devopsy.kinsta.cloud

Tag: Internet of Things

  • Splunk Adds Hub to Extend Observability to Edge Computing Platforms

    Splunk Adds Hub to Extend Observability to Edge Computing Platforms

    Splunk today launched a platform for ingesting data from sensors, industrial equipment and internet-of-things (IoT) platforms so that it can be analyzed alongside data collected from IT environments.

    Announced at the company’s .conf23 conference, the Splunk Edge Hub extends the reach of the troubleshooting platform Splunk provides that increasingly involves various types of edge computing platforms.

    Tom Casey, senior vice president for products and technology at Splunk, said Splunk Edge Hub is designed to be deployed in those edge computing environments and reduce the total amount of data that needs to be transferred back to an instance of the Spunk analytics platform running in a data center or in the cloud.

    That approach makes it possible to remotely monitor everything from environmental conditions to identifying anomalies indicative of an outage that might be prevented. The overall goal is to unify visibility across IT and operational technology (OT) environments as these systems and applications become more integrated, said Casey.

    It’s not clear how quickly that integration is occurring, given the historic cultural divide that has existed between IT and OT teams. But with the rise of digital business transformation initiatives, the data collected from edge computing platforms is increasingly being incorporated into a wide range of applications deployed at the edge, in local data centers and in the cloud.

    In general, observability tools are being used to not only improve processes but identify and block suspicious activity. Of course, OT teams have been monitoring edge computing platforms for decades, but observability platforms make it feasible to interrogate logs, metrics and traces to hopefully discover issues before there is a disruption to services. The challenge, of course, is that not everyone on either the OT or IT team necessarily knows how to shape the queries required to discover the root cause of a potential issue. The Splunk approach essentially leverages the skillset of IT professionals that have mastered its platform to address that issue; something most OT professionals are not going to be able to do using their existing tools and platforms.

    One way or another, DevOps teams will soon need to be able to remotely diagnose edge computing issues as the number of workloads deployed on these platforms expands. IT teams are not going to be able to travel to the physical location of every edge computing platform every time an issue arises. In many ways, the rise of edge computing will force a transition to observability tools that will enable IT teams to more proactively manage IT environments rather than responding after a metric that OT teams are monitoring has already exceeded its threshold.

    In the event there is still an issue, observability platforms should also reduce mean-time-to-remediation (MTTR) as visibility into IT environments, including edge computing platforms, is improved.

    It’s not likely that OT and IT teams will ever be completely unified, but as observability platforms continue to evolve, there will be much greater opportunities for collaboration.

  • A DevOps Guide to IoT Technology

    A DevOps Guide to IoT Technology

    Internet-of-things (IoT) is a term used to describe the network of physical devices—from everyday household items to sophisticated industrial tools—connected to the internet, sharing and collecting data. With the advent of cheap computer chips and the ubiquity of wireless networks, it’s possible to make anything a part of the IoT. Add to that the exponential growth in artificial intelligence and machine learning, and the IoT is a truly significant part of our lives.

    The IoT allows devices to communicate and interact over the internet, and they can be remotely monitored and controlled using technologies many of us have never heard of, such as MQTT, QUIC and AMQP. The proliferation of these devices has led to an exponential increase in the amount of data we can gather, analyze and use to make more informed decisions. We’ve already seen the transformative potential of IoT in our homes, workplaces and cities, and it’s only set to increase as more and more devices come online.

    At the heart of this technology is the concept of seamless connectivity and communication. However, the rapid development and deployment of IoT devices pose significant challenges. This is where the DevOps approach comes in, offering a solution to these challenges by improving efficiency and effectiveness in the development and operation of IoT systems.

    Importance of DevOps in IoT Development and Deployment

    In the context of IoT, DevOps is crucial. IoT devices are often deployed in the field, in homes or in other environments where physical access is difficult or impossible. As such, the ability to update and manage these devices remotely is a critical necessity. DevOps methodologies enable this remote management, providing mechanisms for continuous integration and continuous delivery (CI/CD) that make it possible to push updates to devices regularly and reliably.

    Moreover, given the pace at which IoT technology is advancing, it’s crucial to be able to adapt quickly to changes and new developments. In this regard, DevOps is invaluable. By bringing together development and operations, it allows for more agile response to changes, faster issue resolution and overall better performance.

    The Role of DevOps in IoT

    Speeding Up IoT Development Cycles

    One of the key benefits of using a DevOps approach in IoT development is the ability to speed up development cycles. With traditional development practices, the time between identifying a requirement or an issue and implementing a solution can be lengthy. In contrast, DevOps practices, such as continuous integration and continuous delivery, enable rapid prototyping, development, testing and deployment of new features and updates.

    With the DevOps approach, developers and operations teams work together from the beginning of a project, collaborating closely to ensure that the software being developed is robust, reliable and meets the needs of the business. This cooperative approach, combined with automated testing and deployment processes, significantly reduces the time to market for new features and updates.

    Ensuring High-Quality, Reliable IoT Applications

    Another significant advantage of utilizing DevOps in IoT development is the increased quality and reliability of the applications being developed. With traditional software development methods, testing and quality assurance often occur after the development process. This can lead to issues being identified late in the cycle, which can be costly and time-consuming to fix.

    On the other hand, DevOps practices emphasize continuous testing throughout the development process. This means that issues can be identified and addressed much earlier, leading to higher-quality, more reliable software. In the context of IoT, where devices may be deployed in critical applications such as health care or transportation, the importance of this cannot be overstated.

    Enabling Scalability and Flexibility in IoT Systems

    Finally, DevOps plays a crucial role in enabling the scalability and flexibility of IoT systems. As the number of IoT devices continues to grow exponentially, the ability to manage and monitor these devices efficiently is becoming increasingly important. DevOps practices, such as infrastructure as code (IaC) and the use of containers and microservices, provide the tools necessary to scale and adapt IoT systems as needed.

    With IaC, the infrastructure required to run an IoT application is defined and managed as code, making it easy to replicate and scale. Containers and microservices, on the other hand, allow applications to be broken down into smaller, independent components that can be scaled individually, providing a high level of flexibility and efficiency.

    Implementing DevOps in IoT Development

    Integrating CI/CD in IoT Application Development

    Continuous integration/continuous delivery (CI/CD) is a fundamental DevOps practice that plays a vital role in IoT development. It involves automating the processes of software delivery and infrastructure changes. With CI, developers frequently merge their code changes into a central repository where automated builds and tests are run. CD takes this a step further by automating the release of these changes to the production environment.

    For IoT, integrating CI/CD can help maintain the quality of software, increase efficiency, and speed up the process of delivering software updates or new features to devices. It also ensures that any changes made can be easily rolled back, reducing the impact of any potential issues.

    Applying IaC for IoT Infrastructure Management

    Infrastructure-as-code (IaC) is another key DevOps practice that is highly relevant to IoT. IaC is the process of managing and provisioning computing infrastructure through machine-readable definition files rather than physical hardware configuration or interactive configuration tools.

    In the context of IoT, IaC can simplify the process of setting up and managing the complex infrastructure required for IoT applications. With IaC, developers can quickly and reliably replicate infrastructure setups, making it easier to scale IoT applications as the number of connected devices grows.

    Using Containers and Microservices in IoT Application Architecture

    Containers and microservices are two more DevOps practices that can significantly benefit IoT development. A container is a standalone executable package that includes everything needed to run an application, including the code, runtime, system tools, system libraries and settings. Microservices is an architectural style that structures an application as a collection of small, loosely coupled services.

    In the context of IoT, using containers and microservices can greatly simplify the process of developing, testing and deploying IoT applications. Moreover, they can enhance the scalability and flexibility of IoT systems, making it easier to adapt to changing requirements and scale as the number of connected devices grows.

    Challenges of Implementing DevOps for IoT and How to Overcome Them

    Dealing with Device and Platform Diversity

    One of the main challenges in implementing DevOps for IoT is dealing with the diversity of devices and platforms. IoT devices can range from simple sensors to complex machines, each with its own capabilities, requirements and operating systems. Moreover, these devices may communicate using different protocols and have different connectivity requirements.

    The key to addressing this diversity is to adopt a platform-agnostic approach. This involves developing software that can run on any device, regardless of its hardware or operating system. Containerization can help achieve this by providing a consistent and reproducible environment for running applications.

    Ensuring IoT Security and Privacy

    Security and privacy are significant concerns in IoT, and they can be particularly challenging in a DevOps context. The increased frequency of updates and changes that come with the DevOps approach can potentially introduce new vulnerabilities. Moreover, the interconnected nature of IoT devices means that a security breach can have far-reaching consequences.

    To address these challenges, it’s essential to integrate security practices into the DevOps process. This is often referred to as DevSecOps. This approach involves continuously monitoring and testing for security vulnerabilities throughout the development process rather than treating security as an afterthought.

    Managing IoT Data Volume and Complexity

    The sheer volume and complexity of data generated by IoT devices can also pose a challenge in a DevOps context. Traditional data management and analysis tools may not be able to handle this volume and complexity.

    To tackle this, it’s important to utilize modern data management solutions that can handle large volumes of data. Additionally, employing advanced analytics and machine learning techniques can help make sense of complex data and extract valuable insights.

    Coordinating IoT System Updates and Maintenance

    Finally, coordinating updates and maintenance for a large number of IoT devices can be a significant challenge. This is particularly true in a DevOps context, where updates and changes are frequent.

    To address this, it’s crucial to have a robust system for managing and tracking updates. Automated deployment tools can be invaluable in this regard, allowing updates to be pushed out to devices in a controlled and coordinated manner.

    Conclusion

    In conclusion, implementing DevOps in IoT development can bring significant benefits, including faster development cycles, higher-quality, reliable applications and improved scalability and flexibility. However, it also presents unique challenges that need to be effectively addressed. By understanding and properly implementing the principles and practices of DevOps, we can harness the full potential of IoT technology and drive forward innovation.

  • Chip-to-Cloud IoT: A Step Toward Web3

    Chip-to-Cloud IoT: A Step Toward Web3

    During the first six months of 2021, IoT devices were breached 1.51 billion times, a significant increase from only 639 million breaches observed for the entirety of 2020. This problem can be attributed to the widespread adoption of the internet-of-things (IoT) and the Windows Server Message Block (SMB), and neither can be avoided in the age of remote work. 

    But while these technologies offer unprecedented levels of data mobility and oversight for many interconnected digital and physical systems in industrial settings, they also make it easier for malicious actors to penetrate the very fabric of our lives if left unsecured. 

    This makes it all the more important for DevOps teams and developers to prioritize cybersecurity while creating systems for the IoT. It is important to address the inherent flaws in security like easily-breakable usernames and passwords or saving data without protection on remote access servers. 

    There is a way developers and DevOps professionals can help curb the increasing instances of cybercrime, and it’s called chip-to-cloud IoT. Let’s explore how it is emerging as a viable way to construct a safer, more valuable and more decentralized system for everyone.

    IoT: Understanding the Inherent Security Challenges

    It’s best to investigate potential cybersecurity issues that may befall your organization before finding ways to secure your IoT platforms with solutions such as a shift left security approach (meaning security is embedded in the earliest phases of the application development process) or an IoT decentralization approach, as we’ll expand on below. 

    Some common security concerns include:

    Vulnerabilities in the Software and the Firmware

    It can be challenging to guarantee the safety of IoT systems because of the following security flaws:

    • Lack of computational capacity to provide adequate built-in security
    • Inefficient access control in IoT systems
    • Insufficient funds for adequately testing and further developing the firmware’s security
    • Lack of regular patching and upgrades as a result of IoT devices’ technical and budgetary restrictions
    • Unpatchable vulnerabilities because users don’t regularly update their gadgets
    • Older devices may not be compatible with newer software updates
    • Easy accessibility means attackers could insert corrupted chips or hack via radio waves

    Possibility of Cloud Breaches

    Hackers can gain access to the data processed by your IoT system by intercepting unencrypted messages. 

    Your device might contain sensitive information such as your location, bank account information and medical records. Attackers can access critical information in many other ways, including by exploiting weakly protected communications.

    Even if every piece of data is transported to cloud storage, intruders can potentially target cloud-hosted applications. Therefore, the risk of data leaks is not just from the devices themselves but also from the cloud environments to which they are connected. That is why DevOps pros, developers and software engineers must find ways to protect the technology from the start and prevent hackers from breaching the cloud.

    Risks of Malware

    A recent survey by Zscaler revealed that smart TVs, set-top boxes and smartwatches are most susceptible to malware attacks. 

    If attackers successfully infiltrate an IoT system or insert malware, they may be able to change its functionality, acquire personal data and carry out other malicious activities that can endanger device owners and users. 

    The trouble is that manufacturers struggle to maintain proper software security to keep their devices safe. Security often takes a backseat when these gadgets are built, leaving buyers to deal with the aftermath if they get infected with malware. 

    How Chip-to-Cloud IoT Minimizes Security Risk

    There are two ways for organizations to enhance their IoT security. 

    The first step is ensuring both device manufacturers and software developers adhere to sound security principles. If the value chain is exposed, the solution must be chip-to-cloud. 

    Second, they must take an in-depth approach to protecting key technology by layering security controls to create an iron-clad IoT infrastructure.

    The chip-to-cloud architecture enables the creation of secure, low-energy networks of IoT devices that can communicate directly with cloud hosting platforms. The collective effort to build a cloud-first technology stack has been costly, inefficient and unreliable.

    Traditionally, IT professionals have used non-machine-hosted security tools like firewalls to secure IoT devices. Chip-to-cloud architecture aims to fix this underlying flaw.

    Features of Chip-to-Cloud IoT

    Onboard security and computational power are two of the most significant shortcomings of IoT devices. In addition to being more powerful and safe than previous models, IoT devices built with chip-to-cloud security are also more energy-efficient.

    Here are the features that make the chip-to-cloud technology so effective:

    • An onboard cryptography engine
    • Generator of random numbers
    • Sufficient random-access memory (RAM)

    How It Works

    Reliable software design is essential for IoT devices and other internet-connected devices. It keeps hackers from stealing your identification or duplicating your device for their ulterior motives. Chip-to-cloud delivers on all fronts. 

    These chipset characteristics confer an extra security advantage. Each IoT node is cryptographically unique, making it nearly impossible for a hacker to impersonate it and access the more extensive corporate network to which it is connected. Chip-to-cloud speeds things up by eliminating the need for traffic delays between the logic program and the edge nodes that are ready to take action on the information.

    The chip-to-cloud architecture of the internet-of-things is secure by design. New tools are being developed to provide bespoke and older equipment with data mobility capabilities, just like the current IoT. 

    Nevertheless, chip-to-cloud chipsets are always connected to the cloud. As a result, the availability of assets and the speed of digital communication across nodes, departments and facilities will be significantly improved. Chip-to-cloud IoT is a significant step forward in the evolution of the IoT toward Web3. Experts predict IoT device customers and value producers will benefit more from these design principles than centralized providers.

    Chip-to-Cloud Enables IoT Decentralization

    The traditional approach to IoT is to cover an already-existing cloud of linked devices with third-party firewalls and other security measures. Its equivalent imagery would be a single umbrella covering a family of 12—or at least attempting to do so. The protocols that govern security must be central to decentralization.

    Chip-to-cloud IoT is a powerful, uniquely secured chipset that can be installed inside each device, giving it a far greater connection in the IoT chain than the average IoT gadget.

    The cloud manager or analytics application receives data from every node in real-time using the chip-to-cloud technology. The process does not add another layer of protection; instead, it reduces the latency and loss of data packets as they travel from one destination to another.

    The Future of IoT

    In the wake of recent global events, general cloud technology and chip-to-cloud architecture are receiving huge investments. IoT can supply the data that companies and organizations need to fuel their client engagement portals, machine maintenance platforms and enterprise planning tools.

    That said, the internet-of-things will not be entirely safe even with chip-to-cloud technology. Businesses must have a security-focused culture, standards for managing new IT investments and the expertise to pick the best technology partners.

    The Web3 transition will likely be coupled with future Web3 innovations such as blockchain to improve its utility and security. Seeing how the world’s genuine value-creators use these new solid tools will be intriguing.

    Conclusion

    Considering security at the very onset of any IoT project is critical. Maintaining comprehensive cybersecurity in IoT environments is challenging due to the rising frequency of cyberattacks and increasingly complicated system vulnerabilities. 

    The safety of IoT devices is essential to the operation of many businesses—and even entire economies. Engineers are under increasing pressure to ensure that the rapidly expanding number of interconnected devices is safe. This is why chip-to-cloud technology is poised to become the next big thing in this field. Are you ready to be the change?

  • Why Trust and Integrity Are Critical to IoT

    Why Trust and Integrity Are Critical to IoT

    We hear a lot about how the IoT is transforming people’s work and daily lives, but for me, its impact goes deeper. As a Type I diabetic, I depend on data from an IoT device to stay healthy. If I can’t trust my latest blood sugar reading, the results can be catastrophic. Health care use cases like mine represent some of the many examples that underscore the importance of data integrity. Stacey Higgenbotham expressed it perfectly in a recent post: “If a business or consumers can’t trust the data, the IoT fails.”

    The IoT is all about making better, more informed decisions, and data is the foundation that makes those decisions possible. As the IoT gains maturity, we’re seeing its impact across more and more industries and use cases. 

    In agriculture, smart sensors are in widespread use for real-time crop monitoring to help farmers track the state of their products. Tools like motion detectors, light detectors and moisture sensors can be brought together to support predictive analysis and enable smarter, more automated decisions. IoT sensors are also tracking the location and health of livestock to help farmers detect disease outbreaks and isolate animals if needed. 

    Most of us have seen how the IoT has revolutionized the safety and efficiency of the home, providing unprecedented control over appliances, heating and cooling systems, smart metering and lighting. Security cameras, alarm systems and smart locks are strengthening physical security and bringing residents peace of mind. As these smart home systems mature, they are also becoming increasingly integrated, personalized and automated.

    The global pandemic is also helping shape IoT adoption. Forrester predicts that manufacturers, pharmaceutical firms and utilities are increasingly switching to remote experts and technicians for support. To manage and repair their assets without extended downtime and costly travel, these industries have begun connecting previously disconnected machines.

    What do these diverse use cases have in common? Without trusted data from connected sensors and devices, all of them become vulnerable and the decisions they support become questionable. Inaccurate moisture data from a sensor could cause a farmer’s crops to fail. A compromised smart lock could leave a home vulnerable to theft. In a manufacturing environment, inaccurate telemetry from a connected machine could lead to factory floor shutdowns or damaged assets. The positive business outcomes enabled by the IoT all hinge on working with accurate, timely and trusted data.

    Signing Is Key to Strengthening IoT Data Integrity

    Establishing data trust should be top of mind for IoT device manufacturers, and it is imperative that they take steps to ensure that data is not being manipulated in transit or at rest. This protection applies not only to data packets exchanged by the devices and applications but firmware updates and supply chain processes.

    The recent executive order signed by president Biden underscores the need for measures like code signing. Focused on improving the nation’s cybersecurity, the EO presented guidelines and general best practices for federal departments, agencies and contractors. However, its impact is also likely to extend to technology and infrastructure companies. 

    Some of the strongest direction in the EO is intended to improve the security of software as well as supply chains for technology manufacturers. The order establishes baseline security standards for the development of software sold to the government, including requirements for improved visibility into that software and making security data publicly available. The order acknowledges that too many devices and software releases contain vulnerabilities that bad actors could exploit. 

    Effective Code Signing Requires Strong Management 

    Fortunately, a proven solution is available today to help manufacturers ensure data authenticity, confidentiality and trust for their IoT solutions. Best practices like code signing can help manufacturers bake security into each and every stage of their development processes. By applying digital signatures, organizations can assume full control of their development. They can confirm the integrity of their code before it moves further along in the development cycle and is put out in the field for devices and their customers. 

    Code signing is only as effective as the processes and best practices that support its implementation. To make the most of digital signatures, developers and engineers need a holistic approach to management. The signing process should be seamlessly built into their development processes to simplify and ease adoption. 

    A common management platform should enable manufacturers to fully protect private key usage and signatures, as well as monitor and manage access to digital keys. The process should also enable organizations to support granular monitoring of their code signing processes and include historical tools like reporting and auditing for full accountability and compliance. With a process in place to continually sign firmware, software updates and other components that can ensure data integrity in device interactions, manufacturers can be assured that their IoT solutions will work as intended, using data their end customers can trust. 

    There’s no question that as the IoT continues to extend deeper into our business and personal lives, the importance of data integrity is also rising. The stakes will only increase as more systems, processes and life-or-death decisions rely on trusted IoT data. To sustain the soaring growth of IoT use cases and solutions, it’s up to manufacturers to build security into the supply chain. With a strong data foundation underpinning today’s rapid innovation, the potential of the IoT revolution is limitless.

  • 4 Things to Do When Running the Iot Zoo

    4 Things to Do When Running the Iot Zoo

    Zoos are fascinating places. In just a few acres you can encounter all kinds of interesting, rare and exotic animals from different parts of the world and from different ends of the food chain. But, what keeps the tigers from eating the zebras or even the visitors? Segmentation. Walls, fences, cages and other barriers that keep every critter safe and well behaved. The same concept is vital to the proper security of Internet of Things (IoT) and operational technology (OT) devices. As these devices proliferate, it is segmentation that keeps them all safe and well behaved.

    Here’s what I mean.

    The modern enterprise consists of a huge variety of network-connected devices that play different roles in making the network operate properly, provide services to customers and partners, and that allow employees to do their jobs quickly and efficiently. Once deployed, however, it can be difficult to track and monitor IoT devices—and you can’t manage what you can’t see.

    Using the zoo analogy, if your devices are allowed to roam freely, some will be forgotten and others will act in unexpected ways. There will be unmanageable chaos. But, if the animals are categorized, monitored, segmented and cared for, the zookeeper can keep things operating in an orderly manner.

    If you are among those struggling to keep your IoT and OT device menagerie in line, I have bad news. Your challenges aren’t getting any easier. According to some estimates, there will be between 41.6 billion and 83 billion IoT devices connected to networks by 2025. Those estimates were made before the outbreak of the COVID-19 pandemic. Now that a Pandora’s box of remote work has been opened, there’s a strong chance trends like distributed workforce, manufacturing automation and mobility will result in a sharp acceleration in the use of IoT devices, pushing those numbers higher. Making matters worse, many of those devices will connect to networks unnoticed, unmanaged and unsecured.

    Healthcare is already among the industries feeling the effects of most sharply. Healthcare organizations rely on connected devices to perform their jobs and deliver the highest quality of care possible. It’s not just medical devices like insulin pumps, EKG machines and ventilators. Sophisticated healthcare facilities rely on connected devices for security monitoring and access control, administration, environmental control and IT operations management. The health, security and usage of non-medical devices can impact patient care so, for instance, IP-enabled elevator systems are needed to transport patients while HVAC systems can impact air quality in operating rooms. Protecting and managing IoT and OT devices is especially important in healthcare organizations post COVID-19, as we will be dealing with the aftermath of a surge of new devices being deployed.

    Right now, roughly 15 million IoT devices are being used by healthcare professionals worldwide. Hospitals use an average of 10-15 devices per bed, collecting and communicating highly sensitive protected health information (PHI). It’s no surprise, then, that 82% of healthcare organizations have had their IoT devices targeted. The risk increases when devices used by medical personnel cross from professional to personal use. A tablet used to enter a patient’s PHI and check email makes the network it’s connected to more vulnerable to phishing scams and ransomware. Unfortunately, with hospitals focused on responding to the pandemic, some malicious actors see it as an opportune time to strike.

    What can be done to mitigate the risk? If I ran the IoT zoo, there are four steps I’d take to figure out what was running wild and wrangle everything into its pen.

    Discover and Inventory

    You can’t manage what you can’t see, so complete, real-time discovery of IoT devices is critical. Step four of segmentation is unachievable without proper visibility and classification of devices. The fidelity of visibility and classification of devices is key, and needs to consider ephemeral assets that may go online and be brought up in a different physical or network location. We’ve seen this situation be exacerbated during the COVID-19 pandemic as new network-connected devices are rushed into service. 

    Baseline and Monitor Behavior

    Once you’ve taken inventory, you need to map how devices communicate and with what. Devices use a variety of protocols and communication patterns. Baselining what is normal is crucial to identify when devices start behaving badly. For example, without proper traffic monitoring, we won’t know that the baboons are attacking the pangolins every night. 

    Identify Risks

    With a baseline for recognizing bad behavior, you can identify anomalies that signal potential compromise, high-risk devices such as those running obsolete operating systems and devices with medical or FDA-advisories. The fragile, rare or highly valuable animals can be managed differently than a common “low value” asset, like a sparrow. Look out for solutions that tout their cybersecurity prowess with threat alerts but without providing ways to resolve the issues.  

    Segment and Secure

    Finally, with devices visible and categorized, and associated risks identified, your next step is to secure them. Since you cannot deploy endpoint agents, devices need to be properly secured using appropriate segmentation policies. The key is doing this in an automated manner that is scalable and operationally feasible, and uses the infrastructure that the organization has already invested in—networking products, firewalls and network access controls (NAC).

    And, with apologies to Dr. Seuss, I’ll leave you with a final thought:

    It’s an IoT zoo, said the young CIO, but the people who run it, don’t know what to do. 

    If I ran this zoo, said the young CIO, I’d make a few changes. That’s just what I’d do. 

    The monitors, HVACs and all of that stuff, are not secure or well managed. It’s not good enough! 

    I’d ID and segment, assign policies, too. The old ways just don’t cut it. Time for something new!

  • NetFoundry Network Overlay Advances DevSecOps

    NetFoundry Network Overlay Advances DevSecOps

    NetFoundry, at the recent KubeCon + CloudNativeCon 2019 conference, announced the general availability of a developer platform designed to make it easier for organizations to bake a zero trust networking framework within their applications.

    Company CEO Galeal Zino said NetFoundry has created a network fabric overlay to manage and secure communications between endpoints and applications. Developers now can embed a programmable zero trust networking framework within their applications using a NetFoundry Developer Platform, which consists of software development kits, application programming interfaces (APIs) and connectors, said Zino. DevOps teams can either consume the entire NetFoundry Developer Platform or only the open source components that have been included.

    At the same time, NetFoundry announced it has joined the Cloud Native Computing Foundation (CNCF) to advance the adoption of open source networking services for containerized applications.

    NetFoundry

    Rather than having to become intimately familiar with networking protocols, Zino says NetFoundry provides a layer of abstraction using software to eliminate the need to rely on virtual private networks (VPNs) or network address translation (NAT) tools.

    As the number of endpoints and applications they need to connect to have significantly increased, DevOps teams are finding they need to master each type of dedicated network established for endpoints ranging from mobile computing devices to internet of things (IoT). That endeavor can be cumbersome at best. NetFoundry is making the case for a programmable network overlay that allows endpoints to access applications over public internet connections securely.

    As programmable overlays become more widely available, the rate at which network operations will be incorporated into best DevOps processes is likely to increase. Network managers will continue to set up the physical underlay that enables networking; however, how applications employ that underlay increasingly will be determined by invoking a programmable overlay. A programmable network overlay also provides the benefit of further separation of duties between DevOps teams and networking professionals in a way that doesn’t require networking teams to become deeply involved in every application development project.

    That approach should reduce significantly the amount of time now required to deploy or update a distributed computing application. DevOps teams today may be able to push code into production faster than ever. However, configuring the networking services those applications require remains a set of manual tasks that have become a significant bottleneck to making IT teams more agile.

    It remains to be seen to what degree programmable network overlays will provide something of a demilitarized zone (DMZ) between DevOps teams and networking professionals. Today most networking services are provided via either directly on top of networking infrastructure or using network overlays controlled by networking teams. But it still takes days to weeks for networking professionals to respond to requests for services from DevOps teams. It’s clear the way networking services are provisioned across the enterprise needs to change substantially.

    — Mike Vizard

  • What is so Special About AIOps for Mission Critical Workloads?

    What is so Special About AIOps for Mission Critical Workloads?

    As the wave of digitization sweeps more enterprises with each passing day, the threats posed to organizations, particularly IT organizations, have never been more complex and pressing. With cybercrime statistics, including those for more targeted crimes (such as phishing) pointing towards an alarming frequency of attacks, the stakes for securing enterprises have been higher.

    However, many IT organizations have been unable to smoothly transition into pushing the digitization of their organizations forward. This inability to support and drive digital transformation isn’t a result of a lack of effort on behalf of these organizations. Instead, it has everything to do with the unavailability of the proper management tools needed.

    Unfortunately, many IT organizations lack the tactics and tools needed to overlook the smooth shift to digitization on such a grand scale, which often leads to the degradation of critical business applications, along with IT slowdowns and outages. Luckily, however, artificial intelligence for IT operations (AIOps) arrives like a beacon of hope for revolutionizing IT application, along with increasing business agility.

    The Failure of Enterprise in Tackling the Burgeoning Complexity of IT Infrastructure

    A primary reason behind the ever-present issue of IT slowdowns in enterprises and organizations that is frequently overlooked is the fact that the customer-facing side of IT (applications) is growing increasingly complex with each passing day.

    As the increasing number of applications continue to occupy more and more space, the IT infrastructure grows into a vast and hybrid structure which often spans across multiple clouds on a grand scale.

    Although the vastness of the IT infrastructure is a byproduct of the digitization drive taking enterprises by storm, it is still worlds away from the security infrastructure of yesterday, which was much easier to manage and analyze.

    From the Internet of Things (IoT) connecting thousands of devices onto an organization’s network to complex issues such as bottlenecks, application slowdowns and outages, along with performance latency and the ever-present threat of phishing attacks via a free host website (000webhostapp, being the most commonly used host), organizations are just setting their systems up for failure at some time in the foreseeable future.

    Owing to the flourishing complexity of the IT infrastructure, an organization’s system fails to cope with new, dynamic workloads for any multitude of reasons. Usually, the system is utilizing extra resources or is under the influence of a recent addition to the system.

    In instances of outages or IT slowdowns, the pressure to fix the IT infrastructure falls on the IT team, who are tasked with the immense responsibility of analyzing and diagnosing the issues as they occur in real-time, along with coming up with a solution that satisfies customers and prioritizes the business aspect of an organization as well.

    Unfortunately, however, without access to the proper tools and techniques, the IT team can only conjure security patches that resolve the problem for the moment but fail to withhold security in the long run. Also, without the ability to effectively predict a pattern for the ever-present security threats, the IT team is operating on a whim rather than basing their solutions on the rationale.

    How Can AIOps Help the Situation?

    To leave the momentous challenge of perfecting an organization’s IT infrastructure solely on the IT team is not only outdated, but it is also impractical. Taking into consideration the complexity of the threats facing enterprises, a solution that arches above each aspect of cybersecurity in an organization should be implemented.

    Today, that solution arises in the shape of AIOps. The hybrid IT infrastructure has become too complex to be handled through traditional tools and tactics, which is why AI, along with machine learning and automation, has to step in to bridge the gap.

    Unlike other security strategies, AIOps integrates a wholly modern and unique approach, which allows for the AI to view systems in terms of business outcomes. Simply put, rather than analyzing and diagnosing identities, infrastructure and applications independently, the AIOps platform follows the path taken by the user into the complex IT infrastructure and back out of it.

    Ideally, AIOps platforms run automated investigations that derive the root cause of existing and recent issues on a regular basis. When it comes to managing a business-critical application, an AIOps platform can detect an unusual response within the system, whether it’s an anomaly in a workload profile or variant response to critical workload.

    Other benefits to incorporating AIOps as a security tool include tapping into the truly unique set of capabilities offered, including predictive capacity management and forecasting/predictive abilities. The predictive ability of AIOps allows for the AI to smartly notify IT teams about any attack or potential outage, or slow down, before they actually happen so they may act accordingly.

    By taking a different approach to the pressing issues faced by enterprises today, AIOps manages to do what several security strategies have failed to accomplish—provide organizations with an end-to-end, app-centric approach to security, which also takes into consideration the context at hand.

    Moreover, AIOps will push organizations to shift their focus from reactive problem solving and cause them to optimize their IT infrastructure on a more proactive basis. Fundamentally, AIOps provides IT teams with the necessary tools to diagnose and combat both internal and external threats to an organization’s security infrastructure.

    After the integration of AIOps within an organization’s infrastructure, enterprises can turn their attention into optimizing the balance of critical workloads, along with prioritizing business functions and improving applications, rather than worrying about security.

    What Hurdles Can Enterprises Expect with AIOps?

    Despite the countless benefits AIOps brings to the table, certain obstacles arise when it comes to the implementation of the security model into organizations.

    Perhaps the most apparent obstruction organizations have to deal with is the extensive amount of time investment AIOps requires. Like every other security tool centered around an AI or machine learning technology, time is absolutely pivotal for the learning to actually take place. A simple way to smoothen the transition, AIOps must be fed with data, statistics and analytics originating from multiple data centers.

    Another common issue that arises, mainly because of a lack of research, is when an AIOps platform fails to perform as per the specific requirements of an enterprise. Keeping this in mind, CIOs must voice their concerns about fine-tuning AIOps before committing to a vendor.

    AIOps abilities in performing an in-depth analysis into the IT and security infrastructure—within the context of the applications it performs—gives the unique chance to stay ahead of the threats they face.

    — Rebecca James

  • IoT Security Concerns

    IoT Security Concerns

    The Internet of Things (IoT) is being hailed as the next step in our technological development. It’s hard to argue with that. The abilities it provides are as captivating as they are numerous: smart cars and homes, automatized agriculture, advancements in medicine that help with after-stroke recovery and the list goes on.

    However, while the IoT is truly a huge topic nowadays, we must not let our fascination with it overcome us. It’s too easy to forget about security and privacy concerns when you hear about exoskeletons that can increase a person’s strength and dexterity–trust me, I know. But we can’t afford to forget about them.

    It does seem, though, in our pursuit of the interconnected device environment, the security of those devices was somewhat left behind. Let’s take a look at what the primary IoT cybersecurity hindrances are and what can be done to overcome them.

    When Security Struggles To Keep Pace

    One example of the quantity of devices outrunning their quality safety-wise is smart homes. They are very popular now, and according to the IDC forecast this trend is not going away:

    Data source: IDC Worldwide Quarterly Smart Home Device Tracker.

    While undeniably convenient, smart homes can pose a potential threat to their users. To do their job, they must collect information about those users. And the more interconnected the entire system gets, the more trouble can a single weak link cause.

    Take smart door locks, for example. Some of them come with facial recognition algorithms. That in itself is a pretty big privacy concern. Facial recognition can be used with an alarming accuracy to identify and track individuals. It can have various purposes, but very few of them (if any) are benevolent.

    To add to that, within the smart home system, a smart lock is going to be connected to other devices. Maybe it is safe from cyberattacks on its own, but is the smart thermostat safe? What about the smart water kettle? It only takes one vulnerability to get access to a lot of one’s private data.

    This risk can be somewhat mitigated by users taking certain precautions: installing AV software to protect their devices, updating the said devices regularly to prevent exploits, setting up a VPN on their routers to safeguard all of their internet traffic, etc. But how many users are actually going to go through with all this trouble?

    Physical Problems

    It should be noted that data breaches and cyberattacks are not the only threats the IoT faces. Some problems arise from poor design.

    For example, among other considerations presented in the June NIST publication, a non-descriptive appearance of an IoT device is mentioned. If it’s just a black box with no markings on it to indicate what software and hardware it runs on, updating it (as well as keeping track of its activities) becomes a very unpleasant chore. It is especially true if there are thousands of such devices located on the premises of a company.

    Alternatively, the support of a certain device may get discontinued well before the company plans to replace it. It is also possible the news of its discontinuation can be missed by the company, thus creating a possible vulnerability.

    Sheer Scale of the IoT Makes Threats Bigger, Too

    Another concern with the IoT is it’s so overwhelmingly difficult to maintain secure. If there is the need to install crucial updates on hundreds of millions of devices, the task becomes all but impossible.

    The hundreds of millions of devices example is not an exaggeration, either. Recently, several critical vulnerabilities were found in the VxWorks real-time operating system. Thankfully, this finding was not made by hackers but by a security firm. Some might think it should, therefore, be easy from now on for those vulnerabilities to be patched.

    Here comes the problem. There are 2 billion devices that run on VxWorks. Although not all of them can be affected by the vulnerabilities found, hundreds of millions still can. Moreover, there are difficulties in finding all the devices that need a patch, as it’s not obvious what devices even run on this RTOS.

    Many of the VxWorks devices are used in medicine. To update them, it is required they undergo the certification and testing processes, and that can take a long time. And before all the necessary testing is done, those devices remain vulnerable.

    Making the IoT Safer

    That’s why the approach to IoT device security must become more holistic than it is now. It is necessary for the IoT market itself to develop, as security and privacy issues were named one of the biggest problems hindering the implementation of smart devices.

    According to the recent Deloitte webcast, one of the biggest threats of the IoT today is security measures and systems are not incorporated into the core design of devices and networks. Another top risk is the lack of security awareness and training among engineers. Yet another one is the lack of proper incident response processes due to the wanting skill levels of security professionals.

    It’s obvious the IoT field can benefit immensely from the implementation of DevOps and, especially, DevSecOps. To ensure safety in the IoT, it is not enough to start worrying about it only after the fact, as an addition to other functions. On the contrary, it must become secure by design, and its safety must be a concern on all levels.

    — Dean Chester

  • How IoT Security Risks Derailing Robotics

    How IoT Security Risks Derailing Robotics

    Driven by advances in technologies such as artificial intelligence and deep learning, the mobile robots market is projected to grow to $54.1 billion by 2023 from $18.7 billion last year, according to Markets and Markets. But for robotics to progress, security for the internet of things (IoT) needs to be addressed fast, before the reputation of the entire industry suffers a permanent setback.

    Every industry segment has a journey to maturity that involves ramping up how seriously it takes security. For robotics, that time has come. Failing to start robotics projects on the right software foundations will see confidence continue to drop, impeding the rate at which new solutions are created.

    The future of robotics rests firmly on the shoulders of the IoT. Robots act as one part of intelligent ecosystems—they depend on IoT to link various sensors and smart meters, and pass data to and from third parties.

    The self-driving car, for example, is a robot orchestrated by various smaller devices and smart sensors. In fact, robots are being created to tackle every conceivable problem. Take the Google-funded RangerBot, an underwater machine designed to track down a species of starfish responsible for coral reef destruction, or Small Robot Company, a startup tackling farming deficiencies with bots that autonomously feed, seed and weed arable crops.

    However, while IoT is an established concept and connected devices are now mainstream, its full potential has not been realized in part because of security concerns. Ninety percent of consumers lack confidence in connected devices, according to a recent survey. These concerns are more than valid, as nearly half of companies are unable to detect when a breach occurs, and only 15% of budgets are earmarked for IoT security.

    With IoT security a lingering weak spot, one major attack within robotics, could have a domino effect on the entire industry. Add to this the verticals that robots are beginning to infiltrate—health care and agriculture, for example—and the threat becomes immediate and very real.

    Rising levels of sophistication within robotics go hand in hand with more targeted and damaging attacks. For example, telesurgery uses robotics to help surgeons perform procedures remotely. A malware bug in this scenario could mean the downing of tools, threatening the patient’s life.

    Researchers at Brown University proved how easy it is to hack robots. The industry simply will not be sustainable without the backing of a secure, connected IoT network.

    Robot manufacturers, therefore, must build with a security-by-design mindset. This begins by selecting a robust operating system from the outset—secure now, but also ready for future market demands.

    Hackers are constantly evolving their activities and businesses must be flexible in their approach to security, shedding the old hardware-centric view of IoT security.

    Software no longer can end when a device is shipped. It must align to the lifespan of a robot and be able to update whenever there is a potential flaw. The world of mobile took many years to get to grips with this. Robotics and IoT developers should learn from their mistakes.

    One way developers can safely build and secure software is through snaps, containerized software packages on an open platform for building and publishing applications to an audience of millions.

    If a security vulnerability is discovered in the libraries used by an application, the app publisher is notified so the app can be rebuilt quickly with the supplied fix and pushed out. This allowsr developers to stay focused on innovation while ensuring the longevity of the robotics hardware.

    It remains unclear where the onus lies for IoT security, with nobody holding anyone else to account. Market constraints often prevent device makers from putting more budget than what is necessary into design security, when there is so much pressure to innovate ahead of competitors.

    These issues need to be solved. Robotics has too much potential to let security concerns stunt their growth.

    — Tom Canning

  • Akamai Extends Reach to the IoT Edge

    Akamai Extends Reach to the IoT Edge

    Akamai today unveiled a strategic initiative to extend the reach of its global network out to applications deployed on the network edge.

    Announced at the Akamai Edge World conference, the Edge Cloud portfolio will consist of a mix of existing, new and forthcoming offerings. In terms of new offerings, Akamai launched IoT Edge Connect, which provides access to the Message Queuing Telemetry Transport (MQTT) protocol that gives internet of things (IoT) applications access to a publish-and-subscribe service. Akamai claims IoT Edge Connect will scale to support hundreds of millions of endpoints and is capable of processing 10 times more messages than other IoT or in-app messaging cloud solutions. Those capabilities not only will optimize data delivery, but also should also reduce the amount of power devices will need to send messages, according to the company.

    Scott MacGregor, senior director of engineering at Akamai, said IoT Edge Connect will join Akamai Over The Air (OTA) Updates, an existing service for updating applications using a wireless cellular network, in the Edge Cloud portfolio. Those two offerings will be joined in the future by a key-value store that will make it possible to store data on a local IoT gateway and a tool for running functions on an IoT endpoint, he said.

    Akamai intends to provide the same capabilities it makes available to web applications to a new generation of edge computing applications that need access to a global network, MacGregor noted. In some cases, the data those applications need to access will be stored on local gateways. In other cases, the data being accessed will be stored within the network managed by Akamai. DevOps teams tasked with building IoT applications would view the Akamai network as just another platform they need to push code to from whatever continuous integration/continuous deployment (CI/CD) platform they choose to employ, he said.

    In general, MacGregor said many organizations underestimate the challenges associated with building and deploying distributed IoT applications at unprecedented levels of scale. IoT applications that span global networks are challenging to build, and the processing occurs at the edge, on local gateways and in the cloud.

    Akamai, of course, is not the only provider of a global network looking to entice organizations to leverage their infrastructure to deploy edge computing applications. Everyone from carriers including AT&T and Verizon to cloud service providers such as Amazon Web Services (AWS) and Microsoft are making similar cases. It’s too early even to hypothesize which platform providers might ultimately triumph. Akamai, however, is counting on its relationships with developers to become an edge computing force to be reckoned with, said MacGregor.

    Akamai made its mark in the enterprise by providing a global content delivery network (CDN) that web developers leverage to extend the reach of their applications by leveraging cache memory Akamai makes available on a global network. Since then, the company has been extending the service to include a range of security services that isolate web applications from various potential threats. If Akamai has its way, those same services soon will be pervasive across a broad range of edge computing applications.

    — Mike Vizard