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Tag: digital transformation

Businesses Modernizing Apps in Wake of Pandemic

A survey of 5,000 business decision-makers, IT decision-makers and app developers published suggests organizations are taking advantage of the crisis created by the global COVID-19 pandemic to accelerate the modernizing of apps using DevOps practices.

Conducted by the market research firm Vanson Bourne, the survey finds 80% of respondents said organizations must modernize the technologies they use to develop and deploy software to be more successful. Nearly as many (79%) said their organization will not be able to deliver a best-in-class end user experience without successfully modernizing software development processes.

In addition, 80% of respondents said embracing developer processes such as test and learn would enable organizations to work more effectively and efficiently.

The survey also finds some organizations are not letting a proverbial good crisis go to waste. A total of 70% said they have good or excellent alignment between application development and IT teams, up from 64% prior to the pandemic. Alignment between business teams and application development (67%) and IT teams (67%) increased by 10% and 12% respectively since the start of the pandemic, according to the survey results.

Sumit Dhawan, senior vice president and chief customer experience officer for VMware, said the need to make applications more accessible and reliable is accelerating a transition to the cloud. The survey finds the primary benefits of modernizing apps are enabling remote workforces (54%); pushing quick updates in response to changing landscape (42%); and maintaining reliable uptime (41%).

The scope of application modernization initiatives varies widely. Some organizations are simply lifting and shifting existing application workloads along with the virtual machines they run on into the cloud. Others are refactoring applications to run natively on a different virtual machine platform provider by a cloud service provider. Others are wrapping existing applications in containers so they don’t have to be refactored when deployed on another virtual machine. Still others are employing containers and Kubernetes to develop entirely new microservices-based applications that tend to be more flexible and reliable than existing monolithic applications.

Regardless of the path forward, the inability to physically access local data centers during the pandemic has accelerated a shift to the cloud that was occurring even before the pandemic hit. There still will be many applications that for performance, security and compliance reasons may need to remain in on-premises IT environments. However, it might not be long before IT organizations also modernize those applications to make them both more accessible, flexible and resilient.

Most IT teams will find themselves managing microservices-based applications alongside modernized monolithic applications for years to come. Over time, however, many of those monolithic applications will be deconstructed into a core set of microservices.

At the core of all those initiatives will be a set of best DevOps processes that each IT team defines for itself based on the nature of the application portfolio that needs to be developed, deployed, secured and maintained. The challenge now is determining which applications should be modernized versus simply replaced by either a software-as-a-service (SaaS) application or a custom cloud-native application that is a better fit for the purpose.

June 30, 2020
Report: Confidence in Digital Transformation Lacking

Results of a recent survey conducted by the Corporate Board Member Institute shows a majority of respondents see their organizations’ digital transformation efforts aren’t keeping pace with the current business environment.

The survey polled more than 200 directors of public companies in February, before the global COVID-19 pandemic hit the United States, and the results were compared to PwC’s 2020 Global Digital IQ survey. The results show a lack of confidence in digital transformation initiatives—3 out of 5 respondents admitted their company is behind in their digital transformation processes and within the past three years, only 54% had begun their digital transformation processes.

The PwC survey, however, shows the opposite: According to those results, 70% of U.S. executives said their digital transformation is ahead of their competitors. That 70% of executives compared to 35% of directors shows executives are more positive in their company’s progress and maintain a goal-oriented view, said Paula Loop, leader of PwC’s Governance Insight Agency.

The optimism by executives shows that they have confidence in their ability to get things done with digital transformation now, and that they are planning for what is in the present and the near future. The results from directors show a longer-term view—while things currently might not look so good and they say they are behind, they still have the confidence that they can make strides in improving their digital transformation. Directors still believe that they are on or ahead of schedule in other areas such as integrating new technologies into products and services (70%) and training workers for the digital era (67%).

In interviews conducted post-survey, after the pandemic hit, some directors said COVID-19 will accelerate their digital transformation initiatives. “Regardless of where companies were in digital planning, this pandemic has thrust most, if not all, into some form of digital transformation,” Loop said.

Even when faced with a global pandemic, the business continues. Competition isn’t slowing down; it’s time to see whether digital transformation processes will follow suit.

June 17, 2020
How DevOps Tools Are Contributing to Automation Initiatives Across the IT Landscape

Prolific advancements in IT, specifically in agile methods and culture over the years, has led to burgeoning needs for a more holistic end-to-end software delivery approach. Agile development is an umbrella term that encompasses numerous incremental and iterative software development practices — including Kanban, SAFe (Scaled Agile Framework), Scrum, Extreme Programming (XP), Lean Development, among others.

Each methodology works on its own unique approach. However, the core commonalities they share lie mainly in their values and vision. The methodologies integrate continuous feedback from iteration to refine and deliver a successful software system. They include various forms of continuous evolution, such as continuous integration, planning and testing, of both software and project. Furthermore, one of the most significant aspects of agile methodologies is their keen focus on empowering workforces to work together and collaborate more efficiently, thus simplifying and speeding up decision-making processes.

Advancement in agile development is what has birthed the DevOps culture. The technology is born from the rising need to adapt to increasing software velocity and throughputs generated through agile methods.

Understanding DevOps

The DevOps market consists of a set of practices, designed to integrate and automate processes between IT and software development teams, enabling them to create, test and deploy software in a quicker and more efficient manner.

The term DevOps, which was coined in 2009 by Andrew Clay Shafer and Patrick Debois, is a combination of the words “development” and “operations.” It is also indicative of a cultural shift in the IT sphere, which bridges the gap between historically siloed teams, such as operations and development.

The DevOps framework essentially adopts a culture where the critical focus is on facilitating collaboration between the business, operations and development teams. Although tools are considered as pillars of the technology, DevOps is designed to deliver continuous value for customers, empower organizations to provide solutions of the highest quality at swift rates, and bring about the automation of the entire business process spectrum, from building to deployment of a product or application.

Shifting Trends Toward Automation in Software Development Processes and the Subsequent Impact on DevOps Adoption in the IT Space

The software development process consists of several integral parts, among which testing is a crucial task. It allows developers to monitor the functionality of the software, monitor and register performance, and detect any aspects that require remediation. However, with software projects becoming increasingly more complex as the years progress, and with project development life cycles accelerating, conventional methods of manual QA (quality assurance) testing fall short in meeting testing objectives within the desired time frames.

Consequently, software developers are shifting their focus toward automated workflows and testing tools, in order to expedite testing routines without compromising on consistency and completeness in QA processes.

DevOps practices are significantly dependent on automation to ensure frequent and timely deliveries across platforms. Studies have shown that nearly 85% of IT leaders claim that automation is a critical aspect of their DevOps strategies. This is attributed largely to the fact that automation empowers infrastructures to successfully field constant changes in codes that are associated with DevOps tools.

Furthermore, automation allows the effortless scaling of environments and unburdens skilled workforces from mundane and repetitive tasks, enabling them to focus on more integral aspects.

Considering a process perspective, automation in testing involves the addition of test automation actions and tools to regular software development regimens. For instance, new builds delivered to a repository can be automatically subjected to automated testing procedures using a number of prescribed tools, with little to no need of developer intervention. The results are recorded with care, then compared to previous test runs and eventually submitted for review to developers.

Depending on the outcome, the software can then be cycled back to the developers for further remediation or approved for deployment. This is especially relevant in terms of the DevOps framework, which relies on continuous integration/continuous delivery (CI/CD) pipelines.

CI/CD pipelines are a prominent outcome of developer operations, allowing developers to validate the quality of the software with minimal intervention, and deploy apps and software to customers in a quicker manner.

CI/CD platform CircleCI, for example, has recently raised over $100 million in Series E funding, in an effort to boost the development of their DevOps product suite. This move is indicative of CircleCI’s proficiency in delivering an automated approach to DevOps practices, including tools for companies to create, test and deliver software.

How Is the Current Pandemic Impacting Digital Development?

The COVID-19 pandemic has asserted a massive influence on the industrial landscape, driving workforces across the globe into remote-only work set-ups. With millions of people working from home for a seemingly indefinite period, enterprises across the globe are rallying to accelerate automation efforts in order to more efficiently deliver digital business applications to engage their employees from remote workspaces.

According to various studies, nearly 73% of IT operations and DevOps teams are working toward maintaining and expediting initiatives for digital transformation throughout the current crisis, holding the belief that the value of digital offerings is set to witness a positive growth trajectory in the social distancing era.

DevOps industry players such as JFrog are working toward providing enterprises and teams with access to cloud-based DevOps technologies, free of cost, particularly those which are undertaking active research and response efforts to combat the COVID-19 pandemic. These DevOps technologies include Pipelines, Xray and Artifactory, among others.

While the exact impact of the global crisis on the DevOps environment in particular and the IT space in general is yet unclear, it is becoming more prominent that the strong focus on the prevention of such crises in the future — both in and out of the IT realm — is likely to set a great precedent for the growth of the DevOps industry in the years ahead.

June 16, 2020
How DevOps Powered by AI and Machine Learning Is Delivering Business Transformation

The use of artificial intelligence (AI) and machine learning (ML) is fundamentally changing the way we think about DevOps. Most notably, it is delivering a new form of DevOps that recognizes the need to have systems that are intelligent by design and underpinned by comprehensive security (DevSecOps). For many, this will be the crucial next step if DevOps is to shorten the software development lifecycle for all connected intelligent systems, ensuring the continuous delivery of secure high-quality software.

By now, most organizations understand DevOps is a substantial discipline that they must adopt – according to Deloitte, organizations adopting DevOps see an 18%-21% reduction in time to market. By breaking down the silos between business and IT operations, DevOps can ensure consistent levels of productivity, efficiency and service delivery, all of which hold weight in these times of heightened uncertainty.

To put it simply, DevOps can help businesses compete in already congested marketplaces. Through a foundation of continuous integration (CI) and continuous delivery (CD), organizations can ensure the customer receives the product they demand in the fastest time possible, while mitigating any elongated frustrations experienced from a lack of harmony between systems engineers and operations teams. Incorporating AI and ML into that DevOps strategy will take things to the next level.

AI and ML Are the Next Evolutionary Step for DevOps

Today’s companies are data-driven and being built as digital platforms. However, just 28% of organizations are currently succeeding in their digital transformation journeys. Increasingly, corporations are looking at what AI and ML can do to help them realize their transformative ambitions.

Both the AI and ML markets are expected to experience huge growth over the next three to four years. Analyst firm IDC, predicts worldwide spending on AI systems will reach a href=”https://www.marketresearchfuture.com/reports/machine-learning-market-2494″>42.8% by 2024.

What AI and ML reveals for these companies, and the increasing value of what Al, ML and devices can do together, are changing the way organizations view the world as they digitally transform. Coupling AI and ML with DevOps will lead to a significant shift in what DevOps gets involved with.

Primarily, it sets DevOps front and center of an organization’s wider digital transformation ambitions. If digital companies run on living data, then the development of these intelligent systems is an enticing environment for DevOps to prove its wider value to the organization like never before.

Security Takes the Center Stage

According to a TechTarget survey of key IT decision makers, cybersecurity and risk management were found to be the number one area for spending this year, with more than 53% of respondents saying they saw budgets increase in this area. And security is a crucial element that any organization employing a DevOps strategy should be considering.

DevSecOps is the simple premise that everyone involved in the software development cycle is responsible for security. In fact, the saying “security is everyone’s responsibility,” is a mantra that has been repeated often, and just as often ignored. Embedding security within every part of the development process, ensures security and compliance monitoring tools keep pace with the speed and agility that DevOps offers. It is a common understanding that security is the biggest block to the rapid and seamless development and deployment of systems, as security solutions have not traditionally been built to test and code at the speed DevOps requires.

Ultimately though, more automation from the start, reducing the need for manual configuration from security architect is where DevSecOps shines. This reduces the chance of misadministration and occurring faults, which can lead to downtime, and potential breaches or attacks. Quite often, the best ways to secure your organization is through simple hygiene factors, such as regular patching and software updates.

The reality is that every organization employing DevOps should really be approaching it as DevSecOps. Security is of ever growing importance to each and every organization and, through empowering it with AI and ML processes, it can be enhanced too, simplifying the processing of data to easily identify threats or potential vulnerabilities in the security makeup.

Reaching Beyond Human Capability

The future will be made up of connected intelligent systems that span the intelligent edge, all the way to the cloud. The expectations of these systems are based on the lifecycle of a typical mobile application with constant feature enhancements. But, how do you know what to deliver next, especially when things are moving so quickly, and as developers are inundated with information and data from a number of different sources? This data deluge can be powerful, but it can also be overwhelming.

Crucially, this is where the power of AI and ML comes into play. AI and ML will aid developers in making sense of the information housed across various data warehouses. In DevSecOps, there has always been an approach to automate everything, and AI and ML will be instrumental in automating the analysis and processing of data – a task that is now far beyond the capabilities of humans.

Incorporating AI and ML will enable developers to better understand and use the data at hand. This will see developers understand not only the error, or the occurrence of a fault, but the detail of what happened in the run up to the fault – vastly reducing the chances of incurring that fault again. AI and ML will also be responsible for enabling the transformation from diagnostics to prognostics across any and all tools and systems, making it easier for developers to anticipate, identify and resolve faults or errors.

Increasingly, we’ll see organizations benefit and drive value from real-time insights. They’ll do this through AI and ML frameworks deployed on active systems to deliver optimizations based on real-time development, validation and operational data. This level of real-time actionable insight bolsters DevSecOps’ ability to achieve CI and CD, through improved, reduced mean time to resolution, easing the impact on operations and, ultimately, enhancing the end-user experience. It remains to be seen if incorporating AI and ML into the DevSecOps cycle will achieve the delivery of self-healing systems that can detect and resolve issues without the need for human intervention. With true AI, however, this might well be possible.

The benefits and potential use cases of AI and ML are widely acclaimed, and while we are still some way from seeing their full potential, the capabilities they currently possess are revolutionizing many sectors. The fact is, if DevSecOps is to continue to keep pace with the vastly growing digital data economy, then it will become reliant on advanced technologies such as AI and ML. Data is powerful if used correctly, but with so much of it to process and analyze, that can be a challenge.

A move toward secure automated processes is the progressive step that many organizations need to consider if they are to realize their digital transformation ambitions. Organizations cannot continue to do things the traditional way and expect to get the results that the new world is looking for.

June 3, 2020
Surviving Through the New Normal
As enterprises move from the first phase of the pandemic to the reopening phase, they’re going to have to determine what tech investments going forward will provide the most value in the their new normal.

Emad Georgy, founder and CTO at consulting firm Georgy Technology Leadership, said that while overall tech spending will remain down, that pain won’t be evenly distributed. Georgy claimed that investments will continue to remain high in the obvious industries, of course, such as healthcare, retail and grocery chains.

“However, multiple adjacent and dependent businesses investments will also remain high. Suppliers of materials required by these industries, companies involved in their supply chain, companies supporting remote collaboration tools will continue to thrive,” said Georgy.

Coming off the heels of the economic shutdown, Alex Milowski, platforms researcher and evangelist at database management software provider Redis Labs, said that both people and systems have experienced significant disruptions, and this has hurt their productivity and strained technology platforms in some ways, while for other job functions platform and infrastructure are at over capacity.

Milowski said organizations needed to strike a balance between the immediate needs of staff, so that they could adjust to the changes in their work and lives and still access critical work systems while also ensuring that customer needs are also met.

However, now that enterprises are looking forward, how do they ensure that their digital transformation efforts remain in place?

As enterprises get their footing as the new economic reality settles in, Milowski advised organizations to focus on small wins.

“Prioritizing projects where one can increase the confidence of the team to function under uncertainty may be the best strategy. New projects may need to be created to address surges in demand via caching or acceleration systems,” said Milowski. “A team might use this time to address auto-scaling systems so they can scale-down as a cost-saving measure. The increased collaboration and creative problem solving will build team confidence in their ability to deliver. With each win, ensure readiness is improving.”

Within those early successes, teams can then troubleshoot their processes with less disruption to their business.

“As their confidence grows, they can ease into picking more business-critical and complex projects. In the end, they are more likely to succeed, with less disruption, as their team is now ready as they know how to deliver new digital initiatives in very different contexts. Successive small wins turn into big wins,” said Milowski.

Georgy indicated that such uncertain times require a sharp focus and prioritization.

“Financial insecurity often leads to sharpened discipline which one could argue we should have anyway in an organization. Unfortunately, many companies are plagued by ‘management by assumption.’ That is the practice of managing and deciding based on opinions or second-hand knowledge because they don’t have time to [dig into] the weeds,” he said.

It’s time to prove concepts out. Georgy added that it’s more important than ever to make data-driven decisions based on experiential learning.

“Opinions are no longer welcome. Every person at the decision table must justify their decisions with data, with real-world experience and with action,” he said.

That can be done by CIOs as they track their changing customer base.

“Customers are changing how they spend and re-evaluating what is important to them and this will be reflected in roadmaps as well. Now, more than ever, feedback loops, usability groups and touchpoints with customers to understand this changing dynamic is key to evaluate new approaches and priorities in the roadmap,” said Georgy.

John Belden, project execution advisory services practice leader at UpperEdge, stated that now is the opportunity for CIOs to lead in a way that hasn’t been readily possible in more than 20 years.

Belden advised CIOs to:
- Take the lead: CIOs can win back the seat at the management table that they enjoyed during the Y2K era. By proactively reaching out to work with counterparts in HR, marketing and supply chain, CIOs can shift from order-taker to problem-solver, which will also help in prioritizing projects.
- Determine an approach to road-mapping: There are likely to be three different strategies to road-mapping and navigating this time:
1. 1. Reinvent: This approach establishes a clean sheet of paper and takes a more traditional approach. Companies that could never get the cash or attention to build a roadmap, might have this work thrust upon them if corporate boards demand a pandemic risk mitigation plan.
  2. Revise: This would involve the shuffling of the existing portfolio, some reprioritization and confirmation of direction from the various vendor’s strategies.
  3. Accelerate: Some companies may have already charted a course that accounts for assumptions of a new world order. In these cases, it is likely that CIOs will be asked to accelerate to either leap-frog competitors or solidify their competitive position.
- Transform vendor engagement strategy: The onslaught of vendor marketing initiatives and client targeting strategies could end up being like the wild west with cloud providers bypassing traditional IT channels to market their wares. CIOs need to work proactively with their business counterparts to set the ground rules for engagement and craft a strategy that motivates suppliers to assist clients in developing their own strategies that can be realized quickly and efficiently. Developing a long-term view in managing the short-term downtime will, in the end, pay dividends in executing during this economic downturn.
Short-term survival with an eye on meeting long-term goals is key to survival, and in the months ahead those enterprises that successfully meet that balance will set themselves apart.
May 27, 2020
5 Reasons Your Legacy IT Management Tools Are Holding You Back

Even before the onset of a global pandemic, IT professionals were coming to the conclusion that their legacy tools were no longer fit for the demands of today’s modern organizations. Their tools have likely met the needs they were originally purchased for, but chances are they’re insufficient to help organizations grow, innovate and move their IT teams from a cost-center to an engine for digital transformation and business success for one simple reason: those tools weren’t built for it.

If you look at typical legacy IT monitoring and management tools, you’ll find point solutions that were built in-house are more likely purchased from smaller, point-tool companies. They’ve been augmented, updated and patched as far as they can stretch. Any integration is most likely of the swivel-chair variety, relying on your IT team to jump back and forth among different tools and screens in an attempt to piece together the bigger picture. Bolting afterthought add-ons onto an outdated system is not an effective way to deliver a unified, predictive, automated, machine learning-driven IT management system that can meet the challenges and demands of today’s increasingly digital enterprises.

So, with that being said, let’s take a look at five reasons why your legacy tools are holding your IT team back.

Legacy Tools Weren’t Built for the Cloud

Legacy tools were built for a physical or virtual IT infrastructure that resided within the walls of your data center and under the control of your IT team. They were designed to manage monolithic applications — a single system that scales or changes very slowly and is disconnected from other services and systems. Plus, they were built to deliver data the IT department cared about, not the key performance indicators (KPIs) that drive your organization’s success. The tools you use today that provide domain-specific capabilities already struggle to track and manage complex systems. This difficulty increases when those tools need to manage an infrastructure that comprises multiple hosted cloud solutions or loosely coupled microservices.

Whether your IT operations are completely or partially on-prem, you know your future investments will be in the cloud, and senior leaders are keeping a keen eye on that investment. You’re committed to the cloud journey, but your current tools don’t map your new application destinations. You need to make appropriate investments in tools built to monitor and manage more than physical and virtual IT infrastructure. The tools you invest in today must be able to keep you and your business informed regardless of where your key applications reside and operate, and be future-proofed for whatever technological disruptions come next.

Legacy Tools Have Stretched as Far as They Can

Have the demands on your IT department and your network changed since your current tools were planned and implemented? Legacy tools weren’t designed to handle the demands you face every day. The tools themselves are likely operating at the limit of their capabilities, and they certainly weren’t built to take advantage of the new world of data. Today’s environments produce data from increasingly diverse sources — including containerized workloads, microservices and unique SaaS provider APIs. Applications themselves are now highly distributed, making it even more difficult to collect and use incoming data to gain actionable insights in the environment.

Inflexibility in tools often becomes a key limitation in your organization’s ability to rapidly adopt and operationalize new technologies. And if they’re already struggling today, what does that mean for next year, or three years from now? What happens when your tools prevent you from capitalizing on your business’s most critical services? They become barriers to success. The tools you use will often dictate your outcomes. Modern tools need to be as agile and flexible as the demands you put on them. They can bend, but they should not break.

Legacy Tools Were Not Built for Empowering Digital Transformation

If we’re honest, many of the legacy tools still in use today aren’t very different in design or function than the first IT monitoring and incident management tools that defined the market. In fairness, the demands on those tools did not change much once they adapted to virtualized workloads. Back then the demands on IT were simpler and mirrored the organization’s mission: keep everything up and running.

Management tools gave you numerous dashboards to identify specific issues in limited context. You would seldom be able to get an end-to-end perspective on your applications and infrastructure. If the environment was large or complex, you typically had to choose between moving between numerous instances or having significant gaps in coverage.

These days you may find your IT organization judged by very different criteria, including cost metrics and revenue goals, in a much more complex and diverse landscape. That’s because the mission has changed. You’re expected to be a primary driver of digital transformation, including the adoption of new technology distributed across multiple environments. You won’t be able to do that effectively with tools designed before broad cloud adoption and mobile customer engagement. Modern tools must empower both the IT organization and the business, because technology has become a critical component of every organization and a direct line to the customer.

Legacy Tools Are Domain-Centric

Systems built over time often include a variety of tools, most of which were designed to only handle specific tasks. Combine this with the tooling sprawl that occurred with the adoption of agile development and DevOps and you have a kaleidoscope of complexity, making it very difficult to collect, aggregate, correlate and analyze all the data necessary to view and manage overall business service health and performance. IT departments need a single tool that can handle diverse use cases and provide the right information for the right context. True AIOps platforms were built specifically to address that need.

Legacy Tools Lack Intelligence

Legacy tools are still mostly reactive rather than proactive, let alone predictive. The “AI” in AIOps stands for “artificial intelligence” (even if the functionality is actually machine learning-based). The value of machine learning for IT is pretty well established. The machine learning at the core of AIOps solutions allows them to automate repetitive monitoring and incident management activities and, as they learn, predict an incident before it happens.

While some vendors will tell you they can graft AI-like features onto their legacy systems, at best they’re trying to fill gaps and plug leaks. Only a system built from the ground up with machine learning at its core is able to offer true AIOps functionality and quickly adapt to meet future needs. Learning systems must not be an afterthought, but core to your tooling strategy with intelligence present at every stage of the operational life cycle.

Now Is the Best Time to Investigate AIOps

This is a difficult and challenging time for everyone that raises unique challenges for IT professionals. Recent events have highlighted both successful technology implementations and lingering legacy challenges. I would suggest it’s never been more important for IT teams to ensure alignment with the overall business and show their value beyond the basics.

An AIOps approach can help you succeed in today’s complex technology landscape and reduce cost by consolidating outdated tools that have been holding you back from your true potential. AIOps is the best option to make your IT department more efficient and cost effective while improving your overall customer experience. I’d argue that these are the KPIs that matter most to your organization during these uncertain times. Most of us have a new perspective on the impact unexpected conditions can have on our technology systems. If you think you’ll be asked to reconsider your IT priorities and goals in the next few months, now is the time to build an informed plan.

May 26, 2020
LogicMonitor Releases IT Downtime Detection and Mitigation Study
Although 99.999% availability may be IT’s ambition, it’s far from reality. In March 2019, Google’s Gmail experienced a 4.5-hour global outage. In the same month, Facebook suffered a 14-hour outage, its most massive outage to date, crippling app-accessibility worldwide.

Downtime and low availability will likely occur to all systems eventually, especially when introducing code changes. When outages occur, it’s truly the detection systems and smart mitigation processes that separate quick rebounds from long recoveries.

LogicMonitor has released its IT Downtime Detection and Mitigation Report, a survey of IT professionals to uncover trends and tactics impacting availability in 2020. The report surveyed over 300 IT design makers at organizations with 2,500 or more employees within the U.S., U.K., Australia and New Zealand.

Below, we examine the LogicMonitor report’s key findings. We’ll discover, on average, what sort of projects are causing the most outages and brownouts. We’ll also see what strategies top IT teams are using to prevent, detect and mitigate disruptions.

Which Transformation Initiatives Hurt Availability the Most?

Ninety-six percent of organizations surveyed had experienced at least one outage in the past three years. But why? One reason LogicMonitor conducted this report was to pinpoint which digital transformation initiatives and IT trends are the leading contributors to high-profile outages and brownouts.

When determining causation, answers revolve around novel cloud IT initiatives. Fifty-nine percent of respondents felt that mobile computing was causing more brownouts/outages. Fifty-seven percent found AI and edge computing were making outages more common. Other high-ranking reasons included digital transformation (57%) and IoT (53%).

According to the report, “LogicMonitor’s research suggests that IT decision-makers hold IT transformation initiatives responsible for increasingly frequent outages and brownouts.”

Though we generally view digital transformation initiatives in a positive light, they do come with caveats. The move from private to cloud infrastructure, for example, can bring unforeseen costs. Also, some authorities note a lack of talent specializing in cloud and hybrid environments. The report also suggested that accelerated cloud technologies may require time to mend before they realize positive business returns (and higher availability).

Critical Strategies for Preventing Outages

Another goal of the study was to discover what sort of tactics IT professionals are actively using to prevent outages.

The study exposed many strategies that IT folks are currently undertaking. The top three tactics were performing preventative maintenance (75%), reviewing system logs (71%) and increasing the capacity of systems (71%). Other top strategies included designing redundancy into systems, and keeping an eye on customer support tickets.

With the rise of a completely remote workforce, some IT executives do anticipate higher expenditures due to AI and cloud architecture, which could bring added pressure. However, it’s worthy to note the cloud hasn’t negatively affected all groups, or even reached all companies. According to another study conducted by Adobe and Fortune, only one in three organizations store their data in a public cloud. Of course, one could argue that in doing so, such companies substitute innovation for less breaking change.

Another necessary aspect to keep a vigilant eye on the digital ecosystem is proactive monitoring. According to the report, 74% of teams rely on proactive monitoring to detect outages. Continuous monitoring has been a philosophy trumpeted time and time again by DevOps professionals to enable a better release frequency and a window to detrimental interruptions.

Careful analysis ahead of time, active monitoring systems to spot problems and continuously reviewing system logs were the most important tactics found being applied by IT leaders to mitigate found outages and brownouts.

Best Practices: Prevent, Detect, Mitigate

In terms of takeaways (other than the ultimate LogicMonitor product sell), the IT Downtime Detection and Mitigation Report does reveal some interesting trends on what IT leaders view to be leading causes of system outages. It will be interesting to see how this evolves and what technologies mature (or remain headaches) into the future.

The report leaves IT professionals with some common, albeit helpful, advice to consider going forward:
- Actively monitor IT systems.
- Optimize IT systems with forecasting.
- Prepare for tomorrow’s IT norms today.
- Use intelligent monitoring.
- Design redundancy into your systems.
May 14, 2020
Digital Transformation Is More About a BizDevOps Culture than Tech

Digital transformation is top of mind for every organization now. The problem is, many of these organizations take the phrase too literally and think it’s all about adopting new technical capabilities and tools. Tech is certainly a part of it, but real digital transformation is also about changing company cultures and ways of working. Tech and culture go hand in hand for digital transformation; you can’t change one without the other.

Successful digital transformations mean redefining the way IT works, breaking down the silos between the development, production, UX and business teams in a way that cultivates greater collaboration, unlocks new business value and simply makes work better for everyone. All of that comes down to pivoting to a BizDevOps culture that creates more visibility, and positive reinforcement, for engineers and developers.

Building a Cultural Transformation Around BizDevOps

The goal for BizDevOps is to move development and production teams away from nursing applications and tediously staring at dashboards, and align them closely with the business side, so that they’re putting their time and energy toward delivering more business-relevant services. Shifting gears to a BizDevOps structure is its own culture transformation. Eliminating the silos between teams encourages better cross-collaboration and opens up new visibility for developers to see how their work is being received by users and impacting business value for the organization as a whole.

But, breaking down these silos to get engineers more engaged in production introduces another challenge: Those developers are already busy building products and features that they’re responsible for. Why would they want to get involved in production on top of all their other work? Overcoming this hurdle means making concerted efforts to give developers more visibility into production environments. More than that, it means exposing developers to more positive feedback.

Encouraging Engineers Through Constant Feedback

What makes engineers feel proudest about their work? When they see how it’s being used and enjoyed by their target audience. The problem is engineers rarely get that kind of feedback. The feedback that is typically sent back to the engineers are critical comments and complaints; they rarely see or hear the good things, just the problems they have to fix for the next iteration.

When you consider that, who could blame engineers for feeling discouraged or unwilling to want to take on more work? From their perspective, it’s not just about adding more to their plate, it’s also taking on more negativity and more criticism.

But it doesn’t have to be that way. What if engineers were provided with immediate feedback on all the new applications, features and services they were creating? Both the good and the bad, in real time? That’s part of the key to facilitating a BizDevOps culture: When engineers are seeing how the products they put out into the world are being enjoyed, as well as the positive impact they have on business value, they’ll naturally begin to feel more appreciated and also more reaffirmed that they are doing good, meaningful work and that they’re having an appreciable, positive impact on users and the whole business. This doesn’t mean putting on blinders to negative feedback, but it’s easier to act on negative feedback when it’s balanced out by positive feedback, too. Exposing engineers to more feedback about the impact of their work might also help inspire them to have new ideas and drive new innovations. The more information you’re armed with, the better position you’re in to innovate.

Organizations need to prioritize building easy ways for developers to have this visibility in their environments where they’re getting immediate feedback from end users, both the good and the bad. The more feedback they receive, the more encouraged by, and invested in, their work they become and, consequently, the more responsibility they feel for their contributions to the business. With that responsibility comes the culture change you need to digitally transform.

Top-Down Support

This culture change can’t happen without executive buy-in. The C-level needs to provide the necessary tooling and clarity on new organizational structures to break down silos between the development, operations, business and support teams, and then shepherd those teams into a more collaborative and visible environment. That support creates the foundation for a wider culture change, one that encourages a transition from operations to development and enables a bigger shift to BizDevOps.

Imagine the silos between teams as vertical walls. Now, shift those walls 90 degrees. That changes the structure so that your platform and autonomous cloud teams are sitting on the same level together, providing services across the organization, delivering software into production at faster speeds while simultaneously achieving visibility across the whole environment.

The democratization of data enabled by this level of visibility is helpful in another way. When all teams have access to the same data, and can see what each other is working on and how all that work moves toward a shared goal, it drives everyone to find new ways to make each team’s workload lighter–such as with automation. When teams are not just automating their own work, but automating each other’s because they see how lifting one group lifts the whole organization–and has a concrete impact on business value–that’s what BizDevOps is all about.

A Transformed Culture

In the end, every engineering team should think, feel and act like their own startup, responsible for everything from end to end. That spans from what they’re building, to how they implement it, to the impact it has on the end user and the business. Every engineering team needs to be working like this, keeping top of mind considerations like, how can a new application or feature or service be optimized so that it not only runs well, but also runs efficiently? Not just efficient in terms of performance, but in scalability as well.

Think about how cloud providers have potentially endless resources to deploy code. Just because something might run well doesn’t mean it’s running efficiently, and just throwing more code at a situation will inevitably raise costs and hurt overall business value. That’s something that engineers and developers should be keeping in mind as part of their work–not just how to deliver value in terms of new features or services, but how to bring down the total cost of ownership as well.

That’s what digital transformation looks like: A culture shift where new BizDevOps organizational structures, visibility across production environments and immediate access to feedback, both positive and critical, enables all teams to work together in a cohesive way, driven by what creates value for both the business and the end users.

April 29, 2020
The Way Forward: Digital Resiliency Wins

As we wrote in Digital Transformation: Digitally Resilient Organizations, digitally resilient enterprises have built themselves business-technology platforms that are elastic, agile and can correctly position themselves to securely meet current business demands. These enterprises are also constantly learning from their data and adjusting as markets, workforce and customers demand.

These enterprises have also eliminated the bulk of their technical debt and continue to innovate so they aren’t disrupted by competitors with a better idea, execution or understanding customer needs.

Consider the grocery delivery wars, and how the coronavirus pandemic may have shifted the balance. Today, $78 billion retailer Target has a chance to prove, to a delivery-eager customer base, its prior investments in its online services designed to compete with Amazon Prime. Will its new Drive Up pick-up service and Shipt delivery service meet customer demand during this period of social distancing— and keep those customers over the long run—while Amazon tries to manage its way through supply shortages and shipping delays?

Walmart and Instacart have also seen significant usage surges, due to social distancing mandates. According to app store intelligence provider Apptopia, comparing average daily downloads in February to Sunday, March 15, Instacart, Walmart Grocery and Shipt have seen surges of 218%, 160% and 124% respectively.

“We’ve also noticed people in the United States have been turning to Target to stock up on groceries, entertainment and everyday essentials. March 15’s downloads saw an increase of 98% over the average number of daily downloads in February,” Apptopia wrote in its analysis.

While certain industries, such as online food and grocery delivery, may have seen years of adoption growth condensed into weeks, many enterprises are seeing downturns in demand.

Research firm IDC previously estimated that real GDP in the U.S. would reach 2.4%, but downshifted that to a worst case 1.4%. While IT spending dropped from an expected 5.1% year over year growth to worst case 1.3%. IDC pegs the base scenario for GDP growth now at 2.0% and for IT spending at 4.3%.

This has thrown CIO priorities into the air. According to a recent poll conducted by McKinsey & Company, CIOs are pressed to solve immediate challenges. For example, 32% cited increased demands for collaboration services and operating norms for working from home at scale, and facing increased strain on budgets (22%), a medium- and longer-term consideration.

McKinsey & Company advised CIOs to keep their focus on stabilizing emergency measures by strengthening remote working capabilities, improve cybersecurity, adjust ways of working with agile teams and prepare for a breakdown of parts of the vendor ecosystem (supply chain). In the interim, CIOs need to address immediate IT cost pressures to reduce costs, and creatively redeploy the IT workforce, while also pivoting to new areas of focus in the future.

According to McKinsey & Company, many organizations are successfully digitally engaging with customers, and cited a government in Western Europe who embarked on an “express digitization” of quarantine-compensation claims to deal with a more than 100-fold increase in volume.

“Sometimes this effort is about taking loads from call centers, but more often it addresses real new business opportunities. To engage with consumers, for example, retailers in China increasingly gave products at-home themes in WeChat,” McKinsey & Company wrote.

“Technology departments must anticipate and prepare to offer more of these kinds of digital services, products, and channels,” McKinsey & Company advised. “The key to reaching customers will be creating suitable access interfaces between internal IT systems and external social platforms and accelerating the integration of new vendors and distributors.”

In the months ahead, the organizations to move beyond the economic downturn will be those that built the platforms that enabled them to efficiently endure the recession and position themselves to adapt to whatever the new business as usual turns out to be.

April 20, 2020
Embracing the Journey to Public Cloud

One of the fascinating competitions in today’s business world is the one between the digital disruptors—companies whose business vision is rooted in technology and driven by the cloud—and the so-called incumbents.

One sector where this competition is particularly intense is financial services. In this sector, the digital-first companies typically don’t compete with banks and other financial institutions directly. Instead, they target specific functions based on a clear—and often data-driven—understanding of what customers want. This strategy has proven particularly successful with millennials. For example, until recently the norm for giving money to a friend or family member was to write a check. Now, almost two-thirds of 20- and 30-year-olds use payment apps, such as Venmo.

In healthcare, a different pattern is emerging, one where digital-first giants either buy or innovate their way into the sector. Examples include Amazon’s billion-dollar acquisition of the online pharmacy PillPack and the new Apple Watch, which is capable of taking electrocardiograms.

Whatever the sector, digital disruptors have one characteristic in common. They leverage the capabilities of the cloud to the maximum extent possible. A shift in power toward digital-first companies is underway, and the cloud plays a major role in helping these companies establish themselves.

Many incumbents are just now taking their first steps on the journey to the cloud, and still working on the challenges involved in migrating their existing legacy applications to more scalable and agile public cloud environments. While they’re engaged in this process, digital insurgents are already exploiting the full potential of the cloud to deliver solutions that meet emerging customer needs associated with today’s evolving lifestyles.

In highly regulated industries, such as financial services and healthcare, major brands will not necessarily see an immediate decline in their customer base, nor profits. Nonetheless, digital-first companies are capturing millions of customers annually, and this growth poses a considerable challenge over time. Embracing the journey to public cloud is crucial for legacy enterprises.

The most successful cloud-based disruptors use experimental sandboxes as a critical component of development. The public cloud can drive progress toward almost any business goal involving IT—operational transformation, new market penetration, new product launches, automation.

Digital transformation to the public cloud is also the only way companies can leverage storage scalability and the essential innovations of the open-source community. There are still lingering concerns among executives in highly regulated, data-sensitive industries concerning privacy and regulatory compliance, and these can lead to hesitation. The face is, public clouds have been in place for over two decades now, and their security is often superior to older on-premise security. Incumbents can, therefore, tap into the public cloud to ensure safety for mission critical workloads.

To accelerate the transition to the public cloud, consider the following best practices.

Learning to Fail Fast and Learn from Experience More Quickly

The Silicon Valley maxim to fail fast may run counter to incumbent corporate culture, but it is the best path to success in the new digital reality. The key is being able to learn from failures quickly and adjust accordingly.

Partnering for Progress

A digital native approach to business is often lacking in the corporate culture of incumbents. Cloud partners that have a digital disruption in their DNA can play an important role in driving cultural renewal at every level of the organization. A reliable cloud service partnership can accelerate concepts, pilots, staffing and other mechanisms designed to deliver value quickly and securely.

Re-Examining Compliance Processes

Operations should be streamlined to transform enterprise IT to be well-suited for the cloud. Companies can apply artificial intelligence to supplement human intervention, and encourage cloud adoption among employees. First, building a solid foundation, then working your way up, enables businesses to make important changes that transform the enterprise into an environment that is compliant by design.

Successfully competing with digital natives means using the cloud to find new opportunities to streamline and better comprehend customer needs and behaviors. It also means being unafraid to change time-honored business practices. At the same time, in highly regulated and data-sensitive industries, compliance and security must be prioritized. Cloud transformation has quickly become vital for companies in all sectors and represents an essential foundation for future business success.

April 17, 2020