Category: Blogs

  • Low-Code Providers Continue Enhancing Their Development Platforms

    Low-Code Providers Continue Enhancing Their Development Platforms

    Enterprise low-code development continues to grow in popularity as software vendors continue to unveil tool enhancements designed to help business users and non-developers build functional applications and business processes.

    The help from low-code platforms (and other platforms that are integrating low-code capabilities) couldn’t come at a better time, as enterprises continue to struggle to digitize operations and dig through their application backlogs.

    Consider open source digital process automation platform Bonitasoft and its recent increased support for low-code development and what the company promises to be accelerated user interface development for more customized user experiences. The platform (including a new Bonita Cloud edition) helps to enhance collaboration between professional developers and so-called citizen developers, according to the company.

    Recently, low-code development platform provider OutSystems announced it is adding new artificial intelligence (AI) and machine learning capabilities into its platform. The company said the enhancements provide customers the ability to help automate the creation of self-service portals, respond to text and voice queries and improve customer service.

    OutSystems said citizen developers now can more easily build communication channels into their apps and better utilize virtual assistants such as Alexa, Google and Siri, as well as common chatbot platforms. The company claimed developers don’t need any specialized development skills or knowledge in data science to use these features. “These new, high-level components package everything organizations need to implement rich use cases from end to end. As a result, many more companies can easily adopt AI and machine learning to positively impact their business,” said António Alegria, OutSystems’ head of artificial intelligence.

    According to the research firm Gartner, by next year, consumers will manage 85% of their relationship with enterprises without having to interact with a human. However, despite the use of AI having tripled over the past four years, two-thirds of organizations have yet to deploy AI in some form, it noted.

    According to Research and Markets, the global low-code development platform market size will reach just over $27 billion by 2022, up from $4 billion in 2017 and a 44% annual growth rate.

    According to the research firm, it is the increased demand in software automation and innovative applications and the ease of development of web and mobile apps that are driving enterprise demand for low-code development. “Moreover, the cloud-based deployment mode is gaining high traction in the market, as it requires less capital investment, helps decrease the operational and maintenance costs, and reduces the management’s efforts,” the research firm said.

    While many analyst market predictions do fall short, as long as low-code platforms reduce costs and help organizations move forward rapidly with their digitization efforts, low-code development is here to stay and will continue to grow.

    — George V. Hulme

  • How DevOps Training and Certification Benefits the Team

    How DevOps Training and Certification Benefits the Team

    Cisco Systems recently announced sweeping changes to its training and certification programs to increase the real-world value of both. Cisco’s move demonstrates a trend by organizations that provide training and certification to place more value on the practical aspects of educating technology professionals—which, in turn, should have a major impact on those looking to build DevOps teams.

    “Advances in network technologies have enabled new applications and business models—converged IP networks enabled voice over IP, 3G networks enabled mobile applications and 4G networks enabled mobile video,” said Susie Wee, senior vice president and CTO of DevNet at Cisco Systems. “DevOps has become a key factor for bringing those new networked applications to life. Training and certifications for network professionals and software developers have become a must. The goal here is to bring enhanced software skills to networking, enabling application developers to write applications that leverage the full capabilities of the network.”

    Cisco’s realization that real-world knowledge brings demonstrable value to businesses has culminated in new DevNet Certifications, which are designed to demonstrate an individual’s ability to bring software skills to evolving network technologies. “The only way to fully leverage the capabilities of the network is to build DevOps teams with both networking and software skills that can address the intricacies of both software-defined networking and physical networking solutions,” Wee added.

    Cisco is not the only company pursuing a change in training and certification processes. Industry group CompTIA recently revamped its certification programs. For example, the latest version of the CompTIA Linux+ exam has been redesigned to validate the competencies and skills required of early career IT professionals supporting Linux systems.

    “For certifications to have real value today, people must immerse themselves in the technology,” noted James Stanger, CompTIA chief technology evangelist. “The new Linux + certification uses performance-based testing that presents candidates with real-world scenarios, meaning that achieving certification demonstrates the ability to function in the real world.”

    CompTIA may very well be one of the leaders in the movement to bring real-world relevance to the certification process. The company has been using performance-based testing and has been embracing certification pathways to build teams. “For DevOps teams, critical skills, including project management, both agile and waterfall, are important. Developers will need to know the operating systems they are developing in, so they’ll need to understand Windows and Linux,” Stanger said. “The idea is that for DevOps, you need to get deep into the guts of operating systems and understand them well. You can specialize in one area, but you’ll also need to understand databases, relational databases and object-oriented databases.”

    Cisco also understands the importance of educating DevOps professionals. “Our new Cisco Certifications, with new DevNet Certifications, are designed for training and certifying network professionals and software developers, so they can bring software skills to networking,” Wee noted. “This new education process teaches application developers how to write applications that leverage the full capabilities of the network, and it helps build IT teams with network skills and expertise and software skills and expertise so they can leverage the full capabilities of the network, helping to support the DevOps process.”

    Cisco is also investing in the idea of building a community in the form of the company’s DevNet offering. DevNet was created some five years ago to help network engineers and application developers take full advantage of the revolutionary changes shaping the industry. The company is now focusing its efforts on what it sees as its customers’ biggest problem—network automation—and has created the DevNet Automation Exchange, a community-based developer center where networkers and developers can learn to “walk, run and fly” with network automation using Cisco’s products and the full capabilities of the new network.

    According to Wee, those three processes can be broken down into:

    • Walk: Get visibility and insights into their networks in a read-only way. This enables use cases such as gathering telemetry and insights from running networks and performing audits to ensure the ongoing security of the network.
    • Run: Activate policy and intent across different network domains. This enables use cases such as providing self-service network operations that comply with security policies and operational guidelines.
    • Fly: Proactively manage applications, users and devices with DevOps workflows. This enables use cases such as deploying applications in continuous integration and continuous delivery (CI/CD) pipelines while configuring the network in accordance with new application policies.

    Wee noted Automation Exchange has been seeded with more than 50 code repositories, many contributed by Cisco’s engineering teams and SEs. Now, she said, the company is inviting DevNet community members to submit code that solves their use cases.

    Updated certification and training resources from the likes of Cisco and CompTIA will go a long way to helping build DevOps teams that can hit the ground running.

    — Frank Ohlhorst

  • AI for IT Operations: All It’s Cracked Up To Be?

    AI for IT Operations: All It’s Cracked Up To Be?

    Artificial intelligence for IT operations (AIOps) is becoming a critical tool for organizations attempting to bring automation quickly to network management and IT problem resolution. However, many organizations are still unsure how to deploy AIOps for the most value and to net the full, promised results. Perhaps the challenges come from not looking beyond data silos, or perhaps the problems can be attributed to a lack of understanding AIOps’s full potential in the enterprise.

    Enzo Signore, chief marketing officer at FixStream, lends credence to the problem of siloed information. “Despite continued investments in system resources, IT cannot holistically see what’s in their physical and virtual infrastructure,” he said. “And without a clear view of the entire IT environment and the ability to make sense of the mountain of data being served up by various system tools, Ops teams can’t figure out what’s wrong or how to fix it.”

    In essence, for AIOps to be successful, IT must be able to access that siloed data and then be able to process that data to derive actionable insights, exactly what AIOps is meant to do. Yet, complexity still seems to be one of the major challenges of bringing a holistic approach to managing networks and resolving problems. 

    “IT teams are bogged down by the sheer complexity of today’s hybrid, dynamic IT environments,” Signore noted. “Along with steep learning curves and lightning-fast changes to new technology, IT departments must cope with soaring consumer expectations, supporting legacy systems, lack of skilled talent, disparate tool sets and opaque physical and virtual IT infrastructures. These factors complicate IT staff’s ability to oversee operations and optimize system performance.”

    Naturally, companies such as FixStream have a major stake in the AIOps game; the company offers numerous AI solutions that promise to modernize IT operations and bring AI into the realm of IT operations. However, understanding what AIOps is all about is one of the first hurdles to overcome when contemplating the technology. Gartner defines AIOps as platforms that enhance IT operations through greater insights by combining big data, machine learning and visualization. “IT leaders should initiate AIOps deployment to refine performance analysis today, and as an augment to IT service management and automation within the next two to five years,” advised Pankaj Prasad, senior principal analyst at Gartner.

    Gartner defined some best practices that businesses should adopt, which include: 

    • Deploy AIOps by adopting an incremental approach that starts with historical data and progress to the use of streaming data, aligned with a continuously improving IT operations maturity.
    • Select platforms that enable comprehensive insight into past and present states of IT systems by identifying AIOps platforms that are capable of ingesting and providing access to text and metric data.
    • Deepen the IT operations team’s analytical skills by selecting tools that support the ability to incrementally deploy the four phases of IT operations-oriented machine learning—descriptive, diagnostic, proactive capabilities and root cause analysis, to help avoid high-severity outages.

    Best practices aside, FixStream’s Signore opined that there are some other challenges that must be addressed. “Without the foundational capabilities of accurate discovery, contextualization and full-stack correlation, AIOps can become severely limited,” he said. “The lack of those features have become the big elephant in the room that everyone is not addressing, and it’s holding back the advancement of AIOps and machine learning for many companies.”

    Simply put, when AIOps is not fully deployed, important insights may go unnoticed and leads to data remaining in silos. “Companies are getting all this data, but it’s not being properly processed and correlated, and it’s going to waste,” he said.

    It is those types of deployment issues that are lending credence to AIOps not being as effective as promised. “AIOps is a multi-layered platform whose capabilities should include efficient data collection at big data scale, correlation across the collected data, machine learning, analytics and visualization,” said Bishnu Nayak, FixStream CTO.

    Businesses discouraged by the initial ROI of AIOps should take a long, hard look at their implementation strategy and take into consideration what their data sources are and how they are applying analytics, Nayak said. “Done right, an AIOps implementation can lead to a decreased mean time to remediation and better proactive problem-solving. By increasing system availability and responsiveness, AIOps can enhance your digital business operations and improve profitability.”

    — Frank Ohlhorst

  • 6 Traits That Define DevSecOps

    6 Traits That Define DevSecOps

    How do we define DevSecOps? A combination of DevOps and security is readily apparent, but the philosophy goes much deeper. In a recent eBook, The State of DevSecOps, we asked industry experts to define what DevSecOps meant to them. Below, we’ve condensed their answers into five core attributes.

    Following these principles, CIOs or CTOs now have a DevSecOps doctrine applicable to nearly any software development and release environment.

    Security Automation

    DevSecOps emphasizes security objectives within the automation processes. Ben Newton, director of product marketing and evangelism at Sumo Logic, defines DevSecOps as first making security requirements and objectives a clear part of the continuous integration (CI) and continuous deployment (CD) cycle.

    Culture of Security

    DevSecOps establishes a team culture that embraces security concerns. As stated by Ben, a security team must provide “clear guardrails for developers as to what is fair game and what is not appropriate from a security perspective.” Building security expertise to integrate security into the entire DevOps lifecycle is critical.

    De-Siloing IT

    DevSecOps is about eroding boundaries. Just as DevOps has eroded the traditional separation between software engineering and IT operations teams, “DevSecOps further erases the walls between the DevOps team and IT Security,” said Tim Jarrett, senior director of product management at Veracode. “DevSecOps is about building a bridge between the security and DevOps teams,” echoed Dan Hubbard, chief product officer at Lacework.

    Security Shifts Left

    DevSecOps places security earlier on in the development process. IT security is traditionally viewed from a risk avoidance and compliance standpoint. Rather than viewing security as a gate, Tim noted that within DevSecOps, “security is better positioned to integrate earlier in the development cycle where they can actually make a difference.”

    Security Enables, Not Stalls

    DevSecOps supports, not stalls, agile development. DevSecOps doesn’t have to be sluggish. As Dan described, DevSecOps must “support the need for DevOps to move fast, but in a way where security is not ignored.” By embracing a security-as-code mindset and involving practices such as automated threat detection, agility is not sacrificed.

    — Bill Doerrfeld

  • Linus Torvalds Sees Lots of Hardware Headaches Ahead

    Linus Torvalds Sees Lots of Hardware Headaches Ahead

    Linux founder Linus Torvalds, today at the KubeCon + CloudNative + Open Source Summit China conference, warned attendees that managing software is about to become a lot more challenging, largely because of two hardware issues that are beyond the control of DevOps teams.

    The first, he said, is the steady stream of patches being generated as new cybersecurity issues related to the speculative execution model that Intel and other processor vendors rely on to accelerate performance. That model is the root cause of malware such as Spectre and Meltdown that have roiled the IT industry. Additional bugs in speculative execution with colorful names such as Fallout and ZombieLoad are showing up more frequently. Each of those bugs requires another patch to the Linux kernel that, depending on when they arrive, can require painful updates to the kernel, Torvalds told conference attendees.

    Short of disabling hyperthreading altogether to eliminate reliance on speculative execution, each patch requires organizations to update both the Linux kernel and the BIOS to ensure security. Turning off hyperthreading eliminates the patch management issue, but also reduces application performance by about 15 percent.

    The second major issue hardware issue looms a little further over the horizon, Torvalds said. Moore’s Law has guaranteed a doubling of hardware performance every 18 months for decades. But as processor vendors approach the limits of Moore’s Law, many developers will need to reoptimize their code to continue achieving increased performance. In many cases, that requirement will be a shock to many development teams that have counted on those performance improvements to make up for inefficient coding processes, he said.

    In the meantime, Torvalds noted updates to the Linux kernel are still coming at a rate of every three months, and the Linux team is basically working on a six-month planning cycle—there is no master five-year plan the Linux team is working from. Roughly 1,500 developers work on contributions to the Linux kernel, with 100 maintainers overseeing the implementation of those contributions.

    Naturally, cybersecurity patches at the kernel level have significant implications for all of DevOps. Changes to the kernel need to be absorbed by all the various distributions of Linux, which in turn impacts all the stacks of software that depend on Linux. Jim Zemlin, executive director for The Linux Foundation, said that in the wake of the rise of these hardware issues and previous cybersecurity issues involving open source software such as the Heartbleed vulnerability, cybersecurity is the top priority for The Linux Foundation. As part of that effort, The Linux Foundation is researching various DevSecOps approaches to better securing the global open source supply chain, he said.

    In the meantime, organizations large and small alike will need to up their DevSecOps game significantly if they want to continue to push application performance limits.

    — Mike Vizard

  • 27-Factor Assessments Lead to Success With DevOps

    27-Factor Assessments Lead to Success With DevOps

    October 2019 will mark the 10th anniversary of the first DevOpsDays, where the term “DevOps” began to catch on. In the world of information technology, 10 years is a long time and it is quite evident based on the amount of change that has transpired since then. To name a few, we have seen the maturing of CI/CD automation and many innovations such as application release automation, containers, cloud infrastructure orchestration, DevSecOps, DevOps database, DevOps governance and micro-services.

    These innovations have become part of “mainstream DevOps.” This evolution is continuing with AIOps, machine learning, value stream management and others. Each of these innovations has made DevOps not only more powerful but also more complex.

    As a consultant working on DevOps projects through their life cycle, I have learned that complexity can plague the success of DevOps within an organization. Complexity cannot be avoided, as DevOps is complex and will likely continue to be. However, the key to avoiding failure through your DevOps journey is to engage the complexity by using DevOps tenets to implement DevOps. Do not try to boil the ocean. Instead, at each leg in the journey, take inventory of where you are in terms of current goals, state and best practices. Fine-tune your direction and build your solution using proven continuous delivery methods.

    The 27-Factor Assessment Model

    A comprehensive yet efficient assessment of your current state is key for ensuring complexity has not gotten out of hand and the organization is focused on success criteria that meet the needs of the business.

    I use a 27-factor assessment model. The factors are the cross-product of current best practices for three dimensions (people, process and technology) with nine pillars.

    A Scope of the 9 Pillars

    Leadership: Gain insight and understanding of your leadership practices and how leadership can improve DevOps adoption and performance.

    Culture: Identify opportunities to improve cross-functional collaboration and communication across your organization.

    Application Development (or Design for DevOps): A practical analysis of application development practices identifies improvements for your DevOps performance.

    Continuous Integration: Analysis of branching and software integration workflows and tools identifies bottlenecks and improvements for builds and packaging processes.

    Continuous Testing: Analysis of end-to-end software testing, verification workflows and tools identifies bottlenecks and improvements for accelerating testing while improving the coverage and quality of tests.

    Infrastructure on Demand (or Elastic Infrastructure): Analysis of systems and services for orchestrating and hosting applications and DevOps workloads provides insights to improve performance and utilization of resources.

    Continuous Monitoring: Analysis of end-to-end monitoring workflows and tools for applications, releases metrics and infrastructure provides improved visibility for all business and technical stakeholders.

    Continuous Security: Analysis of security practices and tools identifies opportunities to integrate security practices into the continuous delivery pipeline.

    Continuous Delivery/Deployment: Analysis of delivery and deployment practices identifies improvements for safer, faster and more efficient releases.

    Each combination of pillar and dimension has associated best practices used to score relevance and current state relative a DevOps goal agreed by the organization. Here is an example of the continuous security pillar.

    The 27-factor assessment for an application is an important input to a future state value-stream map workshop. The value-stream map is then transformed into a road map and implementation plan.

    This assessment approach is thorough and yields results that are usually accepted by stakeholders because they are involved in the process at each step. The result is aligned to their priorities and goals and the solution road map is directly traceable to stakeholder inputs. The approach is flexible enough to evolve over time and can be customized to suit the priorities of an organization. For those that argue that 27 factors are too many and too complex, I must say the complexity of DevOps itself requires a comprehensive assessment approach.

    Conclusion

    In this article, I described a comprehensive, efficient and evolvable assessment approach that uses 27 critical success factors for assessing DevOps applications. While DevOps offers immense value for software development, delivery and deployment, a rigorous and thorough assessment with up-to-date best practices are essential to accomplish DevOps goals. Each organization is different and has different DevOps goals and requirements. The changes to the three dimensions vary according to the results of each DevOps assessment.

    — Marc Hornbeek

  • HPE Extends Hybrid Cloud Computing Strategy

    HPE Extends Hybrid Cloud Computing Strategy

    Hewlett-Packard Enterprise (HPE) today advanced its hybrid cloud computing strategy by announcing at its HPE Discover 2019 conference an alliance with Google to embrace Kubernetes in hybrid cloud computing environments and then extending the reach of its software-defined infrastructure for building private clouds to legacy ProLiant servers.

    Lauren Whitehouse, director of marketing for the software-defined and cloud group at HPE, said the HPE Composable Cloud now extends beyond new ProLiant servers to include everything from legacy hardware to cloud computing platforms running virtual machines or as bare metal servers optimized for Kubernetes.

    To achieve that latter goal, HPE will make it possible to deploy Google Anthos, a previously announced framework for delivering cloud-native computing services across public clouds and on-premises IT environments, on HPE-managed platforms.

    HPE is giving customers the option of deploying configuring local servers with virtual machines with either a VMware vSAN storage software or the HPE SimpliVity hyperconverged infrastructure platform. Additionally, customers can choose to deploy Kubernetes on those platforms or run Kubernetes on a bare-metal server. On top of those stacks, HPE also embeds the HPE OneView IT infrastructure management and HPE Composable Fabric networking solution to create what the company calls a composable rack environment.

    Finally, HPE announced it will extend the reach of the HPE InfoSight artificial intelligence engine, which it gained for storage environments when it acquired Nimble Storage, to the rest of its data center portfolio.

    Whitehouse said that, by extending the reach of its composable computing strategy to include legacy servers, HPE seeks to make it easier to modernize on-premises IT environments within the context of a larger hybrid cloud computing strategy.

    One of the primary reasons so many workloads are being deployed in the cloud is because of the inherent flexibility of the IT environment. HPE is investing in higher levels of infrastructure abstractions to enable an equivalent amount of agility to be injected into on-premises IT environments. Those efforts will then make it easier for organizations to extend best DevOps practices across a hybrid cloud computing environment, said Whitehouse. The company is now removing the objection by organizations to have to implement a forklift upgrade across their entire on-premises IT environment to achieve that goal, she added.

    It’s not immediately clear who will manage what in this brave new world of hybrid cloud computing. Application developers have been exercising a lot more influence over platforms, while advances in automation appear to be heralding a consolidation of management functions within the local data center. As site reliability engineers, or so-called “super administrators” capable of managing compute, storage and networking infrastructure continue to emerge, the silos around job functions in the enterprise were built are breaking down. In fact, the more organizations embrace DevOps best practices, the faster consolidation of job functions is occurring.

    In the meantime, whoever provides the infrastructure that remains in an on-premises IT environment had better be able to enable local IT teams to be just as flexible as any cloud service provider an application developer is likely to encounter.

    — Mike Vizard

  • Lessons Learned From the Salesforce Outage

    Lessons Learned From the Salesforce Outage

    Everyone has bad days. Every company has been through some kind of outage due to a buggy database deployment. Even the best of the best, with highly trained staff, world-class best practices and well-thought-out processes make mistakes. On May 17, Salesforce.com had a bad day.

    What Happened?

    The company deployed a faulty database change script that broke permission settings in production and gave users read and write access to restricted data. This opened the door for an unauthorized employee to steal or tamper with the company’s data. As a result, Salesforce needed to take large parts of its infrastructure down to find and properly fix the issue. The outage lasted 15 hours, 8 minutes. According to Gartner’s cost-of-downtime formula ($5,600/minute), this outage cost approximately $5 million. Plus, since so many companies rely on Salesforce, it was a very visible and embarrassing outage. (Just take a look at #SalesforceDown and #permissiongeddon on social media.)

    Salesforce had to shut everything down because of the way databases work. It’s not as easy as pulling a single application. Who knows how many Salesforce employees worked like mad to take the whole database down, find the offending database script, and restore everything—all because of one change script. That’s not a fun way to spend a weekend.

    What Does This Tell Us?

    Historically, Salesforce customers have experienced very little disruption in service. On the day of the outage, many loyal customers were tweeting about how rock solid the service has been, and that’s impressive.

    That being said, this outage should be a wake-up call for users to realize their dependency on their platform, which has become a more integral part of how we conduct business. I’ve heard anecdotes of entire offices being unable to complete work that Friday.

    The customer reactions show that they clearly have their stuff together over at Salesforce. What this outage shows is less about any shortcomings of this company specifically; but rather that everyone has blind spots, no matter how robust the testing process is.

    Lessons for IT professionals:

    • Don’t forget the database. Unfortunately, this problem is all too common. There are countless cases of a database change script being executed in production and causing unexpected issues. This indicates that the database is often the forgotten part of the software test and release cycle. Unless companies start to seriously consider the database when it comes to change management, things like this will continue to happen.
    • Automate everything. Manual efforts fail. Humans make mistakes. Companies such as Salesforce that handle sensitive customer data should not put it on the internet unless they have automated every aspect of the system, including the database. Companies need a robust DataOps process, one that includes production-like data and automates the validation database changes.

    Lessons for end users:

    • Establish a continuity plan. Organizations that depend on systems such as Salesforce need to have a business continuity plan to continue operations if they go down. This includes syncing Salesforce tasks and calendar with Office365, Exchange or Google Apps. However, since Salesforce has become the system of record for most companies that use the technology, having a backup of the data will be very difficult—after all, the point of a company using the platform in the first place was to avoid hosting its own data.
    • Demand accountability. Additionally, users can and should demand more accountability from software vendors. This can take the form of demanding a refund, but also customers need to speak to their account manager to understand what steps Salesforce is doing to make sure this does not happen in the future. It’s 2019 and companies update software all the time without taking down their production systems at the end of a quarter. Moreover, companies also can demand that companies don’t change production systems, outside of necessary security issues, during business hours.

    The bottom line is that, while the mistakes that led to the Salesforce outage are very costly and highly visible to customers, they are also entirely preventable.

    — Robert Reeves

  • The Value of Visual Data in Decision-Making

    The Value of Visual Data in Decision-Making

    Gone are the days when a gut-feeling was a major decision-making driver in business. Instinct has ruled business leaders’ mind for a very long time, but as companies expand their business globally, instinct should give way to data as the best measure to remain competitive.

    We live in a data-driven world. Today, number-crunching algorithms decide who we should hire, where we should invest and even who we should date. In fact, data-driven organizations that harness insights to create a competitive advantage are growing rapidly—at an average of 30% annually. What’s more, data-driven organizations are on a track to earn $1.8 trillion by 2021.

    Data in Businesses

    Technology is tucked inside every nook and corner of modern business. Smart leaders use data generated to understand what’s happening in the organization, and this analysis helps them bring agility to their business.

    Top companies around the world use data to add value to their business. They gain a strategic advantage over their competitors putting data—not instincts—to good use.

    Being data-driven offers multiple advantages:

    • Data is the new gold. A long-term relationship with data helps organizations set trends.
    • Data-driven decisions offer a better customer experience. Data reveals customer patterns and their journey with products.
    • Data-driven organizations respond better to market demands with innovative solutions.
    • Data-driven decisions hone key business areas such as finance and operations.

    Data offers insights and executives turn those insights into key decisions. But you cannot ignore that fact that data is complex, let alone its analysis. We’re all familiar with excel sheets full of thousands of rows and hundreds of columns of numbers. So, how can this turn into insights? That’s where data visualizations come into action.

    Data Visualizations Make Hidden Insights Obvious

    Interpreting a voluminous dataset for actionable insights is tough. Data visualizations make voluminous data accessible and comprehensive. How?

    Data viz, as it is often called, is the transformation of any unstructured data into visuals. Visuals add a component to human understanding.

    For example, the World Bank releases its doing business project data every year, providing insights about countries with conditions for establishing businesses. It was launched in 2002 to measure the regulations applied to various small and medium-size organizations.

    A total of 190 economies were surveyed on 12 topics including employing workers, tax benefits and resolving insolvency. A visual summary of data on doing business in 2018 was produced to make these crucial insights digestible for businesses, which then could put them to use.

    The data science company that created the visualization took the data and plotted it on a world map. It added shades from red to green to indicate the least and the most favored economies for doing business. The data is made easy, appealing and comprehensive. Any business manager or executive can easily identify emerging economies for investment.

    Using visual data, insights such as the best and worst country for doing business and economy rankings are now obvious. Furthermore, companies can turn these insights into key decisions regarding expanding business across boundaries.

    Take a look at the example above: The United States is an economically powerful country; however, data tells that New Zealand tops the list of economies with ease of doing business in 2018 with 86.55 DTF*. Many countries, including Singapore, Demark, Korean Republic and Hong Kong, also rank favorably in the index.

    Three major reasons that data visualization can be crucial for any data-driven organizations are:

    1. Data visualizations amplify a story with pictures and visuals. Its impact on the audience is more powerful than bland numbers and text. Moreover, human minds are hardwired to remember visuals. Data visualizations tap into pictorial strengths to drive executive decision-making.
    2. Data visualizations make difficult data comprehensible. Business executives and key decision-makers are not masters in every field. They need comparative measures to drive their decisions. Data visualizations provide just that.
    3. Data visualizations help in decision analysis. It offers a platform to interact with the facts. Jeff Bezos said that not all the decisions are made by factual analysis. But whichever decisions can be made on facts, should be.

    Conclusion

    Data should be an influence to any major business decision. And so, data visualization is a powerful tool to bring dramatic changes to organizations. It can provide answers to many key questions, and make the data visually appealing, easy to play with and interesting to explore. CEOs and managers should emphasize the importance of the democratization of their data to add value to their processes.

    *DTF: Distance to Frontier. It is a score between zero to one hundred, which illustrates the worst and best performance of an economy observed on each doing business parameter.

    — Naveen Gattu

  • Portable Security Policies: A DevSecOps Primer

    Portable Security Policies: A DevSecOps Primer

    Protecting critical data and applications is a challenge under any circumstances, but it’s especially daunting when resources reside in the cloud. Most organizations today operate a significant portion of their workloads in the cloud, which adds to the complexity of the security problem—a security team can’t fully control cloud environments but is responsible for securing workloads and applications running there.

    Cybercriminals are exploiting the situation. They’re becoming more aggressive and ingenious in their efforts, taking advantage of the fact that there is confusion about who is responsible for which aspects of security under the Shared Responsibility Model. Adding to the chaos is the differentiation between cloud providers’ security offerings and capabilities. Quite simply, in most cases, cloud providers are responsible for the security of the cloud and consumers are responsible for security in the cloud, meaning that security and networking teams still need to ensure their organizations’ workloads and applications are free from malware or other tampering.

    To accomplish this, security and networking teams can’t rely solely on firewalls, threat detection and vulnerability patching to secure vital digital assets. Security tools developed for traditional data centers are not effective at securing workloads in the cloud due to the cloud’s dynamic nature. Security and networking teams must rethink their approach.

    Unfortunately, many organizations are still relying on old and ineffective strategies—further hardening the perimeter, investing in additional threat detection and adding new tools and controls that focus on identification rather than prevention. This security approach has its place, but it does nothing to prevent malicious actors from moving laterally across the network once they achieve a foothold, which leaves cloud-hosted apps and workloads extremely vulnerable.

    Instead, security teams need to enable zero trust in cloud environments, which treats all internal communications as untrusted by default. With zero trust, only authorized applications and services are allowed to send and receive communications, and only in specific ways governed by the principle of least privilege.

    The Second Layer

    Traditional tools aren’t effective in enabling zero trust in the cloud because security and ops teams have a very limited ability to manage all layers of the cloud’s open systems interconnection (OSI) model. Specifically, the lack of Layer 2 controls in infrastructure-as-a-service (IaaS) environments makes tools developed for discrete networks all but useless for locking down ports and controlling or scrutinizing IP addresses.

    Even if an organization manages to implement these tools in the cloud, it cannot provide the level of granularity required to stop malicious lateral movement. For example, when on-premises tools are repurposed for cloud environments, they usually rely on subnets to define the boundaries of communication. Because cloud subnets are designed to handle elastic workloads, they need to be far larger than those in on-premises environments. As a result, cloud workloads are more exposed than is necessary.

    Securely migrating workloads and applications to a cloud environment is a huge and cumbersome job when relying on traditional tooling. The best way to make workloads portable and secure is to decouple workload protection from the underlying infrastructure. In this way, organizations can be certain that any policies applied on-premises can migrate to the untrusted environment of the cloud, without the complexity of mapping changing network addresses, writing policy exceptions or losing fine-grained control during the process.

    Decoupling workload protection from the network requires abandoning a network address-based approach in favor of one based on identity. By using the immutable properties of workloads, security teams can create cryptographic identities for applications and services, which then can be used to determine what is allowed to send and receive communications. Not only does this model provide stronger security, but it also works regardless of where applications are located, because these identities are unaffected when network elements change. What’s more, they can be constructed to tolerate upgrades. By building identity-based policies, security teams can create microperimeters around applications that follow workloads wherever they go, and the policies verify communication across boundaries every time an application attempts to communicate.

    Implementing network-agnostic policies doesn’t just harden security. Software developers benefit as well. Without the roadblock of translating application-speak to network-speak, developers can build software and applications in any environment favorable to their workflow while defining policies to protect their work. Once the software is built, they can securely deploy the finished product to the production environment—even if it is hosted by a third party.

    No organization should have to compromise security to benefit from the efficiencies offered by the cloud and ephemeral auto-scaling containers. Building identity-based policies that enable zero trust and are independent of the underlying network ensures that companies never have to consider making that trade-off.

    — Tom Hickman