack and Terraform, have taken on a life of their own, with vibrant community support. However, not all shops build upon OSS and run it themselves. Somewhat ironically, we’re seeing more managed OSS emerge. One stand-out area is provisioning, where 42% of organizations build with open source and run it themselves.

    On the whole, multi-cloud is working at most enterprises, with 53% of survey respondents saying multi-cloud has helped achieve their business goals. The top benefit of multi-cloud is digital transformation, at 34%. This is followed by avoiding lock-in (30%), reducing cost (28%) and scalability (25%). But multi-cloud does not treat all companies as equals; the likelihood of multi-cloud success increases as the company size increases. Less than half (42%) of small companies say they have multi-cloud success, which jumps to 64% for large enterprises. With fewer resources for support, multi-cloud may be less beneficial for startups and small to medium businesses. In fact, 41% of professionals say a lack of in-house skills inhibits their cloud success.

    Challenges in a Hybrid Multi-Cloud World

    An ongoing talent gap is just one potential challenge to cloud success. Just over half (51%) say cost concerns are a top inhibitor to their cloud program success. Hybrid cloud complexity is another prominent challenge, with 35% of organizations citing it as a major cloud obstacle. Many enterprises are still grappling with the remnants of legacy on-premises estates. But technical debt is not the only reason for hybrid modalities. Surprisingly, large platforms even have constructed their own data centers or used colocation as an intentional strategy.

    Security is a top cloud inhibitor, according to 47% of IT professionals. The leading cloud security concerns include data protection (40%), data theft (33%) and regulatory compliance (31%). The myriad cybersecurity threats evolve each day, and cloud technologies are not immune; for example, web APIs are now a significant threat vector. A separate report found a 300% increase in malicious API traffic in the past six months. Other issues, such as exposed keys, insecure defaults and misconfigurations are known to hamper cloud-native infrastructure.

    Contrary to popular belief, nearly half (46%) of companies reported that COVID-19 has not quickened their cloud adoption. This reality could indicate that cloud migration has been planned for years, and recent adoption is only part of an ongoing trend. The study found that the pandemic did, however, accelerate things like infrastructure-as-code (IaC), container orchestration, compliance and governance and other operational factors.

    Infrastructure Automation Supports Multi-Cloud

    Multi-cloud feels like an inevitable result of accelerating cloud adoption in a more diversified market. Rising multi-cloud use is also arguably in line with Conway’s Law. As organizations develop more and more digital experiences across new verticals, the platforms and backend processes to support these initiatives will inevitably grow more and more complex.

    To mitigate some of the issues posed by multi-cloud, many organizations are turning toward increased infrastructure automation. In fact, 70% of those surveyed said infrastructure automation tools are extremely important to their organization. Of these tools, provisioning automation (75%) is the most popular kind in use. Automation for other areas, like networking (58%), security (50%) and app development (69%) follow.

    Hashicorp’s State of Cloud Strategy Survey boldly announces, “Welcome to the Multi-Cloud Era,” and its findings back up that sentiment. For further insights, you can view the results freely on this website.

  • Infrastructure-as-Code Security will Improve Your Cloud Security

    Infrastructure-as-Code Security will Improve Your Cloud Security

    Moving to the cloud creates a tremendous opportunity to get security right and reduce the risk of a data breach. Most organizations start their cloud security efforts by ‘shifting security left’ thereby addressing issues in the CI/CD pipeline. Fixing known vulnerabilities and risky configurations before pushing images to production makes sense. But there is an opportunity to shift security even further left—as you set up your cloud infrastructure—to reduce risk. Infrastructure-as-code (IaC) security allows you to define security controls as you configure your cloud infrastructure.

    Getting Started on Your Cloud Journey

    Before we dive into IaC security, let’s talk about why platform teams want to deploy infrastructure-as-code as they move through their cloud journey. Most organizations have not yet tackled IaC. They start their journey by experimenting with cloud configurations until they have defined a stack that works for their teams. In this early stage, application teams may be defining their own cloud stacks. They are manually configuring infrastructure or using scripts. Configurations may not be standardized across teams.

    Standardization of Infrastructure Saves Time

    Although experimentation is reasonable early on in the journey, standardization of infrastructure saves time. Cloud services are no different than applications that run on premises. When your teams are using different versions of tools in their stack, getting an application up and running can be a nightmare. Interoperability between services is challenging, and it can feel like you are fixing a different flavor of the same problem over and over.

    Mature cloud platform teams typically prefer to create a ‘golden image’ with a baseline set of services for development teams. They may create a menu of a few standard options to meet different teams’ needs. Because they are standardized, the platform team can take time to validate that they interoperate and are secure. For example, these golden images will be regularly scanned for vulnerabilities and updated to ensure they meet internal security standards and any relevant regulatory requirements.

    IaC security cloud

    Automating Infrastructure Deployment Reduces Errors

    Manually configuring the environment in the cloud for each team is tedious. Once these configurations have been standardized, the cloud infrastructure can be provisioned as code using templates. A declarative approach defines the desired end state, whereas an imperative approach defines the detailed steps to achieve the end state. The templates are normally stored in a Git repository and version controlled. Automating the configuration of infrastructure not only saves time but also reduces errors that can disrupt operations.

    IaC Security Shifts Security Further Left

    Once you have templates that define your infrastructure, standardizing permissions and access rights for services-as-code is a logical next step. The security team typically defines the guardrails or policies for accessing cloud services. These policies can then be defined as code along with the infrastructure configurations. This IaC security is a further ‘shift left’, allowing security to be embedded into infrastructure, even before an application can be deployed. Implementing policy-as-code minimizes the opportunity for human error in configuring security services. By defining these policies and enforcement guidelines together, the DevOps and security teams can establish a trusted partnership.

    Although some organizations may start their journey by implementing IaC security, for most organizations it happens later in the cloud journey. The order is less important than ensuring you take a DevSecOps approach and embed security at each stage to manage risk. Be sure to address the following areas as part of your cloud and container security program:

    Continuously Check Cloud Permissions and Configurations

    Even if you have IaC templates, you need a program to regularly take inventory of all cloud assets and confirm permissions and configurations. The Center for Internet Security (CIS) benchmarks are commonly used to check passwords and access rights. Beyond enforcing these best practices for security on cloud services, continuously checking for changes to permissions and suspicious activity is critical. The cloud vendors capture logs across all of their services, and your security tool should continually monitor and alert using those logs.

    Scan Images for Vulnerabilities and Risky Configurations

    Scanning for vulnerabilities and ensuring configurations use best practices allows you to shift security left into the development pipeline. Scan everywhere you have images—including within registries, pipelines and also check for new vulnerabilities identified for images running in production. Be sure to scan hosts as well as containers. Defining scanning policies and enforcing through the development process creates guardrails for the development team and clarifies expectations. Most regulatory compliance standards have image scanning requirements as well.

    Detect Threats and Respond to Alerts

    Prevention is fundamental but must be supplemented with threat detection and response. Alerting on unexpected behavior can identify the presence of a threat. Initially, teams may use out-of-the-box detection rules as a way to get started and then customize rules over time. Checking configs against dockerfile best practices is a good way to get started. Overly permissive access rights for containers is common in Kubernetes environments and should be allowed only when required.

    As your team develops more expertise with containers and Kubernetes, you can also implement zero-trust network security policies to block unexpected communication between pods, services and applications.

    Some DevOps teams handle triage of alerts, as they can quickly determine if the issue is a configuration issue or an indicator of compromise. Teams often map detection rules to the MITRE ATT&CK framework, allowing their security teams to manage alerts consistently across their environment. For any team to effectively respond to a security alert, it is important to capture a detailed record of exactly what happened before, during and after that event. This visibility can be particularly challenging with containers but it is critical because containers have short lives. The 2021 Sysdig Container Security and Usage Report revealed that about half of containers live less than five minutes.

    Complying with Regulatory Standards

    Complying with regulatory standards can be painful. Some standards were written with cloud computing in mind, like NIST 800-53 and SOC2, and others were not. With those broader standards, it is important to understand the controls that are relevant to containers and the cloud.

    As you consider your compliance program, be proactive—don’t wait until you are ready to roll into production. Start early by engaging your compliance team and helping them get up to speed. Your role is to provide evidence of compliance to pass an audit at any time using the documentation from your security platform.

    Getting Cloud and Container Security Right

    The move to the cloud creates a tremendous opportunity to get security right and reduce risk. The fact that physical security and a chunk of operations are delegated to cloud vendors frees up security and development teams to focus on their more narrow scope within the shared security model. By taking a secure DevOps approach and inserting security into every stage of the application life cycle, your team can confidently and securely run cloud and containers.

  • 5 Steps to a Seamless Multi-Cloud Migration

    5 Steps to a Seamless Multi-Cloud Migration

    With digitization the topic of discussion in almost every boardroom since the onset of COVID-19, it’s no coincidence that migration to the cloud has skyrocketed in tandem. In fact, at the onset of the pandemic, 87% of IT decision-makers noted that the remote restructuring of the workplace would push their organizations to accelerate cloud migrations.

    That trend shows no signs of slowing down. In fact, Gartner predicts that cloud spending will increase by 23% in 2021 to reach $332B. Driving this historic shift is the adoption of multi-cloud infrastructures. Businesses are increasingly separating and distributing their data flows and critical functions across multiple clouds from different service providers. According to Flexera’s 2021 State of the Cloud Report, an overwhelming 92% of enterprises say they now have a multi-cloud strategy, and 82% say they have a hybrid cloud strategy.

    There are many reasons for this increase in adoption. Developers that use containers, for example, can test their applications across multiple systems in the multi-cloud environment to speed up innovation, due to containers’ agility and portability. This use of multiple clouds also allows businesses to tackle cloud migrations in a more measured and deliberate manner rather than a ‘big bang’ approach.

    What this also means, however, is that it multiplies IT’s stress as they deliberate the benefits, costs and risks of moving their business to a multi-cloud strategy. For example, they must consider whether or not to keep their data on-premises, migrate it to a public cloud or some combination of both. They must also ensure their application’s ironclad security, which has become a mission-critical consideration during the unrelenting cybersecurity emergency that is the pandemic. Meanwhile, they may worry that such a large-scale cloud migration will result in lost revenue and increased downtime.

    With these key considerations and challenges in mind, here are five tips to help enterprises seamlessly migrate their resources to a multi-cloud environment.

    Assess Your Application’s Ripeness

    Before any application is migrated, it’s necessary to do a complete audit of current applications to assess their readiness for the migration. Businesses should look at the application’s dependencies and the ecosystem it lives in. This ecosystem could be its physical and virtual network infrastructure, including configurations, policies, load balancers, security and compliance requirements.

    Plan and Prepare

    This is a particularly challenging phase, as IT teams often linger here; wasting valuable hours and productivity. Therefore, the entire organization must outline what their migration journey will look like, discuss which departments will be affected during the process, and delegate responsibilities to facilitate a smooth transition to the cloud. The IT operations team, the development and quality assurance teams, key stakeholders and leadership should all be involved in these discussions—and should share the goal of ensuring a predictable migration process.

    Carefully Weigh Your Cloud Options

    Choosing the right cloud depends entirely on the unique needs, challenges and opportunities for the organization. While there are a number of different providers available to every enterprise, the best option will be influenced by financial constraints, goals for cloud adoption and even the systems already in place.

    Of course, when a business is taking a multi-cloud approach, these decisions become that much more difficult—especially in light of the fact that the average cloud company uses 2.6 public clouds and 2.7 private clouds, according to the Flexera report. Connectivity between these providers is crucial, with 88% of businesses enabling their multi-cloud strategy with a private connection.

    With this in mind, it’s also absolutely vital that decision-makers consider the security risks associated with each provider, as well. The number of cyberattacks on enterprises’ cloud infrastructures has increased significantly since the onset of COVID-19. With the stakes so high, a migration partner can help businesses assess which cloud providers are the right fit for them; accounting for their cost-effectiveness as well as which options will pose the least friction for the migration.

    Construct Your Migration Checklist

    The migration of an enterprise’s workloads is the most critical step of its cloud journey, and every company’s objective is to make a move swiftly and seamlessly. Creating a checklist can help businesses achieve this goal, as it helps them to prioritize the most critical components of their journey and understand the repercussions of a stagnant or inefficient migration.

    For example, every business should aim to achieve minimum downtime during their migration process and little to no disruption of service. Both the loss of network access and system downtime can cause immediate pain in the form of lost productivity and opportunities and even more harmful damage to a company’s brand. In fact, according to Gartner, the average cost of IT downtime is $5,600 per minute, meaning a well-practiced and efficient migration strategy has a significant impact on a company’s financial health.

    Since each migration is unique to the business and, often, unforeseen challenges arise that are native to the environment, it’s beneficial for organizations to have an expert migration team or partner to help them develop their checklist and ensure their migrations are streamlined and airtight.

    Validate Your Cloud Journey

    As the final step in a business’ migration journey, companies must validate that all their resources from their previous environment are fully migrated and operational in their target cloud environments. This step is crucial, as it marks the completion of a successful multi-cloud migration journey! This is primarily a manual process ensuring that nothing is neglected or forgotten and is often followed by an entire testing lifecycle.

    Post-Migration Pointers

    Cloud migrations can be complex, especially for companies relying on a years-old traditional and highly manual approach. Thankfully, in the age of automation, enterprises today are experiencing substantial time and cost savings and deploying migration strategies that move their workloads across multiple clouds in seconds instead of days.

    But even when an organization’s migration journey is complete, the management of several clouds at once creates its own set of challenges and risks—especially true in today’s landscape of skyrocketing climate and cybersecurity risks. It’s therefore vital that business leaders heighten their focus on organizational resiliency and minimizing downtime through things like tightened security and effective disaster recovery strategies.

    After all, with hybrid work forcing C-suites to scale their digital transformation plans even further, it’s becoming increasingly clear that the future of work is in the cloud. It’s therefore imperative that as cloud spending soars, enterprises allocate substantial resources not only to migration and management but protection, too.

  • Are You Wasting Money in the Cloud?

    Are You Wasting Money in the Cloud?

    I’m not the first person to point out the issues with Andreessen Horowitz’s blog post outlining why Dropbox is repatriating from the public cloud to data centers and saving an enormous amount of money. But while others have brought up valid points about how Dropbox is not representative of most companies and that the value in public cloud is in speed, not cost savings, I wanted to address a different angle: How do you, as an IT leader, know if or when you should move your cloud workloads back to the data center? How do you evaluate the ROI on the cloud in general?

    I want to talk through some of the factors that companies should be aware of when they’re thinking about whether or not it would be appropriate to repatriate a workload—and perhaps give some IT leaders peace of mind that staying in the cloud is OK.

    How Mature is your App?

    The earlier you are in the application’s life cycle, the more critical access to cloud infrastructure is. Early in the application’s life cycle, you need to get things out the door and test them with real people. You don’t, at this point, actually know how users will interact with your application or how the application will perform under the stresses of actual use. You also don’t know how much it will cost to run.

    At the beginning, quick iteration is also very important. There will undoubtedly be things in the initial release that go wrong—you need a way to quickly adjust course and improve.

    As the application matures, everything slows down. Your information about the application accumulates, but quick iteration becomes increasingly less important. It’s not until the workload is fairly mature that you can begin to understand how much it costs to run in the cloud and can compare that with how much it would cost to run on-premises.

    At the early life cycle stages, using a public cloud provider is extremely valuable because it allows you to get the application into users’ hands quickly and to iterate fast. As the application matures and changes are made less frequently, moving it back to a data center could make sense—at least in some cases.

    Internal Skill Sets

    Running an application in the cloud involves a different skill set than managing a data center. If you don’t have the internal skills needed to staff your data center, that can add not just cost, but will also increase the risk that something goes wrong.

    If you’re considering moving from cloud to a data center, taking a critical look at your internal skill sets is essential. Without a skilled team to manage the data center, you’re better off staying in the cloud even if it’s expensive. And yes, you can hire the skill sets you need, but that requires both time and money.

    Criticality

    If you have a workload that you never want to go down—because it is mission-critical, because it’s revenue-producing—you should probably keep it in the cloud. The cloud is generally more reliable than individual data centers, and the repatriation itself could easily cause disruptions.

    In addition, the cost of running mission-critical applications is less important simply because they are so essential to the business. If the application is burning money but is also your only source of revenue—unless it’s burning more money than it earns, it probably makes sense to keep things as-is.

    Looking at the Exit

    Of course, depending on your application’s architecture, repatriating it from the cloud to a data center could be either impossible or prohibitively expensive. If the application relies on the cloud provider’s proprietary services—databases, for example, or Lambda functions—moving it off of the cloud is going to be extremely hard. Even if it turns out that moving from the cloud to the data center is possible, it could easily cost so much that it wipes out any potential savings from repatriation.

    This isn’t to say that you should never think about leaving the cloud—in fact, if you think moving cloud workloads back on-premises is something you’d like to do at some point, you should consider it during the architecture phase. The decisions you make at that point will determine how challenging it would be to move off the cloud in the future—or even to change clouds if you want to. Using Lambda is going to make moving off the cloud very difficult, for example, whereas using containers will make it comparatively easier.

    When we talk about the costs of public clouds versus data centers, we’re trying to compare things that are fundamentally different. First of all, public cloud costs are notoriously difficult to understand, whereas understanding the costs for on-premises is relatively easy. Sure, there is overhead—building, staff members, etc — but it’s not that different from calculating any other cost in a business and an accountant could make sense of it in 10 minutes with Excel. Good luck doing that with AWS.

    That’s the core problem with cloud costs—humans have a hard time trusting what they don’t understand. But cloud has never been about reducing costs. And regardless, the cheapest option is not always the best option.

  • Stop Hiding the Cloud From Your Developers

    Stop Hiding the Cloud From Your Developers

    If you say a person or organization “goes to great lengths” to achieve something, it means they try very hard and perhaps do extreme things to accomplish their goal. One example I’ve seen is that of more traditional companies “going to great lengths” to “hide” the cloud from their pool of potential technical consumers doing work like development. Instead of saying, “Here it is,” they block or restrict users from direct consumption. Under this model, developers don’t directly login to Azure or AWS, they go to the “internal corporate portal” and fill out a request form for the resources they want and submit it. Then, someone eventually processes the request and creates what is needed.

    In extreme cases, organizations create “cloud teams” and staff those groups with people who build cloud resources on behalf of downstream technical consumers, like developers. Potential consumers must submit a request with a detailed design document specifying everything they want. Then, the cloud team schedules the project and delivers it at a future point. The whole process mimics the historical waterfall approach to software development or systems implementation.

    Why do things this way? It always seems to come down to four distinct drivers:

    Costs: “If we give open access, we will end up with a huge bill!”
    Compliance: “Everything built must meet our security standards.”
    Complexity: “Most users will waste time trying to figure it out.”
    Control: “Our group has always coordinated access to resources.”

    In traditional companies, the reasons for this restricted access always seem to be some variation of those on the list. And when you rebut with something like “Do you think Facebook, Twilio, Netflix, etc. restrict their developers’ cloud access?” the answer is usually something like, “Well, those are elite tech companies; we’ve always done it the way we do it now …”

    In most cases, there is no singular argument you can make to change someone’s mind, or expand the range of possibilities. But you can offer facts. So, let’s take on their arguments one at a time and see if we can rebut them.

    Costs

    Argument: “If we open up the cloud to everyone, then all the developers will endlessly create virtual machines (VMs) and associated resources and services, and we will end up with a huge bill.”

    Rebuttal: There are certainly examples of this; do a search for some variation of “unexpected cloud costs,” and they’ll pop up, especially from a few years ago when cloud adoption was just taking off. But what about today? What can be done to control costs? Even though there are lots of tips and ideas on how to control cloud costs, I’ll offer one simple possibility that directly applies to developers and development groups that is not often mentioned in many articles: implement a cloud resource quota per developer or dev group.

    In AWS, for example, you can allocate via IAM; with Azure, you can use resource groups. The upshot is that there is a way to restrict the number and amount of resources that a single user can consume. So, whether you have 10 or 1,000 developers, you can use these built-in mechanisms to limit and then estimate what your consumption will be. If I have 100 developers and I put a limit on the number of VMs, the number of GB of RAM they can allocate and the amount of storage each developer can consume, then haven’t I just created a “cap” on consumption? The quota concept gives you a path to a “predictable” bill every month.

    Compliance

    Argument: “If we open up access to everyone, they’ll create VMs that don’t adhere to all our internal security standards.”

    Rebuttal: Aren’t developers just looking for a VM (or VMs) to do dev work? We aren’t talking about building production-hardened VMs to host applications. We are talking about giving developers the proper sandbox in which to do their work. So, from this perspective, requiring that developers only create VMs that adhere to strict compliance standards reserved for production servers doesn’t make sense.

    For example, maybe one of your compliance standards is that all production servers have a monitoring agent installed on them. Fine, that makes sense; what about dev/test? In dev/test, I might be spinning up a VM or a container that only exists for a short time, maybe even less than an hour while some tests are running. Does it make sense to require that a monitoring agent be installed on a VM that will only have a one-hour shelf life? Just throwing out the term “compliance” as a catch-all is not a real solid objection. Perhaps for dev/test, there are minimum standards you would want to follow regarding OS levels, patches, etc., but the VM(s) you use in dev/test do(es)n’t necessarily need to have all the additional security requirements reserved for production servers.

    The other part of this objection we hinted at earlier is that you have to transition to “cloud thinking.” Resources that exist for the next 10 minutes in the cloud could intentionally be gone shortly after that. In the cloud, you can quickly create and destroy VMs, or entire environments of VMs. That is what makes the cloud a game-changer versus traditional on-premises methods. You can’t apply the same on-premises considerations to the cloud one-to-one. You need to come up with a new thinking model that takes into account what it means to use the cloud versus how you did it before on-premises.

    Complexity

    Argument: “It’s too hard to figure out some of these cloud architectures, and developers will waste time trying to do so versus having a central team do all the work correctly the first time.”

    Rebuttal: Without the commitment to being a “learning organization,” there can be no DevOps, no transition/migration to the cloud, no digital transformation. Check out item number six on this list of 7 Ways to Make Developers Happy. (Spoiler alert: it’s ‘promote continuous learning.’)

    If “complexity of learning” is one reason why you restrict your teams’ access to the cloud, then you are missing the point of what it means to be a technical expert. Developers partially define themselves by the depth and the range of knowledge that they have accumulated, so continuous learning is a significant component of keeping developers “happy.” Not to mention that happy developers are more engaged and tend to stick around longer at companies that keep them that way; you’re risking losing the technical talent you do have, which has a host of detriments to your organization.

    Control

    Argument: “If developers are creating their own servers, what does our team do?”

    Rebuttal: This one is the toughest of all to rebut. Many organizations have one or more infrastructure teams who are responsible for creating servers and resources and giving access to downstream consumers. These groups control the resources. Now, along comes the cloud where everything can be self-service. And the natural reaction is, “If developers are creating on their own, what do we do?”

    For many traditional companies making the transition to the cloud, there will still be many opportunities for participation. Instead of “architect,” now we need “cloud architect.” Instead of “engineer,” now we need “cloud engineer.” Also, what other higher-value work could you be doing for the company if you weren’t spending all your time provisioning and maintaining on-premises servers? Do you think all of the existing on-premises applications are going to go away overnight? Will your company become “cloud-native” in the next six months? What about all of the AIX, IBMi, Solaris and other legacy components that are in the data center? There will always be plenty of work for everyone to do. And it’s always an opportunity to learn some new skills.

    The reality is that giving developers direct access to the cloud (with controls) frees up many other corporate resources to work on things that are, strategically, more important. If your company is not cloud-native right now, then guess what? It won’t be for a long time. Maybe in the short term, you’ll be hybrid-cloud and then in the long term, cloud-native. Along the way, there will be opportunities for everyone to rethink how things get done and maybe learn something new along the way.

    If you are hiding the cloud from your internal customers, ask yourself, “Why?” Are the original reasons still relevant, or are they holdovers from a time long past? Maybe it is time to re-examine your original rationale for why developers don’t have direct access to the cloud. If the goal of your organization is to “service the customer,” “do more,” “move faster,” etc., then removing internal barriers to accessing the cloud is one way to make progress.

  • CloudTruth Acquires Tuono to Advance Configuration Management

    CloudTruth Acquires Tuono to Advance Configuration Management

    CloudTruth, a provider of a unified configuration management platform, today revealed it has acquired Tuono, a provider of a cloud secrets management platform, as part of an effort to make it simpler to secure infrastructure provisioned using code. Terms of the deal were not disclosed.

    Greg Arnette, CloudTruth CEO, said misconfigurations are rife across cloud computing environments. IT organizations now need a self-documenting approach to managing configurations as the number of cloud services that organizations can employ continue to multiply. The CloudTruth platform will automatically keep track of all configuration changes made to an IT environment, Arnette said.

    The rise of Kubernetes and microservices is making things even more challenging, introducing a range of additional opportunities to misconfigure cloud platforms and applications.

    Fresh from raising $5.25 million in seed funding, Arnette said one of the least-appreciated aspects of the configuration challenge is how dependent organizations are on tribal knowledge that gets shared unevenly across DevOps teams. The lack of a centralized repository for managing configurations makes it challenging to onboard new members to those DevOps teams, he added, resulting in more opportunities for mistakes to be made.

    Tuono adds a cloud-native secrets management platform that can be deployed across multiple cloud services. The goal is to provide a configuration management platform that functions as a metadata wrapper compatible with configuration tools such as Terraform or CloudFormation from Amazon Web Services (AWS). That approach reduces the cognitive load on DevOps teams that would otherwise have to remember how and why each service is configured the way it is, said Arnette.

    Arnette added that an additional goal is to enable DevOps teams to put guardrails in place that reduce the opportunities for misconfiguration errors to be made while continuing to enable developers to build and deploy applications quickly. Each organization will need to decide where to strike a balance between those competing agendas, noted Arnette.

    The challenge organizations are wrestling with today is just how vulnerable software supply chains are—as a series of cybersecurity attacks have made all too apparent. Organizations are adopting DevSecOps best practices to better secure those supply chains. However, the rate at which DevOps teams can come up to speed on security isn’t fast enough to secure applications that are about to be deployed. At the same time, there are potentially hundreds of applications deployed in cloud platforms with varying degrees of misconfigurations. Cybersecurity teams are now being asked to review how well those applications are configured as part of an effort to address the security of the entire software supply chain.

    It’s not clear if a backlash against DevOps, in general, is in the making as cybersecurity teams review application development and deployment practices. There undoubtedly will have to be adjustments made to those processes, even as most organizations realize just how dependent they are on software. The issue is that deploying more insecure applications faster is, at the end of the day, counterproductive.

  • Leveraging the Cloud for Mainframe Access

    Leveraging the Cloud for Mainframe Access

    Now more than ever, organizations around the world are looking to extend their existing mainframe investments as part of larger digital transformation initiatives. As core systems of record and reliability, mainframes continue to run many organizations’ most important applications and the idea of replacing these systems comes with greater risk than reward. While organizations are considering modernization of their mainframe investments, it’s important to remember that maintaining mainframe access and offering new ways for their users to work with the data and systems is a vital part of the larger project.

    Leveraging the Cloud for Mainframe Access

    With the recent increase in remote work, it’s no surprise that more companies are looking to leverage the cloud for mainframe access. This has many benefits from increasing scalability, availability and performance, to reducing application costs and improving security. Implementing modern mainframe access as part of a larger cloud project ensures that an organization’s modernization journey is not only transformational but also secure.

    If making the decision to leverage the private or public cloud for mainframe access, the integration of a secure host access solution ensures teams have access to the systems and applications needed to do their jobs, wherever they may be located. Deploying this secure access in a cloud environment is made easier by host access administration being integrated and centralized with the corporate user directory. Along with simplifying provisioning and management, centrally managed host access is, most importantly, more secure than other forms of access.

    The extension of enterprise security to the mainframe is sometimes overlooked in a transformation, but it is an integral part of the larger process of strengthening data and system security. In a perfect world, this can best be done through the integration of a host access solution with the existing identity and access management (IAM) system. If this is possible, the authentication credentials that are already in use for authorizing or denying access to the mainframe can be leveraged successfully.

    There are numerous benefits to an IAM integration with regard to access, data, stronger passwords, application security settings and system configurations. With IAM, the benefit of least privilege access means that users can access only the mainframe systems and data that are needed to do their jobs. Additionally, application security settings and session configurations can be changed from a central point by using the user directory. Finally, the stronger credential requirements of the IAM integration get rid of weaker eight-character passwords, strengthening security as a whole.

    Host Access Improves User Experience

    When it comes to host access, having a secure and centralized solution not only improves the mainframe access experience for the user, but also for the administrator. With zero-footprint secure access, users can be moved to a more secure web with higher security standards if needed. Security is also stronger with enterprise credentials that leverage mainframe session authorization to automatically sign them in. The integration of a host access solution gives administrators the ability to quickly deploy secure browser-based sessions, as well as providing web interfaces with no Java required, eliminating workstation dependencies as a result. This is also paired with the use of containers to enable deployment to countless users and support for mobile devices. For these reasons, a host access solution should be a common component in any cloud journey.

    The mainframe and its data, applications and user access remain vital for organizations and it is important that they remain protected and connected. With security being an ever-evolving issue, keeping these core systems secure while ensuring employees are able to access the systems and data they need should always be a priority. In conclusion, organizations looking to leverage the public or private cloud for their mainframe will have more success if they also strengthen their data and system security as part of the process.