Global Teams Management
Automating “Best Practice” Assurance in Software Development
In the ever-evolving software development landscape, ensuring best practices is crucial for delivering high-quality code and maintaining a robust development process. While traditional code and pull request (PR) reviews are valuable, relying solely on human reviewers can be time-consuming, prone to human error, and ineffective at scale. This article explores automating “best practice” assurance in software development and how leveraging tools like static analysis, linting, gated builds, proper member protection, templates, and starter projects can significantly improve code quality and development efficiency. The Limitations of Traditional Code and PR Reviews Code and PR reviews have long been the standard practice for ensuring code quality and adherence to best practices. However, these reviews rely on human reviewers who may overlook certain issues or need help to effectively communicate why specific changes should be made. This approach can overwhelm reviewers, particularly in large-scale projects or teams with limited resources. Moreover, reviewers’ subjective opinions may introduce inconsistencies in the evaluation process, leading to discrepancies in quality across the codebase. Leveraging Automation for Code Quality Assurance Static Analysis: Static analysis tools analyze source code without executing it, uncovering potential issues such as coding errors, security vulnerabilities, and performance bottlenecks. By incorporating static analysis into the development workflow, developers can catch a wide range of problems early on, preventing them from manifesting in production. Tools like SonarQube, ESLint, and Pylint provide customizable rulesets that can be tailored to reflect a project or organization’s specific best practices and coding standards. Linting: Linting tools examine the code for style violations and adherence to coding conventions. Linting ensures readability, maintainability, and collaboration across the development team by enforcing consistent coding styles. Tools like Prettier, JSLint, and RuboCop help automate this process, reducing the burden on individual developers and promoting code uniformity. Gated Builds: Implementing gated builds ensures that code changes are subject to automated checks before being merged into the main codebase. These checks may include running unit tests, validating code quality metrics, and verifying compliance with predefined best practices. By rejecting changes that fail these checks, gated builds act as a gatekeeper, preventing the introduction of poor-quality or non-compliant code into the codebase. Utilizing Member Protection Properly Member protection, such as access modifiers like public, private, and protected, plays a crucial role in object-oriented programming. Proper usage of member protection ensures encapsulation, data integrity, and reduces the risk of unintended side effects. By configuring tools like static analyzers and IDE plugins to enforce member protection rules, developers are guided to follow best practices automatically. These tools can flag violations and offer suggestions for correcting and improving code. Templates and Starter Projects Developing projects from scratch can be time-consuming and may lead to inconsistencies in code quality and structure. By leveraging templates and starter projects, development teams can bootstrap new projects with predefined best practices, code patterns, and architectural guidelines. These templates can include configurations for code quality tools, such as linters and static analyzers, reducing the setup time and ensuring adherence to best practices from the project’s inception. Conclusion Automating “best practice” assurance in software development empowers teams to maintain high code quality, streamline the review process, and reduce the likelihood of errors and inconsistencies. By relying on tools such as static analysis, linting, gated builds, proper member protection, and leveraging templates and starter projects, developers can establish a robust development workflow that enforces best practices from the early stages of coding. As a result, embracing automation enhances code quality and improves collaboration, productivity, and the overall efficiency of the development process.
Unraveling the Differences: Microservices, SOA, and Distributed Monoliths
In today’s rapidly evolving technological landscape, organizations often find themselves facing the challenge of decomposing monolithic systems into more flexible and scalable architectures. Two popular architectural approaches for system decomposition are Microservices and Service-Oriented Architecture (SOA). However, it is crucial to understand the drawbacks of a Distributed Monolith and how to avoid accidentally creating one. In this article, we will delve into the differences between Microservices, SOA, and Distributed Monoliths, discuss the pitfalls of the latter, and provide guidance on choosing the appropriate architecture for monolith decomposition. Understanding Microservices Microservices architecture is a modular approach that structures an application as a collection of small, independent services. Each service is responsible for a specific business capability and can be developed, deployed, and scaled independently. The key principles of Microservices include service autonomy, decentralized governance, and scalability and resilience. Microservices embody the principle of service autonomy, meaning that each service is self-contained and can be developed and deployed independently. This autonomy fosters faster development cycles and enables teams to choose the most suitable technologies and frameworks for each service. Decentralized governance is another core principle that grants individual teams control over their services. This facilitates faster decision-making and allows teams to align their services with specific business requirements. Additionally, Microservices offer scalability and resilience advantages by allowing individual services to scale independently based on their specific needs. This ensures optimal resource allocation and improves the overall scalability and resilience of the system. Exploring Service-Oriented Architecture (SOA) SOA is an architectural style that promotes the development of services as reusable components. Services in SOA are loosely coupled, well-defined, and can be composed to create more complex business functionalities. The key aspects of SOA include service modularity, loose coupling, and various benefits for organizations. SOA decomposes a system into modular services, each responsible for a specific business capability. This modularity enables easier maintenance, scalability, and evolution of individual services. Loose coupling is another crucial aspect of SOA, emphasizing that services should be independent and not tightly coupled to one another. Changes in one service should not directly impact others, allowing for independent development and evolution of services. SOA offers several benefits to organizations. It enables the creation of modular services, making it easier to scale and evolve specific components without affecting the entire system. SOA facilitates seamless integration between disparate systems, leveraging existing IT investments and enabling smooth communication between services. Additionally, service reusability reduces development efforts and fosters agility in delivering new functionalities. By aligning IT systems with business processes, SOA ensures that technology components map effectively to specific business capabilities. Unveiling the Distributed Monolith While Microservices and SOA offer significant benefits, it is essential to understand the pitfalls of a Distributed Monolith. A Distributed Monolith refers to a system that adopts a distributed architecture while retaining the monolithic characteristics, such as tight coupling, shared data models, and synchronous communication among distributed components. In simpler terms, it is a monolithic system divided into smaller services but lacking the benefits of true service autonomy and loose coupling. Distributed Monoliths suffer from several shortcomings. Firstly, they can be as complex to maintain as their monolithic counterparts, as changes in one service often require coordinated modifications in others. This complexity hampers agility and slows down the development and deployment processes. Secondly, Distributed Monoliths may struggle with scalability, as the tight coupling and shared data models hinder independent scaling of services. Thirdly, synchronous communication and shared data models can lead to performance bottlenecks and reduced system efficiency. Finally, the lack of true service autonomy and loose coupling limits the agility and flexibility associated with Microservices and SOA. Avoiding the Distributed Monolith To avoid accidentally creating a Distributed Monolith during system decomposition, organizations should employ specific strategies. The first strategy is to establish clear service boundaries. Clearly defining the responsibilities of each service ensures that they have specific, well-defined functionalities and minimizes dependencies between services. This helps prevent overlapping functionalities and promotes the autonomy of individual services. Promoting asynchronous communication is another crucial strategy. By allowing services to communicate asynchronously, organizations reduce dependencies between services. Asynchronous communication enables services to operate independently, enhancing the scalability and resilience of the system. Independent data management is equally important. Avoiding shared data models among services and allowing each service to manage its data store promotes data autonomy. This eliminates potential data consistency issues and improves the performance of individual services. Decoupling infrastructure components is another key aspect of avoiding the Distributed Monolith. By decoupling databases, messaging systems, and other infrastructure components from individual services, organizations enable independent scaling, fault tolerance, and easier evolution of the technology stack. Choosing Between SOA and Microservices for Monolith Decomposition Deciding whether to adopt SOA or Microservices for monolith decomposition depends on several factors. If the organization already has a mature SOA infrastructure in place, leveraging and extending it for monolith decomposition may be the most viable option. SOA is particularly suitable when the primary goal is to integrate existing systems and enable seamless communication across the enterprise. It can also be advantageous if there are common functionalities or shared services that can be reused across different business units or departments. On the other hand, Microservices may be a better fit when teams require granular control over individual services and want to optimize development speed and autonomy. Microservices are particularly beneficial for organizations that value agility, rapid iteration, and innovation, as they promote faster experimentation and independent deployment. Additionally, if specific services have varying scalability and resilience requirements, Microservices’ ability to scale and recover independently can be advantageous. Conclusion: Microservices and SOA offer distinct approaches to system decomposition, each with its advantages and considerations. Avoiding the creation of a Distributed Monolith requires careful planning, clear service boundaries, asynchronous communication, independent data management, and infrastructure decoupling. Ultimately, the choice between SOA and Microservices when decomposing a monolith depends on factors such as existing infrastructure, integration needs, shared services, development speed, autonomy, scalability, and resilience. Organizations must assess their specific requirements and align them with the architectural […]
The Cost of Not Modernizing
When developing a strategy for application modernization, there are several factors that an organization needs to consider, such as business objectives, system design, regulatory compliance, and more. Of course, cost will also be an important factor, and that discussion should also consider the cost of not modernizing. In this article, we’ll discuss what happens when modernization is overlooked. A lack of modernization can lead to significant costs to your business, resulting from issues like lagging efficiency, security vulnerabilities, missed opportunities, and difficulty retaining talent. Lagging Efficiency Technology evolves quickly. Cloud providers continue to release new versions and generations of their infrastructure and services with the goal of continuous improvement. These improvements come in various forms: faster processors, increased throughput capacity, increased concurrency, greater resilience, and even more efficient energy usage. In addition, newer innovations may be released at lower price points resulting in even greater efficiency for organizations that are able to take advantage of them. The result for those who choose not to upgrade is a widening gap with those in their industry who benefit from newer technology as innovations bring greater efficiency and the expectations of the market change. Companies using older technology aren’t necessarily becoming less efficient, but they’re perceived to be less efficient as they get outpaced by their competitors. The concept of drafting comes to mind, where one racer stays within the slipstream created by a leader to reduce drag and perform more efficiently. The rate at which cloud infrastructure and services improve establishes a type of slipstream. Staying closely aligned to those newer technologies helps companies take advantage of those improvements early. You must do so to avoid falling behind your competitors who maintain that alignment. These improvements are significant enough that AWS considers ignoring this principle to be high-risk and has included it in the Performance Efficiency Pillar of their Well-Architected Framework. Benefits of establishing this best practice: By considering new services or product offerings, you can improve the performance and efficiency of your workload, lower the infrastructure cost, and reduce the effort required to maintain your services. Level of risk exposed if this best practice is not established: High Security Vulnerabilities Here’s a familiar story plot: a location is being defended against an attacking force that keeps looking for weaknesses and making small advances until, eventually, the defenders retreat, and the attacking force overruns the location. Software systems are similar. Bad actors look for weaknesses and vulnerabilities in the software to exploit them. Software vendors and development teams respond in defense by patching those vulnerabilities to maintain the integrity of the software and protect the companies using it. Still, eventually, the system will age out of its support lifespan, at which point patches and security updates will no longer be released. However, those bad actors continue to look for vulnerabilities. When weaknesses are found, no one can patch the software since the support lifespan has ended, and companies who continue to use the software are left vulnerable to attack. Though modernization often involves taking advantage of newer innovations in the cloud, it can be as simple as bringing a legacy system up to date with modern operating systems and frameworks to continue benefiting from security patches and longer support lifespans to minimize the company’s vulnerability to attack. The cost of neglecting this aspect of modernization is high, especially for organizations dealing with sensitive or valuable data. A company with sensitive data and systems is a valuable target for bad actors, making modernization even more critical. Missed Opportunity The COVID-19 pandemic was a strenuous time for many companies, but some thrived and became real lifelines for people and businesses. Companies like Amazon, Grubhub, Netflix, and Zoom provided services that went from convenience to necessity overnight. A common thread with many companies integral to pandemic life was a commitment to innovation that predated the pandemic. Commitment to innovation was a significant factor in positioning those companies to scale the way they did during Covid, not to mention enabling so many of us to weather a challenging time. Conversely, companies that had yet to focus on innovation and modernization found themselves scrambling to adjust, often paying a steep opportunity cost. The point is that opportunities rarely announce themselves ahead of time, and capitalizing on them requires being nimble with the ability to scale in real-time when necessary. The ability to be agile is one of the primary selling points of cloud platforms, but simply moving an application to the cloud doesn’t guarantee you’ll be able to scale how you need to. Some legacy systems may not be able to leverage innovations until dependencies are brought up to date and architectural patterns are refactored. If the cost of modernization seems high, consider this: Modernizing now always costs less than modernizing later because the delta between your system’s current state and modern technology’s current state will only continue to grow. Eventually, the effort required to modernize could become significant, with timelines extending beyond a window of great opportunity. Talent Retention The last issue we’ll look at is talent. I have recently encountered a few companies still relying on applications built on severely outdated technologies. I’ve also interviewed several job candidates who have told me they’re looking to move on from their current employer because they feel their skill sets are becoming outdated. Some support older applications, and some work for companies that don’t intend to modernize. However, each of those developers realizes they need to keep their skills up to date if they want to be marketable. When these employees move on, their companies will need someone to take their place, but those companies will likely find themselves in the same position again before long. As time passes, finding and retaining developers to maintain these systems will be increasingly difficult. IT professionals want to work in technologies that are relevant. If they feel their skills stagnate, they will begin to look elsewhere, and eventually, their roles will become difficult to fill. A company in this position should consider the cost of […]
Preparing for Application Modernization
Application modernization is the process of upgrading legacy systems to modern technology. When considering modernization, there are three basic categories of strategies: rehosting, refactoring, and replatforming. However, selecting a strategy is just the beginning of the journey toward application modernization. To ensure the success of a modernization effort, it’s essential to consider multiple factors such as business objectives, application/system design, operations, regulatory compliance, and developer velocity. In this article, we’ll explore each of these considerations in detail, along with examples of how they can impact the success of an application modernization effort. Rehosting Rehosting involves moving an existing application from its current environment to a newer infrastructure. This strategy attempts to implement this move with as little change to the code as possible. This is usually the least disruptive strategy but is limited in the improvements that can be realized. Refactoring Refactoring modifies significant portions of the system’s design to maximize its efficiency. This strategy entails rewriting code or redesigning the application, sometimes in its entirety. Replatforming Replatforming sits right between Rehosting and Refactoring. It does not attempt to refactor major portions of the system. Instead, it aims at smaller changes that enable the system to leverage cloud capabilities for core components. Considerations If you’re trying to select a modernization strategy, or if you’ve already selected a strategy and are preparing to start, here are some suggestions to consider that may be helpful. Business Objectives Modernization should enable your business to reach its goals. When selecting a strategy, it’s important to clarify your objectives. Determine the criteria you’ll use to measure the success of the modernization effort and document any assumptions you have regarding modernization. Imagine Company A has a goal to reduce its IT operating expenses by 10%. Their system engineers currently spend a significant amount of their time patching and maintaining the company’s on-prem server cluster. Company B has a goal to increase online sales by 25% and needs to ensure its online store can handle the increased traffic without impacting the customer experience. These companies have very different objectives, and a strategy that works for one may work against the other. Questions to consider regarding business objectives What are your business’ current goals? Which of these goals is motivating your consideration of application modernization? What issues are you looking to address by modernizing? What are the specific outcomes you want to achieve with modernization? Application / System Design Most modernization projects require a certain amount of modification to the design of the system. Whether it’s a full refactoring effort or the replatforming of one system component, modifications to the system should focus on areas of improvement that will deliver the most value. Imagine Company A and Company B both have on-prem applications with growing utilization. They are experiencing database latency and are running low on storage space. Company A has heard that the cloud provides practically unlimited storage and scalability and decides to rehost their entire application in the cloud only to realize they are having to continually increase the size of their VM, which is causing budget overrun. Company B chooses a replatforming strategy, moving just their storage and data to managed cloud services that autoscale. By focusing on what will provide the most value, they are able to benefit from the capabilities of the cloud while managing cost and prolonging the lifespan of the infrastructure they’ve already invested in. Questions to consider regarding system design What are the pain points with the current application? Are you predicting usage to increase in the near future? By how much? If a major refactoring is warranted, which core components will need to scale the most? Can poorly performing dependencies be improved, minimized, or avoided? What impact will modernization have on system security? Operations A modernization strategy can have a profound impact on operations and release management. Taking current operations into consideration and examining how they may change allows you to make appropriate preparations. Imagine A software team at Company A is replatforming the database for an on-prem application and is moving it to a new cloud provider account managed by the marketing department. The company has formal change management and release management processes managed by IT. The team is ready to deploy its new architecture, but the change and release management processes have not been updated, causing a delay in the project. Taking operations into account during the preparation phase can help prevent unnecessary delays. Questions to consider regarding system operations Does your change management process need to be modified to account for details that will change during modernization? How will modernization affect release agility and frequency for the application? Do support, systems, and release engineers have the necessary access to modernized system components? Under the system’s current design, can components/modules of the application be deployed independently? If not, how will modernization affect collaboration during releases? Regulatory Regulated environments can put tight constraints on system design and data flow. Considering regulatory guidelines will help you avoid selecting non-compliant service configurations and ensure the design of your modernized system maintains the required compliance. Imagine Company A is a healthcare company with an on-prem application that they want to move to the cloud. HIPAA regulations put constraints on where and how Protected Health Information (PHI) is handled and by whom. Additional internal policies can also limit which systems PHI data flows through. These regulations put strict demands on system design that need to be considered early in a modernization effort. Questions to consider regarding regulatory compliance What kind of compliance regulations need to be kept in mind? How will modernization affect data-flow, storage, and access? Are the target environments compliant with existing regulations? Developer Velocity The speed at which a development team delivers software is directly related to the capabilities of the team and their familiarity with the environment. Selecting a strategy that your current team cannot support results in lower velocity and skill gaps. A clear understanding of your team’s current capabilities can inform which strategy […]
Enhance Patient Impact by Rightsizing Your Digital Infrastructure
The healthcare industry is rapidly evolving, and digital transformation is a key driver of change. Ever since shifting to various electronic health record systems (EHR), the healthcare industry has adopted a multitude of digital bolt-ons to enhance both the provider and patient experience. Everything from telemedicine to mobile health applications has transformed how patients receive care. However, these advancements have also brought new challenges for healthcare organizations, including managing and maintaining complex digital infrastructures. Healthcare administrators and executives understand that digital infrastructure is crucial to providing high-quality care to patients. However, they also recognize that having an excess or a shortage of technology can negatively impact patient outcomes. Therefore, to optimize the benefits of your digital infrastructure, it is essential to rightsize your technology stack. Here are some tips on how to do so: Assess Your Current Digital Infrastructure The first step in rightsizing your digital infrastructure is comprehensively assessing your current technology stack. This involves identifying all the technology solutions in your organization, including EHRs, telemedicine platforms, mobile health applications, and any other digital tools. Once you have a comprehensive overview of your current technology stack, you can evaluate how effectively it meets the needs of your patients and staff. Evaluate Your Technology Needs After assessing your existing digital infrastructure, the next step is to evaluate your technology needs. This requires determining which technologies are essential to providing high-quality patient care and which are not. To do this, you must consider factors such as patient demand, clinical workflows, regulatory requirements, and your organization’s strategic goals. For instance, if you serve a large patient population with complex medical needs, you may need to invest in advanced EHR systems and telemedicine platforms to provide remote monitoring and virtual consultations. On the other hand, if your organization serves a small patient population with relatively simple medical needs, you may not require as much technology. However, advanced systems like EHR are only one piece to your digital infrastructure; many of the advancements are done outside the EHR platform. Consider Your Budget and Resources Rightsizing your digital infrastructure begins with budgeting. You must balance the cost of implementing new technologies with the benefits they provide. You must also ensure you have the resources to support and maintain your digital infrastructure over the long term. Consider adopting a phased approach to rightsizing your digital infrastructure to optimize your budget and resources. This involves prioritizing the technologies that significantly impact patient outcomes and implementing them in stages. For example, you may begin by implementing a new EHR system that improves clinical workflows and then progress to implementing telemedicine platforms that improve patient access to care. Involve Your Clinical Staff in the Process Rightsizing your digital infrastructure is not solely about technology but also about people. Your clinical staff are the ones who will use the technology daily, so it is crucial to involve them in the process of rightsizing your digital infrastructure, but you will also want your patient access, billing teams, and research folks involved as well. Really anyone who utilizes the system should have a voice in the implementation and training. This entails obtaining their input on which technologies are necessary to provide high-quality care and which are not. By involving your entire staff in the process, including providing them with the training and skills needed to assess the process, you can ensure that your technology solutions align with your clinical workflows and meet the needs of your patients. You can also address any concerns or resistance to change that may arise. Ensure Compliance with Regulatory Requirements Rightsizing your digital infrastructure also involves ensuring compliance with regulatory requirements. For example, healthcare organizations are subject to numerous regulations, such as HIPAA, which require them to protect patient privacy and security. Failure to comply with these regulations can result in fines and damage your organization’s reputation. To ensure compliance with regulatory requirements, you must consider how your technology solutions handle sensitive patient data. You must also ensure that your staff is trained on how to use the technology in a compliant manner. Implement a Governance Framework Finally, it is essential to implement a governance framework to ensure that your digital infrastructure continues to provide the most significant impact on patient outcomes over time. This involves establishing policies and procedures for managing and maintaining your technology solutions. It also entails assigning responsibility for technology decisions and ensuring accountability for their outcomes. A governance framework can help ensure that your technology solutions are aligned with your organization’s strategic goals and provide the most significant impact on patient outcomes. It can also help you identify and address any technology-related risks or issues before they become substantial problems. Rightsizing your digital infrastructure is essential to delivering high-quality care to patients. By assessing your current technology stack, evaluating your technology needs, considering your budget and resources, involving your clinical staff, ensuring compliance with regulatory requirements, and implementing a governance framework, you can optimize your digital infrastructure for patient impact. But remember, rightsizing your digital infrastructure is an ongoing process. You should regularly review and update your technology solutions to ensure that they continue to meet the needs of your patients and staff. As a healthcare stakeholder, your efforts to rightsize your digital infrastructure can improve patient outcomes and healthcare delivery. If you have any questions, Technossus is here to assist in reviewing your tech stack and partner with your team to ensure your digital infrastructure runs efficiently.
Building Data-Driven IT Teams
In today’s digital age, businesses produce and collect vast amounts of data daily. This data can provide valuable insights into the organization’s operations and customer behavior, allowing companies to make informed decisions and gain a competitive advantage. However, many organizations need help to make sense of and utilize their data effectively, which is where data-driven IT teams come in. This week’s blog will explain how and why to build data-driven IT teams and how Technossus can help businesses achieve their data-driven goals. What is a Data-Driven IT Team? A data-driven IT team is a group of professionals who use data analysis to improve the organization’s operations and customer experience. These teams use business intelligence software, machine learning algorithms, and data visualization tools to collect and analyze data, identify patterns, and make informed decisions. In addition, data-driven IT teams work closely with other departments, such as marketing and sales, to provide insights and recommendations for optimizing business operations. Why Build a Data-Driven IT Team? There are several reasons why organizations should focus on and build data-driven IT teams. First, when companies rely on data-driven decision-making, they gain an immediate competitive advantage by identifying opportunities for growth and improving customer satisfaction. Additionally, by analyzing that data, companies can identify patterns and trends in customer behavior. Identifying behavior patterns will help to create more targeted marketing campaigns and improve customer experience. Secondly, data-driven decision-making can help organizations save money by optimizing their operations. By analyzing data from various departments such as finance, operations, and supply chain, companies can identify areas where they can reduce costs and improve efficiency. For example, by analyzing sales data, companies can locate products that are not selling well and adjust their inventory levels accordingly, reducing the costs associated with excess inventory. Thirdly, data-driven decision-making can help organizations mitigate risks. Companies can identify potential threats by analyzing data from various sources, including social media, and take proactive measures to minimize them. For example, a company may use social media monitoring tools to identify negative sentiment towards their brand, allowing them to take corrective action before the situation escalates. Building data-driven IT teams involves starting with the organization’s objectives, identifying the data sources that will be used to achieve these objectives, building a team of experts with the necessary skills and expertise to collect, analyze, and interpret the data, and providing access to the latest tools and technologies to facilitate this process. Step 1: Identify Objectives The first step in building a data-driven IT team is to identify the organization’s objectives. These objectives should clearly define and align with the organization’s overall mission and goals. Examples of objectives that can be achieved through data analysis include improving customer satisfaction, increasing sales, reducing costs, and optimizing business processes. Step 2: Identify Data Sources Once the objectives have been identified, the next step is to identify the data sources that will be used to achieve these objectives. This may include internal data sources such as customer databases, sales reports, and financial statements, as well as external data sources such as market research reports and social media analytics. Step 3: Build the Team Building a data-driven IT team requires individuals with diverse skills and expertise. This may include data analysts, data scientists, IT professionals, and subject matter experts who can provide insights into the organization’s specific industry or market. The team should be able to work together to collect, analyze, and interpret data effectively. Step 4: Provide Access to Tools and Technologies To facilitate the data analysis process, the team should be provided with access to the latest tools and technologies, such as business intelligence software, machine learning algorithms, and data visualization tools. These tools can help the team collect and analyze data more efficiently, providing faster insights and recommendations. Why Technossus? The world of IT is constantly evolving, and organizations that want to stay ahead of the competition must adapt to these changes quickly. As an IT consulting firm, Technossus has extensive experience in building these productive data-driven teams for organizations of all sizes. Technossus’s team of experts works closely with companies to understand their specific needs to build customized solutions that meet their objectives.
How to Evaluate the Right IT Services Partner for Your Needs
In today’s business landscape, technology plays a crucial role in every aspect of an organization. Companies rely heavily on IT infrastructure and services, from day-to-day operations to customer engagement and revenue generation, to achieve their goals. As such, partnering with the right IT services provider is crucial for any business seeking to maximize its potential. But with so many providers on the market, how do you evaluate the right IT services partner for your needs? In this article, we’ll provide a step-by-step guide to help you find the perfect fit for your organization. Step 1: Determine Your Business Needs and Objectives The first step in evaluating an IT services partner is identifying your business needs and objectives. It’s essential to clearly understand what you hope to achieve with the partnership, such as improving efficiency, reducing costs, enhancing security, or expanding your technological capabilities. Knowing your goals will help you identify the specific services and expertise you need from a potential partner. Step 2: Evaluate the Provider’s Expertise and Experience The next step is to evaluate the IT services provider’s expertise and experience. You want to work with a partner who has a deep understanding of your industry and the challenges you face. Look for a provider with experience working with businesses like yours who can demonstrate a track record of success. A provider with a strong reputation and a portfolio of satisfied clients is also a good sign. Step 3: Assess the Provider’s Technical Capabilities Once you’ve identified a provider with the right expertise and experience, assessing their technical capabilities is crucial. You want a partner to deliver the specific services you need, whether cloud computing, network infrastructure, cybersecurity, or software development. Look for a provider that uses cutting-edge technology and strongly focuses on innovation and continuous improvement. Step 4: Evaluate the Provider’s Communication and Collaboration Skills Effective communication and collaboration are essential for a successful IT services partnership. You want a provider working closely with your team to understand your needs, provide regular updates and progress reports, and collaborate on solutions. Look for a partner with a clear communication strategy that is responsive to your needs. Step 5: Review the Provider’s Service Level Agreements (SLAs) Service level agreements (SLAs) are contracts between the IT services provider and the client that define the level of service to be provided, including response times, uptime guarantees, and performance metrics. Reviewing the provider’s SLAs to ensure they meet your business needs and objectives is important. Look for a provider that offers SLAs that align with your expectations and has a track record of meeting or exceeding SLA requirements. Step 6: Consider the Provider’s Scalability and Flexibility As your business grows and evolves, your IT needs will change. Therefore, it’s essential to partner with an IT services provider that can scale their services to meet your changing needs. Look for a provider with a flexible service model that can quickly adapt to your changing requirements. A provider with various service offerings and pricing models can also help you optimize your IT spending. Step 7: Evaluate the Provider’s Data Security and Compliance Data security and compliance are critical considerations for any IT services partnership. Look for a provider with strong data security protocols and compliance with relevant regulations, such as GDPR or HIPAA. Ask about the provider’s data backup and disaster recovery procedures and ensure they align with your business needs. Step 8: Review the Provider’s Pricing and Contract Terms Finally, reviewing the provider’s pricing and contract terms is important. Look for a provider that offers transparent pricing and clearly defines their contract terms. You want to avoid surprises or hidden costs down the road. Consider the provider’s payment model and whether it aligns with your budget and cash flow needs. In conclusion At Technossus, we feel choosing the right IT services partner can significantly impact your business’s success. However, following these steps, you can evaluate potential partners and find the perfect fit for your organization. Remember to prioritize your business needs and objectives, evaluate the provider’s expertise and experience, assess their technical capabilities, communication, and collaboration skills, review their service level agreements, consider their scalability and flexibility, evaluate their data security and compliance, and review their pricing and contract terms. While evaluating possible IT service partners, asking the right questions is essential to understand their capabilities, strengths, and limitations. Some questions you may want to ask include the following: What industries have you worked with, and what challenges have you helped them overcome? What specific services and solutions do you offer, and how can they help me achieve my business goals? What kind of SLAs do you offer, and how do you ensure they’re met? What measures do you have in place to ensure data security and compliance with relevant regulations? How do you collaborate with clients, and what communication channels do you use to provide updates and progress reports? How do you handle scalability and flexibility, and what service models do you offer? What kind of pricing models do you offer, and what contract terms can I expect? By asking these questions and evaluating potential IT services partners based on the criteria outlined in this article, you can make an informed decision that will help your business thrive in the ever-changing technology landscape. Remember, choosing the right IT services partner isn’t just about finding a vendor to provide services. It’s about finding a partner who can help you achieve your business goals and position your organization for long-term success.
The Differences Between Application Modernization & Application Performance Modernization
Businesses need to maintain pace with the ever-evolving technology landscape. To do this, they must understand and utilize two important concepts. Application modernization and application performance optimization. In this article, we’ll discuss both in detail so that businesses can make informed decisions when it comes to their IT strategies. What is Application Modernization? Application modernization simply means updating legacy applications to more modern technologies. This may include replacing outdated code with new coding languages, transitioning from physical servers to cloud-based services, and more. By taking advantage of advances in technology, businesses can achieve greater productivity and scalability while reducing costs. What is Application Performance Optimization? Application performance optimization refers to the process of improving an application’s performance. This is done by making changes to existing code or using external software tools. This enables monitoring and adjusting the application for maximum efficiency. Through this process, businesses can rest easy knowing that their applications are running as designed. This means that end users will experience optimal levels of performance. All without compromising on functionality or security. The Connection Between Application Modernization and Performance Management Application modernization and performance optimization go hand-in-hand. As businesses modernize their applications, they need to make sure the new solutions are performing as intended. This is where Performance Optimization is needed. By ensuring that the application is optimized for maximum efficiency and meeting user expectations, businesses can secure their success in the long term. How they are connected The connection between application modernization and performance optimization is clear. Performance optimization ensures applications are running efficiently. This is especially true in an age of rapidly evolving technology, where businesses must quickly adapt to new trends and demands. Application modernization helps businesses keep up with changes in the technology landscape. This is accomplished by: Replacing outdated code with more modern programming languages Transitioning to cloud-based services Leveraging the advantages of current APIs. This can lead to improved productivity, scalability, and cost savings. However, businesses can’t just simply update an application. They also need to virtually guarantee that their users are getting an optimal experience. Performance optimization helps businesses do just that. How? By making sure that their applications are running at peak performance. Through monitoring and analyzing application performance data, weaknesses can be identified and addressed. Once again, this helps improve user experience. Businesses have to make sure that applications are running optimally. This way, they can ensure they achieve their goals of increased productivity and customer satisfaction. Moreover, application performance management (APM) solutions provide detailed insights into an application’s usage patterns. This helps identify opportunities for improvement before they become serious issues. APM solutions also allow businesses to track user behavior over time. This means they can see exactly how changes made over time have impacted their applications’ performance. Overall, application modernization and performance optimization are essential components of any IT strategy. By using a combination of both approaches, businesses can achieve success in this ever-changing environment. How They are Independent Both application modernization and performance optimization are important components. However, they aren’t necessarily symbiotic. Modernization can take place without the need for performance optimization, and vice versa. For example, an application may be modernized to make use of current programming languages or technologies. That should improve performance but, in and of itself, is not an application performance optimization plan. On the other hand, an application may be properly optimized for speed and efficiency without having undergone any modernization efforts. In either case, businesses should strive to take advantage of both approaches. Modernizing legacy systems while also optimizing them ensures the best possible performance from the applications. Best Practices for Achieving Peak Application Performance In order to ensure they’re running optimally, there needs to be a holistic approach. This isn’t limited to only modernizing legacy systems and leveraging current technologies. It’s also done by employing best practices. By doing so, businesses can maximize the efficiency of their applications and ensure user satisfaction. Modernize first… The first step in optimizing application performance is to modernize existing applications. This involves replacing outdated coding languages and transitioning to cloud-based services. As well as leveraging current APIs. After this step has been completed… …then optimize performance Businesses then need to focus on optimizing for performance. This means regularly monitoring and analyzing application usage data. This can identify weaknesses and improvement opportunities. Additionally, tracking user behavior over time is necessary so that changes can be measured in terms of their impact on performance. Furthermore, businesses should consider implementing APM solutions. This practice will give detailed insights into how applications are being used. Finally, businesses should strive to test performance regularly. This is necessary for optimal operation and user experience. Your business does need to take advantage of both application modernization and performance optimization. This will help you verify that everything is running as required. In turn, it will enable you to maximize productivity and customer satisfaction. All while also reducing costs associated with IT operations. Application modernization and performance optimization are essential components of any successful IT strategy. Getting the Most Out of Your Applications Implementing this sort of comprehensive IT strategy will help you get the most out of your applications, maximize productivity, and ensure customer satisfaction. Ultimately, it’s key to driving long-term growth and profitability for your enterprise or organization. This strategic approach to application modernization and performance optimization is critical. With it, you can stay one step ahead of the competition. Taking action now to implement these strategies will help you get the most out of their applications and drive long-term growth for years to come. Technossus is an award-winning technology consulting firm with over two decades of experience in digital transformation, custom application development, and cloud services. Founded in 1999, we’ve partnered with multiple leading Fortune 500 companies all over the world. We have an extensive track record of successfully deploying large-scale applications for high-demand environments and optimizing their performance over time. Our team of experts helps businesses design cutting-edge software solutions that drive innovation and maximize efficiency. We […]
Five Use Cases for AI in the Financial Services Sector
Fortunes are gained and lost in fractions of a second in the financial services sector. A trade made a moment too soon. A policy issued a moment too late. The stakes are high in this industry and every tool that creates a competitive advantage has to be considered. Key among today’s most popular tools? Artificial intelligence. As Artificial Intelligence (AI) technology advances, its uses in the financial sector have become much more prevalent. AI is now being widely used not just to automate manual processes and detect fraudulent activity but helping to streamline customer support and provide personalized investment advice. What’s more, AI is creating predictive models across lines of business to uncover new insights and opportunities to drive the entire financial services industry forward. In this post, we will explore AI in the financial services industry as well as a few key use cases sure to resonate. A Brief History of Artificial Intelligence AI comes out of the computer science world and deals with creating intelligent machines that can think and act like humans. It uses algorithms, machine learning, and robotics to understand how real-world objects and data sets interact. AI systems can learn from their experiences or the experiences and data sets of other machines to make decisions based on their observations and achieve specific tasks. AI technologies include: Natural language processing (NLP) for understanding text or speech Machine vision for analyzing images or videos Robotic process automation (RPA) for automating tasks Deep learning for advancing image recognition accuracy Reinforcement learning for enhancing decision-making processes This technology is used in a wide variety of industries. This includes healthcare, finance, transportation, marketing, and more. These industries are using AI to automate tasks, detect fraud, provide personalized advice, build design models, optimize logistical routes and much, much more. Five AI Use Cases for the Financial Services Sector AI technology is quickly becoming the go-to tool for optimizing financial services operations.Here are five of the most common use cases for AI in financial services. Fraud Detection AI-powered algorithms can detect fraudulent transactions and activities more quickly than humans. Even the most complicated frauds can be detected in moments by advanced AI. By using machine learning, the system is able to identify abnormal patterns in financial data that might indicate fraud. AI is also helping with fraud detection in other ways. AI-powered facial recognition technology can be used to spot suspicious activity in real-time. Sophisticated algorithms enable it to identify and track faces and analyze behavior. Additionally, it can detect any abnormalities or discrepancies in facial recognition patterns that are indicative of fraudulent activity. Portfolio Balancing AI can be used to find the best investment opportunities. This includes for both individuals and companies. By using predictive analytics, AI can help financial advisors make informed decisions about investments. For example, AI can build an ordered list of which investment opportunities have highest potential for returns while minimizing risk. AI-powered algorithms also allow companies to automate the process of portfolio balancing. This helps ensure that a portfolio is properly diversified and well-balanced to maximize returns. Insurance Claims Processing AI is increasingly being used to automate the process of insurance claims processing. AI-powered systems can quickly and accurately: Assess claims Identify any necessary documentation Verify the accuracy of information provided by claimants. This helps streamline the process and process claims in a timely manner. New Product Development AI can be used to develop new products and services. It helps by analyzing data from various sources such as customer feedback, market research, and more. AI-powered algorithms can identify trends in customer behavior. This could help inform product development decisions. Another way is identifying customer needs and preferences. Especially those that may not be easily identifiable through traditional marketing methods. AI-powered algorithms can analyze customer data and look for patterns or trends. It can then suggest new products or services that could meet those needs. AI can also help with predictive analysis. This can help forecast future market trends and develop products tailored to those predictions. Regulatory Compliance AI can help financial services firms comply with regulations. Machine learning algorithms can quickly and accurately detect any potential compliance issues and flag them for remediation. This reduces the risk of non-compliance. AI can also be used to automate the process of monitoring customer transactions for suspicious activity, helping to prevent money laundering or terrorist financing. Additionally, it can identify any irregularities in transactions. This includes incorrect payments being sent or received and potential violations of tax or other regulations. Implementing AI into your Financial Services Business In order to embrace AI, there are several key steps Decide on Desired Outcomes When a financial institution is considering the use of AI, it’s important to decide on desired outcomes first. This helps the institution maximize the potential benefits of AI and minimize any risks associated with its implementation. Having clear objectives in mind upfront makes it easier to develop an effective strategy for incorporating AI into operations. Having a set of desired outcomes will help guide decision-making when selecting the best AI solutions. It will also provide clarity on areas that need improvement. Additionally, it will reveal whether additional resources need to be allocated in order to achieve those goals. Lastly, having an understanding of this can help form necessary training programs and processes. Employees will need to be trained to work with new technologies and systems. Once these objectives are established, the task of choosing which specific solutions should be implemented takes place. That means assessing different types of technology platforms. This includes machine learning algorithms or natural language processing tools based on their ability to meet your predetermined objectives. While of course minimizing risk factors like data security concerns or cost implications. Choosing wisely here can make all the difference between success and failure. Form a Plan for Integration and Maintenance Once there’s a decision to integrate AI, it’s time to plan the integration and maintenance of this technology. This will ensure that all stakeholders are in […]
Latest Innovations in Process Automation of Healthcare Ops
Automation has become an essential part of the healthcare industry. The trend to reduce tedious work has increased the quality of healthcare for both patients and care providers. This blog post will look at why there has been an increasing demand for automation. We’ll also discuss the benefits and the latest innovations in healthcare operations. Increasing demand for automation Technology is the center of modern business There has been an increasing demand for automation to improve operations in healthcare. Organizations have already seen the benefit of data-driven decisions and integrated systems. For healthcare, this means reducing time spent on administrative tasks and providing care for more patients. Process automation maximizes resource utilization Staffing and costs have always been a challenge for healthcare. This is why there has been a demand for automation to maximize resource utilization. By finding gaps in processes, staff can be enabled to focus on more critical activities. This improved efficiency translates into better resource allocation and cost savings. Automation systems also result in faster response times and better productivity. As healthcare organizations look for ways to improve the experience of both care providers and patients, automation has played an important role in maximizing limited resources. Benefits of automating tasks We’ve talked about the benefits of automating tasks, but what exactly can be automated? Healthcare providers spend a significant amount of time on administrative tasks. Specific tasks such as data entry, record keeping, and reporting can all be automated. This allows healthcare professionals to improve care delivery and efficiency of the work. Below are three benefits to automating tasks in healthcare operations. Improved patient care The healthcare industry has seen how automation benefits the patient experience. First, automating time-consuming tasks speeds up the process of delivering care. From scheduling appointments to document management, patient care has improved with automation. For patients, this means a seamless experience and faster response time. Improved employee efficiency Another benefit of automation is how it can improve employee efficiency. For example, automating medical testing procedures have added a layer of convenience and reliability for care providers. This also means that employees are able to handle more patients with limited resources. For employees working in operations, automation has allowed systems to be integrated. This allows patient records to be coherent and doctors to better rely on them. Improved efficiency and effectiveness from healthcare providers Automation is a common solution to improve efficiency and effectiveness for healthcare providers. Because automations free up time, healthcare professionals can focus on curating effective care. They can also rely on automation to schedule follow-ups and treatments so that patients are receiving the care they need. Other ways automations improve effectiveness in healthcare are with automated check-ins and prescriptions. Latest innovations in the field of process automation for healthcare providers Access to care Access to care is an entirely different experience today. Through new technologies, people can now book virtual medical appointments, order tests, and medications, and even receive diagnoses without ever leaving their homes. An example of these innovations includes medical apps such as Babylon Health. This solution enables users to access virtual consultations with doctors from anywhere. Meanwhile, telemedicine tools like WebMD Connect provide remote monitoring solutions. Lastly, AI-driven chatbots such as Flo provide real-time answers about health-related topics. Such innovations are making life more convenient, especially in areas of limited healthcare. From saving hours of online waiting rooms to receiving immediate advice, access to care has changed for the better. Employee workflows Automating employee workflows is a popular topic among businesses. Many industries are benefiting from productivity tools like project management or document sharing. As healthcare providers look for ways to increase efficiency and productivity, there has been a growing demand for such tools. A popular solution is online scheduling apps. This has removed an entire chunk of tasks in the employee workflow to boost productivity. Documents are also shared over the cloud, which removes any gap in communication. As employees can access information securely from anywhere, it removes the need for the physical transfer of records. Patient care delivery Diagnoses Automating diagnoses has come a long way in recent years. Technology today plays an important role in the medical process. Much of diagnosis is assisted by technology, and there are even autonomous robots examining patients. This has helped doctors to accurately diagnose patients and reduce human error. Additionally, healthcare providers can access medical databases to arrive at diagnoses faster. Treatments Whether it is treatment planning or delivering surgery, technology has taken up more responsibility. Thanks to advances in artificial intelligence, computers can now curate treatments for patients. In addition, robots are performing surgical maneuvers that would challenge even the most well-trained human physician. Automating medical treatments has become so accurate and reliable in some areas that many experts believe it could revolutionize the healthcare industry for years to come. Choosing the right process automation solutions Choosing the right automation solutions for your practice, provider, or use case is not a “one size fits all” proposition. In fact, getting the most out of any automation investments requires seeing the world through a different lens. Consider the following game plan when introducing automation to your healthcare operations. Determine the desired outcomes Automations are changing the healthcare industry and the number of innovations will continue to grow. If you are debating on a solution, it is essential to first determine the desired outcomes. A clear picture of goals will allow you to focus on a need and avoid derailing. One way to do this is by choosing a specific pain that you’d like to resolve. For example, maybe you’d like to reduce the number of administrative tasks to manage. This can help you focus on improved scheduling systems or digital payment methods. Setting expectations and building desired outcomes should be the first step of an automation strategy. Build a plan for evaluation Before choosing an automation solution, develop a plan for evaluating the technology. This should include all of the available features and capabilities, as well as […]