Tapeis in the Enterprise Collaboration Industry

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In a seismic shift in the tech landscape, the has unearthed a disquieting reality: the confidence of U.S. workers in their employers has hit an all-time low, echoing through the corridors of power like a server crash. Glassdoor survey Registering at a paltry 45.6%, this is not just a dip; it's a full-scale system failure, marking the most precipitous decline since Glassdoor started parsing the tech workforce matrix in 2016. Strap in, folks, as we dissect the intricacies of economic entropy, tightening budgets, and the impending algorithmic apocalypse. Layoffs and the Job Market Crunch As the startup unicorns shed their glitter, the Glassdoor survey is the red alert: the majority of tech talents foresee stormy skies in the next six months. like weeds in a neglected codebase, and job options are dwindling faster than the lifespan of a trending app. Layoffs are sprouting It's a survival-of-the-fittest moment, pushing tech professionals into a 'grin-and-bear-it' scenario as they reconcile with the harsh realities of a turbulent job market. Byte-Sized Budgets In this era of innovation, budgetary constraints are threatening to stifle the tech ecosystem. Smaller budgets are akin to a memory leak, sapping the efficiency and potential of the workforce. The equation is simple: less capital equals more burdens for the tech workforce – increased workloads, slashed benefits, and a perilous drop in growth opportunities. The ever-shrinking staffing levels are turning the once vibrant tech hubs into desolate coding wastelands. The Ripple Effect on Digital Morale Beyond the lines of code and the intricacies of algorithms, the nosedive in confidence is causing a digital discontent epidemic. Stress levels are escalating, job satisfaction is crashing harder than outdated software, and the morale of the tech troops is at an unprecedented low. It's a digital meltdown in slow motion, threatening to disrupt the harmonious symphony of innovation. Tech Titans and the Path Forward In the labyrinth of economic uncertainties, transparency emerges as the secret sauce. Tech leaders, take note – open communication regarding the glitches in the system, proactive strategies to navigate the digital turbulence, and fostering a sense of belonging among the workforce can serve as the ultimate debug session. Tech companies need to reboot their support initiatives, provide mental health resources, invest in skill development programs, and establish channels for constructive feedback. In the tech crunch era, cultivating a culture of transparency and prioritizing the digital well-being of the workforce is not just a strategy; it's a survival imperative. As U.S. tech workers grapple with their lowest confidence levels since the dot-com bubble burst, it's a call to action for tech titans to lead with resilience. Rewriting the code, shoring up the digital defenses, and navigating this tech tempest together will be the defining challenge. By embracing transparency, providing unwavering support, and fortifying the digital backbone, tech companies can steer through the current crisis and emerge stronger in the ever-evolving tech landscape.

Unraveling the Tech Tapestry: US Workers' Confidence Plummets in the Face of Economic Dystopia

This piece of mine originally blog in March 2017. Enjoy! appeared on Tripwire’s State of Security When hard disk drives contain super sensitive data, professionals like myself will usually recommend that they shouldn’t be placed in any computers that have an operational TCP/IP stack. There are various ways that internet-connected computers can secure themselves against attack, such as firewalls, IPS devices, antivirus software, and OS configuration. That’s good enough for most personal and professional computing needs. cybersecurity security There’s always the potential for attack even when you take many security precautions, but most computers need to use the internet. But when attackers want your data, such as in the financial industry or in intelligence, the best bet is for your most sensitive data storage to have no network connectivity whatsoever. We refer to that technique as air-gapping. really Well, these days, air-gapping may no longer be enough. Can people see your HDD’s blinky lights? of Ben-Gurion University has discovered a new way for attackers to get data from air-gapped machines. Guri and his research team developed malware that operates at the user level that’s designed to communicate an HDD’s data through its LED light. The challenge for an attacker is to get the malware on an air-gapped machine. But it’s possible for an attacker to do that with removable media, such as a or an optical disc. your way to physical access to a target machine, and bingo! Mordechai Guri USB stick Socially engineer has focused on the security of air-gapped machines for years. The technique they developed improves upon previous exploits for getting data from air-gapped computers because it’s more covert and the malware doesn’t require kernel-level privileges. Guri’s team Here’s how an attacker could implement Guri’s attack. An attacker puts the malware on some sort of removable media. Then they acquire physical access to a target machine. If the USB ports haven’t been disabled from mounting filesystems, or the optical drives haven’t been disabled from reading discs, there’s an easy way in. They don’t need to go through an administrator, privilege-escalate, or crack an admin password because the malware is user-level. The next step follows once the malware is in the target machine. A camera gets a view of the target machine’s HDD light. (Guri’s team used a camera attached to a drone in their research.) Software attached to the camera interprets the light signals, or a video file taken from the camera is read by the same sort of software. Then the attacker has the data that they want. When a LED light blinks at 4000hz, it can’t be detected by the human eye. Guri’s team was able to transmit a 4096 bit encryption key between a few minutes and mere seconds, depending on the quality of a camera’s reception. Wow! The technique transmits data relatively slowly, but some of the most sensitive data, such as keys, is very small. So, to harden against Guri’s exploit, here’s what you can do: Lock down physical access to your data center in the usual ways. That reduces the likelihood of removable media transmitting malware to an air-gapped HDD. Disable USB ports, optical drives, and HDD connections that don’t absolutely need to be enabled. Make sure that your server room has no windows. Or, the simplest measure is to put opaque tape over your LEDs. A roll of duct tape can be purchased for as low as 68 cents. $4.52 shipping to my mailing address would bring the grand total to just under five bucks. What an affordable cybersecurity measure! from Amazon But the risk of increasingly inventive and covert techniques to extract data from air-gapped machines must not be trivialized. Frankly, I didn’t even think of the possibility of an HDD LED light as a vulnerability until Guri’s research was publicized. Information security researchers must really think outside of the box these days! If you like my writing and wish to support me, please consider donating to my Patreon.

Tape Over Your Hard Drive Lights: The Latest Security Hardening Measure

I feel there is a tendency to forget that we, or somebody else, will have to maintain our code weeks, months or even years after its creation. Sooner or later some problems or new features appear that will make you have to adapt you long after you forget all the details of what it does. codebase Testing is like leaving a live documentation of what your code is expected to do Types of tests I will be focusing on unit tests in particular but just to give you an ideia: Unit — Testing the functionality of a function usually using fake data when the code depends on external sources like databases; Integration — Let us say you have a connection to a database, integration tests is when you are testing the data that you are getting from that connection; End-to-end — Used for application with UI, it’s basically having the simulate what the user would do. test The distribution is usually like this, end to end are the less amount you do and unit the most So according to the image let us say you have implemented all those three types of tests, you have 10 tests 1 should be end to end, 2 would be integration and the remaining 7 would be unit tests. You don’t have to faithfully follow this metric is just a good to have guideline. You can have an extensive read about testing in general in article by . Martin Fowler Why test Its important to test your project code for reasons like: Logic is documented — Self explanatory, just by reading the tests you have an overview of what the code is expected to do; Faster debugging — If something went wrong you will have instant feedback on your tests by seeing them fail; Less to worry in new features — When developing new features that can have an impact on existing code you can change logic around knowing that if you are breaking any part of your code the tests will tell you by failing. There are some arguable like: cons It takes more time to develop — I refute this by saying that the time you spend developing and debugging with tests outweighs the time you would otherwise spend; less One more thing for a team to learn — There is usually quite a big tech stack in projects and it can end up being “yet one more thing I have to learn” *rolls eyes* Jargon Some of the terms that you usually see associated with tests are: Assertions — This is what you are trying to prove in your test, if you are testing for equality and for the type of a returned value one would say that for that test you have two assertions. Each test can have as many assertions as you like but try to keep each test with few assertions for simplicity and readability; Spy — A spy is when you are using a real method that your code being tested depends to work; Fixtures —Code or files that simulate a certain state of your application so that you always have a fixed environment to repeat your tests whenever you want to evaluate certain states; Stubs — You want to mitigate the amount of external influence in your test (like spies) so to have more control over the test we simulate a method that is require for our code being tested to work instead of using the original one. For example, let us say we are using a third party library to concatenate, we would replace the original method of that library with one of ours; Mocks — These are the hardcoded values you create yourself for the test to work, one example of it would be a sample of a server response to be used by the test. You can have a more extensive explanation with examples . here Example For the example I will be using a lightweight library with modules to extend it for unit tests called but you have alternatives like jest, jasmine and mocha. tape Ideally if you should try using a TDD (Test driven development) or similar approach where you start by creating the test and only after you create your code. When this is not possible and the methods you are testing are already implemented make sure that you change your method so that you see your test fail. If the test never fails then you are testing nothing. Let us assume we want to create an utility file named that will have a method for lowercase and another for concatenate. We create our files string I prefer the tests near the file being tested approach but some people have all the tests in a separate folder, I leave it up to your preference to decide which approach to take In out test file we create our first test with two assertions, one to check if everything ran “ok” and the other call the lowercase function and compare the result with the expected hardcoded value const test = require('tape')const stringUtils = require('./strings.js') test('lowercase should make everything in the original string lower case', function (t) {const result = stringUtils.lowercase('Testing lowerCase')const expected = 'testing lowercase' t.ok(result)t.deepEqual(result, expected) t.end()}); This is the point were we run our test and we see that it fails miserably since lowercase is defined nowhere so we go to our and make it return a function with the method string.js lowercase function lowercase(value) {return value.toLowerCase()} module.exports = {lowercase,} And if we run our test again it should show a success! Hurray! A first test passing! Now we think “what if I send a number to that method?”, well in that case we create another test to test that out and implement accordingly to our expected behaviour, in this case I want an error to be thrown when an invalid type is sent to our method The test test('if we send a number it should throw an error from lowercase method', function(t) {const result = stringUtils.lowercase.bind(null, 1)t.throws(result)t.end()}) The changed function after we see the test fail function lowercase(value) {try {return value.toLowerCase()} catch(e) {throw e}} A good thing to also do it’s change a random part of your code being tested so that you can make sure your tests are actually being useful. In this scenario you could change the for a for example. throw return Note that the tests in tape must have either or else the tests will hang. t.plan([assertionsNumber]) t.end() For our method concatenate we want to test if it concatenates and, when you send an object we want it to be concatenated as {} and not as [object Object]. You can try it yourself or just see a possible solution just below The test test('concatenate should return the two strings concatenated', function (t) {const result = stringUtils.concatenate('test', 'concat')const expected = 'test concat' t.deepEqual(result, expected)t.end()}) test('concatenate should consider {} as a string', function (t) {const result = stringUtils.concatenate('test', {})const expected = 'test {}'t.deepEqual(result, expected)t.end()}); The function function concatenate(start, end) {start = typeof start === 'string'? start: JSON.stringify(start)end = typeof end === 'string'? end: JSON.stringify(end) return `${start} ${end}`} With the exports now with the new method module.exports = {lowercase,concatenate} This are “trivial” tests made for simplicity and you should add as many as you feel necessary for each method, “the more the merrier” as long as they are useful (meaning that they are testing something core to the method and not just there to “have more assertions”. As the application grows we can add multiple test files and we could run them by using the following tape ./utils/*.test.js Demo of this example here For existing projects you can start by adding tests for new features and for older features refactor the code while adding tests as you go, eventually you will have to propagated to most of your codebase if not all. And remember to always see the test fail Code coverage There are tools like to check how much of your code is being tested, I don’t like to focus on that metric to much since it can get you to chance your code not because you need to but just because you want to have 100% coverage, you want to develop new features that are tested without having to spend much time adapting the code just to get 100%. istanbul It’s better to have 10% of your code tested than to have nothing nonetheless if you want to impose a minimum coverage I would say that 70% is a good place to start. Article 9 of 30, part of a project for publishing an article at least once a week, from idle thoughts to tutorials. Leave a comment, follow me on and then go back to your brilliant project! Diogo Spínola

Unit testing Node.js with Tape

Cryptography and the Golden Security Line

HEPT MOVES ON

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A Dozen (or so) Learnings From 15 Years of Software Incident Management

সফ্টওয়্যার ঘটনা ব্যবস্থাপনার 15 বছর থেকে এক ডজন (বা তাই) শিক্ষা

Ein Dutzend (oder so) Erkenntnisse aus 15 Jahren Software-Vorfallmanagement

Una docena (más o menos) de aprendizajes de 15 años de gestión de incidentes de software

Une douzaine (ou deux) d'enseignements tirés de 15 ans de gestion des incidents logiciels

सॉफ्टवेयर घटना प्रबंधन के 15 वर्षों से एक दर्जन (या लगभग) सीखें

15 年間のソフトウェア インシデント管理から学んだ 12 の教訓

15년간의 소프트웨어 사고 관리 경험을 통해 얻은 12가지 정도의 교훈

Uma dúzia (ou mais) de aprendizados de 15 anos de gerenciamento de incidentes de software

Дюжина (или около того) уроков за 15 лет управления инцидентами с программным обеспечением

15 Yıllık Yazılım Olay Yönetiminden Bir Düzine (ya da O Kadar) Ders

Hàng chục (hoặc hơn) bài học từ 15 năm quản lý sự cố phần mềm

从 15 年的软件事故管理中学到的十几个经验

In the same league as the United States with of respondents using artificial intelligence (AI) in at least one of their business functions, progress in the Middle East and North Africa (MENA) can be seen — but there’s still significant untapped potential. Already AI is poised to deliver over 9% of the Middle East’s Gulf Cooperation Council (GCC) countries’ combined GDP, and the swift progress of generative AI implies that the figure will be quickly exceeded. 62% While many energy and materials companies, operating and competing internationally, are keen to raise production, distribution, and maintenance efficiency with AI, retail sectors are racing ahead; having long-mined consumer data to inform pricing and promotions. However, for industries like construction, getting started is a little more tricky since they either cannot yet collect the data required to train AI models or need additional technical expertise. Going deeper into the business functions, marketing and sales is the most common application of AI across MENA industries. What needs to be done to tap into other functions, such as supply chain management, risk, and corporate finance? The answer lies in the intersection of cultural, regulatory, and infrastructure changes — which are individually complex, if not thought out carefully. Bridging the Cultural Divide for AI in MENA While McKinsey’s highlights the need for internal transformation across the GCC, the UAE stands out as a leader in fostering the right culture and workflows to embed AI tools seamlessly. report As part of the region’s strategy to ensure students and employees have access to the right training and knowledge to build digital-native enterprises, the UAE established . This university educates and develops skills in computer vision, machine learning, natural language processing, and beyond. MBZUAI When it comes to making cultural shifts, it’s critical to ensure senior leadership is aware and on board with the scope of AI potential in each business function to justify budgets and needs holistically. Leaders must get the right training and unite board members to develop a business-led use case roadmap. The ideal blueprint comes with clear communication of the benefits of workflow changes, and what they mean for individual roles. As part of the change management process, appointed leaders that open multi-channel two-way communication can formally collect feedback and informally gather worker perceptions, praising or addressing any ideas and concerns. Involving team members in the process this way helps to boost acceptance and engagement with the strategy. Working with MBZUAI students will help UAE businesses build an AI-focused culture from the beginning. Businesses in the region may choose to invest in upskilling, collaborating with graduated tech specialists, or consider offshore services to bridge any talent gaps — although, this is where the regulatory challenges come in. Clearing the Red Tape: Streamlining Regulations for MENA’s AI Stringent data storage regulations in many MENA countries restrict companies from leveraging public cloud options abroad. This, coupled with a lack of globally established AI risk frameworks, creates roadblocks for organizations seeking to deploy AI, despite its perceived value. For this reason, predicts a significant rise in security and risk management (SRM) spending across the MENA region. Their forecast expects a 12.1% increase in 2024, reaching a total of US$3.3 billion. Investment in AI-powered SRM helps regional leaders to reduce the threat landscape, proactively identifying potential vulnerabilities or malicious behavior across their digital ecosystems. Gartner Organizations must establish policies that govern application usage and also implement training on cybersecurity incidents associated with employee behavior in their change management strategy. This will help minimize the risks of privacy and copyright infringement and align with the for handling personal data of identifiable individuals — which require MENA organizations to maintain a higher standard of data privacy and cyber security measures. GCC’s latest data protection laws With increased security, training, and governance, MENA companies reduce the risk of collaborating overseas, enabling them to maximize the global market. Building the Infrastructure for High-Speed AI It takes agile companies and infrastructure to scale globally. Yet, only of companies in the MENA region feel they have the technology infrastructure and architecture to support AI. UAE paves the way with the recently creation of MGX, a company focused on investing in: 35% announced data centers and connectivity AI infrastructure: logic and memory chip design and manufacturing Semiconductors: AI models, software, data, life sciences and robotics AI core technologies and applications: Data needs to flow through data pipelines like items on a production line. You can add parts and modify them to different customers or business use cases, but the core product is the same. This type of data structure is beneficial in the short term as it makes data transfer seamless. It also provides longer-term value by making it easier to integrate new technologies later down the line. This is where the UAE’s advanced training programs set the region as an AI frontrunner, ensuring regional data users understand how to navigate data pipelines efficiently. This is a two-pronged effort of flexible technological architecture and user-friendly analytics. With the right training and API-based middleware, employees can maximize a combination of intuitive applications across IT and business teams. These modern-built apps are rich in automation, helping teams alleviate manual, technical tasks and improve the employee experience. AI adoption in MENA is in full swing, with industries across retail, energy, and financial services looking at ways to increase efficiency. A solid change management plan rooted in the company culture makes a successful rollout possible. Strong regional performers will have a well-informed leadership team, clear AI objectives communicated, and investment into agile and scalable infrastructure. This article was originally published by on Maryam A Hassani 150sec.

Navigating the Future of AI in MENA Countries

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