Tag: Predict 2020 Virtual Summit

  • It’s Almost Here: Predict 2020 Virtual Summit

    It’s Almost Here: Predict 2020 Virtual Summit

    We’re a little less than two weeks away from Predict 2020 Virtual Summit, our annual online event during which we ponder the future of DevOps, serverless, cybersecurity, digital transformation and IT. This year’s event will be held Jan. 23, featuring an impressive lineup of industry luminaries offering up their visions for 2020 and beyond.

    Among the keynote speakers for this daylong event are analysts, practitioners, venture capitalists and thought leaders, each with their perspective on the trends, tools and technologies most likely to impact the IT space. Those scheduled to speak include:

    We also have a full slate of panel discussions featuring industry speakers on topics ranging from IoT security and continuous delivery in a Kubernetes world to the state of analytics and scaling enterprise DevOps. Each panel is sure to be chock-full of lively discussion and insight from those in the know.

    Similar to last year’s event, Predict 2020 also will feature a virtual environment with a conference lobby, presentation theater, expo hall and more. There will also be an exhibit hall where you can interact with other attendees and sponsors, watch videos and download more information. It is truly a conference experience from the comfort of your desk.

    Registration and Sponsor Info

    You can register now at https://predict2020.io. Attendance is free. Download the Program Guide here: https://bit.ly/predict2020ProgramGuide

    If you are curious about what the experts, pundits and luminaries think will be the big trends and stories of the coming year, mark your calendar and attend Predict 2020.

    Save Your Virtual Spot

    — Alan Shimel

  • Predictions 2020: Infrastructure and Ops Trends to Watch in 2020

    Predictions 2020: Infrastructure and Ops Trends to Watch in 2020

    Today, modernizing systems is more than simply moving technology to a new location. It requires an IT stack of a new generation of technologies and tools to work.

    As we head into the new year, let’s take a look at the top eight trends that will shape how we will develop and deliver software. 

    Kubernetes

    Yes, it’s big and getting bigger. The pace of enterprise adoption of this leading container orchestration solution will only gain momentum in 2020. Look no further than the 2,300% attendance increase from KubeCon 2015 (500) to KubeCon 2019 (12,000). As more companies begin to see the direct financial and operational benefits to the flexibility, scalability, automation, high availability and portability of Kubernetes, the demand for developers and engineering experts in this complex software will grow accordingly. Case in point: A 2019 national job search on LinkedIn turned up 16,744 open positions for Kubernetes-related roles. Given the already large and still developing Kubernetes community, we should also see an increase in the speed and volume of feature releases. 

    Microservices

    It’s predicted that by 2022, 90% of all apps will feature microservices architectures. The growing business imperative for software engineering teams to produce and release software in ever shorter cycles—continuous delivery—has paved the way for a huge surge in microservices, the ideal architecture for CD. As enterprises continue their accelerated move to the cloud in 2020 and beyond, they increasingly prize the flexibility to try out the new technology stacks that microservices provide. All businesses want to optimize resources, minimize downtime, reduce infrastructure costs and avoid technology or vendor lock-in. In 2020, microservices architectures will continue to offer up more and better of all these benefits as the migration from monoliths picks up speed. 

    Service meshes

    The rise of microservices has led to a parallel boom in service meshes. This will only accelerate, given how integral the current class of service meshes—Istio, Linkerd, Consul, Envoy—is to the successful functioning of microservices. As a software designed to enable the thousands of microservices that make up an application to talk to each other, it’s quickly become an essential component with a vendor ecosystem poised for substantial growth. Feature-rich Istio, backed by IBM, Google and Lyft, is the leading Kubernetes service mesh, and that shows no signs of changing in 2020, especially given the relative ease of setting up and running it. If your enterprise has embarked on the journey from monolith to microservices, it will soon be crossing paths with service meshes. 

    Observability

    In the recent past, the sheer complexity of modern distributed systems has outstripped the tools designed to allow teams to see into them. Enter observability—which isn’t monitoring. Like good helicopter parents, software engineers, application developers, SREs and DevOps teams want to know and understand what their systems are doing at all times. LightStep, Datadog and Honeycomb, to name a few, are vendors poised to offer logging, tracing and metrics solutions to the rapidly growing number of enterprise teams building cloud native systems. Keep a close eye out for OpenTelemetry, an open source observability framework currently a member of the CNCF Sandbox. 

    SRE

    One of the great challenges ahead for this still-emerging field is for enterprises of varying sizes and work cultures to find a form of SRE that works. What succeeds at Google may not be the recipe for SRE implementation at smaller tech enterprises or startups. The role of SRE and the expectations that go with it remain fluid. The SRE’s constant imperative to automate will only add to the profile of critical SRE and DevOps tools such as Terraform, Ansible and Jenkins. Ponder Amazon’s Prime Day 2018 losses of up to $99 million for a clear understanding of the business-critical importance of SREs in the years to come. The job market reflects this new reality. 

    Security

    The shift-left movement in the software development lifecycle is on. The days of bolted-on post-production security are rapidly fading. DevSecOps, though still a buzz term, is here to stay, with more practice and use cases added to the theory. There are huge opportunities here for automated application security tools that support the software development workflow. 

    Then there’s privacy. The GDPR took effect last May and the California Consumer Privacy Act takes effect January 1, 2020. On top of these, there’s HIPAA and the regulatory compliance pressures on businesses in the area of security, which are already enormous—plus the immense challenges of cloud security. A 2019 Symantec survey on cloud security threats reports that 65% of businesses in the cloud still aren’t using multi-factor authentication. The same survey also notes that an astounding 85% of Symantec’s cloud customers aren’t employing security best practices. Look for businesses to tend to security earlier in the process. 

    Serverless

    It’s a boom time in serverless, with Google’s Functions, Microsoft’s Azure Functions and IBM’s OpenWhisk all offering their serverless solutions following the 2014 rollout of AWS Lambda. Look for more businesses to adopt a serverless-first approach as they upgrade legacy systems and see the substantial cost saving and application development benefits. Startups, too, will see the cost-cutting upside and the agility that serverless brings. The changes in application development and architecture in the cloud as a result of serverless are hard to overstate. With the vendor solutions now on offer, developers are freed up to do what they most like to do: run code and add functionality to their application, faster, without worrying about scaling and availability. Like microservices, serverless will see a huge upsurge in usage as the age of the monolith fades. 

    DevOps

    With the demands of cloud computing and far greater enterprise investment in dedicated teams, DevOps in 2020 is poised to make the transition from policies and principles to actual practice. The addition of baked-in security to the DevOps realm—DevSecOps—adds urgency to the automation of building, provisioning and deploying secure software. ML- and AI-driven apps have arrived, and DevOps practices will play a large role in the development workflow. The goal of zero-touch automation looms large, and this adds urgency to the need for clean data, organizational buy-in and more integrated systems. AIOps, though getting plenty of attention, is still young and its benefits to IT operations are still more theoretical than actual–but stay tuned.

    As we head into 2020, it will be exciting to watch these trends unfold. DevOps teams can expect the way we develop and deploy applications–in any architecture–to continue to evolve. By keeping a pulse on new developments in Kubernetes, microservices and other new technologies, they’ll be well prepared to bring their businesses into the new decade.

    Want to learn more about what to expect in 2020? Join us Jan. 23 for our Predict 2020 Virtual Summit  featuring discussions from some of the industry’s best and brightest offering up their visions for the future. Sign up today for this free daylong virtual event.

    — Kelsie Pallanck

  • Predictions 2020: Key Trends that Will Shape the Autonomous Digital Enterprise

    Predictions 2020: Key Trends that Will Shape the Autonomous Digital Enterprise

    As 2019 comes to an end, and we look toward trends driving innovation in 2020 and beyond, technology advancements in hyper automation, AIOps, edge computing and the convergence of IT service management and IT operations management will be at the forefront. 

    Autonomous Digital Enterprise

    In order to thrive in the 2025 futurescape, organizations will need to evolve to Autonomous Digital Enterprises (ADE), a state where intelligent, integrated, value-creating functions can operate with minimal (ideally zero) human involvement or interference, across every facet of the organization, and its ecosystem of partners.

    This concept is based on the notion that every company today is being disrupted by technology and that’s fundamentally changing their business model. The notion of every company being a technology company means that software becomes more than just a system of record to be the system of action, the system of insights and the system of engagement.

    Edge Computing and IoT

    Over the next couple of years, partnerships will prove to be the pathway to success in realizing value from edge computing and IoT solutions. By using seamlessly integrated, multi-vendor, commercial off-the-shelf solutions, enterprises will experience more success than they would with single-vendor niche products. At the end of the day, what we need is an ecosystem of integrated solutions as opposed to a single silver bullet. This ecosystem will be able to harness data and look at it in meaningful ways and translate information into insight that then translates into actions that businesses can take to optimize the use of IoT assets.

    Convergence of IT Service Management and IT Operations Management

    As IT service management and IT operations continue to converge in 2020, CIOs will rely on AI. More than ever, CIOs will need to address this convergence and work to break down silos between these departments. To obtain a comprehensive view of the IT landscape, CIOs will begin to adopt AI, cognitive and robotic process automation. This will bring end-user support and managed back-end infrastructure more closely together. 

    If we look beyond traditional IT and service management, in the near future we will have the ability to go to market with fully integrated solutions that enable boundary-less operations across AppDev, SecOps, ITOps and service management. This will further enable the use of DevOps in organizations using the power of AI to improve existing capabilities and create new capabilities. This doesn’t mean companies have to start from the ground up on AI efforts, rather they need to look for software solutions that can offer prebuilt AI/ML solutions that drive change.

    AIOps

    The demand for AIOps in the enterprise will continue to rise as AI and machine learning have taken the industry by the jugular. Due to an expansion in the number of workloads—both in public cloud and on-premises—and an increase in application complexity, investment in AIOps will increase and ultimately lead to better business outcomes. Today’s challenges place a premium on differentiated vendor solutions powered by AI/ML and big data analytics techniques that can help modern IT operations evolve from traditional monitoring to observability to actionability.

    All of these trends open realms of possibilities for what businesses can achieve in 2020—as long as they can harness the massive amounts of data enterprises have access to and the technology that will allow them to unlock those insights.

    Want to learn more about what to expect in 2020? Join us Jan. 23 for our Predict 2020 Virtual Summit  featuring discussions from some of the industry’s best and brightest offering up their visions for the future. Sign up today for this free daylong virtual event.

    — Ram Chakravarti

  • Predictions 2020: The Year of DevOps Empowerment

    Predictions 2020: The Year of DevOps Empowerment

    Every year since mid-decade, it seems, one publication or another has declared it to be “the year of DevOps.” Allow me to make the case that it really will happen in 2020.

    The reason? IT leaders are finally empowering their engineers with full-service ownership.

    In a world in which speed, quality and precision will continue to determine the difference between continued success and unmerciful failure–particularly with regard to delivering best-in-class, end-to-end experiences for all stakeholders–full-service ownership is a matter of reality and necessity. Not to mention common sense.

    Developing and delivering products and services that maintain pace and meet the needs of businesses is dependent on achieving faster release cycles without sacrificing quality. But running reliable systems at ever-increasing speeds presents huge challenges that software teams can meet by changing their service ownership policies. The good news is DevOps practices have been gaining considerable traction because they help teams deliver with increased velocity coupled with reduced risk. This enablement, similar to any change introduced, takes time and practice to make work for your needs.

    Code It, Ship It, Own It

    Full-service ownership grants engineers greater responsibility for the code they write and the services they develop during production. The importance of owning and operating your own code and taking responsibility for all deliverables should not be underestimated, because it is the engineers, after all, who should be–and have earned the right to be–accountable. They are the ones designing architectures and systems, coding software and writing runbooks. They are the ones on whose shoulders the overall quality of service sits. They are the ones who are on call when issues arise (invariably, as Murphy’s Law implies, in the middle of the night).

    If they are the ones who code it, then they are the ones who should ship it and own it. The days of engineers “throwing code over the wall” to operations or depending on site reliability engineering (SRE) teams to guarantee the performance of services in the wild are no longer relevant, much less workable.

    That’s particularly important going forward, considering the DevOps market is predicted to grow 18% to nearly $13 billion by 2025. As DevOps tools and solutions become more ingrained in IT operations, the most logical and proactive way to manage this growth, and the inevitable chaos it will bring, is to empower IT with full-service ownership.

    The Forces Behind Full-Service Ownership

    This is happening for three reasons:

    Accountability

    It’s a simple truth; consumers implicitly expect the services they use to work seamlessly and with minimal latency. Considering that consumers will simply move to another site when a page is slow to load or returns a 404 error, the payoff in terms of increasing business’ competitive advantage is immense.

    Full-service ownership promotes higher-quality work because it gives engineers clear visibility into how the code and services they’ve created are performing and impacting their customers’ daily activities. 

    Reliability

    It’s not rocket science to ask the scientist who built the rocket to fix it when it breaks. Likewise, businesses can reduce the amount of downtime and customer impact when a serious incident occurs by immediately bringing in the engineers who wrote the code or created the service. 

    Full-service ownership offers another important advantage: overall institutional knowledge among IT teams. Individual engineers benefit greatly from code reviews, on-call hand-offs, daily standups, casual information sharing and other exercises that build redundancy in knowledge and expertise.

    Continuous Improvement

    A common misconception in the engineering world is that “on-call” is synonymous with “always-on.” That in itself is counter-productive because it can lead directly to alert fatigue. In an ideal world, teams will build time in their development work to go “off-call,” a practice that alleviates alert fatigue and that full-service ownership encourages.

    It also fits perfectly with an integral element of the culture of engineers: a commitment to continually refine and improve their code, product, services and alerting. The most effective process goes beyond just fixing problems, it also includes getting ahead of them, by automating the work needed to prevent them, freeing engineers up to focus on the work that matters most. 

    Five Benefits of Full-Service Ownership

    1. The quality of the code will increase.
    2. Engineers will know when they are off-call, and alerts will be covered by another developer with equal expertise.
    3. Team knowledge and skills will increase through a deeper understanding of the codebase.
    4. Services will become more reliable.
    5. Operations will become more agile.

    When engineers are empowered to code it, ship it and own it, businesses put themselves in a better position to enhance the customer experience and reduce the impact of disruptions, which enables them to focus more on innovation. By defining and refining roles and responsibilities, full-service ownership also reduces the chaos associated with incidents, eliminates silos and unnecessary layers and, ultimately, promotes a culture of empowerment and accountability.

    Want to learn more about what to expect in 2020? Join us Jan. 23 for our Predict 2020 Virtual Summit  featuring discussions from some of the industry’s best and brightest offering up their visions for the future. Sign up today for this free daylong virtual event.

    — Tim Armandpour

  • Predictions 2020: Application Trends, Opportunities and Challenges

    Predictions 2020: Application Trends, Opportunities and Challenges

    Without wheeling out all the usual clichés, 2019 has been another whirlwind of disruptive innovation and opportunity–with plenty of challenges to tackle and circumvent along the way.

    The threat landscape mutated with predictable unpredictability, multi-cloud app deployments are becoming mainstream fixtures and DevOps methodologies started exerting a newfound influence on business plans.

    The big question is what happens next? What anticipated app-centric trends will change the game and tear up the rule book (again)?

    Digital Transformation Takes Shape

    In 2020, we will see more organizations shift away from aspirational sloganeering to substantively embrace what can, and should be, a seismic step-change.

    Inevitably, business leaders will get more involved in application decisions designed to differentiate or provide unique customer experiences.

    Expect a new generation of applications that support the scaling and expansion of business’ digital models to emerge. This will include taking advantage of cloud-native infrastructures and driving automation through software development.

    Further down the line, digital transformation efforts will likely be AI-assisted, particularly as they leverage more advanced capabilities in application platforms, telemetry, data analytics and ML/AI technologies.

    End-to-end instrumentation will enable application services to emit telemetry and act on insights produced through AI-driven analytics. We anticipate that these distributed application services will improve performance, security, operability and adaptability, without significant development effort.

    The Rise of Application Capital

    Applications are now firmly established as the main conduit for companies to develop and deliver goods and services. They have become modern enterprises’ important assets.

    Even so, most still only have an approximate sense of how many applications they have, where they’re running or whether they’re under threat.

    This will soon change.

    To manage Application Capital effectively, it is essential to establish a company-wide strategy that sets policy and ensures compliance. This includes addressing how applications are built, acquired, deployed, managed, secured and retired. At a high level, there are six distinct and unavoidable steps that need to take place: build an inventory, assess the cyber risks, define application categories, identify the application services needed for specific activities, define deployment parameters and clarify roles and responsibilities.

    The primary aim of an application strategy should always be to enhance and secure all digital capabilities–even as their reach and influence shift and expand.

    DevOps’ Culture Club

    The technical minutiae DevOps methodologies and associated tools got a lot of publicity this year. 

    2020 will be all about getting the culture right, marrying theory with best practice and unlocking new levels of productivity without upsetting the operational apple cart.

    Culture is not optional. Team structure alone dramatically changes pipeline automation, with traditional single-function teams often falling behind their contemporary, DevOps-driven counterparts. 

    Consequently, we will see more collaborative team structures and alignment on key metrics that give NetOps additional means to focus on what the business requires: faster and more frequent deployments.

    DevOps has a 10-year head start on NetOps in navigating and overcoming obstacles around certain types of integration, tools and skillsets. Collaborative teams can explode the status quo by promoting standardization on tools that span from delivery to deployment (such as Jenkins and GitHub/GitLab).

    DevOps should not–and cannot–end with delivery. That means deployment functions–along with a complex pipeline of devices and application services–must be automated. This won’t happen without effective cultural realignment.

    The Data Center Is Alive and Kicking

    Conflating the adoption of SaaS with IaaS caused speculation that cloud was cannibalizing IT. Pundits warned that data centers would disappear. 

    The rumors were exaggerated. Data centers are still being built, expanded and run around the globe. The cloud hasn’t managed to–and likely never will–kill the data center.

    Early in 2019, an IDC executive told channel partners at the IGEL Disrupt conference that over 80% of companies they surveyed anticipated repatriating public cloud workloads. Security, visibility and performance remain common concerns.

    Repatriation-related opportunities include improving availability of multi-cloud operational tools and a push toward application architectures that rely on more portable technologies such as containers. 

    The data center is not dead. It’s just evolving. 

    Application Protection Challenges

    According to F5 Labs, the server-side language PHP–used for at least 80% of websites since 2013–will continue to supply rich, soft targets for hackers. Situational awareness is critical to mitigate both vulnerabilities and threats.

    Businesses are also realizing that applications encompass more than just the code they execute. Attention needs to be paid to everything that makes them tick, including architecture, configurations, other connectable assets and users. The prevalence of access attacks, such as phishing, are an obvious case in point.

    F5 Labs analysis of 2019 breach data confirms the need for risk-based security programs instead of perfunctory best practice poses or checklists. Organizations need to tailor controls to reflect the threats they actually face. The first step in any risk assessment is a substantive (and ongoing) inventory process.

    As ever, the industry will gradually incorporate emerging risks into business models. For example, cloud computing has gradually shifted from a bleeding-edge risk to a cornerstone of modern infrastructure. The risks associated with the cloud have either been mitigated or displaced to contractual risk in the form of service level agreements and audits. 

    API and You Know It

    The word is out. Application programming interfaces (APIs) can transform business models and directly generate revenue. Cybercriminals know this.

    More than ever, organizations need to focus on the API layer, particularly in terms of securing access to the business functions they represent.

    One of the biggest issues is overly broad permissions, which means attacks through the API can give bad actors visibility into everything within the application infrastructure. API calls are also prone to the usual web request pitfalls such as injections, credential brute force, parameter tampering and session snooping.

    Visibility is another major and pervasive problem. Organizations of every stripe–including IT vendors–have a notoriously poor track record of maintaining situational API awareness. 

    API security can be implemented directly in an application or, even better, in an API gateway. An API gateway can further protect APIs with capabilities such as rate limiting (to prevent denial of service attacks) and authorization. Authorization narrows access to APIs by allowing access to specific API calls to only specified clients, usually identified by tokens or API keys. An API gateway can also limit the HTTP methods used and log attempts to abuse other methods so you’re aware of attempted attacks.

    Appy New Year!

    All this is of course the tip of an increasingly interconnected iceberg. Any New Year’s resolution worth its salt should include a commitment to comprehensively master the development, deployment, operation and governance of application portfolio. The best way to do this, and to get visibility into the code-to-customer pathways for all applications, is to leverage a consistent set of multi-cloud application services. Here’s to a safe, innovative and transformational 2020!

    Want to learn more about what to expect in 2020? Join us Jan. 23 for our Predict 2020 Virtual Summit  featuring discussions from some of the industry’s best and brightest offering up their visions for the future. Sign up today for this free daylong virtual event.

    — Vincent Lavergne

  • Predictions 2020: Five Real-Time Data Predictions

    Predictions 2020: Five Real-Time Data Predictions

    According to Gartner, 85% of big data initiatives end in failure. In 2020, organizations are out of budget and operational runway, and need to start executing and getting the big data recipe right.

    It is not just about big data; it is about using data differently. Rather than rearward-facing business intelligence, leading companies are driving differentiation and profit by using data to make fact-based decisions in real time. This requires the broader application of real-time information to make a difference in user experience, in prioritization of production and manufacturing schedules, and in spotting problems before they happen.

    Rather than reports for a few people, the new data-driven business processes are engaged continuously, and across all customer engagements, transactions and decision points within business processes. Scale means throughput across millions of transactions and with potentially millions of customers. Database systems have to be engineered differently, with different technology built to deal with real-time demands and high throughput across huge numbers of endpoints.

    As we enter the next decade, here are five predictions, centered on real-time data, that we expect to emerge.

    Machine Learning and AI Models Finally Get the Data They Deserve

    Most AI and machine learning initiatives are niche, nascent and not operating anywhere near scale. According to industry research (O’Reilly), hardware and data are the primary bottlenecks in getting enough data processed fast enough to harness the full promise of AI. That’s changing, with the arrival of new wire-speed hardware (from companies such as Intel) and clever data platforms designed to leverage hardware innovations for real-time efforts on a massive scale. It’s all about the amount of data you can process in real time to make AI and machine learning actually work. This is what is needed, and it’s becoming practical.

    Privacy Prompts a New Era of Data Innovation

    Businesses hoard data. And often, so much of it isn’t used due to infrastructure costs and technology bottlenecks. Now, as new privacy laws (GDPR, CCPA, etc.) show their teeth, companies really need to make all that data worth the risk. It will drive new real-time business processes that are not only safer but squeeze value out of data in new and exciting ways.

    Companies face a delicate balancing act. They must comply with the realities of new regulations, while also being able to use personal data in real time to serve customers what they want and expect. Companies that can satisfy the regulators and appeal to customers will win.

    If an Economic Downturn Occurs, Data Will Drive the Next Round of Economic Gains 

    An economic downturn is inevitable. When it happens, companies will be asked to do more with less. As a result, they will need to completely rethink their solution and delivery strategies.

    In that environment, with fewer markets opening or providing a sufficient return on investment, the next wave of gains is to optimize your existing segments and operations to the fullest extent. These data-driven initiatives require that companies understand customers better, and be able to instantly target them in critical moments—harnessing massive amounts of data to suggest and expand purchases. 

    5G Will Accelerate Customer Expectations

    As bandwidth increases and high bandwidth communication becomes available across devices (on cars, planes, homes, ships, buildings, etc.) and in more situations, we will see data being used differently. What may have been processed intermittently in batches with high degrees of latency will now be processed in real time, driving higher efficiency and removing risk from supply chains, customer interactions and equipment maintenance and performance. It will no longer be OK to know how you’ve done and correct it next quarter; rather, things must be corrected in near real time. New standards will be set by the highest-performing companies, and entirely new businesses will emerge that are leveraging a new level of availability to real-time data.

    Decline of Globalization Will Force Companies to Know Their Customers Better

    As global markets shrink, it becomes imperative for companies to up their game and drive for more market share within the available market. Companies that have been treading water and growing at the rate of the global market expansion are going to start to shrink. Differentiation through better customer experience and better management of supply chains will make the difference between continuing to grow versus stagnation or shrinkage.

    Companies that have invested in instrumenting their supply chains, who have a deep understanding of what comes from where and what the alternatives are, have already begun to optimize around the new web of tariffs. Those that are less agile are seeing reduced profits or reduced sales based upon the elasticity of their pricing options.

    The more real-time data one has, the clearer the picture of what options are available as the global situation changes. The faster a company can process that data means either missing financial targets or outperforming peers.

    Want to learn more about what to expect in 2020? Join us Jan. 23 for our Predict 2020 Virtual Summit  featuring discussions from some of the industry’s best and brightest offering up their visions for the future. Sign up today for this free daylong virtual event.

    — Lenley Hensarling

  • Predictions 2020: The Future of the Mobile Industry

    Predictions 2020: The Future of the Mobile Industry

    The mobile device industry continues to grow in leaps and bounds. Statistics show that, today, over 5 billion people have mobile devices and there are over 9.2 billion mobile connections worldwide. Add to these statistics the fact that the number of consumers who shop and bank online continues to grow as well–presenting hackers with increasing numbers of mobile applications and end-points to target. As developers of software that protect mobile apps from reverse engineering and hacking, at Guardsquare we have a unique purview into the mobility space, and therefore have some pertinent 2020 predictions for the mobile industry.

    Mobile Payments Apps on the Rise

    As consumers’ comfort with, and reliance on, personal technology increases, we expect to see purchases via mobile payment apps grow rapidly throughout 2020. Great news for the global economy, but the downside of this trend is it will serve to exacerbate opportunities for hackers to take advantage of mobile applications and devices that are not properly secured.

    Fake Apps Abound

    Fake apps or hidden apps have historically been a problem and we don’t see that changing any time soon. In December of last year alone, almost 65,000 new fake apps were detected among the various app stores, and we expect this to become increasingly common and problematic. Consumers need to be alert when downloading new apps and developers should be wary that fake apps can negatively affect their own reputation and their company’s. 

    Developers Beware Kotlin’s Hidden Vulnerabilities

    The new development language, Kotlin, is catching on now that it has been designated Google’s preferred language for Android development. However, many developers using the language still do not fully understand security best practices, including how to protect Kotlin code against OWASP’s well-known Mobile Top 10 risks. As with many apps written in Java, apps written using Kotlin must be protected against both static and dynamic attacks using a combination of code hardening and RASP.

    iOS Is Vulnerable Too

    We believe that 2020 will be the year in which awareness increases around the security shortfalls of iOS. Many application developers still believe iOS apps are virtually immune to reverse engineering, but, in reality, all iOS versions have already been jail-broken at some point.  We anticipate developers will take better security measures to ensure the integrity of their apps by employing a multi-layered approach to security to ensure the protection of their iOS applications.

    We continue to see the more sensitive an organization’s data, the more likely it is the mobile app will become a target for hackers. According to OWASP’s Mobile Top 10, reverse-engineering and tampering ranked the eighth and ninth most prevalent mobile security risks. Verizon’s Mobile Security Index 2019 highlights that more than 80% of organizations said they are at risk from mobile security threats, and 69% said those risks increased in the last year.

    It is our hope that, in 2020, all apps—but especially apps housing sensitive customer data—evolve from going unprotected to incorporating key security measures that protect the users and the organizations.

    Want to learn more about what to expect in 2020? Join us Jan. 23 for our Predict 2020 Virtual Summit  featuring discussions from some of the industry’s best and brightest offering up their visions for the future. Sign up today for this free daylong virtual event.

    — Roel Caers

  • Predictions 2020: How to Make the Case for Adopting CI/CD in Your Organization

    Predictions 2020: How to Make the Case for Adopting CI/CD in Your Organization

    The practice of continuous integration and continuous delivery (CI/CD) is fundamental to modern software development. And yet, many organizations are still using slow, error-prone, manual processes to build, test and deploy their software. Sometimes, the blocker can be engineers who don’t want to change how they’ve always done things, but most often folks in the trenches are chomping at the bit to automate. All too frequently, it is IT leadership and executives who need to be convinced that making a large investment in updating tools, training and culture will net returns greater than the cost.

    If you want to change management’s mind about an investment in CI/CD, focus on making a strong business case. This may sound daunting, but it’s easier than you think. Learning a bit about how to advocate for budget and organizational change can go a long way. Just think about what life would be like if, instead of sitting in endless change management meetings, you could get your code to production simply by merging to master while automation takes care of the rest.

    This article will get you started with some concrete tips you can use to get CI/CD green-lit by your leadership.

    Start Small

    Agile and DevOps are all about breaking things up into smaller chunks. It may seem counterintuitive, but deploying more frequently equates to less risk because small changes are easier to orchestrate, troubleshoot and roll back than large complicated deployments. In that same way, you can reduce the risk to the organization by taking a DevOps approach to transformation. Rather than trying to upend your entire process, see how you can break the change up into small, iterative chunks.

    Almost every large enterprise that has successfully adopted wide-spread CI/CD started with one lighthouse team. Changing everything is a tough sell. Instead, approach management with a low-risk proposal: “We’d like to run an experiment to see if we can deliver more quickly and reduce costs. We have one team that will take one small project and test CI/CD automation to see what the results will be. We can leverage open source tooling to get started at a low cost.” Even the most stingy budget holder should find the proposal intriguing.

    Measure the Results

    Once you’ve started to conduct your experiment, it’s important to measure what you observe. What are the differences between the old way and the new way? The more concretely you can quantify it, the better. Saying, “We went faster,” doesn’t carry a lot of weight. But if you can quantify it, your message becomes more potent. For example, “Our previous cycle time from the moment a developer begins work on a ticket to the time that code is running in production and useable was 30 days. By automating some of our manual efforts using CI/CD we have cut that to five days.”

    For this part of the process there’s no need for exact numbers. Most likely if you aren’t doing CI/CD today, you likely don’t have the instrumentation in place to accurately measure cycle time. But don’t let that be a blocker. You can give estimates. “From about one month to one week,” is still a powerful story.

    Some other metrics to capture that can help make your case are:

    • Number of tests run.
    • Code coverage in terms of percentage of code tested.
    • Number of people-hours required.
    • Number of defects in production or number of regressions/roll backs needed.
    • Mean time to repair (MTTR): The average time from when a bug/failure is discovered in production to when the fix is running.
    • Frequency of releases—how often new capabilities are available for users.
    • Cost to deploy: This is a very powerful metric if you can estimate it. A good rule of thumb is: (number of people minus hours, times average hourly rate) plus (cost of assets and services required).

    Aim to use three to five metrics to prove your case. You don’t want to overwhelm with data. The point is to show that things are better with CI/CD, not that you’ve gathered a lot of numbers. Use a simple before-and-after format to show the change. State the changes in terms of increased value, reduced cost and/or reduced risk. For example, “We increased value for our users by shipping 10 times more features in the same time frame, reduced deployment costs by 80% and reduced risk by increasing code coverage by 30 points from 40% to 70%.” 

    Couple Your Efforts to Business Outcomes

    A critical element of IT success is how closely you can partner with the business. It can be next to impossible to get initiatives green-lit if the only benefit is to make things better for IT. But if you can show how some extra effort spent on IT modernization can drive results for the business, then you’ll find you start getting enthusiastic approval from leadership.

    Collaborating with people outside of IT or software R&D is a career-enhancing skill every technical practitioner should strive to improve. 

    Get to know what efforts in sales, marketing and product are dependent on IT. For example, the sales department may desperately need additional capabilities in their forecasting tool if they are going to execute strategic deal acceleration, ensure quarterly numbers are consistent and avoid unpredictability with shareholders. In other words, the fact that your slow delivery cycle can’t get those new features on the release calendar for another three months is putting the stock price in jeopardy.

    To avoid this tragedy, you can tie your CI/CD efforts to the sales outcomes. By getting to know the pain points of your sales colleagues, you can craft a powerhouse “ask” to leadership. “We’d like implement CI/CD to automate deployments for our sales data management system. This will allow us to implement new filters in a matter of days rather than months which sales needs to hit their numbers.” 

    Pulling It All Together 

    It can be demoralizing to feel like you are behind the curve. Looking at other businesses who have already adopted CI/CD it can feel like you might never catch up. If this is the case, some axioms are appropriate, such as the famous Chinese proverb from the Tao Te Ching “A journey of a thousand miles begins with a single step.” And as Theodore Roosevelt said, “Comparison is the thief of joy.”

    The reality is that you are not alone. Many organizations, especially large enterprises, are relying on outdated software practices. Convincing leadership to green-light IT modernization efforts can be a challenge. Adopting CI/CD in a meaningful way does require significant investment, but there is a lot you can do to smooth the path for them and earn their support.

    Begin by identifying a small adventurous team who can serve as an experimental testing grounds. Not only will their success help to convince leadership, but their example serves to light the way for other teams to adopt DevOps. Identify metrics you want to capture and be sure to instrument so you can measure the improvement. Pick a few metrics that show increase in value, decrease in cost and decrease in risk. Finally, reach across the org to collaborate with your non-engineering peers. By showing how your modernization effort drives outcomes for the business you’ll be sure to earn respect as well as additional budget to expand your CI/CD efforts.

    Want to learn more about what to expect in 2020? Join us Jan. 23 for our Predict 2020 Virtual Summit  featuring discussions from some of the industry’s best and brightest offering up their visions for the future. Sign up today for this free daylong virtual event.

    — William Chia

  • Predictions 2020: The Future of APM Strategies and Tools

    Predictions 2020: The Future of APM Strategies and Tools

    As 2019 comes to an end, it’s safe to say that multi-cloud strategies are here to stay. We can predict that 2020 will bring an ever-increasing demand for application performance management (APM) tools and services.

    So what does the future of APM look like? Let’s dive in.

    Multi-Cloud Strategies Increase the Demand for APM Tool Adoption

    Companies are increasingly adopting more than one platform—either for financial leverage or to create a time-to-market or feature race between the platforms. To remain competitive, public cloud providers must offer unique features or capabilities differentiating them from competitors. This has created an upsurge in new and more complex technologies, increasing the need for APM tool adoption.

    Logs Will Be Recognized as Key Aspects of APM

    APM is a puzzle made up of user experience, metrics and traces, and logs—and each piece must be incorporated to achieve full-stack visibility and ultimately seamless app performance. However, a healthy app is not characterized solely by top performance, but also availability—making a log management solution that monitors availability, enables proactivity and reacts quickly to remediate problems key.

    In 2020, implementing solutions that achieve integrated application performance and availability management for any type of organization, including those operating on-premises and/or cloud-based applications across all mixes of cloud environments, will become increasingly important and prioritized.

    APM Skills in a Cloud-First World

    The nouns have changed, but the verbs remain the same: APM skills are among the top skills tech pros want to develop in the coming year, according to the recent SolarWinds IT Pro Day survey, Building Confidence for Tech Pros of Tomorrow. However, in 2020 tech pros will begin to recognize that many of the skills they already possess are sufficient to manage the new realm of integrated solutions in the cloud. Tech pros can leverage some of the same skills they could before as the nouns have changed, but the verbs remain the same. Where we used to have server or virtual machine, now we have containers. But the verbs? They’ve always been focused on optimizing performance, ensuring availability and planning capacity.

    In 2020, the extent to which tech pros will discover they don’t need to fear new nouns (more than they did when they moved from client virtualization) will increase.

    Universal Adoption of APM Tools

    As environments become more dynamic and complex, the opportunity for applications to break increases—creating the need for robust monitoring tools. In 2020, as buyers see the benefit of leveraging APM tools on a regular basis rather than only in critical moments, the market will adjust accordingly. We can expect easier-to-implement solutions that are more highly valuable and affordable. The paradigm that APM tools have to be expensive will be broken once and for all.

    Want to learn more about what to expect in 2020? Join us Jan. 23 for our Predict 2020 Virtual Summit  featuring discussions from some of the industry’s best and brightest offering up their visions for the future. Sign up today for this free daylong virtual event.

    — David Wagner

  • Predictions 2020: Ushering in 2020 Data Predictions

    Predictions 2020: Ushering in 2020 Data Predictions

    2019 brought us more data organizations running more advanced analytics, AI and ML workloads than ever before. 2020 is the year where we’ll see a spike in both the number of technologies and data teams that support these types of workloads internally. We’ll see AI and analytics teams merge into one as the new foundation of the data organization, focused on areas such as moving to the cloud while maintaining on-prem Hadoop, “Kubernetifying” the analytics stack and Hadoop compute. These are the trends I believe we’ll see come about in 2020.

    Rise of the Hybrid Cloud

    We’ve been hearing people talk about the hybrid cloud for the past three years now. For the most part, that’s all it’s been talk—but in 2020 it gets real. We are seeing large enterprises refusing to add capacity on-prem to their Hadoop deployments and instead invest in the public cloud. But they are still not willing to move their core enterprise data to the cloud. Data will stay on-prem and compute will be burst to the cloud, particularly for peak demands and unpredictable workloads. Technologies that provide optimal approaches to achieve this will drive the rise of the hybrid cloud. 

    One Machine Learning Framework to Rule Them All

    Machine learning with models has reached a turning point, with companies of all sizes and at all stages moving towards operationalizing their model training efforts. While there are several popular frameworks for model training, a leading technology hasn’t yet emerged. Just like Apache Spark is considered a leader for data transformation jobs and Presto is emerging as the leading tech for interactive querying, 2020 will be the year we’ll see a front-runner dominate the broader model training space with pyTorch or Tensorflow as leading contenders. 

    Kubernetifying the Analytics Stack

    While containers and Kubernetes works exceptionally well for stateless applications such as web servers and self-contained databases, we haven’t seen a ton of container usage when it comes to advanced analytics and AI. In 2020, we’ll see a shift to AI and analytic workloads becoming more mainstream in Kubernetes land. Kubernetifying the analytics stack will mean solving for data sharing and elasticity by moving data from remote data silos into K8s clusters for tighter data locality. 

    Hadoop Storage (HDFS) is Dead but Hadoop Compute (Spark) Lives Strong

    There is a lot of talk about Hadoop being dead, but the Hadoop ecosystem has rising stars. Compute frameworks such as Spark and Presto extract more value from data and have been adopted into the broader compute ecosystem. HDFS is dead because of its complexity and cost and because compute fundamentally cannot scale elastically if it stays tied to HDFS. For real-time insights, users need immediate and elastic compute capacity that’s available in the cloud. Data in HDFS will move to the most optimal and cost efficient system, be it cloud storage or on-prem object storage. HDFS will die but Hadoop compute will live on and live strong.

    AI and Analytics Teams Will Merge Into One as the New Foundation of the Data Organization

    Yesterday’s Hadoop platform teams are today’s AI/analytics teams. Over time, a multitude of ways to get insights on data have emerged. AI is the next step to structured data analytics. What used to be statistical models has converged with computer science to become AI and ML. So data, analytics and AI teams need to collaborate to derive value from the same data they all use. This will be done by building the right data stack—storage silos and computes, deployed on-prem, in the cloud or in both, will be the norm. In 2020 we’ll see more organizations building dedicated teams around this data stack.

    Talent Gap Will Inhibit Data Technology Adoption

    Building the stacks that enable data technology into practice is hard, and this will only become more obvious in 2020. As companies discuss the importance of data in their organizations, they’ll need to hire the data, AI and cloud engineers to architect it. But there aren’t enough engineers who have expertise in these technologies to do that. This super-power skill is the ability to understand data, structured and unstructured, and pick the right approach to analyze it. Until the knowledge gap closes, we’ll continue to see a shortage of these types of engineers—many companies will come up short on their promises of “data-everywhere.”

    China Is Moving to the Cloud on a Scale Much Larger than the US and Will Leap Frog From On-Prem to Massive Cloud Deployments for Advanced Workloads

    Over the past five years, while enterprises in the U.S. have been moving in leaps and bounds to public clouds, enterprises in China have been investing mostly in on-prem infrastructure primarily for data-driven platform infrastructure. 2020 will be the inflection point where this changes. China will leapfrog into the cloud at a scale much larger than the U.S. by adopting the public cloud for new use cases, bursting in the cloud for peak loads and over time move existing workloads. Public cloud leaders in China will see dramatic growth that might outpace the growth of the current cloud giants.

    2020 is the year where the rubber meets the road when it comes to advanced analytics and AI. Companies that back the types of technologies that enable and support this kind of data and workloads will emerge as leaders in the space. On the other side, companies that structure their data teams to meet the requirements of the new data stack will emerge as leaders as well. I’m excited to see how advanced analytics and AI opens up new and innovative applications and use cases.

    Want to learn more about what to expect in 2020? Join us Jan. 23 for our Predict 2020 Virtual Summit  featuring discussions from some of the industry’s best and brightest offering up their visions for the future. Sign up today for this free daylong virtual event.

    — Haoyuan Li