Fraud Prevention and IP Geolocation using the power of AI.

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United States v. Apple INC Court Filing, retrieved on March 21, 2024 is part of . You can jump to any part in this filing . This part is 9 of 25. HackerNoon’s Legal PDF Series here C. Apple’s “moat” around its smartphone monopoly is wide and deep: it uses a similar playbook to maintain its monopoly through many other products and services 119. The exclusionary and anticompetitive acts described above are part of Apple’s ongoing course of conduct to build and maintain its smartphone monopoly. They are hardly exhaustive. Rather, they exemplify the innovation Apple has stifled and Apple’s overall strategy of using its power over app distribution and app creation to selectively block threatening innovations. 120. Apple has deployed a similar playbook for a much broader range of third-party apps and services as well, many of which present technologies that function as middleware, facilitate switching, reduce the need for expensive hardware, or disintermediate Apple’s iPhone by enabling the development of cross-platform technologies. For instance, Apple has undermined third-party location trackable devices that fully function across platforms. Apple has impaired third-party, cross-platform video communications apps while steering users to its own video communication app, FaceTime. Apple has limited the capabilities of third-party iOS web browsers, including by requiring that they use Apple’s browser engine, WebKit. Protocols that Apple has placed around new “eSIM” technology may introduce additional frictions for any user who seeks to transition from an iPhone to a different phone while maintaining the same phone number. Apple has impeded cross-platform cloud storage apps in order to steer iPhone users into iCloud, making data transfer between different devices more difficult. Apple uses restrictions in sales channels to impede the sale and distribution of rival smartphones. And Apple has worsened its users’ experience by making it difficult for iPhone users to use superior voice and AI assistants and steering users to use Siri as a voice assistant. 121. Ultimately, the strategies Apple has employed to date are not the only ones Apple can use to achieve its anticompetitive and lucrative ends. As technology evolves, Apple continues to evolve and shift its anticompetitive behavior to protect its monopoly power. For example, in recent years, Apple has increasingly moved into offering its own subscription services, including news, games, video, music, cloud storage, and fitness subscriptions that could be used to keep users tethered to the platform. These subscription services and other ancillary fees are a significant part of Apple’s net revenue. These subscriptions services can also increase switching costs among iPhone users. If an Apple user can only access their subscription service on an iPhone, they may experience significant costs, time, lost content, and other frictions if they attempt to switch to a non-Apple smartphone or subscription service. 122. These subscription services can also increase Apple’s power over content creators and newspapers, among others, by exerting control over how audiences access their work, decreasing traffic to their websites and apps, and positioning Apple as the middleman or tollbooth operator in the relationship between creators and users. In so doing, Apple takes on outsize importance and control in the creative economy, which may diminish incentives to fund, make, and distribute artistic expression. 123. In addition, when one road is closed to Apple, Apple has demonstrated its ability to find new roads to the same or worse ends. For example, Apple was recently ordered to stop blocking link-outs by third parties to their websites where users could buy the third party’s product cheaper. In response, Apple reportedly allowed link-outs to websites but now charges for purchases made on the web even if they are not an immediate result of a click from a link in a native iPhone app. 124. Apple has also attempted to undermine cross-platform technologies like digital car keys in ways that benefit Apple but harm consumers. For example, Apple has required developers to add digital keys developed for their own apps to Apple Wallet as well. The default status of Apple Wallet steers users to the Apple Wallet rather than allowing third parties to present digital car keys only in their own cross-platform app, increasing dependence on Apple and the iPhone whenever they use their car. At the same time, it decreases the incentives of automakers to innovate because automakers are forced to share data with Apple and prevented from differentiating themselves as they could absent Apple’s conduct. 125. Apple’s threatened dominance over the automotive industry goes well beyond the Apple Wallet and Apple’s demands on car makers to allow innovative products and services on the iPhone. Apple’s smartphone dominance extends to CarPlay, an Apple infotainment system that enables a car’s central display to serve as a display for the iPhone and enables the driver to use the iPhone to control maps and entertainment in the car. Like the smartphone market, infotainment systems are increasingly considered must-have capabilities in newer vehicles. After leveraging its smartphone dominance to car infotainment systems, Apple has told automakers that the next generation of Apple CarPlay will take over all of the screens, sensors, and gauges in a car, forcing users to experience driving as an iPhone-centric experience if they want to use any of the features provided by CarPlay. Here too, Apple leverages its iPhone user base to exert more power over its trading partners, including American carmakers, in future innovation. By applying the same playbook of restrictions to CarPlay, Apple further locks-in the power of the iPhone by preventing the development of other disintermediating technologies that interoperate with the phone but reside off device. Continue Reading . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case retrieved on March 21, 2024, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. justice.gov

Apple's Monopoly Tactics: How the Tech Giant Maintains Its Grip Across Products and Services

Just this morning at work I had to search a file for occurences of a certain keyword (to keep this interesting, let’s say I had to search for a password named NUCLEAR_CODES_PASSWORD inside a file). It would be easy to just import that file into Visual Studio Code, click , and search the file for occurences. Ctrl + F Well, it would be even easier (and more hackerish) to navigate to the folder inside my terminal, type in a command, and get the result of my search almost instantly, right? Well, thankfully, the terminal has a command that is pretty useful with use cases like these. It is called . grep is a powerful command line utility used to find text patterns within files. It stands for lobal egular xpression rint. It is used like this: grep g r e p grep [options] pattern [files] is the text we’re searching for in our files. When the command encounters any patterns in the file (or files) it runs upon, it will return/print the lines that contain those patterns. We can match simple patterns, but we can also search for really complex ones. Grep can also filter out regular expressions (a sequence of characters that define a pattern). Pattern are self-explanatory, they are the elements the pattern search will be run upon. Files are additional flags that can tweak the search. Options The examples Let’s jump right into the examples. I have a file called on my machine. If I want to check the contents of the file, I can write the following command: passwords.txt $ cat passwords.txt 
FACEBOOK_PASSWORD=q.Gcyt;Z`3S8$'@H
INSTAGRAM_PASSWORD=GhgpgYy4P2PaZY2U
NUCLEAR_CODES_PASSWORD=0000
BICYCLE_LOCK_PASSWORD=123
PHONE_PASSWORD=8UeNwDFskR9r9LxZ OK, if I am searching for NUCLEAR_CODES_PASSWORD it is obviously not that hard to notice it. We only have five lines in this document. But, what if the file was really long – 100, 1000, or even more lines in the document? Then navigating the file, and noticing changes by the naked eye wouldn’t be that easy. Below you can see some of the most common uses of grep inside the terminal. Searching inside a file To print out lines from the file that contain a specific pattern of characters, let us say our NUCLEAR_CODES_PASSWORD we could do something like this: $ grep NUCLEAR_CODES_PASSWORD passwords.txt
NUCLEAR_CODES_PASSWORD=0000 Searching inside multiple files We can also search multiple files, by inserting the filenames you want to search. Let’s say we have an additional file inside here, called . We could search both of those files by doing this: passwords2.txt $ grep NUCLEAR_CODES_PASSWORD passwords.txt
passwords.txt:NUCLEAR_CODES_PASSWORD=0000
passwords2.txt:NUCLEAR_CODES_PASSWORD=a_more_complex_code_1234_ Case Insensitive search If we add the option to the search we can ignore the string case sensitivity. ‘nuclear’ would return anything including ‘NUCLEAR’, ‘nUcLeAR’ or ‘nuclear’. -i $ grep -i nuclear passwords.txt
NUCLEAR_CODES_PASSWORD=0000 Displaying the number of matches We can also search for the total number of matches by using the option. Here we searched the whole file for the ‘password’ pattern (we also combined options by adding , so we ignored the case). We get 5 because ‘password’ appears five times in our document. -c i $ grep -ci password passwords.txt
5 Showing Line Numbers By using we can show the line for every occurrence. -n $ grep -ni password passwords.txt
1:FACEBOOK_PASSWORD=q.Gcyt;Z`3S8$'@H
2:INSTAGRAM_PASSWORD=GhgpgYy4P2PaZY2U
3:NUCLEAR_CODES_PASSWORD=0000
4:BICYCLE_LOCK_PASSWORD=123
5:PHONE_PASSWORD=8UeNwDFskR9r9LxZ Caret (^) metacharacter Caret metacharacter matches patterns at the beginning of the line. Only lines that start with ‘instagram’ (again ignores case) will be matched. -i $ grep -i "^instagram" passwords.txt
INSTAGRAM_PASSWORD=GhgpgYy4P2PaZY2U Dollar sign ($) metacharacter Dollar sign metacharacter will only match patterns at the end of the line, and return those lines. We only have one line having ‘0000’ as the ending sequence, so we return that line. (again we ignored the case, but here that isn’t so important) $ grep -i "0000$" passwords.txt
NUCLEAR_CODES_PASSWORD=0000 Conclusion We only scratched the surface here, is really complex and has lots of functionality. grep If you want to read more about you can check out the . grep official documentation Also published . here

Making Text Searches Easy With Linux Grep Commands

Regulatory capture is a concerning phenomenon that occurs when regulatory agencies tasked with safeguarding the public interest become beholden to the very industries they are meant to oversee. It is a form of governmental corruption that has the potential to wreak havoc on economies, societies, and individual citizens. Nobel laureate economist George Stigler introduced this concept in the 1970s, highlighting the disproportionate influence industries have on regulators compared to ordinary citizens ( ; ). GWU Regulatory Studies ProMarket In this article, we will explore the concept of regulatory capture in detail, examining its causes, consequences, and potential implications in the context of AI doomers' unbridled pessimism. We will also paint a likely scenario where a country like the Philippines could fall into the grip of regulatory capture due to the negative influence of AI doomers. Understanding Regulatory Capture: Regulatory capture occurs when regulatory agencies prioritize the interests of industries over the welfare of the general public. This distortion of purpose can lead to detrimental consequences such as market inefficiencies, compromised safety standards, and economic inequalities. Industries often allocate substantial resources to influence regulators, while individual citizens have limited means to advocate for their interests, resulting in a disparity in advocacy power ( ). Investopedia Key Mechanisms of Regulatory Capture: : Industries may employ lobbying efforts and cultivate personal relationships with regulatory officials to shape policies that favor their interests. This undue influence can undermine the regulatory process, tilting the balance in favor of industry. Lobbying and Personal Relationships : A significant factor in regulatory capture is the "revolving door" phenomenon, where industry experts and employees frequently move between regulatory agencies and the industries they regulate. This can lead to conflicts of interest and a culture of favoritism ( ). Revolving Door Phenomenon Chicago Booth Review : Regulatory capture often exacerbates the inequality of influence within the same sector. Larger firms with greater resources wield more power to influence regulators, marginalizing smaller players and startups. Inequality of Influence The Consequences of Regulatory Capture: When regulatory capture occurs, it can result in dire consequences for society. Special interests supersede the public good, leading to a net loss for society. Economic rationale dictates that industries with the most at stake regarding regulation are the most likely to attempt to influence regulators, often to the detriment of the public interest. Moreover, a captured regulator can be worse than no regulation at all, as it wields government authority while serving private interests. AI Doomers and the Threat of Regulatory Capture: AI doomers are individuals who hold extremely pessimistic views about the potential impact of artificial intelligence on society. While constructive criticism and cautious approaches to AI development are essential, unbridled pessimism can become a self-fulfilling prophecy. When AI doomers relentlessly propagate negative narratives about AI, they can inadvertently contribute to regulatory capture. Scenario: The Philippines Falling into Regulatory Capture Due to Pessimism: Imagine a scenario where AI doomers in the Philippines relentlessly advocate for strict regulations on AI development. These doom-laden narratives create fear and apprehension among policymakers and the general public. Concerned about potential AI disasters, regulators become overly cautious and solicit input primarily from AI experts who share these pessimistic views. As a result, regulatory agencies in the Philippines become dominated by individuals who align with AI doomers' negative outlook. These agencies impose stringent regulations on AI innovation, hindering progress in the field. Meanwhile, industry experts who hold more optimistic views are marginalized, leading to an imbalance in regulatory decision-making. The Outcome: In this hypothetical scenario, the Philippines falls into the deadly grip of regulatory capture driven by AI doomers' unbridled pessimism. AI innovation is stifled, economic growth is hindered, and the nation misses out on opportunities for technological advancement. The interests of a minority group with a negative outlook on AI dominate, to the detriment of the broader public interest. Conclusion: Regulatory capture is a complex and insidious phenomenon that can have far-reaching consequences for society. It is essential to strike a balance between responsible regulation and innovation. While AI doomers' concerns should be heard, policymakers must ensure that regulations are based on sound evidence and a comprehensive understanding of the potential benefits and risks of AI. Failing to do so could plunge nations like the Philippines into the abyss of regulatory capture, hindering progress and stifling economic growth. References https://regulatorystudies.columbian.gwu.edu/lets-not-forget-george-stiglers-lessons-about-regulatory-capture https://www.chicagobooth.edu/review/how-george-stigler-changed-analysis-regulation https://www.promarket.org/2021/05/20/george-stiglers-lesson-regulatory-capture-rent-seeking/ https://www.investopedia.com/terms/r/regulatory-capture.asp https://www.masterclass.com/articles/regulatory-capture https://faculty.haas.berkeley.edu/dalbo/Regulatory_Capture_Published.pdf

How AI Doomers Could Push a Nation Like the Philippines Into the Deadly Grip of Regulatory Capture

FTC v. Amazon Court Filing, retrieved on Sep 26, 2023, is part of . You can jump to any part in this filing . This is part 58 of 80. HackerNoon’s Legal PDF Series here COUNT II: MONOPOLY MAINTENANCE OF THE ONLINE MARKETPLACE SERVICES MARKET (15 U.S.C. § 45(a)) 448. Plaintiff FTC re-alleges and incorporates by reference the allegations in paragraphs 1-447 above. 449. At all relevant times, Amazon has had monopoly power in the worldwide market for online marketplace services for U.S. customers. 450. Amazon has willfully maintained its monopoly power through its course of anticompetitive and exclusionary conduct, including Amazon’s anti-discounting practices, which stifle price competition and tend to create an artificial price floor, and Amazon’s practice of coercing sellers who want their products to be Prime eligible into using Fulfillment by Amazon, which makes it more difficult and more expensive for rivals to offer increased product selection. 451. Although each of these acts is anticompetitive in its own right, these interrelated and independent actions have had a cumulative and synergistic effect that has harmed competition and the competitive process. 452. There is no valid procompetitive justification for Amazon’s anticompetitive and exclusionary conduct in the online marketplace services market. 453. Amazon’s anticompetitive and exclusionary conduct constitutes unlawful monopoly maintenance, in violation of Section 5(a) of the FTC Act, 15 U.S.C. § 45(a), and Section 2 of the Sherman Act, 15 U.S.C. § 2. Continue Reading . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case 2:23-cv-01495 retrieved on October 2, 2023, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. ftc.gov

Lina Khan, FTC Chair, Aims to Loosen Amazon's Iron Grip on Online Marketplaces

Once upon a time in the land of Silicon Valley, there was a company called AcmeCorp. They claimed to be the ultimate protectors of digital security and boasted about their prestigious . Little did the world know, their certification was nothing but a scam hiding behind a fancy acronym. SOC 2 certification One day, a curious entrepreneur named Jack stumbled upon AcmeCorp while searching for a cybersecurity partner for his startup. Intrigued by their promises of impenetrable defenses, he decided to pay them a visit. As Jack walked into their office, he was greeted by the company's CEO, Mr. Smith, who was a charismatic man with a winning smile. Jack couldn't help but feel like he was in good hands. However, as the conversation progressed, he started to notice some questionable things. "Mr. Smith, I've heard great things about your SOC 2 certification. Can you tell me more about it?" Jack asked, hoping for some reassurance. Smith leaned back in his chair, twirling his mustache, and replied, "Ah, yes, SOC 2. It's the gold standard in cybersecurity. We've gone through rigorous audits to ensure we meet all the necessary requirements." Jack nodded, impressed by the CEO's confident tone. "But what exactly does the SOC 2 certification entail?" Smith chuckled, almost as if he knew a secret. "Well, my dear friend, SOC 2 stands for 'Security of Conspiracy 2.' It's a certification that proves we're experts at keeping secrets, especially the fact that our security measures are nothing more than smoke and mirrors!" Jack's eyes widened in disbelief. "Wait, you're telling me that the certification is a scam?" Smith grinned mischievously. "You catch on quick, my friend. SOC 2 certification is just a piece of paper that makes us look good on the surface. It's like buying a fancy car with no engine under the hood!" Jack couldn't believe his ears. He felt like he had stepped into a where everything he thought he knew about cybersecurity was a lie. parallel universe "But why would you deceive people like this?" Jack asked, trying to make sense of it all. Smith leaned in, his voice dropping to a whisper. "Well, my naive friend, it's all about appearances. You see, by having that shiny SOC 2 certification, we attract gullible customers who think we have their back. We charge them a hefty fee, and in return, we give them a false sense of security. It's a win-win for us!" Jack shook his head in disbelief. "That's outrageous! You're playing with people's trust and putting their businesses at risk." Smith shrugged nonchalantly. "Business is business, my friend. Besides, who needs real security when you can have an illusion of security?" Jack stormed out of the office, vowing to expose AcmeCorp and their deceptive practices. He spent the next few months tirelessly researching and gathering evidence to unveil the truth. Eventually, Jack's efforts paid off, and he presented his findings to the public. The news spread like wildfire, and AcmeCorp deceitful practices were exposed for all to see. The company faced severe repercussions, and Mr. Smith found himself behind bars for fraud. And so, the tale of AcmeCorp and their fake SOC 2 certification serves as a cautionary reminder that not everything that glitters is gold. In the world of cybersecurity, it's crucial to look beyond fancy certifications and do thorough research to ensure you're placing your trust in the right hands.

The Gripping Tale of SOC 2 Certification

Getting Started With Linux: Your Gateway to the Open-Source Realm

Author:
(1) Mohammad Akhlaghi, Centro de Estudios de F´ısica del Cosmos de Aragon (CEFCA), Plaza San Juan 1, 44001, Teruel, Spain {mohammad@akhlaghi.org}. Table of Links Abstract and Intro Simulating the Exposure Map Acknowledgment and References Appendix APPENDIX A. SOFTWARE ACKNOWLEDGEMENT This research was done with the following free software programs and libraries: 1.23, Bzip2 1.0.8, CFITSIO 4.1.0, CMake 3.24.0, cURL 7.84.0, Dash 0.5.11-057cd65, Discoteq flock 0.4.0, Expat 2.4.1, File 5.42, Fontconfig 2.14.0, FreeType 2.11.0, Git 2.37.1, GNU Astronomy Utilities 0.20.72-08b0 (Akhlaghi & Ichikawa 2015; ?), GNU Autoconf 2.71, GNU Automake 1.16.5, GNU AWK 5.1.1, GNU Bash 5.2-rc2, GNU Binutils 2.39, GNU Bison 3.8.2, GNU Compiler Collection (GCC) 12.1.0, GNU Coreutils 9.1, GNU Diffutils 3.8, GNU Findutils 4.9.0, GNU gettext 0.21, GNU gperf 3.1, GNU Grep 3.7, GNU Gzip 1.12, GNU Integer Set Library 0.24, GNU libiconv 1.17, GNU Libtool 2.4.7, GNU libunistring 1.0, GNU M4 1.4.19, GNU Make 4.3, GNU Multiple Precision Arithmetic Library 6.2.1, GNU Multiple Precision Complex library, GNU Multiple Precision Floating-Point Reliably 4.1.0, GNU Nano 6.4, GNU NCURSES 6.3, GNU Readline 8.2- rc2, GNU Scientific Library 2.7, GNU Sed 4.8, GNU Tar 1.34, GNU Texinfo 6.8, GNU Wget 1.21.2, GNU Which 2.21, GPL Ghostscript 9.56.1, Help2man , Less 590, Libffi 3.4.2, Libgit2 1.3.0, libICE 1.0.10, Libidn 1.38, Libjpeg 9e, Libpaper 1.1.28, Libpng 1.6.37, libpthread-stubs (Xorg) 0.4, libSM 1.2.3, Libtiff 4.4.0, libXau (Xorg) 1.0.9, libxcb (Xorg) 1.15, libXdmcp (Xorg) 1.1.3, libXext 1.3.4, Libxml2 2.9.12, libXt 1.2.1, Lzip 1.23, OpenSSL 3.0.5, PatchELF 0.13, Perl 5.36.0, pkgconfig 0.29.2, podlators 4.14, Python 3.10.6, utilLinux 2.38.1, util-macros (Xorg) 1.19.3, WCSLIB 7.11, X11 library 1.8, XCB-proto (Xorg) 1.15, xorgproto 2022.1, xtrans (Xorg) 1.4.0, XZ Utils 5.2.5 and Zlib 1.2.11. The LATEX source of the paper was compiled to make the PDF using the following packages: courier 61719 (revision), epsf 2.7.4, etoolbox 2.5k, helvetic 61719 (revision), lineno 5.3, pgf 3.1.10, pgfplots 1.18.1, revtex4- 1 4.1s, tex 3.141592653, textcase 1.04 and ulem 53365 (revision). We are very grateful to all their creators for freely providing this necessary infrastructure. This research (and many other projects) would not be possible without them. This paper is available on arxiv under CC 4.0 DEED license. Author: (1) Mohammad Akhlaghi, Centro de Estudios de F´ısica del Cosmos de Aragon (CEFCA), Plaza San Juan 1, 44001, Teruel, Spain {mohammad@akhlaghi.org}. Author: Author: (1) Mohammad Akhlaghi, Centro de Estudios de F´ısica del Cosmos de Aragon (CEFCA), Plaza San Juan 1, 44001, Teruel, Spain {mohammad@akhlaghi.org}. Table of Links Abstract and Intro Abstract and Intro Simulating the Exposure Map Simulating the Exposure Map Acknowledgment and References Acknowledgment and References Appendix Appendix APPENDIX A. SOFTWARE ACKNOWLEDGEMENT This research was done with the following free software programs and libraries: 1.23, Bzip2 1.0.8, CFITSIO 4.1.0, CMake 3.24.0, cURL 7.84.0, Dash 0.5.11-057cd65, Discoteq flock 0.4.0, Expat 2.4.1, File 5.42, Fontconfig 2.14.0, FreeType 2.11.0, Git 2.37.1, GNU Astronomy Utilities 0.20.72-08b0 (Akhlaghi & Ichikawa 2015; ?), GNU Autoconf 2.71, GNU Automake 1.16.5, GNU AWK 5.1.1, GNU Bash 5.2-rc2, GNU Binutils 2.39, GNU Bison 3.8.2, GNU Compiler Collection (GCC) 12.1.0, GNU Coreutils 9.1, GNU Diffutils 3.8, GNU Findutils 4.9.0, GNU gettext 0.21, GNU gperf 3.1, GNU Grep 3.7, GNU Gzip 1.12, GNU Integer Set Library 0.24, GNU libiconv 1.17, GNU Libtool 2.4.7, GNU libunistring 1.0, GNU M4 1.4.19, GNU Make 4.3, GNU Multiple Precision Arithmetic Library 6.2.1, GNU Multiple Precision Complex library, GNU Multiple Precision Floating-Point Reliably 4.1.0, GNU Nano 6.4, GNU NCURSES 6.3, GNU Readline 8.2- rc2, GNU Scientific Library 2.7, GNU Sed 4.8, GNU Tar 1.34, GNU Texinfo 6.8, GNU Wget 1.21.2, GNU Which 2.21, GPL Ghostscript 9.56.1, Help2man , Less 590, Libffi 3.4.2, Libgit2 1.3.0, libICE 1.0.10, Libidn 1.38, Libjpeg 9e, Libpaper 1.1.28, Libpng 1.6.37, libpthread-stubs (Xorg) 0.4, libSM 1.2.3, Libtiff 4.4.0, libXau (Xorg) 1.0.9, libxcb (Xorg) 1.15, libXdmcp (Xorg) 1.1.3, libXext 1.3.4, Libxml2 2.9.12, libXt 1.2.1, Lzip 1.23, OpenSSL 3.0.5, PatchELF 0.13, Perl 5.36.0, pkgconfig 0.29.2, podlators 4.14, Python 3.10.6, utilLinux 2.38.1, util-macros (Xorg) 1.19.3, WCSLIB 7.11, X11 library 1.8, XCB-proto (Xorg) 1.15, xorgproto 2022.1, xtrans (Xorg) 1.4.0, XZ Utils 5.2.5 and Zlib 1.2.11. The LATEX source of the paper was compiled to make the PDF using the following packages: courier 61719 (revision), epsf 2.7.4, etoolbox 2.5k, helvetic 61719 (revision), lineno 5.3, pgf 3.1.10, pgfplots 1.18.1, revtex4- 1 4.1s, tex 3.141592653, textcase 1.04 and ulem 53365 (revision). We are very grateful to all their creators for freely providing this necessary infrastructure. This research (and many other projects) would not be possible without them. This paper is available on arxiv under CC 4.0 DEED license. This paper is available on arxiv under CC 4.0 DEED license. available on arxiv

Gnuastro: Simulating The Exposure Map of a Pointing Pattern - Appendix

Author:
(1) Mohammad Akhlaghi, Centro de Estudios de F´ısica del Cosmos de Aragon (CEFCA), Plaza San Juan 1, 44001, Teruel, Spain {mohammad@akhlaghi.org}. Table of Links Abstract and Intro Simulating the Exposure Map Acknowledgment and References Appendix 3. ACKNOWLEDGEMENT The workflow of this research note was developed in the reproducible framework of Maneage (Managing data lineage, Akhlaghi et al. 2021, latest Maneage commit 8161194, from 22 May 2023). This note is created from the Git commit 4176d29 that is hosted on Codeberg[4] and is archived on SoftwareHeritage for longevity. The analysis of this research note was done using GNU Astronomy Utilities (Gnuastro, ascl.net/1801.009) version 0.20.72-08b0. Work on Gnuastro has been funded by the Japanese Ministry of Education, Culture, Sports, Science, and Technology (MEXT) scholarship and its Grant-in-Aid for Scientific Research (21244012, 24253003), the European Research Council (ERC) advanced grant 339659-MUSICOS, the Spanish Ministry of Economy and Competitiveness (MINECO, grant number AYA2016-76219-P) and the NextGenerationEU grant through the Recovery and Resilience Facility project ICTS-MRR-2021- 03-CEFCA. I also acknowledge the financial support provided by the Governments of Spain and Aragon through their general budgets and ´ the Fondo de Inversiones de Teruel, and the Spanish Ministry of Science and Innovation (MCIN/AEI/10.13039/501100011033 y FEDER, Una manera de hacer Europa) with grant PID2021- 124918NA-C43. REFERENCES Akhlaghi, M., & Ichikawa, T. 2015, ApJS, 220, 1, doi: 10.1088/0067-0049/220/1/1 Akhlaghi, M., Infante-Sainz, R., Roukema, B. F., et al. 2021, CiSE, 23, 82, doi: 10.1109/MCSE.2021.3072860 Calabretta, M. R., & Greisen, E. W. 2002, A&A, 395, 1077, doi: 10.1051/0004-6361:20021327 Illingworth, G. D., Magee, D., Oesch, P. A., et al. 2013, ApJS, 209, 6, doi: 10.1088/0067-0049/209/1/6 Trujillo, I., D’Onofrio, M., Zaritsky, D., et al. 2021, A&A, 654, A40, doi: 10.1051/0004-6361/202141603 This paper is available on arxiv under CC 4.0 DEED license. [4] https://codeberg.org/gnuastro/paper-pointing-simulate Author: (1) Mohammad Akhlaghi, Centro de Estudios de F´ısica del Cosmos de Aragon (CEFCA), Plaza San Juan 1, 44001, Teruel, Spain {mohammad@akhlaghi.org}. Author: Author: (1) Mohammad Akhlaghi, Centro de Estudios de F´ısica del Cosmos de Aragon (CEFCA), Plaza San Juan 1, 44001, Teruel, Spain {mohammad@akhlaghi.org}. Table of Links Abstract and Intro Abstract and Intro Simulating the Exposure Map Simulating the Exposure Map Acknowledgment and References Acknowledgment and References Appendix Appendix 3. ACKNOWLEDGEMENT The workflow of this research note was developed in the reproducible framework of Maneage (Managing data lineage, Akhlaghi et al. 2021, latest Maneage commit 8161194, from 22 May 2023). This note is created from the Git commit 4176d29 that is hosted on Codeberg[4] and is archived on SoftwareHeritage for longevity. The analysis of this research note was done using GNU Astronomy Utilities (Gnuastro, ascl.net/1801.009) version 0.20.72-08b0. Work on Gnuastro has been funded by the Japanese Ministry of Education, Culture, Sports, Science, and Technology (MEXT) scholarship and its Grant-in-Aid for Scientific Research (21244012, 24253003), the European Research Council (ERC) advanced grant 339659-MUSICOS, the Spanish Ministry of Economy and Competitiveness (MINECO, grant number AYA2016-76219-P) and the NextGenerationEU grant through the Recovery and Resilience Facility project ICTS-MRR-2021- 03-CEFCA. I also acknowledge the financial support provided by the Governments of Spain and Aragon through their general budgets and ´ the Fondo de Inversiones de Teruel, and the Spanish Ministry of Science and Innovation (MCIN/AEI/10.13039/501100011033 y FEDER, Una manera de hacer Europa) with grant PID2021- 124918NA-C43. REFERENCES Akhlaghi, M., & Ichikawa, T. 2015, ApJS, 220, 1, doi: 10.1088/0067-0049/220/1/1 Akhlaghi, M., Infante-Sainz, R., Roukema, B. F., et al. 2021, CiSE, 23, 82, doi: 10.1109/MCSE.2021.3072860 Calabretta, M. R., & Greisen, E. W. 2002, A&A, 395, 1077, doi: 10.1051/0004-6361:20021327 Illingworth, G. D., Magee, D., Oesch, P. A., et al. 2013, ApJS, 209, 6, doi: 10.1088/0067-0049/209/1/6 Trujillo, I., D’Onofrio, M., Zaritsky, D., et al. 2021, A&A, 654, A40, doi: 10.1051/0004-6361/202141603 This paper is available on arxiv under CC 4.0 DEED license. This paper is available on arxiv under CC 4.0 DEED license. available on arxiv [4] https://codeberg.org/gnuastro/paper-pointing-simulate

Gnuastro: Simulating The Exposure Map of a Pointing Pattern - Acknowledgment and References

Author:
(1) Mohammad Akhlaghi, Centro de Estudios de F´ısica del Cosmos de Aragon (CEFCA), Plaza San Juan 1, 44001, Teruel, Spain {mohammad@akhlaghi.org}. Table of Links Abstract and Intro Simulating the Exposure Map Acknowledgment and References Appendix 2. SIMULATING THE EXPOSURE MAP Within Gnuastro, the executable in charge of simulating the exposure map of a given list of pointings is called astscript-pointing- -simulate. As with all Gnuastro features, it has a complete documentation in Gnuastro’s manual[2] which is available in many formats (on the command-line, as web pages, PDF and etc). A complete and dedicated tutorial is also available within the tutorials chapter[3] of the manual. Three of the images produced in the tutorial (as of version 0.21) are displayed in Figure 1. The left image shows the exposure map that is produced from a five-point, “+”-shaped set of pointings on the sky, with one pointing in the center and four on the outer extents. The middle image uses one of the hooks that are available within the script to produce a noisy image and not an exposure map. This hook can also be used to insert simulated/real objects. The right image shows how another hook can be used to account for trimming of the outer edges (which sometimes do not get exposed enough due to vignetting). This hook can also be used to insert any random area of bad pixels or to simulate persistence in near infra-red detectors (these can be large). For its processing, this script needs two input files: 1) a table containing the RA and Dec of each pointing, 2) a FITS image from the camera that the dither pattern is meant for. The image has to contain the celestial world coordinate system (WCS, see Calabretta & Greisen 2002) headers. Having a WCS is very important, especially for cameras with a wide field of view, because distortions can become visible/significant. The tutorial and dedicated manual for this script are available in the Gnuastro manual and will always be up to date with the running version; therefore for the practical details, we encourage readers to follow the Gnuastro manual. The future changes in the script that break with this research note will be clearly designated in a “changes after publication” subsection of the section describing this script. This paper is available on arxiv under CC 4.0 DEED license. [2] https://www.gnu.org/software/gnuastro/manual [3] https://www.gnu.org/software/gnuastro/manual/html node/Tutorials.html Author: (1) Mohammad Akhlaghi, Centro de Estudios de F´ısica del Cosmos de Aragon (CEFCA), Plaza San Juan 1, 44001, Teruel, Spain {mohammad@akhlaghi.org}. Author: Author: (1) Mohammad Akhlaghi, Centro de Estudios de F´ısica del Cosmos de Aragon (CEFCA), Plaza San Juan 1, 44001, Teruel, Spain {mohammad@akhlaghi.org}. Table of Links Abstract and Intro Abstract and Intro Simulating the Exposure Map Simulating the Exposure Map Acknowledgment and References Acknowledgment and References Appendix Appendix 2. SIMULATING THE EXPOSURE MAP Within Gnuastro, the executable in charge of simulating the exposure map of a given list of pointings is called astscript-pointing- -simulate. As with all Gnuastro features, it has a complete documentation in Gnuastro’s manual[2] which is available in many formats (on the command-line, as web pages, PDF and etc). A complete and dedicated tutorial is also available within the tutorials chapter[3] of the manual. Three of the images produced in the tutorial (as of version 0.21) are displayed in Figure 1. The left image shows the exposure map that is produced from a five-point, “+”-shaped set of pointings on the sky, with one pointing in the center and four on the outer extents. The middle image uses one of the hooks that are available within the script to produce a noisy image and not an exposure map. This hook can also be used to insert simulated/real objects. The right image shows how another hook can be used to account for trimming of the outer edges (which sometimes do not get exposed enough due to vignetting). This hook can also be used to insert any random area of bad pixels or to simulate persistence in near infra-red detectors (these can be large). For its processing, this script needs two input files: 1) a table containing the RA and Dec of each pointing, 2) a FITS image from the camera that the dither pattern is meant for. The image has to contain the celestial world coordinate system (WCS, see Calabretta & Greisen 2002) headers. Having a WCS is very important, especially for cameras with a wide field of view, because distortions can become visible/significant. The tutorial and dedicated manual for this script are available in the Gnuastro manual and will always be up to date with the running version; therefore for the practical details, we encourage readers to follow the Gnuastro manual. The future changes in the script that break with this research note will be clearly designated in a “changes after publication” subsection of the section describing this script. This paper is available on arxiv under CC 4.0 DEED license. This paper is available on arxiv under CC 4.0 DEED license. available on arxiv [2] https://www.gnu.org/software/gnuastro/manual https://www.gnu.org/software/gnuastro/manual [3] https://www.gnu.org/software/gnuastro/manual/html node/Tutorials.html https://www.gnu.org/software/gnuastro/manual/html

Gnuastro: Simulating The Exposure Map of a Pointing Pattern - Simulating the Exposure Map

Kubernetes Dashboard is a web-based user interface for performing Kubernetes operations. It helps to get a brief overview of workloads running in the cluster. With a Kubernetes dashboard, one can visualize Kubernetes(K8s) applications, monitor the performance, manage the cluster resources, and enable team collaboration between Developers and DevOps teams. As per the state of Kubernetes 2022 report by Vmware, the increase in the adoption of Kubernetes brings domain complexities into the process. In this blog, we will talk about the need for a Kubernetes dashboard,
the features provided by Devtron’s Kubernetes dashboard, and
how it can help you in Kubernetes management. Why is there a need for a Kubernetes dashboard? Kubernetes comes with a command line utility called “kubectl”. It is efficient enough to perform routine activities like deploying, updating, deleting, monitoring, and debugging within a cluster and on Kubernetes objects. Developers have to expend additional time and resources to learn an extra set of commands to debug in case of an issue in their application. It also becomes challenging to monitor and observe resources when dealing with Kubernetes at scale, especially in multi-cluster deployments. To solve all these challenges and accelerate software development, Kubernetes Dashboard was born. It provides a graphical user interface to manage your Kubernetes applications and clusters, making it really easy for developers to use. The K8s dashboard improves collaboration between the DevOps and developers by providing resource visibility and control, thus increasing productivity. Why the standard Kubernetes dashboard falls short of expectations? The vanilla Kubernetes dashboard provides essential features suitable for small-scale use cases. Though the community heavily uses it, it still has few challenges that we have listed down which you might face with the standard dashboard by Kubernetes. Unsupported multi-cluster and multi-cloud view: The standard Kubernetes Dashboard doesn’t support a multi-cluster view because it is designed with namespace first. This increases complexity at scale.
Manual RBAC: Kubernetes dashboards have RBAC that needs to be managed manually using a token or the kubeconfig file. In the case of Devtron, it has centralized access management wherein users don’t have to deal with RBAC or Kubeconfig files.
No SSO: The traditional Kubernetes dashboard doesn’t support SSO Login services, whereas it is a standard feature in Devtron’s Kubernetes Dashboard.
Complex node management: Users have to edit the entire Node manifest to make any changes, which is error-prone and cumbersome. With Devtron, one can efficiently perform node operations such as adding a taint, cordoning a node, etc., from the dashboard. However, Devtron also allows to access and edit the Node manifest for cases requiring advanced customization.
Absent cluster terminal access: In the traditional Kubernetes dashboard, users cannot use CLI tools like Netshot, Busybox, K9s, etc., for debugging clusters if required. Kubernetes dashboard by Devtron comes with cluster terminal access that helps users easily debug and troubleshoot cluster issues.
Unsupported Helm release management & resource grouping: The vanilla Kubernetes dashboard doesn’t provide any features to simplify the Helm release lifecycle but Devtron’s K8s dashboard supports Helm release management and provides an efficient way to deploy and observe helm charts. Presenting the Kubernetes Dashboard by Devtron The Kubernetes dashboard offered by Devtron is open-source and has multiple features that are not available in the standard dashboard on Kubernetes. From providing a comprehensive overview of Kubernetes resources deployed across multiple clusters to an intuitive user interface that enables development and operations teams to interact with Kubernetes clusters and collaborate, Devtron’s Kubernetes dashboard helps accelerate an organization’s maturity of operation on Kubernetes. The Kubernetes dashboard by Devtron comes with a wide range of features such as — helm release management, cluster terminal access, node operations from the dashboard, Kubernetes resource browser, cluster operations, and a lot more to manage your clusters and k8s applications. Let’s dive deep into the features that Devtron has to offer. K8s Clusters Management Kubernetes dashboard by Devtron provides a brief overview of clusters added to the dashboard and helps you monitor the cluster performance. It gives the real-time node health status and summary of nodes, including resource usages, labels, annotations, taints, pods on each node, and a lot more. The dashboard also helps you perform node operations such as: cordon a node,
drain a node,
taint a node,
debug node/cluster using cluster access terminal,
edit the node manifest,
delete a node from the Kubernetes dashboard. K8s Application Management The Kubernetes dashboard by Devtron comes with a dedicated K8s Resource Browser which provides a detailed overview of all k8s resources deployed in a cluster. The resource browser aggregates all k8s resources within a cluster and helps you quickly troubleshoot & debug from the intuitive dashboard. With the k8s resource browser, you can easily navigate across multiple clusters and filter resources by using the namespace filter, as highlighted in the image. It also allows you to create new resources through the K8s manifest. The resource browser helps you perform pod operations such as: check live manifest, edit & apply manifest changes,
check events,
view real-time logs,
exec into a terminal, and
delete resources and all that from the browser window. Helm Release Management The Kubernetes dashboard by Devtron is packaged with Helm Release Management and helps you deploy any helm chart directly to your cluster from the dashboard. It provides easy access to manage the entire lifecycle of a helm release. Though Helm is great at packaging K8s applications, it needs some catch-up regarding debugging and troubleshooting applications using Helm CLI. Helm CLI poses multiple challenges while managing the lifecycle of helm apps, like the absence of real-time monitoring, the inability to group resources, and no way to compare deployment values across multi-cluster deployments and a lot more. But the Devtron Kubernetes dashboard has addressed the complexities and challenges of Helm CLI. The dashboard provides a brief overview of helm apps deployed across multiple clusters and is rich in features such as: real-time application status,
grep logs across multiple pods with Log Analyzer,
k8s resource grouping at the application level,
check real-time logs of pods, check events, manifests,
exec into pod shell for easier debugging,
check configuration diff of helm charts deployed,
easy rollback with config details of each helm chart revision,
easily deploy and upgrade helm charts and a lot more. Conclusion The Kubernetes dashboard by Devtron is a holistic tool for Kubernetes management that takes care of all aspects of managing Kubernetes through a dashboard. We would love to hear your thoughts on the dashboard. Feel free to join the devtron discord community and give it a star if it helped ease your journey into Kubernetes or improved your day-to-day operations. Kubernetes Dashboard is a web-based user interface for performing Kubernetes operations. It helps to get a brief overview of workloads running in the cluster. With a Kubernetes dashboard, one can visualize Kubernetes(K8s) applications, monitor the performance, manage the cluster resources, and enable team collaboration between Developers and DevOps teams. As per the state of Kubernetes 2022 report by Vmware , the increase in the adoption of Kubernetes brings domain complexities into the process. state of Kubernetes 2022 report by Vmware state of Kubernetes 2022 report by Vmware In this blog, we will talk about the need for a Kubernetes dashboard, the features provided by Devtron’s Kubernetes dashboard, and how it can help you in Kubernetes management. the need for a Kubernetes dashboard, the features provided by Devtron’s Kubernetes dashboard, and how it can help you in Kubernetes management. Why is there a need for a Kubernetes dashboard? Kubernetes comes with a command line utility called “kubectl”. It is efficient enough to perform routine activities like deploying, updating, deleting, monitoring, and debugging within a cluster and on Kubernetes objects. Developers have to expend additional time and resources to learn an extra set of commands to debug in case of an issue in their application. It also becomes challenging to monitor and observe resources when dealing with Kubernetes at scale, especially in multi-cluster deployments. To solve all these challenges and accelerate software development, Kubernetes Dashboard was born. It provides a graphical user interface to manage your Kubernetes applications and clusters, making it really easy for developers to use. The K8s dashboard improves collaboration between the DevOps and developers by providing resource visibility and control, thus increasing productivity. Why the standard Kubernetes dashboard falls short of expectations? The vanilla Kubernetes dashboard provides essential features suitable for small-scale use cases. Though the community heavily uses it, it still has few challenges that we have listed down which you might face with the standard dashboard by Kubernetes. Unsupported multi-cluster and multi-cloud view: The standard Kubernetes Dashboard doesn’t support a multi-cluster view because it is designed with namespace first. This increases complexity at scale. Manual RBAC: Kubernetes dashboards have RBAC that needs to be managed manually using a token or the kubeconfig file. In the case of Devtron, it has centralized access management wherein users don’t have to deal with RBAC or Kubeconfig files. No SSO: The traditional Kubernetes dashboard doesn’t support SSO Login services, whereas it is a standard feature in Devtron’s Kubernetes Dashboard. Complex node management: Users have to edit the entire Node manifest to make any changes, which is error-prone and cumbersome. With Devtron, one can efficiently perform node operations such as adding a taint, cordoning a node, etc., from the dashboard. However, Devtron also allows to access and edit the Node manifest for cases requiring advanced customization. Absent cluster terminal access: In the traditional Kubernetes dashboard, users cannot use CLI tools like Netshot, Busybox, K9s, etc., for debugging clusters if required. Kubernetes dashboard by Devtron comes with cluster terminal access that helps users easily debug and troubleshoot cluster issues. Unsupported Helm release management & resource grouping: The vanilla Kubernetes dashboard doesn’t provide any features to simplify the Helm release lifecycle but Devtron’s K8s dashboard supports Helm release management and provides an efficient way to deploy and observe helm charts. Unsupported multi-cluster and multi-cloud view: The standard Kubernetes Dashboard doesn’t support a multi-cluster view because it is designed with namespace first. This increases complexity at scale. Manual RBAC: Kubernetes dashboards have RBAC that needs to be managed manually using a token or the kubeconfig file. In the case of Devtron, it has centralized access management wherein users don’t have to deal with RBAC or Kubeconfig files. No SSO: The traditional Kubernetes dashboard doesn’t support SSO Login services, whereas it is a standard feature in Devtron’s Kubernetes Dashboard. Complex node management: Users have to edit the entire Node manifest to make any changes, which is error-prone and cumbersome. With Devtron, one can efficiently perform node operations such as adding a taint, cordoning a node, etc., from the dashboard. However, Devtron also allows to access and edit the Node manifest for cases requiring advanced customization. Absent cluster terminal access: In the traditional Kubernetes dashboard, users cannot use CLI tools like Netshot, Busybox, K9s, etc., for debugging clusters if required. Kubernetes dashboard by Devtron comes with cluster terminal access that helps users easily debug and troubleshoot cluster issues. cluster terminal access cluster terminal access Unsupported Helm release management & resource grouping: The vanilla Kubernetes dashboard doesn’t provide any features to simplify the Helm release lifecycle but Devtron’s K8s dashboard supports Helm release management and provides an efficient way to deploy and observe helm charts. Presenting the Kubernetes Dashboard by Devtron The Kubernetes dashboard offered by Devtron is open-source and has multiple features that are not available in the standard dashboard on Kubernetes. From providing a comprehensive overview of Kubernetes resources deployed across multiple clusters to an intuitive user interface that enables development and operations teams to interact with Kubernetes clusters and collaborate, Devtron’s Kubernetes dashboard helps accelerate an organization’s maturity of operation on Kubernetes. The Kubernetes dashboard by Devtron comes with a wide range of features such as — helm release management, cluster terminal access, node operations from the dashboard, Kubernetes resource browser, cluster operations, and a lot more to manage your clusters and k8s applications. Let’s dive deep into the features that Devtron has to offer. K8s Clusters Management Kubernetes dashboard by Devtron provides a brief overview of clusters added to the dashboard and helps you monitor the cluster performance. It gives the real-time node health status and summary of nodes, including resource usages, labels, annotations, taints, pods on each node, and a lot more. The dashboard also helps you perform node operations such as: cordon a node, drain a node, taint a node, debug node/cluster using cluster access terminal, edit the node manifest, delete a node from the Kubernetes dashboard. cordon a node, drain a node, taint a node , taint a node taint a node debug node/cluster using cluster access terminal, edit the node manifest, delete a node from the Kubernetes dashboard. K8s Application Management The Kubernetes dashboard by Devtron comes with a dedicated K8s Resource Browser which provides a detailed overview of all k8s resources deployed in a cluster. The resource browser aggregates all k8s resources within a cluster and helps you quickly troubleshoot & debug from the intuitive dashboard. With the k8s resource browser, you can easily navigate across multiple clusters and filter resources by using the namespace filter, as highlighted in the image. It also allows you to create new resources through the K8s manifest. The resource browser helps you perform pod operations such as: check live manifest, edit & apply manifest changes, check events, view real-time logs, exec into a terminal, and delete resources and all that from the browser window. check live manifest, edit & apply manifest changes, check events, view real-time logs, exec into a terminal, and delete resources and all that from the browser window. Helm Release Management The Kubernetes dashboard by Devtron is packaged with Helm Release Management and helps you deploy any helm chart directly to your cluster from the dashboard. It provides easy access to manage the entire lifecycle of a helm release. Though Helm is great at packaging K8s applications, it needs some catch-up regarding debugging and troubleshooting applications using Helm CLI. Helm CLI poses multiple challenges while managing the lifecycle of helm apps, like the absence of real-time monitoring, the inability to group resources, and no way to compare deployment values across multi-cluster deployments and a lot more. But the Devtron Kubernetes dashboard has addressed the complexities and challenges of Helm CLI . complexities and challenges of Helm CLI complexities and challenges of Helm CLI The dashboard provides a brief overview of helm apps deployed across multiple clusters and is rich in features such as: real-time application status, grep logs across multiple pods with Log Analyzer, k8s resource grouping at the application level, check real-time logs of pods, check events, manifests, exec into pod shell for easier debugging, check configuration diff of helm charts deployed, easy rollback with config details of each helm chart revision, easily deploy and upgrade helm charts and a lot more. real-time application status, grep logs across multiple pods with Log Analyzer, k8s resource grouping at the application level, check real-time logs of pods, check events, manifests, exec into pod shell for easier debugging, check configuration diff of helm charts deployed, easy rollback with config details of each helm chart revision, easily deploy and upgrade helm charts and a lot more. Conclusion The Kubernetes dashboard by Devtron is a holistic tool for Kubernetes management that takes care of all aspects of managing Kubernetes through a dashboard. We would love to hear your thoughts on the dashboard. Feel free to join the devtron discord community and give it a star if it helped ease your journey into Kubernetes or improved your day-to-day operations. devtron discord community

How to Manage Kubernetes like a Pro with Kubernetes Dashboard by Devtron

Devtron দ্বারা Kubernetes ড্যাশবোর্ড সহ প্রো-এর মতো কুবারনেটস কীভাবে পরিচালনা করবেন

So verwalten Sie Kubernetes wie ein Profi mit dem Kubernetes Dashboard von Devtron

Cómo administrar Kubernetes como un profesional con Kubernetes Dashboard de Devtron

Comment gérer Kubernetes comme un pro avec Kubernetes Dashboard de Devtron

Devtron द्वारा Kubernetes डैशबोर्ड के साथ एक प्रो की तरह Kubernetes का प्रबंधन कैसे करें

Devtron の Kubernetes ダッシュボードを使用してプロのように Kubernetes を管理する方法

Devtron의 Kubernetes 대시보드를 사용하여 전문가처럼 Kubernetes를 관리하는 방법

Como gerenciar o Kubernetes como um profissional com o Kubernetes Dashboard da Devtron

Как управлять Kubernetes как профессионал с помощью Kubernetes Dashboard от Devtron

Kubernetes Dashboard by Devtron ile Kubernetes'i Profesyonel Gibi Yönetme

Cách quản lý Kubernetes như một chuyên gia với Bảng điều khiển Kubernetes của Devtron

如何使用 Devtron 的 Kubernetes 仪表板像专业人士一样管理 Kubernetes

Are VPNs Legal in Your Country? Well.. It Depends

Reading code manually is a time-consuming process. It is also error-prone, as it is easy to miss important details. As developers and penetration testers, we need to find a way to automate this process. SAST is a technique that can help us with this task. SAST is not a silver bullet. It is usable only for use cases with access to the source code for open-source projects or white-box penetration testing. However, it can help you find some low-hanging fruits and save time. What is SAST? Static application security testing (SAST) is a subset of static code analysis used to increase the security and reliability of the code. SAST detects old dependencies, secret detection, logical errors that lead to vulnerabilities, and more. SAST includes testing that affects cybersecurity secondarily, such as visual code complexity, code ambiguity, and non-intuitive practices that can lead to vulnerabilities. Tools in practice SAST tools are usually regex pattern matchers on steroids that look for known vulnerabilities in the code.
For example, a SAST tool might look for the use of eval, exec, or pickle in Python code, these functions can be used to execute arbitrary code. Hacking and SAST I would divide my approach to SAST into three categories: Vulnerability detection: I use tools like Semgrep, Bandit, Nodejsscan to find attack vectors in the code. You can usually find low-hanging fruits such as unsanitized inputs, bad cryptography, or vulnerable libraries. By the way, the Semgrep PRO version has more rules; it is free if there are not more than 10 developers on the project.



Secret detection: Gitleaks, Trufflehog, or Grep can help you find secrets in the code. This is important because secrets can be used to escalate privileges or access sensitive data. Usually, database connection strings, API keys, or passwords are stored in the code.


Misconfigurations: Tools like Checkov or Trivy can help you find misconfigurations. Misconfigurations are usually in "infrastructure as code" (IaC) files but can also be in the code itself. An example would be a misconfigured docker-compose file that exposes a database to the internet. For scanning Dockerfiles, I recommend a combination of hadolint and grype
More info: https://dkb-zh.gitlab-pages.ics.muni.cz/vulnerability-management/web-guides-external/docs/guide_iac_sast/#docker SAST tools are not perfect. They will give you false positives and false negatives. **However, it saves much time compared to randomly exploiting some applications.  I used SAST tools in my penetration testing engagements and competitions. It helped me get started with the codebase and gave me some hints about where to look for vulnerabilities. How to train using SAST in hacking I recommend that you start with Hack The Box. This platform offers challenges, such as getting source code and finding vulnerabilities. Then, exploit them on a real machine. This is a great way to learn how to use SAST tools in practice. Or, if you are a developer, you can use SAST tools in your CI/CD pipeline. This way, you can get used to the tools and their output. Simultaneously, you will improve the security of your application. Guides recommendation I have prepared a list of guides to help you start with SAST and secret detection. These guides are written as part of my thesis and are a great starting point for anyone interested in SAST tools. How to start with secret detection. When detecting secrets, remember: it's not a secret if hackers know it. Even seasoned developers can accidentally push passwords or connection strings into remote source control. Using various tools, this guide offers quick and easy methods to mitigate this risk. How to automate secret detection This guide focuses on understanding secret detection using pre-commit hooks and CI/CD pipelines. While the code primarily focuses on GitLab, the last section will also cover GitHub. How to start with SAST pipelines This guide efficiently outlines the steps for initiating Static Application Security Testing (SAST) in GitLab. SAST is a process that uses static code analysis to identify potential vulnerabilities. How to start with IaC SAST This cheatsheet introduces helpful tools for scanning Infrastructure as Code (IaC) artifacts and provides examples on how to integrate them into your CI/CD pipeline. Custom tool in Golang I have created a custom tool in Golang that helps me quickly match regexes against huge codebases. There is an infinite tradeoff between precision and variance. Suppose you need more variance and don't mind more manual reviewing. In that case, you can try RegFinder, which is like grep but more suited for secret detection (faster in bigger repos, clear output, ignoring some file extensions). Or you can use grep directly. Most valuable are the regexes in the repo, not the tool you will use. Clone this repository
Run grep -n -r your_app/ -Ef regex_dir/general.txt Or Run ./regfinder.elf -d your_app/ -f regex_dir/general.txt It is straightforward to extend existing regex patterns. This tool is not feasible for automated pipelines. However, it comes in handy if you need to find a non-standard secret or in other assessments, such as security reviews, where more manual work is expected. Comment if you have great experience with other tools. Thank you for reading. Reading code manually is a time-consuming process. It is also error-prone, as it is easy to miss important details. As developers and penetration testers, we need to find a way to automate this process. SAST is a technique that can help us with this task. SAST is not a silver bullet. It is usable only for use cases with access to the source code for open-source projects or white-box penetration testing. However, it can help you find some low-hanging fruits and save time. SAST is not a silver bullet. What is SAST? Static application security testing (SAST) is a subset of static code analysis used to increase the security and reliability of the code. SAST detects old dependencies, secret detection, logical errors that lead to vulnerabilities, and more. SAST includes testing that affects cybersecurity secondarily, such as visual code complexity, code ambiguity, and non-intuitive practices that can lead to vulnerabilities. Tools in practice SAST tools are usually regex pattern matchers on steroids that look for known vulnerabilities in the code.
For example, a SAST tool might look for the use of eval , exec , or pickle in Python code, these functions can be used to execute arbitrary code. eval exec pickle Hacking and SAST I would divide my approach to SAST into three categories: Vulnerability detection: I use tools like Semgrep, Bandit, Nodejsscan to find attack vectors in the code. You can usually find low-hanging fruits such as unsanitized inputs, bad cryptography, or vulnerable libraries. By the way, the Semgrep PRO version has more rules; it is free if there are not more than 10 developers on the project. Secret detection: Gitleaks, Trufflehog, or Grep can help you find secrets in the code. This is important because secrets can be used to escalate privileges or access sensitive data. Usually, database connection strings, API keys, or passwords are stored in the code. Misconfigurations: Tools like Checkov or Trivy can help you find misconfigurations. Misconfigurations are usually in "infrastructure as code" (IaC) files but can also be in the code itself. An example would be a misconfigured docker-compose file that exposes a database to the internet. For scanning Dockerfiles, I recommend a combination of hadolint and grype
More info: https://dkb-zh.gitlab-pages.ics.muni.cz/vulnerability-management/web-guides-external/docs/guide_iac_sast/#docker Vulnerability detection: I use tools like Semgrep, Bandit, Nodejsscan to find attack vectors in the code. You can usually find low-hanging fruits such as unsanitized inputs, bad cryptography, or vulnerable libraries. By the way, the Semgrep PRO version has more rules; it is free if there are not more than 10 developers on the project. Vulnerability detection : I use tools like Semgrep , Bandit, Nodejsscan to find attack vectors in the code. You can usually find low-hanging fruits such as unsanitized inputs, bad cryptography, or vulnerable libraries. By the way, the Semgrep PRO version has more rules; it is free if there are not more than 10 developers on the project. Vulnerability detection Semgrep Semgrep Bandit , Nodejsscan Bandit Nodejsscan Secret detection: Gitleaks, Trufflehog, or Grep can help you find secrets in the code. This is important because secrets can be used to escalate privileges or access sensitive data. Usually, database connection strings, API keys, or passwords are stored in the code. Secret detection : Gitleaks , Trufflehog , or Grep can help you find secrets in the code. This is important because secrets can be used to escalate privileges or access sensitive data. Usually, database connection strings, API keys, or passwords are stored in the code. Secret detection Gitleaks Gitleaks Trufflehog Trufflehog Grep Grep Misconfigurations: Tools like Checkov or Trivy can help you find misconfigurations. Misconfigurations are usually in "infrastructure as code" (IaC) files but can also be in the code itself. An example would be a misconfigured docker-compose file that exposes a database to the internet. For scanning Dockerfiles, I recommend a combination of hadolint and grype More info: https://dkb-zh.gitlab-pages.ics.muni.cz/vulnerability-management/web-guides-external/docs/guide_iac_sast/#docker Misconfigurations : Tools like Checkov or Trivy can help you find misconfigurations. Misconfigurations are usually in "infrastructure as code" (IaC) files but can also be in the code itself. An example would be a misconfigured docker-compose file that exposes a database to the internet. For scanning Dockerfiles, I recommend a combination of hadolint and grype Misconfigurations Checkov Checkov Trivy Trivy hadolint hadolint grype grype More info: https://dkb-zh.gitlab-pages.ics.muni.cz/vulnerability-management/web-guides-external/docs/guide_iac_sast/#docker https://dkb-zh.gitlab-pages.ics.muni.cz/vulnerability-management/web-guides-external/docs/guide_iac_sast/#docker SAST tools are not perfect. They will give you false positives and false negatives. **However, it saves much time compared to randomly exploiting some applications.  I used SAST tools in my penetration testing engagements and competitions. It helped me get started with the codebase and gave me some hints about where to look for vulnerabilities. How to train using SAST in hacking I recommend that you start with Hack The Box . This platform offers challenges, such as getting source code and finding vulnerabilities. Then, exploit them on a real machine. This is a great way to learn how to use SAST tools in practice. Hack The Box Hack The Box Or, if you are a developer, you can use SAST tools in your CI/CD pipeline. This way, you can get used to the tools and their output. Simultaneously, you will improve the security of your application. Guides recommendation I have prepared a list of guides to help you start with SAST and secret detection. These guides are written as part of my thesis and are a great starting point for anyone interested in SAST tools. How to start with secret detection. How to start with secret detection. When detecting secrets, remember: it's not a secret if hackers know it. Even seasoned developers can accidentally push passwords or connection strings into remote source control. Using various tools, this guide offers quick and easy methods to mitigate this risk. How to automate secret detection How to automate secret detection This guide focuses on understanding secret detection using pre-commit hooks and CI/CD pipelines. While the code primarily focuses on GitLab, the last section will also cover GitHub. How to start with SAST pipelines How to start with SAST pipelines This guide efficiently outlines the steps for initiating Static Application Security Testing (SAST) in GitLab. SAST is a process that uses static code analysis to identify potential vulnerabilities. How to start with IaC SAST How to start with IaC SAST This cheatsheet introduces helpful tools for scanning Infrastructure as Code (IaC) artifacts and provides examples on how to integrate them into your CI/CD pipeline. Custom tool in Golang I have created a custom tool in Golang that helps me quickly match regexes against huge codebases. There is an infinite tradeoff between precision and variance. Suppose you need more variance and don't mind more manual reviewing. In that case, you can try RegFinder , which is like grep but more suited for secret detection (faster in bigger repos, clear output, ignoring some file extensions). Or you can use grep directly. Most valuable are the regexes in the repo, not the tool you will use. RegFinder grep Most valuable are the regexes Clone this repository Run grep -n -r your_app/ -Ef regex_dir/general.txt Clone this repository repository Run grep -n -r your_app/ -Ef regex_dir/general.txt grep -n -r your_app/ -Ef regex_dir/general.txt Or Run ./regfinder.elf -d your_app/ -f regex_dir/general.txt Run ./regfinder.elf -d your_app/ -f regex_dir/general.txt ./regfinder.elf -d your_app/ -f regex_dir/general.txt It is straightforward to extend existing regex patterns. This tool is not feasible for automated pipelines. However, it comes in handy if you need to find a non-standard secret or in other assessments, such as security reviews, where more manual work is expected. Comment if you have great experience with other tools . Thank you for reading. Comment if you have great experience with other tools

Read Code Like a Hacker With the SAST

SAST টেকনিক দিয়ে হ্যাকারের মতো কোড পড়ুন

Lesen Sie Code wie ein Hacker mit der SAST-Technik

Lea código como un hacker con la técnica SAST

Lisez le code comme un hacker avec la technique SAST

SAST तकनीक से हैकर की तरह कोड पढ़ें

SAST テクニックでハッカーのようにコードを読む

SAST 기술을 사용하여 해커처럼 코드 읽기

Leia o código como um hacker com a técnica SAST

Читайте код как хакер с помощью техники SAST

SAST Tekniği ile Kodu Hacker Gibi Okuyun

Đọc mã như một hacker với kỹ thuật SAST

使用 SAST 技术像黑客一样阅读代码

Simple Wonders of RAG using Ollama, Langchain and ChromaDB

The Press Release is NOT Dead (Neither is the Funding Announcement)

প্রেস রিলিজ মৃত নয় (ফান্ডিং ঘোষণাও নয়)

Die Pressemitteilung ist NICHT tot (ebenso wenig wie die Finanzierungsankündigung)

El comunicado de prensa NO está muerto (tampoco el anuncio de financiación)

Le communiqué de presse n’est PAS mort (l’annonce de financement non plus)

प्रेस विज्ञप्ति ख़त्म नहीं हुई है (न ही फंडिंग की घोषणा)

プレスリリースは死んでいない（資金調達の発表も同様）

보도 자료는 죽지 않았습니다 (펀딩 발표도 마찬가지입니다)

O comunicado de imprensa NÃO está morto (nem o anúncio de financiamento)

Пресс-релиз НЕ умер (как и объявление о финансировании)

Basın Bülteni ÖLÜ DEĞİLDİR (Finansman Duyurusu da Değil)

Thông cáo báo chí KHÔNG chết (Thông báo tài trợ cũng không)

新闻稿还没有过时（融资公告也没有过时）

deployments come in all shapes and sizes. We support bare metal installs on any version of , containerized installs on any version of (including Red Hat OpenShift), and installs just about anywhere you can deploy a small lightweight single binary. But with flexibility comes the inevitability that edge case issues will require debugging. MinIO Linux Kubernetes In this blog post, we’ll show you how to debug a MinIO install running in Kubernetes and also some of the common issues you might encounter when doing bare metal installation and how to rectify them. Kubernetes Debugger Pod There are a few ways to access the MinIO API running inside a Kubernetes cluster. We can use or set up a listening on to be able to access the API. Both of these methods offer a way to access the service from outside the network, but they do come with one major downside: You can only access the Service that the NodePort or Port Forwarding references on an available port (not the usual configuration for the application). For example, you have to access the MinIO API, usually found on port , via a randomly assigned port. kubectl port-forwarding Service NodePort 9000 3xxxx What if I told you there was a better way – and it's not novel? When debugging applications you want to have full access to the native run-time environment so you can use various tools to troubleshoot and debug the cluster. One way to do that is launching a “busybox” style pod and installing all the required tools needed to debug the application. First launch a into the same namespace as your MinIO install. In order to do this create a yaml file called with the following yaml. Pod debugger-pod.yaml apiVersion: v1

kind: Pod

metadata:

  name: mc

  labels:

    app: mc

spec:

  containers:

  - image: minio/mc:latest

    command:

      - "sleep"

      - "604800"

    imagePullPolicy: IfNotPresent

    name: mc

  restartPolicy: Always The above Pod configuration is pulling the image for MinIO utility. In order to ensure the pod doesn’t just launch and then exit, we’ve added a command. mc sleep Once the yaml is saved apply the configuration to the Kubernetes namespace where the MinIO cluster is running kubectl apply -f debugger-pod.yaml Once the pod is up and running access it via shell $ kubectl exec -i -t -n default mc -c mc -- sh -c "(bash || ash || sh)"

[root@mc /]# Then with you can access the MinIO cluster mc [root@mc /]# mc alias set myminio    --insecure

Added `myminio` successfully. Now that we have a debugger pod up and running, you can perform action on the cluster directly within the same network. For example, if the replication was broken due to an site going offline or a hardware failure, you can resync any pending objects to be replicated using the following command [root@mc /]# mc admin replicate resync start minio1 minio2


[root@mc /]# mc admin replicate resync status minio1 minio2


✔ ✔ ✔

ResyncID: 		 2248d1d1-633f-4d61-b938-d8ea0b9b2d31

Status:   		 Completed

Objects:  		 2225

Versions: 		 2225

FailedObjects:     0

Throughput:   	 5.3 MiB/s

IOPs:     		 124.23 objs/s

Transferred:  	 94 MiB

Elapsed:  		 17.909833202s

CurrObjName:  	 testbucket/web-app/tsconfig.json Another reason you would run the debugger pod is if there are some file system permissions or invalid groups configurations in your pod, you can update them using the debugger pod [root@mc /]# chgrp -R 1000780050 .minio.sys/ The above debugging method can also be used in bare metal environments. For instance you can launch a busybox or bastion node with installed and follow the same instructions as above. mc Debugging Bare Metal Bare metal Linux installs are the most straightforward. In fact it just takes a few commands to get MinIO installed and running with SystemD. For details, please see . Configuring MinIO with SystemD Once in a great while, bare metal installs go awry. Here are some of the (not-so-common) pitfalls that we are asked about  in or . These pitfalls are not hardware or operating specific but can be useful to know in any kind of environment. SUBNET Slack File Permission One of the most common pitfalls is the file permissions of the MinIO binary and the configuration file. If this occurs, when you start MinIO using SystemD you will see and here is the full stack trace Assertion failed for MinIO. # systemctl status minio.service

● minio.service - MinIO

     Loaded: loaded (/etc/systemd/system/minio.service; enabled; vendor preset: enabled)

     Active: inactive (dead)

     Assert: start assertion failed at Tue 2023-12-26 18:21:38 PST; 8s ago

             AssertFileIsExecutable=/usr/local/bin/minio was not met

       Docs: https://docs.min.io


Dec 26 18:13:37 minio1 systemd[1]: minio.service: Starting requested but asserts failed.

Dec 26 18:17:50 minio1 systemd[1]: Assertion failed for MinIO.

Dec 26 18:21:38 minio1 systemd[1]: minio.service: Starting requested but asserts failed.

Dec 26 18:21:38 minio1 systemd[1]: Assertion failed for MinIO. This could be caused by a number of reasons, let's go down the list and check for each of them. : The binary, in this example located at needs to have permission for user and group, respectively. MinIO Binary /usr/local/bin/minio root:root # ll /usr/local/bin/minio

total 93804

-rwxr-xr-x 1 root    root    96018432 Nov 15 16:35  minio* : The MinIO service needs to run under a unique Linux user and group for security purposes, never run as a user. By default we use for the user and group names. In the SystemD service config file you should see something like this MinIO Service User and Group root minio-user User=minio-user

Group=minio-user : The directory where MinIO data will be stored needs to be owned by or whichever user you decide to run the MinIO service as above. MinIO Data Dir minio-user:minio-user # ls -l /mnt

total 4

drwxrwxr-x 2 minio-user minio-user 4096 Dec 27 09:58 data : Both the config files should have permissions for user and group like so SystemD and MinIO config root:root # ls -l /etc/default/minio

-rw-r--r-- 1 root root 1330 Dec 27 09:52 /etc/default/minio


# ls -l /etc/systemd/system/minio.service

-rw-r--r-- 1 root root 941 Dec 26 17:13 /etc/systemd/system/minio.service : The entire install process should be run as . You can also try if your user has permissions but the recommendation is to run as root as the install needs to place files in a bunch of places that only the user can access. Your bash prompt should have a and not a like so Run as Root root sudo root # $ vs # $ If none of the above work, the best approach is to remove the app, directories and configs and start a fresh install as a root user. Port conflict Another common issue related to deleted files which still hold on to the process, which causes port conflicts. Even when a service is not running, you may be unable to start a new service on the existing port or the service that is running will misbehave (such as not allowing you to login). # lsof -n | grep (deleted)

COMMAND PID USER FD TYPE DEVICE   SIZE 	NODE NAME

nginx   	13423 root 5u  	REG 253,3   42949672960 	17 (deleted)

minio 	13423 minio 6u    REG 253,3 	0         	      18 (deleted)

minio       13423 minio 7u    REG 253,3 	0         	      19 (deleted) You might see errors such as those below on a MinIO install Login Failed net::ERR_FAILED 500 Internal Server Error 401 Unauthorized The screenshot above shows an internal server error and an unauthorized error. While looking at the surface it looks unclear what has caused this error, we can debug with a little linux knowledge what to look for that could cause this, let's take a gander. There are several ways to debug this issue, first lets check to see if multiple MinIO processes are running on the same node # ps aux | grep -i minio

minio-u+    5048  0.3  1.7 1594008 144384 ?      Ssl  11:03   0:01 /usr/local/bin/minio server --console-address :9001 /mnt/data/disk1/minio


minio-u+    9276  0.3  1.7 1594208 144301 ?      Ssl  11:25   0:01 /usr/local/bin/minio server --console-address :9001 /mnt/data/disk1/minio As we can see above there are 2 MinIO processes running. Start by killing the process that is older or has been running the longest, in this case it seems to be the process ID . 5048 kill -9 5048 Sometimes even after killing the process the service might still not start or might still get hung up because it has reserved a process number but not let it go. This can be caused by files that have been deleted but are still being tracked by the operating system. You can find the deleted files via LSOF lsof -n | grep '(deleted)' Last but not least, if there are no deleted files left over or hung processes and if everything looks absolutely clean, the last resort is to quickly restart the node. This is a no-nonsense method that  shuts down and clears any pending files and processes so you start a fresh install. SUBNET to the rescue Although rare, installation edge cases will always exist. MinIO customers know that they have nothing to worry about because they can quickly message our engineers – who have written the code – via the portal. We've seen almost everything under the sun, so while the issue might look cryptic or mind boggling at first glance, we'll put our years of expertise debugging installations in many varied environments to work and help you in a jiffy. SUBNET If you have any questions on troubleshooting and debugging installs be sure to reach out to us on ! MinIO Slack

Pro Tips for Debugging MinIO: Overcoming Common Issues in Kubernetes and Bare Metal Environments

MinIO ডিবাগ করার জন্য প্রো টিপস: কুবারনেটস এবং বেয়ার মেটাল পরিবেশে সাধারণ সমস্যাগুলি অতিক্রম করা

Profi-Tipps zum Debuggen von MinIO: Überwindung häufiger Probleme in Kubernetes- und Bare-Metal-Umgebungen

Consejos profesionales para depurar MinIO: superar problemas comunes en Kubernetes y entornos bare metal

Conseils de pro pour déboguer MinIO : surmonter les problèmes courants dans les environnements Kubernetes et Bare Metal

मिनियो डिबगिंग के लिए प्रो टिप्स: कुबेरनेट्स और बेयर मेटल वातावरण में आम समस्याओं पर काबू पाना

MinIO デバッグのプロのヒント: Kubernetes とベアメタル環境での一般的な問題の克服

MinIO 디버깅을 위한 전문가 팁: Kubernetes 및 베어메탈 환경의 일반적인 문제 극복

Dicas profissionais para depuração do MinIO: superando problemas comuns em ambientes Kubernetes e Bare Metal

Советы для профессионалов по отладке MinIO: решение распространенных проблем в Kubernetes и средах с голым железом

MinIO'da Hata Ayıklamaya Yönelik Profesyonel İpuçları: Kubernetes ve Bare Metal Ortamlarında Yaygın Sorunların Aşılması

Mẹo chuyên nghiệp để gỡ lỗi MinIO: Khắc phục các sự cố thường gặp trong môi trường Kubernetes và Bare Metal

调试 MinIO 的专业技巧：解决 Kubernetes 和裸机环境中的常见问题

Leetcode is famous for being a perfect platform for practicing coding problems and mastering coding interviews, unlike others, it is not for competitive programming, this guide will help you to get started with Leetcode without losing hope too early. Tip 1: Follow a list The biggest reason why people don't find DSA interesting is because they are unable to discover good problems which are easier to solve, simply solving popular questions with no track of questions will bore you very quickly. Even worse, you might try solving a really hard problem and lose motivation when it wasn't that hard, you just had to get a grip on it. That's why it's necessary to follow a list of questions, that way you won't have issues discovering new questions. Solving problems in the right order is very important You might see a question marked easy which isn't actually easy. The solution will be small, but sometimes, it isn't easy to come up with that solution if you haven't done a simpler version of it, thus, it will be demotivating. Blind 75 Leetcode Questions Above is an awesome list that is asked in interviews and is ordered by actual level of difficulty with prerequisites coming before harder questions. If you follow this, you'll feel more engaged. Once you have done most of this, do problems in the “similar questions" section below. Solve each problem till you master that category. Once you feel confident, you can use these - Leetcode Patterns Solve problems by category. This will help you master a data structure or some algorithm. Don't get afraid of “hard" questions as there is no hard problem that can't be broken up. Try to break every ‘difficult’ challenge into smaller clumps. You might not be able to solve it but you'll convert it to a much shorter set of problems that can be solved with some practice. Thinking abstract and looking at the bigger picture is very important. Leetcode is addictive if you improve gradually, try it. Tip 2: Avoid looking at solutions too quickly It's not bad to look at solutions. After all, you can't know everything and learning is necessary. However, looking at solution just after a few minutes of brainstorming is bad. You have to give your absolute best and try every possible "inefficient" solution you can come up with. The first phase is to figure out what Algorithm and data structure will be used. If you can determine what data structure will be used, you can check the section to verify if your assumption was correct, and if after a few minutes, you can't figure it out, you should still check the data structure that will be used and then try to figure out how and where it will be used in the given problem. Related Topics If you can come up with a solution that works correctly but isn't the best one, that's still a success as coming up with a brute-force solution is a bare minimum in an interview. You can try improving the brute force solution by using some optimization techniques. You might find the optimal solution immediately, but improving a solution is a great skill. After spending an hour, if you can't solve the problem, you should understand that you just aren't well versed with the given algorithm and should try solving related problems with that data structure and understand how it works. You should avoid looking at solutions as a solution you made yourself will help you much more. You should abandon the question and maybe revisit it in the future when you have some experience with that data structure. That way you can also track if you made some progress with that technique and if you could solve a new problem given to you in an interview, Tip 3: Interview Questions don't come with hints One thing to remember is that Interview questions won't tell you what data structure will be used for the problem. That's something you can only master with practice. The patterns and requirements of problems determine what's going to be used. There is no substitute for practice! Reading about algorithms will surely improve your range of thinking, but practice is what will help you master it. Tip 4: Be Consistent This goes without saying that practice needs consistency, simply overdoing it once and abandoning it for months will be destructive. It doesn't take much to take out some time every day for Leetcode, as far as discovering questions is concerned, you can use Daily Challenges to keep the consistency and maybe also earn Leetcode coins which might buy you a Leetcode T-Shirt one day. Tip 5: Turn Demotivation into a learning opportunity There will be times when you can't solve a problem despite all efforts, that's very common and bound to happen, but some questions being too hard is not something that should demotivate you. Every question is a learning opportunity and you have what it takes to learn it. Demotivation should be avoided and that's only possible if you have confidence in yourself and are willing to learn as much as you can. Tip 6: Participate in contests Even though Leetcode isn't a competitive programming platform, some contests allow you to try out brand-new problems and even compete with others. They have categories of 1 easy, 2 Medium, and 1 Hard, and solving 3 is more than enough. Once you have enough confidence in your problem-solving ability, these contests will help you gain interview experience as they don't have any hints, and solutions aren't available during the contest. This is pretty close to a real interview experience where time is limited. Tip 7: Keep Hustling Leetcode is an addiction and soon you'll fall in love with it, all you need to do is start, there is only one good time to start anything great, NOW. Just do it and you'll be satisfied with your decision and be proud of yourself. That's all, It's never too early and never too late.

7 Tips for Grinding Leetcode

Requests are undeniably unmissable for anyone willing to start in the Python ecosystem. Yet, the community is broadly unaware of how sad the situation has become. The Incident Due to dramatic circumstances, it was partially locked and put in "maintenance mode" only, meaning it would no longer evolve (features speaking). Some of you may have heard that more than six years ago, Requests was working toward a major version, namely the V3. There was even r with a substantial amount, around $30k. a completed fundraise At the time, there was a plan to bring Async and HTTP/2 support (most notably). You'll guess that none of the exposed promises ever landed. Impacts This incident led to several impacts. Maintainers felt too much pressure to make steps toward a major; some of them said: . "We just can't deliver the promises, and it's going hard to explain why" All the back pressure landed at urllib3. Abruptly started to refuse any changes, saying: "Requests is feature complete, and it's popularity makes it nearly impossible to fix bugs that may be considered feature to this point." Newer projects started ditching HTTP client Requests by learning to use a new one. Some large-scale projects bound to Requests did not migrate because of the potentially high cost of doing it. Let's be clear, this article is not about saying "Requests maintainers are bad" but rather saying we don't agree, and everyone is entitled to their choices. For many years now, Requests have been frozen. Being left in a vegetative state and not evolving, from using more advanced features. this blocked millions of developers The Journey Into Waking Up Initially, like many other reasonable people, I said to myself "Let's wait, Requests will eventually unblock the situation!" Yet, the years are still passing, and nothing. Let's realize something, Yet, Requests is unable to do so. Internet Explorer 11 just celebrated its tenth anniversary last year, and you’ll never guess that it has support for HTTP/2 integrated! I said to myself: "Why are we waiting for this indefinitely? They don't owe us anything! There's a reasonable chance we are waiting... trapped in a circular reference… Let's act." Then, I tried to get a firm grip on the urllib3 base code, contributing and until I was ready to kick things up with that would have put urllib3 far ahead. Without any breaking changes. I was delusional. This was a bit of a shock, but six months passed between my initial kick-off and , and here's why in a nutshell: this there a proof of concept my formal give-up Every bit of idea brought to the table was dismissed, and never seriously analyzed. This felt as good as taking the coldest wind on your face while exiting your warm home. It's the hard truth of the OSS; it's not a democracy, and it's not ruled by pure logic, but by humans. Not far later on, urllib3 called out to help with HTTP/2 support (only) and claimed around $40k to be able to deliver. They probably meant well, but[...] a fundraiser This was the last straw for me, knowing the past mistakes, and actually the best incentive to break the cycle. Everything points to another year before having the slightest sign of a into our production pipes. They clearly lack the time to move forward (or incentives? or both?). No worries, as developers, we should share this burden for the greater good. PRI * HTTP/2.0\r\n\r\nSM\r\n\r\n From my perspective (my opinion only), the OSS ecosystem should not fundraise money for a decade-old protocol, and most of the time should deliver prior to asking. Entities raising money with no solid proof of concept; that's rare! This felt like a bit of a hostage situation, but it could only be me seeing it this way. The Solution So many years and various expertise have been brought to Requests and urllib3… Do we throw all of it into the garbage disposal? Engineers should be reasonable scientists and not revisionists. We don't have to reinvent the wheel all over again; HTTP client Requests are established and really pleasant in their usage. We believe that Requests has the most inclusive and developer-friendly interfaces. So, how to propose an attractive continuity for Requests? How hard could this be to (i) bring a true upgrade experience and (ii) keep the compatibility as high as possible? Sometimes, the OSS ecosystem acts like it is trying to land a rover on the Moon, let's be more realistic and bring our vision down to firm ground. There's a chance offered to us to rehabilitate Requests (and urllib3) and give a fresh breath of air to us, the developers. Without having to learn something as basic as handling an HTTP client. So, the work started, without looking back. Just around my intent to give up on urllib3 evolution, we proposed a fork of both urllib3 and Requests, namely and . urllib3-future Niquests They are (truly) drop-in replacements, at the time of writing, those forks are six months old! And the whole work around this is roughly a year old. We listened to what the community needed by... triaging all the issues on major repositories (Requests, urllib3, and dependants of them) so that the upgrade would be truly useful. Are you seeing it coming? Great! against ! Let's look at the feature table comparison requests, httpx, and aiohttp Feature niquests requests httpx aiohttp HTTP/1.1 ✅ ✅ ✅ ✅ HTTP/2 ✅ ❌ ✅ ❌ HTTP/3 over QUIC ✅ ❌ ❌ ❌ Synchronous ✅ ✅ ✅ ❌ Asynchronous ✅ ❌ ✅ ✅ Thread Safe ✅ ✅ ❌ N/A Task Safe ✅ N/A ✅ ✅ OS Trust Store ✅ ❌ ❌ ❌ Multiplexing ✅ ❌ Limited ❌ DNSSEC ✅ ❌ ❌ ❌ Customizable DNS Resolution ✅ ❌ ❌ ✅ DNS over HTTPS ✅ ❌ ❌ ❌ DNS over QUIC ✅ ❌ ❌ ❌ DNS over TLS ✅ ❌ ❌ ❌ Multiple DNS Resolver ✅ ❌ ❌ ❌ Network Fine Tuning & Inspect ✅ ❌ Limited Limited Certificate Revocation Protection ✅ ❌ ❌ ❌ Session Persistence ✅ ✅ ✅ ✅ In-memory Certificate CA & mTLS ✅ ❌ Limited Limited SOCKS 4/5 Proxies ✅ ✅ ✅ ❌ HTTP/HTTPS Proxies ✅ ✅ ✅ ✅ TLS-in-TLS Support ✅ ✅ ✅ ✅ Direct HTTP/3 Negotiation ✅ N/A N/A N/A Happy Eyeballs ✅ ❌ ❌ ✅ Package / SLSA Signed ✅ ❌ ❌ ✅ And you would think... performance..? are bad? against ! Look at the performance comparison them Fetch a thousand requests using 10 tasks or threads, each with a hundred requests using a single pool of 10 connection. Scenario: High-Level APIs Client Average Delay to Complete Notes requests 987 ms ThreadPoolExecutor. HTTP/1.1 httpx 735 ms Asyncio. HTTP/2 niquests 470 ms Asyncio. HTTP/2 Simplified APIs Client Average Delay to Complete Notes requests core 643 ms ThreadPoolExecutor. HTTP/1.1 httpx core 550 ms Asyncio. HTTP/2 aiohttp 220 ms Asyncio. HTTP/1.1 niquests core 210 ms Asyncio. HTTP/2 Did you give up on HTTP/2 due to performance concerns? Think again! open up a wide range of possibilities! Multiplexing and response laziness And everything you are witnessing is in fact "Requests"-extended, and you have nothing to learn again to get started. We kept 98% of the test cases from both Requests and urllib3, then extended them to cover newer features. We are looking forward to seeing you at the Niquests repository! Let's say it's a promotional offer, get everything and more for $̶4̶0̶k̶  $0! #1 You depend on Requests? Discover instead. Niquests Drop-in replacement, simple patch needed, tiny effort required. #2 You depend on urllib3? Discover instead. urllib3.future Drop-in replacement, no patch required, atom-like sized effort required. By visiting the GitHub repository and documentation, you will be able to learn more about this, and hopefully make a decisive switch!

The Promise That Was Made Six Years Ago for Requests 3 Is Revived

Recently while trying to integrate a devsecops tool in my pipeline, i was trying to find the GitHub action which would simplify my workflow. Since i could not find it, i have to write the commands inline to run the command. Although it is not a hassle to write it within the script, it would be beneficial to have an action which we could directly call, pass parameters and run the action within the pipeline. In this blog, i will walk you through different steps on how you can create a custom GitHub actions which would satisfy your requirement. The blog will be of 2 parts: Understanding what the GitHub action are Creating your custom GitHub actions GitHub actions: Often when we write pipelines, we would have a set of actions which we would like to perform based on the type of application that we are developing. In order for us to run these actions across the repos in our organization, we would have to copy + paste this code across the repositories, which would make this process error prone and maintenance tussle. It would be better if we take DRY principle of software engineering and apply it to CI/CD world. GitHub action is exactly this principle in practice. We create and host the required action in a certain GitHub public repository and this action is used across the pipeline to perform the action defined in the action. Now that we understand what GitHub action is, lets explore how we can build a custom GitHub action which can help automate set of actions. For this blog, i illustrate it with an example of SBOM enrichment tool Parlay, for which i have built a custom action. Creating Custom Action - A case on Parlay We will be creating our custom action in the following steps: Defining inputs and outputs in action.yml Developing business logic in bash script Dockerize the bash application Test the action Publish it in GitHub action Marketplace Defining inputs and outputs in action.yml To start creating custom action create a custom git repository, clone that repo in your local system and open it up in your favourite code editor. We start by creation a file named actions.yml. This actions.yml defines the inputs that the action would take, the outputs that it would give and the environment it will run. For our use case we have 3 inputs and 1 output. The actions.yml should have following arguments: name: This would be the name of the action, which would be used to search in GitHub action marketplace. Since it would be published in marketplace, it’s name should be globally unique like s3 bucket. description: This describes what your action would do. This would be helpful to identify which action would be the right fit for our use case. inputs: Defines the list of options which would be used within the action. These can be compulsory or optional, which can be defined using “required” argument. In our current use case we are passing 3 arguments, input_file_name, enricher and output_file_name. outputs: This enlists the list of outputs that the action gives. runs: defines the environment in which action will execute , which in our case is docker The action.yml will look something like this: action.yaml

name: "Parlay Github Action"
description: "Runs Parlay on the given input file using the given enricher and outputs it in your given output file"
branding:
icon: "shield"
color: "gray-dark"
inputs:
input_file_name:
description: "Name of the input SBOM file to enrich"
required: true
enricher:
description: "The enricher used to enrich the parlay sbom. Currently parlay supports ecosystems, snyk, scorecard(openssf scorecard)"
required: true
default: ecosystems
output_file_name:
description: "Name of the output file to save the SBOM enriched using the parlay's enricher"
required: true
outputs:
output_file_name:
description: "Prints the output file"
runs:
using: "docker"
image: "Dockerfile"
args:
- ${{ inputs.input_file_name }}
- ${{ inputs.enricher }}
- ${{ inputs.output_file_name }} Developing business logic in bash script Once we have defined the inputs, outputs and environment that we are going to use, we would like to define what we are going to do with those inputs ( basically our logic) in a file. We can either define this in JavaScript or bash. For my current use case, i am using bash. In my current logic, i am going to check if all the inputs are first given, if not the action fails. Once i have these 3 arguments, i am going to construct the command to run the action and save the output in an output file. This file is printed in stdout and formatted using jq utility. #!/bin/bash

Check if all three arguments are provided

if [ "$#" -ne 3 ]; then
echo "Usage: $0 <input> <input_file_name> <output_file_name>"
exit 1
fi

Extract arguments

INPUT_INPUT_FILE_NAME=$1
INPUT_ENRICHER=$2
INPUT_OUTPUT_FILE_NAME=$3

Construct command

full_command="parlay $INPUT_ENRICHER enrich $INPUT_INPUT_FILE_NAME > $INPUT_OUTPUT_FILE_NAME"
eval "$full_command"

Check if the command was successful

if [ $? -eq 0 ]; then
echo "Command executed successfully: $full_command"
cat $INPUT_OUTPUT_FILE_NAME | jq .
else
echo "Error executing command: $full_command"
fi Dockerize the bash application Once we have the bash script ready, we will be dockerizing it using the following script. Whenever we invoke the action, this action which is defined in the bash script runs in an isolated docker container. In addition to the bash script in entrypoint.sh, we would also be adding the the required libraries such as wget, jq and installing parlay binary. Base image

FROM --platform=linux/amd64 alpine:latest

installes required packages for our script

RUN apk add --no-cache bash wget jq

Install parlay

RUN wget https://github.com/snyk/parlay/releases/download/v0.1.4/parlay_Linux_x86_64.tar.gz
RUN tar -xvf parlay_Linux_x86_64.tar.gz

RUN mv parlay /usr/bin/parlay

RUN ls /usr/bin | grep parlay
RUN parlay

Copies your code file  repository to the filesystem

COPY . .

change permission to execute the script and

RUN chmod +x /entrypoint.sh

file to execute when the docker container starts up

ENTRYPOINT ["/entrypoint.sh"] Test the action No amount of software is good without running some tests on it. To test the action, lets first push the code to GitHub. Once pushed, lets define the pipeline in pipeline.yaml file in .github/workflows folder. For the sake of input file, i am using a sample sbom in cyclonedx format and have pushed it to GitHub. In my pipeline.yaml file, i am cloning the GitHub repo and using my action called krishnaduttPanchagnula/parlayaction@main on cyclonedx.json. file on: [push]

jobs:
custom_test:
runs-on: ubuntu-latest
name: We test it locally with act
steps:
- name: Checkout git branch
uses: actions/checkout@v1

  - name: Run Parlay locally and get result
    uses: krishnaduttPanchagnula/parlayaction@main
    id: parlay
    with:
      input_file_name: ./cyclonedx.json
      enricher: ecosystems
      output_file_name: enriched_cyclonedx.json Once the pipeline runs, this should give output in the std-out in pipeline console as follows. Publish it in GitHub action Marketplace Once we have tested the action and that is running fine, we are going to publish it GitHub actions market place. TO do so, our custom app should have globally unique name. To make it more unique we can add icon with our custom to uniquely identify the action in marketplace. symbol and colour Once that is done you would see the button, “Draft a Release”. Ensure that your action.yml file has Name, description, Icon and color. Once you have tick marks, you would be guided to release page where you can mention the title and version of the release. After that, click on “publish release” and you should be able to see your action in GitHub Actions marketplace. Like my content? Feel free to reach out to my for interesting content and productive discussions. LinkedIn

Building & Publishing Your Own Custom GitHub Action in Marketplace

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