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Killexams : Copedo Developer approach - BingNews Search results Killexams : Copedo Developer approach - BingNews Killexams : Small business needs a different sort of software developer

Software developers are some of the most highly sought-after IT professionals, and many companies consistently struggle to find the coders they need. 

That can be especially true of smaller businesses, particularly if they lack the money to tempt developers who might otherwise end up going to big technology companies. But what's also true is that not every developer wants to work for a giant, faceless corporation. And in any case, every software developer has to begin designing code somewhere, whether at a mid-size tech company or their old college roommate's startup, which means that smaller businesses are often a route into the industry for many developers just starting out.

And depending on a company's size, a developer will face different challeges and use different skill sets.

Brendan O'Leary, developer evangelist at GitLab, says that smaller companies can offer greater feelings of connectedness between a developer and their work's impact on their company. O'Leary says smaller companies allow developers to focus more on their cycle time, which is the time it takes from writing the first line of code to seeing it go into production.

That can be a huge advantage that a small company can offer, he says: "That's an intrinsic motivator that's really hard to replace with money or anything else."

O'Leary says developers at larger companies are more likely to feel disconnected from their work's direct impact on their company and its customers. 

Also: The future of the web will need a different sort of software developer

Amanda Richardson, CEO of CoderPad, agrees that developers at smaller companies have a unique chance to witness the fruits of their labor by working on a project in its entirety.

"Working at a smaller company can provide the opportunity to work from start to finish on projects while seeing the immediate impact of your work," she says. 

According to Richardson, small businesses might be the route new or inexperienced developers choose, as startups are typically operating within the bounds of small budgets. Developers at smaller companies will need excellent problem-solving and research skills. On the other hand, she says more prominent companies are in the market for IT professionals who might not have a broad scope of experience in all facets of software development but have a deep understanding of one specific topic.

"Because budgetary constraints often mean startups can't match the pay of large companies, they are more open to considering profiles that don't tick all the boxes in terms of degrees or professional experience," she says.

Bigger businesses do offer specific advantages for certain types of individuals. At a larger company, software developers and engineers can expect more structure, clearly designated roles and responsibilities, and established processes. A larger company is probably further along in its DevOps growth and hires developers who are ready to face a project head-on. That can be a good environment for someone just starting out.

"Working as a developer at a large company implies a structured environment with well-established processes and roles," Richardson says. "It can be especially valuable for young graduates to learn within a structured environment and see software development at scale while acquiring best practices."

The downside, of course, is that developers in a bigger business might find themselves completing mundane tasks. According to a Stack Overflow survey, 45% agreed that feeling unproductive is the number one reason they're unhappy at work, with inflexible working practices not far behind as something to complain about.

This issue is particularly true at larger companies if developers work on a small part of a larger project, with each team of developers holding one piece of the puzzle, and little sense of what the completed work looks like.

In contrast, smaller companies can offer software developers a more comprehensive range of knowledge, as each developer will need to take on more pieces of the puzzle and manage more parts of a project. At these companies, developers will be closer to understanding a problem and will work closely with the required steps to find a solution. 

Both Richardson and O'Leary agree that smaller companies have a slight advantage over larger companies with how fast they can develop new software. 

Richardson thinks this advantage is because larger companies must make more complex decisions. At the same time, O'Leary says it's because developers can focus more intensively on their cycle time at smaller companies.

Larger companies overcome some of the challenges of building software by using smaller groups to make the process more manageable. Smaller teams can communicate and collaborate faster, releasing software at lightning speed. As a company grows, it will need to split its engineers and developers into much smaller teams, and each team will oversee a small portion of a project.

Even some of the largest tech companies still want their developers to keep to small teams, to emulate the agility of small businesses.

"The smaller the team, the better the collaboration," says Amazon – hardly a small company – in its so-called "two-pizza team rule", which states that DevOps teams should be small enough for two pizzas to feed everyone on the team.

"Collaboration is also very important as the software releases are moving faster than ever. And a team's ability to deliver the software can be a differentiating factor for your organization against your competition. Imagine a situation in which a new product feature needs to be released or a bug needs to be fixed – you want this to happen as quickly as possible so you can have a smaller go-to-market time," it says.

Also: GitHub vs GitLab: Which program should you go with?

Flexibility is another factor. Richardson says developers working at small companies and startups have more autonomy and responsibilities than they would at larger business. This autonomy creates room for developers to pitch new ideas to the company. According to the Stack Overflow survey, 39% of respondents said that a lack of growth opportunities makes them unhappy with their jobs. A developer's possibilities to expand and grow in their career might be much higher at smaller companies.

But the same autonomy can mean a lack of guidance and more room for error.

"The drawback of working for a smaller company is you're unlikely to have the reassuring support of a seasoned engineer to answer questions and help you ramp up or be able to test your ideas at scale," she says.

O'Leary says it all depends on the developer and what kind of career goals they have. Some people might enjoy the challenges of trialing new code and solving problems that small businesses face. Others might prefer the stability of a larger, more established company.

Working at a small, mid-size, or large company has positive and negative aspects. It all depends on what an individual developer or engineer strives for in their career, and how many responsibilities they'd like to take on in their professional lives.

But it's almost universal for developers to want to understand the impact of their work and feel like the work they complete is meaningful and valuable to society. So in a tough market, hiring managers at companies big and small should look at the work they are offering and consider how the developers they recruit can be made to feel like they are really making a difference.

Sun, 09 Oct 2022 12:00:00 -0500 en text/html
Killexams : Why developers hold the key to cloud security

In the days of the on-premises data center and early cloud adoption, the roles of application developers, infrastructure operations, and security were largely siloed. In the cloud, this division of labor increases the time-to-market for innovation, reduces productivity, and invites unnecessary risk.

In a data center environment, developers build software applications, IT teams build the infrastructure needed to run those applications, and security teams are responsible for ensuring that applications and infrastructure are secure. Developers must build software within the constraints of the underlying infrastructure and operating systems, and security processes dictate how fast everyone can go. When security discovers a vulnerability in production, the remediation process typically involves all stakeholders—and considerable rework.

By freeing teams of the physical constraints of the data center, the cloud is bringing the biggest shift in the IT industry in decades. But it’s taken years for organizations to start unlocking the true potential of the cloud as a platform for building and running applications, as opposed to using it as a platform for hosting third-party applications or those migrated from the data center. When the cloud is used simply as a “remote data center,” the classic division of labor is carried over, and much of the potential of the cloud goes unrealized.

But the shift to using the cloud as a platform for building and running applications is disrupting security in profound ways. From the perspective of the cloud customer, platforms like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud are 100% software, and developers are now programming the creation and management of their cloud infrastructure as an integral part of their applications. That means developers are designing their cloud architecture and setting security-critical configurations—and then changing them constantly.

An opportunity for organizations

This shift represents a massive opportunity for organizations operating in highly competitive industries, because application and cloud teams can innovate much faster than they could in a data center. But it presents a serious challenge for those teams that need to ensure the security of increasingly complex and highly dynamic cloud environments.

The only effective way to approach cloud security today is by empowering the developers building and operating in the cloud with tools that help them proceed securely. Failing to do so makes security the rate-limiting factor for how fast teams can go in the cloud and how successful digital transformation can be.

Copyright © 2022 IDG Communications, Inc.

Tue, 04 Oct 2022 17:28:00 -0500 en text/html
Killexams : Drug Development Can Benefit from an Integrated Approach

When you’re trying to solve a puzzle, having all the pieces isn’t enough. You need a strategy. For example, if you want to complete a jigsaw puzzle, you’ll probably begin by piecing together its edges. More challenging puzzles, such as those encountered in drug development, require strategies that are rather more sophisticated. Indeed, in drug development, the strategic challenges are so involved that they often prompt biotechnology and biopharmaceutical companies to secure the services of a contract research organization, or CRO.

The CRO known as IRBM advocates what it calls an integrated approach. This approach, IRBM explains, is all about pulling together technologies to enable target identification, candidate screening, biomarker development, in vivo testing, and clinical development. What’s more, IRBM emphasizes the importance of having a vision. What good is piecing together a border or frame if one cannot see the big picture?

In drug development, envisioning the big picture is equivalent to knowing how to exploit fundamental biological insights and move toward the ultimate goal: a safe and effective drug. Moreover, it is desirable to achieve this goal with all deliberate speed.

Michele Luche
Michele Luche
Vice President and Head of North American Business Development, IRBM

IRBM argues that in drug development, speed is about cultivating collaborative relationships. These are relationships in which data is shared freely among drug development partners, enabling data-driven workflows. To explain how these relationships form the basis of strategic drug development efforts, two IRBM executives, Alberto Bresciani and Michele Luche, agreed to an exclusive interview with GEN magazine. Bresciani is IRBM’s director of high-throughput biology and screening, and Luche is the CRO’s vice president and head of North American business development.

“In drug discovery and development programs,” Bresciani and Luche agree, “it is necessary to address questions about fundamental biology and optimal therapeutic modality, and to find answers using advanced methods and data-driven decisions.” Bresciani and Luche maintain that IRBM is able to ask the right questions and find the right answers because it “has expertise in imaging, in structural biology, in evaluating molecules in primary cell lines, and in using stem cells, 3D cell cultures, and co-cultures that support disease-relevant systems.” Besides noting that IRBM employs technologies that offer better spatial and temporal resolution, Bresciani and Luche emphasize that the CRO can accelerate drug discovery by leveraging artificial intelligence and machine learning (AI/ML) technologies and implementing disease-relevant model systems.

Strategic elements

Luche emphasizes the importance of considering targets, goals, model systems, libraries, and liabilities at the outset of the drug discovery program. Doing this makes it easier to identify optimal drug candidates. Luche adds that a high degree of transparency in data sharing between collaborating organizations and within departments in an organization facilitates expediency and high-level strategy in the iterative discovery process. She says, “To have different pieces of the puzzle interact efficiently, reduce cycle times, and leverage powerful collective experience, it’s important that data be promptly reviewed by everybody involved.”

IRBM fosters collaborations diagram
IRBM fosters collaborations with organizations from the pharmaceutical, biotech, and academic sectors to accelerate drug discovery from target validation and hit identification to candidate nomination. The firm’s R&D engine integrates all major areas of expertise involved in the development of therapeutics across modalities.

Luche senses that data sharing is becoming more acceptable through the success of collaborative programs. “Traditionally, data was held very close to the chest,” she observes. “Of course, assets should be protected, but we must understand there’s a lot of experience out there that should be harnessed to efficiently bring a candidate to clinic.”

Investing in front-end strategizing, supporting data transparency, and adopting a step-by-step problem-solving approach that incorporates insights from basic biology and AI/ML can be crucial in identifying optimal candidates and terminating suboptimal ones. “Terminating a program is never pleasant, especially if researchers have a personal stake in the project,” Luche relates. “It’s very important that crucial questions are answered quickly via data-driven approaches.”

For example, in the development of proteolysis targeting chimeric (PROTAC) drugs, access to systematic and quantitative assays can be invaluable. If a candidate were to form a ternary complex and bind a target in a biochemical setting, yet fail to degrade the target in cells, such assays could indicate where improvements are needed. “A sequence of assays may be used to test cellular permeability, ternary complex formation, target ubiquitination, and proteasomal delivery and function,” Bresciani details. “These assays can help the design team develop the right solution.”

Under one roof

IRBM believes in the practical merits of maintaining the organization’s capabilities under one roof and applying them to support iterative processes. Short cycle times in complex workflows depend on quick responses and flexibility. Groups looking into biology, chemistry, metabolism, and pharmacokinetics must interact and respond quickly to incoming data.

“Being in the same physical location makes the programs go that much faster,” Luche insists. “You can do research at different locations, but it adds complexity and delays that can be overcome if everybody with a critical role in the program is together.”

Customized systems

A productive strategy at IRBM has been to begin with a modality-agnostic mindset, one that stays focused on basic mechanisms that dictate the development or selection of tools and disease-relevant model systems. “For each target, we develop tailor-made systems,” Bresciani asserts. “Rather than use general libraries to identify hits, we try to understand the biology of the target and ligand, and design ad hoc libraries to maximize our chances.”

For example, IRBM utilizes phage display libraries to identify therapeutic peptides. Phage display, a technology for screening protein interactions at high throughput using bacteriophages, remains one of the most powerful tools for the identification and maturation of protein ligands. IRBM uses phage display to segregate, create, or identify ligands for a target, and to weed out targets with undesirable biological responses.

“We’re fortunate that phage display is part of our broader capabilities in peptide drug discovery to identify high-affinity and high-avidity hits,” Luche notes. “Importantly, it’s not an isolated technology.” When identifying and optimizing candidate peptide drugs for clinical progression, IRBM may draw on a comprehensive array of in vitro and in vivo tools. These tools facilitate studies of various kinds, including pharmacodynamic and pharmacokinetic studies.

AI/ML applications

Traditionally, decisions in drug discovery have depended on expert assessments, linear interpretations of limited data, or intuitive hunches. These counsels are being superseded by AI/ML. By forging new connections between basic biology and decision making, AI/ML can help developers zero in on the best targets, development strategies, and responder populations.

“AI/ML offers testable options based on large training and validation sets,” Bresciani says. “It can present parameters that together [indicate] whether something can be progressed or not.”

Although AI/ML is a powerful technology, it has its limits. “It’s risky,” Bresciani cautions, “to think that AI/ML is applicable under every condition.” The first step to benefiting from AI/ML is understanding when it is appropriate.

For example, AI/ML can be helpful in protein structure–based drug design. AlphaFold-enabled prediction of 3D structure is particularly useful when targets cannot be crystallized, purified directly, or act as disease modulators. Like all tools, Bresciani explains, AlphaFold may be more useful in some contexts than others. He adds that recognizing a suitable context requires that “you have your fundamental biology and the plausibility of your rationale defined.”

specialists use Bruker 600 UltraShield nuclear magnetic resonance (NMR)
IRBM’s multidisciplinary team includes certified in structural biology. In this image, some of them are shown using a Bruker 600 UltraShield nuclear magnetic resonance (NMR) spectrometer. By exploiting NMR technology, IRBM can study the 3D structures of peptides, proteins, and protein complexes. Moreover, IRBM can apply the structural knowledge it gains to advance aggregation state analysis, hit validation, and lead optimization.

In the context of drug discovery, AI/ML often complements traditional approaches instead of replacing them. For example, AI/ML can support a hypothesis-driven approach in drug discovery and evaluate the premises of particular drug discovery projects. “With AI/ML,” Bresciani says, “we can define a target and identify how to measure whether the target is relevant for a certain phenotype, profile, or function.”

Luche also believes AI/ML and basic biology go hand in hand. “Many drugs have been developed because somebody paid attention to a piece of data that wasn’t necessarily on the path but produced a result that warranted follow up,” he explains. “If your AI/ML doesn’t [have a built-in ability to assess] alternative scenarios, you could be missing important things.”

Biomarkers of safety and efficacy

For IRBM, an integrated approach to drug discovery is one that collates all major areas of expertise involved in various therapeutic modalities under one roof. One area of expertise that IRBM prioritizes—and makes a point of employing early in discovery—is biomarker development.

“Biomarkers play a huge role in patient stratification and in characterizing patient responses,” Luche points out. “Where possible, we try to build that into the early discovery phase for all disease areas where it can be useful.” She stresses that early-stage biomarker development is critical in translational research.

Having a biomarker helps in determining how the therapeutic candidate behaves toward its target. It helps identify imaging agents for diagnostics and efficacy estimations. And it helps uncover potential liabilities.

“We start thinking about pharmacodynamic biomarkers when we begin testing target engagement in vitro, long before the discovery process reaches clinical trials,” Bresciani remarks. “We consider how to adapt these biomarkers to measure target engagement in vivo or the primary effect in preclinical and clinical trial stages. This approach can be invaluable for interpretation of results as well as in the identification of the optimal candidate.”

There is a distinct advantage in some of the new therapeutic modalities, such as PROTACs, antisense oligonucleotides, siRNAs, gene therapies, and splicing modulators. The advantage is that the desired pharmacodynamic endpoint is known. “Being able to develop a direct measure of target modulation provides additional information during the discovery and development stages in an in vivo model,” Bresciani explains. “It underpins decisions on dosage, final target levels, and safety.”

Alternative models

In vitro models now include induced pluripotent stem cell–derived blood-brain barrier systems and complex 3D organoid systems. They are gaining popularity in drug development because they can do what animal model systems cannot. Specifically, they can capture the intrinsically human-centric processes that influence and are influenced by certain novel therapeutic modalities.

For example, splicing modulators are a popular new therapeutic modality that are quickly moving from being scientific tools to experimental drugs, based on structure-activity studies. “To test a splicing modulator’s function, you need to have the splicing sites, introns, and exons laid out in a specific way to make it work,” Bresciani notes. With such modulators, testing for on- and certain off-target toxicities may be difficult if animal models are used. In vitro model systems based on human cellular components reserve a predictive advantage.

In the early stages of drug development, the use of in vitro organ-on-chip systems is increasingly common, particularly in certain scenarios. Indeed, the advantages of substituting such systems for animal model systems are beginning to be recognized by regulatory agencies. Whether these advantages should be sought depends on the specific project and the availability of suitable in vivo models.

“The more complex an in vitro system becomes, the more complicated it is to have everything under control to ensure reproducibility,” Bresciani says. “It could take a long time to trust predictions in a new system. For example, we developed a blood-brain barrier system to understand the permeability of compounds and how the barrier responds to the presence of certain drugs. It took us a long time to validate the model.”

Microphysiological model systems such as explant cultures or organoids require extensive testing and validation under stringently controlled conditions before they gain acceptance as reliable models for efficacy and safety studies. Bresciani states, “Regulatory agencies are already evaluating such in vitro organoid or 3D culture systems in scenarios where animal models cannot be predictive due to the lack of underlying biology for a specific intervention.” Such systems may be easier to use in efficacy tests than in safety tests, as the former involve confirming the activity of molecules under specific conditions in a disease-relevant system.

Sat, 15 Oct 2022 07:17:00 -0500 en-US text/html
Killexams : Find out how much software developers are making in Germany in 2022

This article was originally published on .cult by Mikaella C, Inês Almeida. .cult is a Berlin-based community platform for developers. We write about all things career-related, make original documentaries, and share heaps of other untold developer stories from around the world.

Last year we brought you our first comprehensive breakdown of developer salaries in Germany. We used extensive data gathered over the course of five years, breaking down all the variables that go into making up that magic number: your salary.

In 2021, we found that while COVID-19 impacted developer hirings, it didn’t make a noticeable difference in salary. In this year’s report, we’ve found that hirings have bounced back, with a 54% increase in developer hirings from 2020 to 2021. Developer salaries have continued to rise, with a year-on-year improvement from 2021 to 2022, proving again that Germany is indeed a good place to be a developer.

 Average developer salary in Germany offered salary by role and years of experience 2021

Breakdown of developer salaries in Germany

Experience, role, tech stack, gender, and even nationality contribute to how much a developer earns. And the city you live in plays a role, too. The highest average salaries are found in Munich, but the best bang for your buck is in Berlin, which offers generous salaries with a lower cost of living.

GER Average Offered Salary 2021

If you’re not originally from Berlin, you can still set your sights on the city. Our data found that being a local doesn’t necessarily guarantee a higher pay grade. In both 2021 and 2022, salaries rose not just for local native German speakers but also for local, non-native speakers and for those who emigrated to Germany from the EU and the rest of the world.

Offered salary in Germany per talent type and role 2021

Offered salary in Germany per talent type and role 2022

  • Depending upon the role, non-native-speaking locals can earn up to 4% more than their native-speaking counterparts.
  • Not from the EU? No worries. Developers who have moved to Germany from the rest of the world have found consistently higher salaries than those who moved from the EU. Just get that visa sorted!

Here’s how that data starts to look when we factor in not just role, but years of experience.

 Average offered salary per talent type and years of experience in Germany in 2021

Average offered salary per talent type and years of experience in Germany in 2022

The gender pay gap is still a problem

In both 2021 and 2022, male developers were paid consistently more than female developers, sometimes by as much as 5%. In fact, data shows that the gender pay gap widened in 2022, with women more consistently receiving lower salaries across both junior and senior roles.

Offered salary in Germany per gender and years of experience 2021/2022

Location and nationality don’t affect interview invites and hires

Along with the fairly equitable rates of pay for developers no matter where you’re from, we analysed how likely you are to make it to the job interview based on your location.

Here, locals have the advantage, with the lion’s share of interview invites and hires going to candidates already located in Germany.

However, after a decline in hiring candidates from the rest of the world in 2019 and 2020, rates are rising again for 2021 and 2022, proving that borders aren’t a barrier for the right job.

Interview invites in Germany by talent per year

GERMANY Hires per talent type per year (Germany)

Expectations are low… too low!

We found one consistent factor across all of our data: developers typically underestimate the salary they deserve. For example, check out the difference between the estimated salary for junior management (€39,200) and the average offered salary for junior management (€67,500): a whopping 41% difference.

Typically, the expected salary and average offered salary tend to align more in senior roles, suggesting that more experienced developers have a more accurate idea of what they’re worth. But even then, they are still consistently underestimated, leading us to the conclusion that many developers don’t have a precise picture of the real salary landscape out there.

Germany: Expected salary by role and years of experience 2021

Expected salary by role and years of experience 2022

Once again women are expecting less than their male counterparts. They consistently ask for €2,000+ less, while that number grows as the experience grows.

Germany: Expected salary by gender and years of experience 2021/2022

Expected salary by talent type and role 2021

GERMANY Expected salary per talent type and role 2022


Our key data source is the salaries specified by hiring companies during the interview process on the Honeypot platform. If an interview invite was missing significant information (like position, title, or company location), we removed those from the study to ensure the data can be compared consistently. We also removed unusually low or high salaries to avoid extreme outliers and used an external library to determine gender based on the individual’s first name. All salaries are based on the company’s initial offer, and not a final negotiated and contracted amount.

The best way to make sure you’re getting the best possible salary is to be informed and prepared to talk about it! So share what you’ve learned and sign up for our fabulous newsletter for even more reports, videos, interviews and insights.

Sun, 25 Sep 2022 06:18:00 -0500 en text/html
Killexams : Modernization: An approach to what works

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With digital disruptors eating away at market share and profits hurting from prolonged, intensive cost wars between traditional competitors, businesses had been looking to reduce their cost-to-income ratios even before COVID-19. When the pandemic happened, the urgency hit a new high. On top of that came the scramble to digitize pervasively in order to survive.

But there was a problem. Legacy infrastructure, being cost-inefficient and inflexible, hindered both objectives. The need for technology modernization was never clearer. However, what wasn’t so clear was the path to this modernization.  

Should the enterprise rip up and replace the entire system or upgrade it in parts? Should the transformation go “big bang” or proceed incrementally, in phases? To what extent and to which type of cloud should they shift to? And so on.

The Infosys Modernization Radar 2022 addresses these and other questions. 


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The state of the landscape

Currently, 88% of technology assets are legacy systems, half of which are business-critical. An additional concern is that many organizations lack the skills to adapt to the requirements of the digital era. This is why enterprises are rushing to modernize: The report found that 70% to 90% of the legacy estate will be modernized within five years.

Approaches to modernization

Different modernization approaches have different impacts. For example, non-invasive (or less invasive) approaches involve superficial changes to a few technology components and impact the enterprise in select pockets. These methods may be considered when the IT architecture is still acceptable, the system is not overly complex, and the interfaces and integration logic are adequate. Hence they entail less expenditure.

But since these approaches modernize minimally, they are only a stepping stone to a more comprehensive future initiative. Some examples of less and non-invasive modernization include migrating technology frameworks to the cloud, migrating to open-source application servers, and rehosting mainframes.

Invasive strategies modernize thoroughly, making a sizable impact on multiple stakeholders, application layers and processes. Because they involve big changes, like implementing a new package or re-engineering, they take more time and cost more money than non-invasive approaches and carry a higher risk of disruption, but also promise more value.

When an organization’s IT snarl starts to stifle growth, it should look at invasive modernization by way of re-architecting legacy applications to cloud-native infrastructure, migrating traditional relational database management systems to NoSQL-type systems, or simplifying app development and delivery with low-code/no-code platforms. 

The right choice question

From the above discussion, it is apparent that not all consequences of modernization are intentional or even desirable. So that brings us back to the earlier question: What is the best modernization strategy for an enterprise?

The truth is that there’s no single answer to this question because the choice of strategy depends on the organization’s context, resources, existing technology landscape, business objectives. However, if the goal is to minimize risk and business disruption, then some approaches are clearly better than others.

In the Infosys Modernization Radar 2022 report, 51% of respondents taking the big-bang approach frequently suffered high levels of disruption, compared to 21% of those who modernized incrementally in phases. This is because big-bang calls for completely rewriting enterprise core systems, an approach that has been very often likened to changing an aircraft engine mid-flight. 

Therefore big-bang modernization makes sense only when the applications are small and easily replaceable. But most transformations entail bigger changes, tilting the balance in favor of phased and coexistence approaches, which are less disruptive and support business continuity.

Slower but much steadier

Phased modernization progresses towards microservices architecture and could take the coexistence approach. As the name suggests, this entails the parallel runs of legacy and new systems until the entire modernization — of people, processes and technology — is complete. This requires new cloud locations for managing data transfers between old and new systems.

The modernized stack points to a new location with a routing façade, an abstraction that talks to both modernized and legacy systems. To embrace this path, organizations need to analyze applications in-depth and perform security checks to ensure risks don’t surface in the new architecture. 

Strategies such as the Infosys zero-disruption method frequently take the coexistence approach since it is suited to more invasive types of modernization. Planning the parallel operation of both old and new systems until IT infrastructure and applications make their transition is extremely critical.

The coexistence approach enables a complete transformation to make the application scalable, flexible, modular and decoupled, utilizing microservices architecture. A big advantage is that the coexistence method leverages the best cloud offerings and gives the organization access to a rich partner ecosystem. 

An example of zero-disruption modernization that I have led is the transformation of the point-of-sale systems of an insurer. More than 50,000 rules (business and UI) involving more than 10 million lines of code were transformed using micro-change management. This reduced ticket inventory by 70%, improved maintenance productivity by about 10% and shortened new policy rollout time by about 30%. 

Summing up

Technology modernization is imperative for meeting consumer expectations, lowering costs, increasing scalability and agility, and competing against nimble, innovative next-generation players. In other words, it is the ticket to future survival. 

There are many modernization approaches, and not all of them are equal. For example, the big-bang approach, while quick and sometimes even more affordable, carries a very significant risk of disruption. Since a single hour of critical system downtime could cost as much as $300,000, maintaining business continuity during transformation is a very big priority for enterprises.

The phased coexistence approach mitigates disruption to ensure a seamless and successful transformation. 

Gautam Khanna is the vice president and global head of the modernization practice at Infosys.


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Wed, 05 Oct 2022 09:32:00 -0500 Gautam Khanna, Infosys en-US text/html
Killexams : Coinbase Cloud debuts Web3 developer platform

Blockchain infrastructure platform Coinbase Cloud has officially rolled out its Web3 developer platform, allowing users to build new decentralized applications free of charge. 

The new developer platform, dubbed Node, allows users to create and monitor Web3 applications while accessing the Ethereum blockchain and indexers, the company disclosed Wednesday. While Node offers a tiered subscription model, the free plan includes access to advanced APIs that allow for the creation of decentralized applications and nonfungible token (NFT) applications.

Coinbase Cloud claims that Node enables faster creation of Web3 applications while reducing both complexity and cost. This feeds into the platform’s broader service offerings, which include all-in-one access to payments, identity, trading and data infrastructure.

As the name implies, Coinbase Cloud was created by crypto exchange Coinbase in 2021 to provide developers with familiar tools for building decentralized products. Shortly after the developer suite was launched, Coinbase executives proclaimed that they “want to be the AWS of crypto,” referring to Amazon Web Services, which powers the enterprise cloud market.

Related: Web3 is creating a new genre of NFT-driven music

Web3 has become an all-encompassing buzzword describing some future version of the internet. Still, developers, venture capitalists and investors have a keen interest in identifying and formulating what this future internet will look like beyond the common features of decentralization and user-controlled communities.

At the recent Australian Crypto Convention, whic Cointelegraph attended, Trust Wallet CEO Eowyn Chen said three roadblocks were preventing widespread Web3 adoption: security, ease of use and privacy. While she outlined some solutions, Chen said the bear market could provide an excellent opportunity to address consumer concerns before Web3 concepts attract more mainstream attention.