Improving Software Delivery Process by Shifting the Balance Between Security and Speed

Alex Thompson Digital Engineering March 24, 2022

Software Delivery with DevSecOps

Few things are more important to software delivery with DevSecOps than finding the balance between security processes and speed. When security measures are shifted to better catch problems early in the development process, the process moves along faster, and application speed becomes more efficient.

Companies are slowing down the development of their applications due to intricate security measures implemented at the wrong time. While this is expected on a certain level, it’s challenging to find the balance. In the world of development and security operations, it’s a constant tug of war regarding which aspect of the application should trump another.

For most businesses, risk management and security measures for their data and sensitive customer information always come first, but what can they do when security is drastically slowing down the performance of their systems, thwarting new customers, and frustrating existing ones? Making a choice here is challenging, primarily because you know the right one.

It’s crucial to know how other businesses implement their security processes when you’re trying to correctly employ security features into your development operations (DevOps). Knowing the standard approaches for DevSecOps can help you decide the path you’d like to take on the subject and assist you in figuring out what will work best for your business.

The Components of DevSecOps

DevSecOps has quite a few components that should be identified when learning how to balance security and speed. Areas such as design and people management are just as important as quick application response time and state-of-the-art security measures.

No single approach will work across the board when it comes to DevSecOps and automated security testing. Every company has different goals and application requirements, and it’s best to determine what you need before you begin hashing out a thorough development plan. A solid understanding of your organization and your goals as a business will encourage you to move forward.

Of course, DevSecOps and the delicate balance between speed and functionality don’t come without challenges. To address those difficulties head-on, you should know the problems that your own company faces, both current and projected.

Shifting security means doing more security upfront as the development lifecycle of your software unfolds. One of the main points behind software delivery DevSecOps is to acquire assurance without friction while utilizing more automation.

Know Your Level of Risk Management

When discussing software delivery with DevSecOps, experts and industry enthusiasts will always address the topic of risk management. Businesses must realize that risks look different for every organization, and you have got to have some idea regarding the level of security risk your company faces each day.

For organizations that are just beginning their journey to balance security and speed through the proper implementation of DevSecOps, you’ll likely notice there is a tad more wiggle room when it comes to the tolerance presented for security risks. As your business grows and your development and security operations become more concrete and evolved, risk tolerance goes way down.

Not only do you have less room for risk as your software implementation develops, but you’ll also catch possible risks earlier on in the development process. In the gating process, also known as the beginning of DevSecOps employment, you’ll gauge your risk tolerance level and aim to lower it.

In general, most companies face risks that are unbeknownst to them. Unfortunately, it’s one factor that comes into play when running a company. Begin by setting achievable goals and fully understanding that you’re absolutely going to discover new risks along the way.

It will all be worth it in the end. Not only will you increase the speed of your applications, but you’ll put security measures in place that you would have never otherwise known you needed.

The DevOps Tools Needed for Development Operations

A few tools are needed to support development and operations so that weaving security into the mix is possible. Continuous integration (CI) and continuous deployment (CD) are necessary to integrate application and data structure changes as they come and to deploy all changes to the testing and production teams.

CI/CD are the components of DevOps that work undeniably well together, and they’re needed to avoid integration challenges in development and production. Before you dig into the nitty-gritty of DevSecOps, you must have the correct tools in place within your DevOps program.

Understanding DevSecOps

Now you know the fundamental aspects that make up DevOps and DevSecOps, but do you fully grasp the difference between the two? What exactly is DevSecOps, and how can you make it work for your company?

DevSecOps (or Development Security Operations) is the process of integrating security into the DevOps cycle. It’s all about making security easier for development teams. If you can figure out how to make things easier for them, you can be confident that security and development will become (somewhat) flawlessly intertwined.

A good company-wide understanding of security and software delivery with DevSecOps is indeed necessary to succeed in DevSecOps overall, but you’ve got to decide what that means to you. DevSecOps means a few things for most businesses, including building a security culture, shifting security, automating testing and assurance through digital modernization, and governance of the operation to establish what works.

While all of these aspects are incredibly important, we’re going to discuss shifting the security balance left to gain better application speed while maintaining safety levels. Let’s get into it.

Shifting Security Left

Hearing the phrase “shift security left” can be highly confusing for many development teams and business owners, but it doesn’t have to be. Shifting testing to the left means that you have to do more testing early in the development process to avoid running into issues later on. A shift in security can save money while moving along with application development.

Shifting security left doesn’t apply only to testing but focuses on security requirements as well. If you’re going to move your security to catch problems in the beginning phases of development, then you’ve got to change security all around.

When it comes to testing, DevSecOps teams should focus on the following:

Soft gates are what you’ll want to utilize at the beginning of the development process when risks can be assessed and mitigated. At the same time, the team moves forward with their primary focus, which is (obviously) software and application development.

Hard gates come later down the line, where you’re less likely to survive significant security risks, and if discovered, production should halt until it’s rectified. As a tech leader, you’ll set the criteria for your soft gates and hard gates, determining where the team should move forward and where they have to stop due to the risk level.

Set the risk levels to where they’re acceptable for your business, and go from there. The idea behind evaluating and implementing risk levels is to increase development and speed regarding development. Shift security left, and automating the process as much as possible, will allow you to make decisions in real-time.

Transform Your Security Culture

One of the most critical parts of establishing a security-first attitude and increasing development speed is to focus on the people. You have to build a security culture within your business by nurturing security skills and knowledge and eradicating a lack of understanding.

When security is emphasized at every production level, it becomes difficult to ignore the potential security issues that pop up because that’s where the team remains focused. Security is definitely a niche all on its own, and it can be challenging for people to grasp every intricate detail.

The only way to truly combat a lack of knowledge is to develop a training program that touches on every aspect you need to cover to catch your team up to date. Hands-on training is the best way to teach security within development teams. You should know your team quite well, which will put you way ahead of the game regarding how to help them learn.

Security scalability focuses on spreading the knowledge of a handful of people to various teams within a company. You can scale security knowledge to your development teams by using outside tools (such as learning applications) and developing incentives for skills gained.

It seems silly from a professional perspective, but giving your team a goal to work toward, even if it’s a teaching program, can raise morale and stress the importance of grasping the importance of security throughout the development process.

Security and then Speed

If you’re unsure where you stand regarding security and speed, you’ll want to restructure your IT strategy to put security first. Gone are the days when placing security before development slows down the process significantly, especially if you shift your security and focus on it at all times.

By harboring a “security-first” workplace culture, you’ll find that employees from every team will catch issues and flag them as the process moves along at an acceptable, agile pace. Also, you won’t have to halt production before your application launches, which most business owners can agree is ideal.

Driving Innovation Through Data Architecture

Alex Thompson Data and AI March 22, 2022

Data Architecture

Data architecture is more important than you might think to modernize your applications and drive team and company-wide innovation. Agility is the driving factor behind updating legacy systems and creating an overall successful upgrade.

The data architecture of today demands flexibility and consistent innovation. However, it can be difficult for companies of all sizes to incorporate flexibility into their existing systems while focusing on deploying new data technologies to flow with the times.

Consumer markets continue to drive external innovation, encouraging development teams to create ways to better connect with them. Predictive maintenance, real-time alerts, and personalized offers are options that consumers expect from their applications and the businesses they choose to utilize.

The Result of Technical Additions

Data architecture becomes more complex when companies embrace technical additions to older applications, such as stream processing and detailed customer analytics platforms. When data architecture gets too involved, it can create a data lake and hinder the ability of your organization to efficiently deliver new features and capabilities to consumers and ensure the integrity of your AI models.

In short, too much data in the mix means inaccurate AI results and applications that cannot work correctly. Due to current market demand, slow systems are never an option. Today’s consumer is looking for speed and efficiency around every corner, and unfortunately, if your organization cannot offer them that, there is one right behind yours that can.

So, how can you continue to build your data architecture without failing and super slow systems? As usual, the answer lies in technology and utilizing artificial intelligence and cloud migration. As companies increase the amount of sensitive and vital data they deem necessary to operate, cloud providers have focused on data modernization while launching features that make lives easier and new and old systems faster.

If the amount of data you have is slowing down your business processes considerably, it’s time to look into how you’re stacking your data. Data modernization is essential to build a competitive edge successfully, and there’s no longer a way around it.

Shifting Your Data Architecture

Before we dive into the steps you can take to change your data’s architecture, it’s crucial to understand that cloud provider and serverless data platforms have become necessary regarding information storage and access. If you have zero intentions of moving your data to the cloud, you’ll find that you consistently fall behind, even if your data architecture is relatively sturdy.

We exist in a time where analytics tools are the key to success, and businesses need to market faster and with agility. There must be room for flexibility, and the only way to achieve that within your ever-growing data pool is to migrate to the cloud.

Practices such as adopting APIs will give you immediate information regarding your data lake and deliver it to the front-end analytics. The need for efficient data storage has been on the rise for decades and was merely amplified by the COVID-19 pandemic, when the world turned to the internet for, quite literally, everything.

As we prepare to exist in what we can only refer to as our “new normal,” companies on a global scale must make significant shifts in the way they define, implement, and store data stacks. Leveraging new concepts, the cloud included, is the only way to do this and avoid system overload and failure.

Encompassing all Components

If you want to change the structure of your data architecture, you’ve got to step back and look at the situation from every angle. Making the necessary upgrades and changes to update each of your data activities is crucial. If you must, you can make significant changes while leaving your current data stack as is, but this may cause some issues later down the line.

For the most part, companies will benefit the most from a complete and careful restructuring of the existing platform. This re-architecting will affect legacy systems and the new technologies you’ve undoubtedly added over the years.

Cloud-Based Data Platforms

If you’ve heard it once, you’ve probably heard it a million times. Switching to a cloud-based platform is the best method for hosting your data while providing your customers with the best experience possible. The cloud is complete technology innovation, and building on it correctly will provide your company with the tools you require to gain a competitive advantage.

Serverless data platforms and containerized data solutions will enable your company to make better decisions based on accurate AI and human-powered information. Migrating to the cloud gives you the capability to revolutionize how you’re currently sourcing, deploying, and running your data infrastructure.

Making the switch to a cloud-based platform is not a change you can make overnight, but it’s crucial to change. You cannot keep running on-premise legacy systems and expect to take your company and consumer interactions to the next level. When you utilize serverless or containerized data (or both), you’re taking a step into the future.

Real-Time Data Processing

In the not-so-far past, we processed data in batches. Typically these batches would provide insights that offered information that was a few days (if not weeks) old. While some of this data would prove helpful, it became difficult for business owners to understand where their business stood at the present moment.

Real-time data processing offers a whole new take on analytics and informed business decisions. Other than access to more accurate data, the good news is that the cost of the platforms that offer real-time data services has dramatically decreased, enabling a whole new host of data capabilities.

Businesses need to remember that real-time data processing includes streaming services. So, not only does access to data as soon as it’s available benefit you (the business owner), but it offers plenty of perks to your clients as well! Examples of technology and AI that allows live data include messaging applications, streaming solutions, and alerting platforms.

These options allow room within your data architecture, along with plenty of current (more accurate) feedback that can move you forward to higher innovative levels. You need technology that will inspire you to move in your business’s best interest, as well as your customers’ experience.

Moving to Modular Platforms

As frustrating as it can be, doing away with your outdated legacy systems is necessary. It might not be an immediate overhaul, as many businesses successfully operate within a cloud platform while keeping their legacy applications intact.

However, as time goes by, it becomes more difficult to find a balance between the two, which will likely encourage you to move from pre-integrated commercial solutions to the modular platforms that will best serve you and your data architecture.

There are open-source modular components available within the cloud that you can easily replace with new technologies as needed, all while keeping the rest of your data as is. Not only is this crucial to transitioning, but it’s an essential part of enabling new concepts for your data storage and access.

Rigid Data Models Become Flexible

To successfully transition your data architecture into a system that adds ease and makes sense for your business, you’ve got to move from the rigid data models of yesteryear and leap into the future of flexibility. Pre-defined data models have become increasingly difficult to work with while expressing the inability to provide data that isn’t completely rigid.

In short, the data development cycle is much too long, and businesses need access to insights as soon as possible. While changes can affect data integrity, a potent edge on the competition and extreme flexibility comes with denormalized data models and a “schema-light” approach.

There are a few ways to make your data more flexible and readily available. Data point modeling, for example, will ensure that you can change your data in the future without extensive disruption. Graph databases are another way to access real-time capabilities and utilize AI to tap into your unstructured data, which can provide you with some incredible results.

Technology services, such as the capabilities that come with Microsoft Azure Synapse Analytics, allow the flexibility of accessing standard interfaces and stored data simultaneously. Also, implementing JavaScript Object Notation will enable you to change database structures without requiring you to revise your business information models.

Getting Started

Building your data architecture in a way that drives internal and external innovation is easier now than it has ever been, though it still tends to prove difficult for businesses of all sizes. There’s no question that data technologies evolve quickly, seemingly at the speed of light, and this alone makes change beyond overwhelming for development teams.

Your goal here is to determine which practices will assist you in evaluating and employing new technologies as they come, adapting to a mindset based on testing and learning. Look to create a data culture within your company, encouraging employee excitement regarding implementing new data into their everyday roles.

Data, artificial intelligence, and analytics have concreted their roles in regular business functions. Technology leaders that take advantage of new approaches to data architecture are sure to weather the storm.

Quantum Computing is Nearly Here: Are You Ready?

Alex Thompson Digital Engineering March 21, 2022

Quantum Computing

There’s no question that quantum computing is making its way into the limelight at what could be a record-breaking pace. In somewhat simple terms, quantum computing encompasses the study of how humans can use the phenomena of quantum physics to create new ways of computing.

Unlike a standard computer bit, quantum computing consists of qubits. Qubits can be either a zero or a one or a superposition of both. By harnessing the collective properties of quantum states, such as entanglement, superposition, and interference, Its is making great strides toward successful calculations.

Quantum computers possess the potential ability to process far more information (correctly) than non-quantum computers. By performing calculations based on the probability of an object’s state before it’s measured without relying on only zeros and ones, the data storage of quantum computing is exponential.

Utilizing Quantum Computing

As quantum technology accelerates toward commercial visibility, technology buffs (and the general public) have begun questioning the intended use of quantum technology as a whole. The internet is alive with searches that contemplate whether or not it’s even real, and major corporations, like IBM, are here to tell us that quantum computing is more than real.

In fact, quantum computing is solving problems that our supercomputers cannot. Very recently, a research center in Japan announced its success with entangling qubits, which could improve the potential for error correction in quantum computers. This discovery alone makes it entirely possible to develop large-scale quantum computers, but for what?

Ending Our Reliance on Supercomputers

For decades, we’ve relied on supercomputers to solve major technological issues, but there are some problems that supercomputers cannot resolve. Unfortunately, time has revealed that in some instances, supercomputers aren’t that effective and do not have the working memory to sort the myriad of combinations that come with real-world problems.

Also, it’s crucial to consider that humans built supercomputers to analyze each combination, one after another, which can take an excruciatingly long amount of time. To help paint a clearer picture, here are a few examples:

Pharmaceutical companies simulate molecules to understand drug interactions better
Investment companies balancing the risks of their current portfolios
Logistics companies, delivering nationwide, require the best route combinations to save on fuel costs

While a supercomputer could technically determine these results, quantum computers have the capacity and understanding to deliver faster and more accurate results over a much shorter time. From reducing carbon emissions into the atmosphere to implementing quantum battery technology, quantum computers solve major problems where supercomputers fall short

The Development of Quantum Technology

Breakthroughs regarding quantum technology are growing at exponential rates, and investment dollars are pouring in just as quickly. Quantum computer start-ups are beginning to increase, and larger-scale tech companies are also getting in on the quantum computing action. From Amazon and Google to Microsoft and IBM, cloud-based commercial quantum communication is here.

It’s important to note that the number of companies utilizing and building themselves upon quantum computing does not necessarily equate to commercial success. Quantum computers show a ton of promise regarding the ability to help businesses solve problems at exponential rates, but the application is in its somewhat early experimental phases.

In most cases, experts are still attempting to determine the best topics for the field to test a hypothesis. Harnessing the power to make business-related decisions (that would take a conventional computer more than a week to make) in less than a second is desirable. Still, we must understand where and when to apply it safely.

The Benefits of Quantum Computing

It’s possible that the leaps and bounds made in the field of quantum computing could change the world. However, it’s the responsibility of technology leaders to realize that not every aspect of quantum computing is beneficial and educate ourselves as much and as often as possible on the reality and capabilities of these machines and the extent of artificial intelligence presented.

The Risk of Quantum Computing

One of the most significant risks that we face concerning cyber security and the overall risk of access to sensitive information. In reality, quantum computers will possess the ability to break into the public access key widely used by companies globally to protect consumer data.

In short, this unprecedented hacking possibility presented by quantum computers means that data that’s secure now may not be in the future. Figuring out how to combat this is key in utilizing, and we should encourage investments into quantum-resistant security measures.

Debates Within the Field of Quantum Computing

While experts continue to debate over very fundamental aspects of quantum computing, it’s becoming more and more crucial that we begin to prepare for the quantum era. Technology and business leaders should be in the process of formulating their versions of quantum computing, primarily in industries that will likely be the most affected, such as big pharma, in preparation to reap early benefits.

The change will come more quickly than most of us have ever imagined, with commercial services making public debuts as soon as 2030. Reports on have been developed to help leaders better prepare and find balance in an ever-emerging quantum ecosystem.

Equipping for the Era of Quantum Computing

If your company hasn’t begun dipping its toes into the quantum computing pool, the time is now. Companies and their technology leaders and teams must prepare for the quantum boom because it’s nearly here, and the evolution is moving quickly.

Commercial uses for quantum computing in pharmaceuticals, chemicals, automotive, and finance are imminent. The sooner our teams can figure out how to implement this unprecedented technology safely, the better the outcomes.

Preparing for the quantum era means fully accepting that these machines will heavily impact the world, possibly advancing technology in ways we might not fully understand. While this message can feel scary, taking quantum development seriously every step of the way will be essential to skirting misuse.

As calls for ethical guidelines become louder, we must support the movement. Education is power, and we should ensure that businesses, governments, and the public are fully educated on the possibilities that come with quantum computers.

Using AI and Machine Learning for Better Customer Satisfaction

Alex Thompson Data and AI March 18, 2022

Customer Satisfaction with AI & ML

Without a high level of customer satisfaction, most businesses would cease to exist. There is no way to survive in today’s all-around competitive environment without establishing the role you play in your customer satisfaction with ai & ml are the ways that artificial intelligence and machine learning can yield better results.

Currently, artificial intelligence is one of the leading technology trends, growing in leaps and bounds and gaining the attention and affection of business owners and marketing teams across the globe. Most brands today prefer to deliver a personalized approach to customer service, and in markets that continue to oversaturate with options, it’s an ideal choice.

It’s not to say that artificial intelligence should replace the relationships you build with your customer base as much as it should enhance it. With AI-run CRMs (customer relationship management) and CDPs (customer data platform), your business can move ahead of the competition by leaps and bounds.

The best part? AI no longer comes with a sky-high price tag, letting businesses build through AI and ML without breaking budgets. In reality, most tech leaders are utilizing AI technology, and it shows no signs of slowing down, with substantial projected growth within the next five years.

So, now that you know that it’s likely quite affordable for you to experience the benefits and perks that come with employing AI when it comes to your customers, how should you do it? While no business is the exact same, particular methods and utilization techniques will ensure you’re using AI to its fullest extent concerning customer satisfaction.

Understanding Your Customer

You cannot sell to a demographic that you don’t understand. The combination of artificial intelligence and machine learning can fuel your understanding of your customer while making them feel seen.

It might seem silly, but customers want and expect to feel heard when dealing with any business. If you can tailor your AIML technology to align with that need, you’ll notice growth without question.

Historical and behavioral data are often tracked by artificial intelligence, and unlike traditional analytics software, these tools can gain a much more extensive understanding of customer behavior. Keep in mind that AI is always learning.

AIML consistently analyzes new information and combines it with what it already knows to develop solutions and recommendations. Because of the ability of this incredible technology, business owners and marketing teams can predict the behavior of their past, current, and prospective customers.

When you expect your customer to act in a specific way, you can fully align your content calendar with relevant topics. This targeted content alone will raise the opportunities you have to make sales while increasing social interactions and engagement, kicking off your customer journey the right way.

Connecting with your clientele personally has become essential in the era of options and transparent social feeds. When you establish a connection, you can build trust, and in most cases, that trust results in loyalty. Brand loyalty on behalf of the consumer is imperative to business growth and survival.

Remember, you don’t have to be fully present to begin building that connection, as the employment of AI will jumpstart the outreach and response process for you. When combined with NLP, or natural language processing, we can improve interactions and gain valuable insight.

Predictive Behavior and Decision-Making

In the past, making essential business decisions typically included massive piles of spreadsheets and printed data analysis. Of course, these papers moved to a digital platform with the invention of computers and the evolution of technology, it still took a long time to go through the presented data.

Today, decisions are made in real-time and, for the most part, fueled by data collected and presented by artificial intelligence. Machine learning has become such a massive part of the customer experience, and this includes influencing the way you make decisions for your business that directly affect your customer base.

A fantastic example of data presentation in real-time could be the saved interactions that take place between your customers and your AI messaging system. Not only is this technology easy to implement, but it gives you an excellent idea of what the customer is thinking and feeling, heavily based on their responses to straightforward questions regarding their experience.

When “speaking” to your customers, AI can make decisions related to the responses your customer is typing and base those decisions on similar customers it’s experienced in the past. From personalized recommendations to recognizing and understanding intent, there is little that AI cannot do to move us forward toward our goals of stellar customer service.

When engaging with AI, customers are often presented with the opportunity to view content curated just for them. There are few better ways to gain sales and new, dedicated customers. Every interaction with your company is an experience, and you want it to be great every time, even if the customer is showing up with a complaint.

Machine learning works heavily, especially in real-time data, with the concept of predictive customer behavior using data mining, modeling, and statistics. AI doesn’t come up with its answers out of the blue but instead relies on what it already knows to learn even more. AI understands when and how to interact with your customer, and though AI never comes with a lack of complaints, this is where it truly shines.

If deeper insights are what you need, then AI is the choice you want to make. Predictive analytics go much further than historical information alone, making AI a powerful tool in the customer experience. When using AI correctly, you’re more likely to generate a sale and provide your customers with various ways to form an emotional connection to your brand.

The Pros and Cons of Chatbots

Though chatbots have been around for quite some time in various forms (the help tool on AOL Instant Messenger comes to mind), companies have only begun to use them to interact with customers in recent years. There are many ways to tailor your chatbot, whether you want it to act merely as customer contact or solve mild to moderate complaints.

Today, many businesses employ the use of chatbots to monitor customer interactions, and that number continues to grow as chatbots become more intelligent and efficient. While AI is a fantastic way to interact with your customers, you must remember that you are not providing a substitute for human interaction but more of a placeholder.

Yes, customers absolutely want the tailored experience that a chatbot can offer by gathering information, comparing it to past experiences, and predicting how a customer will behave. However, consumers are more than familiar with a company’s use of AI, and they know when they’re not dealing with a human. In many cases, the interaction will result in the need for human contact.

Utilizing chatbots in your business is all about finding a balance between artificial and actual human interactions. While NLP has made it possible for chatbots to interact successfully while solving various transactional issues, nothing understands your product as entirely as you do. At times, you’ll have to step in.

Today, chatbots no longer fail when presented with separate topics during one conversation. They can juggle a stream of random questions without issue, providing a service that rivals human contact to an extent. Still, it’s not a replacement for you.

To fully enhance your customer’s journey, you’ve got to find the perfect combination of artificial and human intelligence to address your customer needs. Once you step in, you’ll have full access to the data collected by your AI, giving you even more ammunition to make your customer’s experience a fantastic one!

Personalizing Your Customer Experience

Your customers already know that you have other customers, but they want to feel that their business is appreciated and essential. Let’s face it, every sale is important, and through hyper-personalization, AI makes it possible for us to convey that to our clients.

AI uses data in real-time to deliver content specific to the current customer’s experience, creating an incredibly convenient way for consumers to interact with your business. Gone are the days of flipping through page after page of products and content.

Instead, you can utilize AI and create the ultimate customer experience through product, service, and content recommendations. Customers despise entering repeat information, such as shipping and email addresses or telephone numbers. When your AI performs a task as simple as filling that information in for them, you’ll be ahead of the game regarding customer satisfaction.

Customer Service AI Challenges

It’s not to say that AI comes without challenges because we all know that there are plenty. Those challenges aside, recent years have proven that AI isn’t killing jobs or collecting information to use in nefarious ways.

When used correctly, AIML can absolutely take your customer experience to new heights by creating a targeted and personalized experience from one customer to another. It’s time for your business to take advantage of predictive analytics and super customized customer experiences, thereby improving your customer journey as a whole across all active channels.

Five Steps to Modernize Your Data Using Azure

Alex Thompson Digital Engineering, Modernization March 15, 2022

Data modernization with Microsoft Azure

In recent years, it’s become evident that the modernization of data and cloud migration is essential to the survival of businesses. Microsoft azure It’s not to say that legacy systems have to fall by the wayside altogether. Still, it’s crucial to establish a new way to distribute and provide access to company data for both your customers and employees/teams.

Companies that provide on-premises software will best understand the need to modernize existing applications and how it’s necessary when moving to a SaaS model. Updating your environment as a whole can help you make a move more flexibly and efficiently.

What is Microsoft Azure?

Modernizing data is essential to moving to a SaaS model, but it’s one of the first steps you should take in the migration. Other than improving communications between teams and automating redundant business functions, the whole point of modernizing and moving to a cloud platform is to enhance the user experience for your customers greatly.

Microsoft Azure is cloud engineering that continues to make the process of switching to the cloud easier for businesses across the board. Azure is a multi-cloud platform designed to help companies manage data applications. Microsoft Azure can store your data and transform it, depending on how you utilize the services.

Essentially a massive collection of networking hardware and servers tasked with running complex distributed applications, Microsoft Azure is compelling because of the way its servers are orchestrated. Azure is fantastic in the way that you can successfully add cloud services to your existing technology and legacy systems, which can make change easier for some.

Suppose you don’t want to add cloud technology to your current systems. In that case, you can use Azure as a Saas service, entrusting them with all of your network and computing needs. You can start using Azure for free, making it incredibly appealing for companies across the board, ranging from start-ups to established corporations.

Knowing if You’re Ready to Move to SaaS

It doesn’t take long to use up resources when operating within the software business. Building usable software isn’t easy, and there is a fair share of distractions, ranging from troubleshooting customer issues to sales. The cycle is relatively nonstop, and you’ll probably find that you’re spending quite a bit of time just maintaining operations without leaving anything left to dedicate to modernizing your operating systems.

By pulling your technology into the future, you can streamline your operations and reduce the time spent on tedious and repetitive tasks. This provides the opportunity to broaden your customer base and deliver new data.

If your business is based on an on-premises approach, it’s time to take a look at what Microsoft Azure can do for you. Your application services likely expect plenty of requirements from your customers and clients.

From scalability to security, you have essential application components that you have to deliver on to build the solutions you desire. To support millions of users worldwide, you have to find a way to draw them in and impress them in new ways. This becomes near impossible when you’re operating on old legacy systems that no longer make sense to your business model.

In short, if you’re ready to go big with data modernization, eliminating repetition, and enhancing the customer experience, you’re ready to move to a SaaS platform. Microsoft Azure can help.

Choosing a Cloud Program that Works

There’s no question that customers today demand a flawless experience intricately interlaced with fantastic customer service and state-of-the-art technology. It has become increasingly more challenging to meet the demands of the public. Modernizing your data through an efficient cloud program can help, but where do you begin?

Knowing that you need to meet customer expectations but not having the technology to do so can put plenty of pressure on your development teams and operation as a whole. To choose the right cloud program for you and determine whether you can entrust the cloud with your current systems, you’ll have to ask yourself a few questions.

Avoid Downtime

The cloud program you choose should help you avoid downtime at all costs, whether planned or unplanned. You want to avoid poor interactions with customers at all costs. While systems are expected to go down now and then, is your platform of choice able to help you deal with that?

Unexpected Spikes

Will your cloud platform of choice be able to help you handle unexpected spikes in traffic? Most cloud platforms, Azure included, are set up to help avoid customer complaints regarding poor working performance. You need a platform that will not require you to pay for a large amount of storage that you might not need in the long run, and Microsoft Azure is very customizable.

Expansion

The cloud platform you work with should assist you in expanding to regions beyond your average reach. With modernization and growth, new business should come, and your new platform must assist in that expansion. Azure will also give you access to the legacy systems that you’ve come to know and depend on, which is comforting to business owners of all sizes.

Secure Data

Regardless of your business type, you have got to keep your customer data (as well as your own) as secure as possible. Your cloud platform should go above and beyond to ensure that your data stays clear of jeopardy and Microsoft Azure is well respected in terms of security.

Azure: A Deeply Trusted Cloud Platform

Microsoft Azure is a cloud platform that more than 90% of fortune 500 companies rely on to monitor, upgrade, and secure their data. Azure was constructed from a cloud-first standpoint, which means that the platform knows how to deliver exceptional value to your customers regardless of where you live in the world.

Azure gives business owners on a global scale the comfort of knowing they no longer have to worry about performance or capacity. The platform allows you to scale up and down whenever needed without jumping through various hoops and financial commitments.

Your development team can easily tailor Azure to your operational needs, alerting you to performance issues and configuring your applications to scale up and down on their own, according to demand. When you use Azure, your customers will have consistent app availability, as the platform uses built-in automatic patching and backup and security and monitoring.

Azure is available in more than 140 countries, allowing you to put your data where your clientele resides. Overall, the platform has become essential to helping various businesses see sustainable and substantial growth quickly. The availability of Microsoft Azure is unparalleled, and if you’re considering a data modernization (and you should be), it’s time to seriously look into your options with Azure.

The Importance of Modernization with Azure

Moving your data to a cloud platform with the capabilities of Azure is sure to streamline your business processes over time. Of course, the modernization of data takes time, and it’s crucial to maintain a line of open communication with your team. When substantial changes take place, communication is vital to avoid confusion.

Data modernization can take your company to the next level, skyrocketing you to levels of growth you may never see otherwise. Now is the time to take advantage of the fantastic possibilities Azure has to offer.

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