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Article / Updated 08-19-2024
The landscape of contract lifecycle management (CLM) is rapidly evolving with the advent of advanced technologies like generative AI (Gen AI). Gen AI is a new iteration of AI whose key benefit is the generation of new content based on the patterns and information it’s learned from existing datasets. Gen AI isn’t a trend or a fad. It’s a new technology that represents a seismic shift in many ways. Organizations are no longer asking if they should embrace AI in CLM but rather how swiftly and effectively they can adapt. The golden age of powerful intelligent technology must be embraced, and you must adapt to advance your business. Integrating these technologies into your CLM can make your CLM an even more powerful tool. AI is like giving machines a brain to think and learn, while Gen AI is about giving them creativity to make new things. When you apply Gen AI to CLM and your contracting processes, it truly expedites your third-party paper review, contract redlining, playbook review, negotiation, and more. In this article, you discover how Gen AI’s powerful use cases are wielded in CLM. Tackling Gen AI Use Cases that Impact CLM Gen AI streamlines contract creation, analysis, and risk assessment, revolutionizing how businesses manage contracts. It’s an exciting development that promises efficiency and accuracy in CLM processes. Within CLM, Gen AI’s prominent use cases include the following: Drafting your contracts with ease: Transform how your organization handles your contracts and their processes. Creating contracts through traditional methods is a time-consuming process that requires highly trained experts, but Gen AI can flip that old way of doing things and start automating your contract drafting. Gen AI does this by learning from your existing contracts and then generating new ones based on your specific business needs and specific inputs that you provide to the tool. Improved adoption: Gen AI becomes a critical co-pilot, working with your users without requiring training. By adding this resource capacity, you can increase efficiency through automating repetitive processes, such as expedited contract review and risk analysis. Your business can do more and free up valuable human resources to focus on strategic initiatives. While Gen AI is still new and slowly being adopted, the benefits are compelling for businesses to adopt Gen AI faster. Voice and text-activated operation: You can easily communicate your objectives through voice commands or by typing, and Gen AI provides guided, click-free actions to efficiently achieve your goals. Intelligent search: Gen AI is able to review large amounts of data quicker than before, allowing for less time spent on searches and more time achieving precise results faster. It can identify key provisions and the existence of specific business terms across agreements swiftly, making audits or merger and acquisitions (M&A) transactions much easier. Advanced business intelligence: Gen AI offers more robust contextual insights and actionable recommendations, including summaries of data that it then can use to drive more data-driven decisions. These AI insights can help you negotiate better terms, optimize contract structures, and align legal strategies with broader business objectives. Proactive support and risk management: Gen AI facilitates smooth collaboration during document review, and it can proactively identify legal risks, offering recommendations to ensure compliance and mitigate potential issues. In today’s culture, minimizing risk and ensuring compliance are paramount. Gen AI can leverage advanced algorithms to systematically analyze agreements, flag potential compliance issues, and ensure adherence to legal standards. With Gen AI’s contract analysis and risk assessment, your organization can make better informed decisions about its contracts. Using Gen AI Use Cases to Strengthen Your Teams AI-powered CLM use cases provide value in diverse scenarios. By implementing AI contract software, all your teams benefit: Legal: Legal departments can automate contract analysis, strategy development, and negotiations. AI also ensures that contracts comply with the latest legal standards and regulations. Procurement: Procurement teams can automate the vendor contract lifecycle and third-party paper reviews. AI streamlines the creation, review, and approval of contracts, ensuring that procurement processes are seamless and compliant. Sales: Sales teams leverage AI to accelerate the contract negotiation process. By expediting redlining and ensuring the accuracy of contract terms, sales professionals can close deals more efficiently and with reduced risks. Compliance: AI helps you monitor and ensure adherence to contractual obligations. By providing real-time insights into contract performance, AI-enhanced solutions help identify and mitigate risks associated with non-compliance. Expanding Gen AI in CLM with Malbek You’re ready to elevate your CLM experience and unleash the power of Gen AI. You want to maximize the power of your digital contracts, but you need a solid partner along the way. In this section, you learn more about Malbek and how the company can help you do just that. To learn more about Malbek, you can also visit one of these resources: • www.malbek.io • www.malbek.io/platform Simplify CLM complexity Malbek empowers its customers with a dynamic, centralized, and fully configurable CLM platform that simplifies your CLM processes. CLM can be complex, but with a trusted partner, you can distill critical insights from contracts for actionable decision-making and peak profitability. Accelerate contracting velocity Build and launch contract and approval processes with ease. From intuitive workflows and seamless approvals to swift contract generation, Malbek’s platform empowers enterprises to navigate contracts with unprecedented speed, ensuring efficiency, compliance, and strategic impact at every turn. Unite global teams and improve collaboration Malbek seamlessly integrates with your favorite business apps, such as Salesforce, Microsoft, SAP, NetSuite, Slack, Coupa, OneTrust, Adobe Sign, DocuSign, and more. By connecting your CLM system with the rest of your business, you can maintain a single source of truth and streamline your operations. Improve decision-making and minimize risk Eliminate time-consuming, manual tasks that take away from high-value objectives. With Malbek AI infused throughout the contracting process, you gain immediate access to timely contextual insights and recommendations to have the greatest impact on your business. AI also streamlines negotiations and shortens review cycles. Download your free copy of Contract Lifecycle (CLM) Management For Dummies, Malbek Special Edition today.
View ArticleArticle / Updated 08-19-2024
The need to fortify your digital assets is crystal clear — or at least it should be. Having robust security depends on integrating diverse security protocols. Utilizing a framework like the Capability Maturity Model (CMM) enables your organization to evaluate how well it’s protected and provides a clear path of progression for improving protection. Managing risk and becoming resilient against prevalent cyber dangers is an increasingly complex task. We live in a mega-connected world, and organizations are assessing and improving their governance maturity step by step to ensure a more secure digital environment for everyone. Applying the CMM approach to SAP application security involves strategically integrating governance maturity best practices into every aspect of your SAP system’s management. The governance and compliance life cycle involves the ongoing management and safeguarding against internal and external threats toward your information systems and data. This cycle includes three stages: getting clean, staying clean, and optimizing. The goal of this cycle is to establish and maintain effective access control measures. Utilizing CMM enhances your security measures through more efficient organization for assessing and improving your risk mitigation efforts. Keep reading for a primer on each stage in the governance and compliance life cycle. Getting Clean In the first stage of the governance and compliance life cycle, the goal is to produce a more risk-free environment by creating more visibility into your risk landscape. You do that in two stages: Identify the scope of your application landscape. What does that mean? You take inventory. This assessment starts with creating a record of all applications within your organization. Identify and document all applications you’re currently using, along with the users with access to each system. Identifying technical debt and user access bloat can help streamline focus to critical applications with key user bases. Execute access risk analysis (ARA) to identify and correct risks in any existing access. Look at your existing access rights and permissions for each application. Determine who has access to what and assess if these permissions are appropriate. Keeping sensitive data safe is more important than ever. Conducting this risk analysis ensures that only the right people can access the appropriate data. When you take the time to conduct a thorough ARA, you’ll see many benefits: Enhanced security and authorized access Effective regulatory compliance Optimized resource utilization Improved data integrity Strengthened reputational standing Reduced operational costs Staying Clean After you’ve done the detective work in the getting clean stage, you stay clean by using an automated process. Here, you start implementing preventative risk checks to ensure that you address the potential security threats when people come, go, and move within your business. Streamlining with access request management Streamlining your access request management efforts centralizes access requests, approvals, and auditing — all within a user-friendly interface. After getting the appropriate approvals, you ensure that the right people have access to the right data. Those approvals can include manager review, role or access owner review, and risk owner approval with any necessary mitigating controls applied prior to provisioning access. Validating user access certifications User access certifications ensure that users’ outdated access rights don’t remain. They also maintain the regular review and revalidation of controls and risks so you stay up to date. Strike the right balance between efficiency and effectiveness in application access certifications. Automating, centralizing, and optimizing the certification process reduces the amount of time it takes to complete user access reviews and enhances their accuracy and impact. Optimizing In the last stage, optimizing, you focus on continually improving your environment after establishing a documented, repeatable, and automated risk management process (that’s in the first two stages: getting clean and staying clean). Automating elevated access management processes The automation of elevated access management processes enables you to optimize how sensitive access is requested, provisioned, and monitored. This approach builds on the access risk analysis results to identify sensitive access and enable end-users to request temporary, time-bound checkout of the access. After approvals are received, access is automatically provisioned and deprovisioned in alignment with the approved timeframe, with change logs available for management review. Ensuring that elevated access processes are efficient and consistent helps your company implement improved risk management, gain auditor approval, and improve end-user satisfaction. Monitoring and quantifying risk exposure You can’t eliminate every risk, and you may go crazy trying. Set predefined thresholds for your risk exposure so you can identify the risks that threaten those limits. That way, you’re only tracking and reporting on all quantifiable risks that actually occurred instead of the thousands of risks that never happened, which wastes everyone’s precious time. Executing continuous controls monitoring and risk quantification produces efficient and consistent processes to help save time, increase productivity, lower costs, and implement approved designs. Addressing threat detection Focus on what matters. Security and operations teams often lack visibility and understanding of the data that can indicate potential architecture-level security threats — threats that may harm your critical business applications. But with a continuous monitoring system, you can reap the benefits of threat detection and response capabilities, such as Continuous threat detection coverage for thousands of threat indicators Automatic updates with the latest threat information, patch availability, and ongoing research Rapid response to threats with resolution guidance so you can reduce investigation response times Enriching your security information and event management (SIEM) applications with detailed threat detection data How Pathlock Can Help When dealing with risk, Pathlock provides customers with a comprehensive set of modular capabilities. Designed to seamlessly work together, the available tools reduce potential risk by following the get clean, stay clean, optimize methodology. To learn more about this practice, visit www.pathlock.com/sap. To find out more about Pathlock and SAP application security, check out SAP Application Security For Dummies, Pathlock Special Edition. Head to get.pathlock.com/direct-ebook-sap-application-security-for-dummies-special-edition for your free e-book and start planning your SAP application security strategy to get clean, stay clean, and optimize.
View ArticleCheat Sheet / Updated 08-07-2024
Photoshop CS6 retains all it had in previous versions —, and provides new features to help you with your tasks, such as a darker, more immersive, User Interface, true vector Shape layers, the Oil Paint filter, Adaptive Wide Angle correction, Content-Aware Move tool, new brush tips, and more. None of it is hard to learn, and all of it will help enhance both your productivity and creativity.
View Cheat SheetCheat Sheet / Updated 07-27-2024
When you're podcasting, you have to keep track of a lot of components. Besides checking that the hardware is operating properly, your software is capturing audio without fail, and you're keeping track of your latest episode’s analytics, you also have to keep straight all the minute details. Ensure that your podcasts are well-received by adhering to technical standards for artwork and audio. Check out some of the podcasting directories where you want to have your podcasts listed. And if you’re doing a podcast interview, a little prep time can save a lot of embarrassment.
View Cheat SheetArticle / Updated 06-26-2024
Capacitors are among the most useful of all electronic components. And capacitance is the term that refers to the ability of a capacitor to store charge. It's also the measurement used to indicate how much energy a particular capacitor can store. The more capacitance a capacitor has, the more charge it can store. Capacitance is measured in units called farads (abbreviated F). The definition of one farad is deceptively simple. A one-farad capacitor holds a voltage across the plates of exactly one volt when it's charged with exactly one ampere per second of current. Note that in this definition, the "one ampere per second of current" part is really referring to the amount of charge present in the capacitor. There's no rule that says the current has to flow for a full second. It could be one ampere for one second, or two amperes for half a second, or half an ampere for two seconds. Or it could be 100 mA for 10 seconds or 10 mA for 100 seconds. One ampere per second corresponds to the standard unit for measuring electric charge, called the coulomb. So another way of stating the value of one farad is to say that it's the amount of capacitance that can store one coulomb with a voltage of one volt across the plates. It turns out that one farad is a huge amount of capacitance, simply because one coulomb is a very large amount of charge. To put it into perspective, the total charge contained in an average lightning bolt is about five coulombs, and you need only five, one-farad capacitors to store the charge contained in a lightning strike. (Some lightning strikes are much more powerful, as much as 350 coulombs.) It's a given that Doc Brown's flux capacitor was in the farad range because Doc charged it with a lightning strike. But the capacitors used in electronics are charged from much more modest sources. Much more modest. In fact, the largest capacitors you're likely to use have capacitance that is measured in millionths of a farad, called microfarads and abbreviated μF. And the smaller ones are measured in millionths of a microfarad, also called a picofarad and abbreviated pF. Here are a few other things you should know about capacitor measurements: Like resistors, capacitors aren't manufactured to perfection. Instead, most capacitors have a margin of error, also called tolerance. In some cases, the margin of error may be as much as 80%. Fortunately, that degree of impression rarely has a noticeable effect on most circuits. The μ in μF isn't an italic letter u; it's the Greek letter mu, which is a common abbreviation for micro. It's common to represent values of 1,000 pF or more in μF rather than pF. For example, 1,000 pF is written as 0.001 μF, and 22,000 pF is written as 0.022 μF.
View ArticleCheat Sheet / Updated 06-17-2024
Google Workspace offers a huge number of keyboard shortcuts that not only enable you to navigate the app interfaces quickly but also let you easily invoke many app features and settings. Here you see some of the more useful shortcut common to the Google Workspace apps, as well as some handy shortcuts you can use with Gmail and Calendar. Do you need to memorize them all? Don't be silly. But do read through the lists, as you'll probably find two or three that you'll find useful every day.
View Cheat SheetCheat Sheet / Updated 06-17-2024
Your MacBook keyboard puts efficiency at your fingertips. Startup keys, shortcut key combinations, and special function keys invite you to perform different tasks with a single touch — from turning up the sound volume to deleting selected text.
View Cheat SheetArticle / Updated 05-31-2024
At work as well as in your personal life, you’ve almost certainly been bombarded with talk about generative artificial intelligence (AI). It’s all over the mainstream media, in trade journals, in C-suite conversations, and on the front lines of whatever work your organization does. There’s no escaping it. The stories make AI sound so miraculous that, in fact, you could be forgiven for thinking it must be a bunch of hype. But the reality is, generative AI can truly be transformational for businesses. You can leave it for textbooks to fill in the details about what AI is and how it works. But in a nutshell, AI relies on building large language models (LLM) with the help of machine learning (ML). AI trains on vast amounts of data, immerses itself, and learns from the data in ways not unlike how humans learn (but a whole lot faster, and ingesting far, far more data). Notice that the title of this article refers to generative AI. This AI doesn’t just make recommendations — it actually creates new data or content, or generates insights by using the power of natural language processing (NLP) and ML. Tackling many tasks What can generative AI really do for your business? What business problems can it solve? For starters, it’s a fantastic headache remedy. Some of the business headaches generative can cure include Production bottlenecks: Got processes that are stuck and unable to keep up with the demands of customers? Generative AI breaks through bottlenecks by automating processes, improving efficiency, facilitating faster and better human decisions, increasing output, maximizing resources, and speeding up development cycles. Tedious tasks: Generative AI can tackle mundane and tedious tasks, freeing up human brainpower for real value-creating initiatives that your people will find more fulfilling. Inconsistencies and noncompliance: Generative AI creates consistency across your organization’s communications and enforces compliance with internal and external standards. It’s easy for discrepancies and errors to pop up and multiply — generative AI can identify these issues, offer insights and recommendations, and even automatically fix them. Training hurdles: Generative AI helps new hires onboard and get up-to-speed quickly by generating training materials and job simulations. Personalized instruction can fill knowledge gaps. Customer-service struggles: When equipped with information-retrieval solutions, the technology can answer questions quickly and can even handle some customer interactions entirely on its own. It also improves live human interactions by empowering agents and creating instant conversation summaries. Exploring the use cases What generative AI can do for your organization boils down to three primary areas: Creating: This is what it sounds like — using AI to come up with something new. It also may mean editing or revising something that has already been created, by a person or AI, perhaps by turning it into a different format. For your marketing team, a generative AI tool can write the first draft of an ebook about a new product, or create a press release or search engine optimization (SEO)-ready web content. It can come up with a knowledge base article on the latest product feature to help the support team, or a best-practices management article for learning and development. It can help the human resources (HR) team write a job description, making sure it’s doing so in inclusive language. The product development team will love how it ingests and crunches a list of features and bug tickets to come up with release notes. Analyzing: This means taking an in-depth look at content of some kind and generating insights. Generative AI can spot trends or reach conclusions of some sort, perhaps even analyze sentiment amid a batch of customer feedback. Marketing may ask the AI platform to process a webinar recording and summarize the key takeaways. The support team can have it scour customer support survey responses to come up with insights on areas of improvement to consider. Generative AI can help learning and development conjure up some FAQs by analyzing and categorizing what’s in an internal wiki. AI can listen to a recording of a job interview and create a summary for a recruiter. Product developers can have it study customer feedback to find insights for what new features to prioritize. Governing: The govern use case includes a focus on compliance, looking for language that runs afoul of legal and regulatory rules. It finds incorrect terminology and statements and works to prevent data loss and global compliance problems. This type of AI work also means checking for factual accuracy, detecting claims that are wrong and suggesting replacement wording. Marketers can use it to find errors and violations in advertising copy, and for HR, AI can flag non-inclusive language in employee communications, then make suggested revisions. The learning and development team may use it to ensure training materials are compliant with industry certification requirements and other vital standards. Making it happen Many generative AI tools are out there right now, and they’re ready for the masses. Countless people subscribe to platforms such as ChatGPT and Google’s Gemini, and Meta AI is now built right into social media platforms. For the use cases outlined in the preceding section, though, it’s essential to seek an enterprise-grade, full-stack generative AI platform rather than a consumer-targeted AI assistant. Your organization will want a platform that can be truly customized to your needs and integrated with your operations, trained on accurate data that’s relevant to your business and industry, and fully in line with your security and compliance requirements. So, do it yourself? That’s not such a great plan, either. Building your own AI stack can be slow and expensive. Look for a partner that can abstract the complexity so you can benefit from the AI-first workflows, not get bogged down building and maintaining infrastructure. When picking a platform, follow these tips: Keep pace with your organizational needs. Get a tool that can deploy custom AI apps in a snap for any use case, including digital assistants, content generation, summarization, and data analysis. Seek the right model. Palmyra LLMs from Writer, for example, are top-ranked on key benchmarks for model performance set by Stanford’s Holistic Evaluation of Language Models. Connect to your company knowledge. An LLM alone can’t deliver accurate answers about information that’s locked inside your business knowledge bases. For that, you need retrieval-augmented generation (RAG), which is basically a way to feed an LLM-based AI app company-specific information that can’t be found in its training data. Check out writer.com/product/graph-based-rag for more information. Be sure it’s fully customizable. You need consistent, high-quality outputs that meet your organization’s specific requirements, and a general consumer tool can’t do that. You also must have AI guardrails that enforce all your rules and standards. Integrate the tool. To fit into your flow, AI apps need to be in your people’s hands however they’re working. You need an enterprise application programming interface (API) and extensions that’ll build tools right into Microsoft Word and Outlook, Google Docs and Chrome, Figma, Contentful, or whatever else your people love to use. Deploy it your way. Look for options that include single-tenant or multi-tenant deployments. Get things done quickly. Look for a platform that can have you up and running in days, not months. Wouldn’t you rather spend your time adopting than tediously building? Keep it secure. Here’s an incredibly vital area where consumer tools can leave your enterprise at great risk. You need an LLM that’s secure, auditable, and never uses your sensitive data in model training. You’ll lose a lot of sleep if your tool doesn’t comply with the standards your organization must follow, whether that means SOC 2 Type II, HIPAA, PCI, GDPR, or CCPA. Find a tool that manages access with single-sign on (SSO), multifactor authentication, and role-based permissions. Writer is the full-stack generative AI platform for enterprises. It empowers your entire organization to accelerate growth, increase productivity, and ensure compliance. For more information on how to transform work with generative AI, download Generative AI For Dummies, Writer Special Edition.
View ArticleArticle / Updated 05-30-2024
For each web coding issue identified by a validator, you need to determine what course of action to take. Although some culprits that repeatedly crop up are easy to fix, such as missing alt text and <noscript> tags, you’re bound to find coding issues that completely baffle and stump you. For instance, if you get an error message that reads XML Parsing Error: Opening and ending tag mismatch: br line 52 and body, it might be difficult to figure out what that means, let alone why it was caused and how you should fix it. As a strategy then, try to fix the issues within the code from the top down, as they’re listed in the validation results, because sometimes fixing one issue resolves another. With the XML parsing error, that issue might disappear when you correct for an omitted closing element on a <br /> tag listed earlier in the error results. The best way to find out how to code better and make fewer mistakes before validation testing is to make lots of honest mistakes and figure out how to correct them on your own. Most often, you can fix noncompliant code by hand or with the help of a good HTML editor. To help you identify some of the more common coding mistakes, here several code issues along with suggestions about how to fix them. Problem Solution alt text attribute missing from <img> tag Add the alternative text attribute, either with or without a description, as in <img src="images/logo.gif" width="150" height="150" alt="Pete’s Pizza"> <img src="images/flourish.gif" width="200" height="150" alt=""> . <noscript> tags missing from code Add <noscript> tags below each instance when JavaScript is present in in-line JavaScript or at the end of the content before the closing body tag. Between the <noscript> tags, insert HTML content (text, graphics, media files, and so on) that describes the function of the JavaScript and, when appropriate, how visitors can access the information revealed by it, as shown here: <script language="JavaScript" src="bookmark.js" type="text/javascript"></script><noscript>The JavaScript used on this page provides a quick link that allows visitors to automatically bookmark this page. As an alternative, please use your browser’s Bookmark This Page feature.</noscript> Flashing or flickering element(s) detected, such as animated GIFs, Java applets, and other multimedia plug-ins Adjust the speed of any animations to avoid causing the screen to flicker with a frequency between 2 Hz and 55 Hz. Animations that exceed these two measures may cause seizures in visitors with photosensitive epilepsy. No DOCTYPE specified Add a valid DOCTYPE above the opening <head> tag. No HTTP charset parameter specified This special meta tag specifies the character set used in the HTML code. Some HTML editors include it automatically when generating new blank web pages. If validation finds that this tag is missing from your HTML or XHTML code, insert the following code by hand: <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> . For HTML5, insert <meta charset="utf-8"> . No <title> tag specified Add a unique title between <title> tags in the head area on each page. No <meta> tags specified Add meta keywords and meta description tags to the head of each page. These can be identical on every page on the site. If desired, you may also add additional meta tags as needed. No Robots tags specified Add the Robots <meta> tag in the head of the page to instruct web spiders and robots whether to index the page and follow any hyperlinks, such as <meta name="Robots" content="All"> . Deprecated <font> tags detected Move all the presentation markup of the HTML (page, fonts, tables, links, and so on) to an external CSS file and remove all <font> tags and HTML and inline formatting attributes. Deprecated table height attribute detected Control table cell heights, when necessary, with CSS styles. Style attributes detected in the opening <body> tag Move body attributes, like margin attributes and background page color, to a BODY tag redefine style in an external CSS file. type attribute not specified for JavaScript or CSS Add the type="text/css" attribute for <style> tags and the type="text/javascript" attribute for <script> tags: <style type="text/css" ><script type="text/javascript"> . Entity name used instead of entity number Change the entity name to an entity number, such as using $#169; instead of © to create the copyright symbol (c). No background color attribute was specified for a CSS style that specifies text color Provide each style that contains a text color attribute with an attending background color attribute. The background color should match, or closely match, the background color upon which the text will display on. When you’re finished identifying and adjusting all the noncompliant code identified by the validation tools, and have fixed everything that needed fixing, move on to the retesting and acceptable failure phase of the testing process.
View ArticleArticle / Updated 05-30-2024
The success of your DevOps initiative relies heavily on following the process, but it’s also important to use the right tools. Selecting a cloud service provider isn’t an easy choice, especially when DevOps is your driving motivation. GCP (Google Cloud Platform), AWS (Amazon Web Services), and Azure have more in common than they do apart. Often, your decision depends more on your DevOps team’s comfort level with a particular cloud provider or your current stack more than the cloud provider itself. After you’ve decided to move to the cloud, the next decision is to decide on a cloud provider that fits your DevOps needs. Here are some things to consider when evaluating cloud providers with DevOps principles in mind: Solid track record. The cloud you choose should have a history of responsible financial decisions and enough capital to operate and expand large datacenters over decades. Compliance and risk management. Formal structure and established compliance policies are vital to ensure that your data is safe and secure. Ideally, review audits before you sign contracts. Positive reputation. Customer trust is absolutely key. Do you trust that you can rely on this cloud provider to continue to grow and support your evolving DevOps needs? Service Level Agreements (SLAs). What level of service do you require? Typically cloud providers offer various levels of uptime reliability based on cost. For example, 99.9 percent uptime will be significantly cheaper than 99.999 percent uptime. Metrics and monitoring. What types of application insights, monitoring, and telemetry does the vendor supply? Be sure that you can gain an appropriate level of insight into your systems in as close to real-time as possible. Finally, ensure the cloud provider you choose has excellent technical capabilities that provide services that meet your specific DevOps needs. Generally, look for Compute capabilities Storage solutions Deployment features Logging and monitoring Friendly user interfaces You should also confirm the capability to implement a hybrid cloud solution in case you need to at some point, as well as to make HTTP calls to other APIs and services. The three major cloud providers are Google Cloud Platform (GCP), Microsoft Azure, and Amazon web Services (AWS). You can also find smaller cloud providers and certainly a number of private cloud providers, but the bulk of what you need to know comes from comparing the public cloud providers. Amazon Web Services (AWS) As do the other major public cloud providers, AWS provides on-demand computing through a pay-as-you-go subscription. Users of AWS can subscribe to any number of services and computing resources. Amazon is the current market leader among cloud providers, holding the majority of cloud subscribers. It offers a robust set of features and services in regions throughout the world. Two of the most well-known services are Amazon Elastic Compute Cloud (EC2) and Amazon Simple Storage Service (Amazon S3). As with other cloud providers, services are accessed and infrastructure is provisioned through APIs. Microsoft Azure Before Microsoft launched this cloud provider as Microsoft Azure, it was called Windows Azure. Microsoft designed it to do just what the name implies — serve as a cloud provider for traditionally Windows IT organizations. But as the market became more competitive and Microsoft started to better understand the engineering landscape, Azure adapted, grew, and evolved. Although still arguably less robust than AWS, Azure is a well-rounded cloud provider focused on user experience. Through various product launches and acquisitions — notably GitHub — Microsoft has invested heavily in Linux infrastructure, which has enabled it to provide more robust services to a wider audience. Google Cloud Platform (GCP) The Google Cloud Platform (GCP) has the least market share of the three major public cloud providers but offers a substantial set of cloud services throughout nearly two dozen geographic regions. Perhaps the most appealing aspect of GCP is that it offers users the same infrastructure Google uses internally. This infrastructure includes extremely powerful computing, storage, analytics, and machine learning services. Depending on your specific product, GCP may have specialized tools that are lacking (or less mature) in AWS and Azure. Finding DevOps tools and services in the cloud Literally hundreds of tools and services are at your disposal through the major cloud providers. Those tools and services are generally separated into the following categories: Compute Storage Networking Resource management Cloud Artificial Intelligence (AI) Identity Security Serverless IoT Following is a list of the most commonly used services across all three of the major cloud providers. These services include app deployment, virtual machine (VM) management, container orchestration, serverless functions, storage, and databases. Additional services are included, such as identity management, block storage, private cloud, secrets storage, and more. It’s far from an exhaustive list but can serve as a solid foundation for you as you begin to research your options and get a feel for what differentiates the cloud providers. App deployment: Platform as a Service (PaaS) solution for deploying applications in a variety of languages including Java, .NET, Python, Node.js, C#, Ruby, and Go Azure: Azure Cloud Services AWS: AWS Elastic Beanstalk GCP: Google App Engine Virtual machine (VM) management: Infrastructure as a Service (IaaS) option for running virtual machines (VMs) with Linux or Windows Azure: Azure Virtual Machines AWS: Amazon EC2 GCP: Google Compute Engine Managed Kubernetes: Enables better container management via the popular orchestrator Kubernetes Azure: Azure Kubernetes Service (AKS) AWS: Amazon Elastic Container Service (ECS) for Kubernetes GCP: Google Kubernetes Engine Serverless: Enables users to create logical workflows of serverless functions Azure: Azure Functions AWS: AWS Lambda GCP: Google Cloud Functions Cloud storage: Unstructured object storage with caching Azure: Azure Blob Storage AWS: Amazon S3 GCP: Google Cloud Storage Databases: SQL and NoSQL databases, on demand Azure: Azure Cosmos DB AWS: Amazon Relational Database Service (RDS) and Amazon DynamoDB (NoSQL) GCP: Google Cloud SQL and Google Cloud BigTable (NoSQL) As you explore the three major cloud providers, you notice a long list of services. You may feel overwhelmed by the hundreds of options at your disposal. If, by chance, you can’t find what you need, the marketplace will likely provide something similar. The marketplace is where independent developers offer services that plug into the cloud — hosted by Azure, AWS or GCP. The table below lists additional services provided by most, if not all, cloud providers. Common Cloud Services Service Category Functionality Block storage Data storage used in storage-area network (SAN) environments. Block storage is similar to storing data on a hard drive. Virtual Private Cloud (VPC) Logically isolated, shared computing resources. Firewall Network security that controls traffic. Content Delivery Network (CDN) Content delivery based on the location of the user. Typically utilizes caching, load balancing and analytics. Domain Name System (DNS) Translator of domain names to IP addresses for browsers. Single Sign-On (SSO) Access control to multiple systems or applications using the same credentials. If you’ve logged into an independent application with your Google, Twitter or GitHub credentials, you’ve used SSO. Identity and Access Management (IAM) Role-based user access management. Pre-determined roles have access to a set group of features; users are assigned roles. Telemetry, monitoring and logging Tools to provide application insights on performance, server load, memory consumption and more. Deployments Configuration, infrastructure and release pipeline management tools. Cloud shell Shell access from a command-line interface (CLI) within the browser. Secrets storage Secure storage of keys, tokens, passwords, certificates and other secrets. Message Queues Dynamically scaled message brokers. Machine Learning (ML) Deep learning frameworks and tools for data scientists. IoT Device connection and management.
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