On Cloud

When digital transformation initiatives struggle, the blame often gets assigned to the technology implementation. However, in many cases, it's actually more of a people than a technology issue. Fear of change often plays a critical role in project failures. In this episode of the podcast, Mike Kavis and guests, Jeffrey Fredrick and Douglas Squirrel, discuss barriers to digital transformation success and how fear of change can hobble success and set the project team—and company—up for failure. Their solution is to reduce fear—and promote collaboration—by understanding what motivates people, embracing differences, building trust, and modeling behavior that produces positive changes.

Edge computing has the potential to revolutionize IT—especially the way organizations interact with customers. But the edge space is still somewhat of a wild west, and there are competing theories of where it should go and how it can be utilized most effectively. There are even competing definitions of what "edge" truly is. In this episode of the podcast, David Linthicum and Edgevana CEO Mark Thiele break down edge computing—what it is, and isn't, and ways companies can leverage it to help create better value for customers. Mark also gives his take on what an edge-enabled future would look like, and he gives some pointers on how organizations can build a path to get there.

With a shift to cloud, it's crucial for organizations to re-evaluate how they approach security—specifically how they evaluate risk. It's always been critical to take a proactive, predictive approach, but with cloud that criticality is magnified because of the distributed nature of cloud computing. In this episode of the podcast, Mike Kavis and guest, Trend Micro's Mark Nunnikhoven, discuss evaluating risk in the cloud. Mark's take is that, while cloud is more secure because of its shared-responsibility model, predicting the likelihood and type of security events is still incredibly difficult. He also argues that, even with the application of AIOps to bolster predictive capabilities, humans still need to interpret model results and make final decisions on which actions to take.

This special episode of Deloitte's "On Cloud" podcast focuses on the role an integrated core plays in recovery and lasting resilience, with examples of how companies are integrating AI, cloud and cyber today.

Once considered to be an unusual development methodology, open source has come into its own. Companies now understand that they can take advantage of different perspectives and collaboration in the open source community to drive cloud innovation and deliver better products faster than ever.

We already live in a connected world, but technologies like cloud, edge computing, ML, and 5G will profoundly reshape the way people and technology connect and interact with each other, and they will usher in a future that is scarcely imaginable now.

There are a bevy of new technologies in the market to help with IT ops in the cloud--AIOps for example. However, to get the most out of AIOps (or any tech), match the tool to the needs and define the needs--and success metrics--based on your service-level objectives.

Software testing isn't glamourous, but it's critical. It's also often misunderstood or siloed. However, DevOps has highlighted the importance of testing and the cloud has transformed the testing process, making it faster and easier and freeing up resources to focus on human-centric testing.

Using FinOps to more effectively govern cloud usage and match cost to need to value can help organizations avoid potentially costly reactions, such as overprovisioning.

The COVID-19 pandemic and resulting economic downturn have most likely accelerated a shift to cloud for some companies. Why? Because cloud provides the agility and scalability that can help companies weather this, and other crises, more effectively.

The disruption caused by the COVID-19 pandemic has encouraged many companies to accelerate their journey to cloud. The impetus? Improved security and business continuity, as well as the scalability to handle this disruption--and the new normal it will create--more effectively.

The world is in crisis, and many businesses are too. However, with the elasticity to enable organizations to scale to need, cloud can help beat back some of that disruption by helping maintain business continuity, which--aside from keeping safe right now--is a top priority.

Intelligent automation can change the way companies automate much of the software production and management process. That's a good thing, but some companies are hesitant. However, in this new "normal" organizations should welcome tools that can help them manage disruption and stay competitive.

The current environment is unprecedented--at least in modern times, and organizations need a strategy for continuity. With its ability to scale to need, cloud can help. Also key will be rethinking operational and IT strategies in the new normal when things settle down.

Cloud adoption is growing, but one obstacle organizations face is a lack of cloud skills within their IT ranks. One solution is to build a cloud learning center to give workers the skills they need to help their companies more effectively realize the potential of the cloud.

Cloud is transforming the way business is done, but many companies are reluctant to fully automate business processes--especially where data security is a concern. To overcome that reluctance, and gain efficiency, it's crucial to implement effective cloud-governance policies.

Technologies such as artificial intelligence, machine learning, and automation are the future. Companies that invest in new technologies can use it as a force multiplier and reap enormous benefits, but they must retrain their manual workforce to focus on value-added activities.

There's a growing need for top talent in the cloud space and not enough people to fill it. One possible solution? Get more women into the cloud talent pool, mentor them, promote them, and help them become the next generation of great cloud leaders and innovators.

Workflow management is designed to make IT operations flow more smoothly. However, that's not always the case, as the management process often becomes the issue to manage. One solution: effective tools, along with a common language to implement the workflow management process.

New changes in accounting rules may provide more beneficial accounting treatment for cloud costs. However, there will be challenges in implementation. To more easily navigate the changes, companies may need to put new controls in place and invest in more process automation.

Once relegated to IT infrastructure and middleware, open-source software has gone commercial. Cloud providers are taking notice, and the push to leverage open source at the application layer holds tremendous potential to power the future of cloud and drive innovation.

2020 promises to be a breakout year for cloud. But to take advantage of the cloud's potential, companies will need to focus on leveraging AI advances and edge computing, as well as investing in enhanced security to build and keep user trust.

Struggling with delivering apps on time and in budget? Many companies do. Often, the reason is invisible work that robs time from the development process. To fix it requires identifying, and remediating, pain points caused by invisible work, i.e., catching the "thieves" that steal your time.

Even with firm resolution to move to the cloud, many companies struggle with complexity management. Having a thorough understanding of your application environment and a solid strategy to get to the cloud can help. So can putting development guardrails in place and focusing on security.

As the cloud matures, many companies aren't reaping the value they expected. For some, it's because they haven't transformed their IT operations as they've digitally transformed. To maximize the cloud's advantages, however, it's essential to match IT Ops transformation with cloud adoption.

It's not too much to say cloud has changed the way the world works. However, challenges such as data issues, economic concerns, and cloud complexity still remain--and are imperative for companies to solve. Those that do will be well poised to define the future of cloud.

The cloud space is ever-changing, and 2019 was no exception. Top trends included AI, Kubernetes, and cloud-complexity. 2020 promises more complexity, exploding AI/ML use, and business taking the lead on driving cloud expansion.

Despite being a relatively new practice, DevOps is already experiencing big changes. New disciplines, consolidation among vendors, and competition to introduce new, better technologies are making DevOps an exciting place to be right now--and in the future.

IoT has revolutionized the capabilities of countless consumer products. Now, Deloitte has introduced Smart Factory Fabric powered by AWS, a suite of services designed to revolutionize IoT and help manufacturers reimagine their business.

Machine learning has revolutionized analytics, yet it still has untapped potential. This year at AWS re:Invent 2019, AWS introduced new ML offerings, as well as a collaboration with Deloitte, to help companies enhance their ML capabilities, make them more secure, and speed up implementation.

At AWS re:Invent 2019, AWS introduced new, exciting, and evolutionary products and services in the cloud space. There's lots of buzz around IoT, machine learning, and 5G, making companies smarter—and helping developers move more operations to the cloud.

Despite the strong imperative to digitally transform, many companies still struggle with it. One strategy is to adopt a cloud-native mindset that leverages AIOps and shifts DevOps bottlenecks left to re-think software development, delivery, and deployment in a cloud-native world.

As the panoply of cloud vendors and products grows ever larger, so does the configuration and management complexity of the cloud. For many companies, this complexity can reduce the value of their cloud-computing investments. In this episode of the podcast, David Linthicum and guests, Intel's Lisa Davis and Deloitte's Doug Bourgeois, discuss ways companies can tackle cloud complexity and leverage multi-cloud architectures to help optimize cloud deployments in terms of performance, cost, and agility. Lisa and Doug also argue that companies need to realize that hardware isn't a commodity and that cloud architectures—and talent acquisition decisions—must be driven by mission-critical business needs and workloads.

There's little doubt of the value of agile and DevOps, but many companies still struggle to innovate with IT. It's often because they're stuck in a project management paradigm. One solution is to focus on product value streams and measure the business value delivered by software.

DevOps is a boon to software development and delivery, but companies sometimes struggle to get DevOps right. Most often, it's a people, rather than a tooling issue. Successful DevOps takes the right people and leadership, and a view from a product, rather than a project, lens.

Many companies struggle with technology in general, and cloud migration in particular. What's needed is a fresh perspective—a new look at how to accelerate what's possible. Savvy companies understand that to be able to drive increased value, they should increase diversity in the tech workforce. They also recognize the need to better understand and navigate the massive disruptions and cultural changes that come with their cloud computing journey. In this episode, David Linthicum and guest, industry thought leader Rashim Mogha, discuss ways companies can build a more inclusive, diverse workforce and manage the disruption that comes with digital transformation. Mogha's recipe for success: give everyone a seat at the table, automate, manage disruption, and focus relentlessly on building an adaptive culture from the top down.

Cloud architectures are incredibly complex and, often, it's all but impossible to predict and prevent failure scenarios. Enter the ascendant discipline of chaos engineering, which aims to discover cloud failure points, in in-production systems, before they become disasters.

Increasingly, companies are realizing that their cloud migration journey is defined as much by their culture as by their technology choices. Indeed, effectively managing the seismic changes that come with cloud computing is key to enabling a successful cloud adoption strategy.

Companies often struggle to develop efficient cloud-native application environments. Frequently, it's because they haven't implemented product-oriented, enterprise-ready application delivery methods. Those that can make the shift, however, can reap enormous benefits.

As DevOps matures, and the "shift-everything-left" philosophy gains ascendancy, there's a movement to automate all—or most—phases of testing. However, there are some critical functions that may resist automation. In fact, contrary to the "automate-everything" impetus, human testers won't ever go away. Indeed, human testers need to be more involved, and earlier in the development process. In this podcast, Mike Kavis and guest, Angie Jones, discuss the human aspect of testing and how humans add significant value by assessing the system as a whole, helping developers design better code, and determining the level of testing automation that should occur. Angie also shares the testing automation matrix she has developed. Finally, they cover testing of machine learning algorithms—ways to help prevent or reduce bias and make algorithms more effective, and the emerging field of visual testing, which uses humans to ensure that graphics-heavy apps function and appear as designed.

The current hype cycle is all about 5G and its tremendous promise. That promise may be fulfilled someday, but right now the IoT and edge technologies are helping organizations across all industries revolutionize their business and view most technologies through an as-a-service lens.

Yes, there's complexity in the cloud journey, but that doesn't mean that the cloud isn't the place to be now, and in the future. As cloud adoption rises, it's important to understand which apps are right for the cloud and to manage complexity to make cloud adoption easier.

Because of its flexibility, Kubernetes is delivering on the promise of PaaS for cloud app deployment. However, container management is complex, and there are often gaps with orchestration engines. Companies that manage Kubernetes effectively, though, can reap the benefits--especially at the edge.

Many organizations are wowed by new cloud tecnologies and deploy them to solve specific issues. Instead of getting the magic bullet they hope for, sometimes they only add to their cloud complexity. However, one key to cloud success is a sound strategy that drives business value.

The tax function has historically been reluctant to fully embrace the cloud. However, regulatory demands, coupled with the need to gain more information security and deeper insight into performance, is pushing them to adopt the cloud. The payoff for companies that make the leap can be huge.

Developing scalable, efficient cloud architectures requires fresh thinking. Infrastructure as Code, along with other tools like Kubernetes--when properly managed--can help companies create robust cloud architectures that produce more value from their cloud journey.

The cloud's value proposition is almost limitless, but as deployments become more complex, cloud complexity can degrade that value. To manage cloud complexity effectively, leading practices include increasing agility while focusing on improved governance, automation, and data architecture.

Where DevOps meets security you get DevSecOps, but are companies doing it right? If not, how can they avoid the seven deadly diseases of DevOps?

Despite rapidly growing cloud adoption, mainframes remain at the core of IT for many large companies. Migration from mainframe to the cloud can be challenging, but the right strategy and tools can ease the transition and bring tremendous benefit.

When applications fail to live up to their promise, technology isn't always the culprit. Often, the failure is a result of ineffective teamwork. To combat the problem, successful companies are building better teams and improving communication throughout the DevOps process.