A hard refresh is a way of clearing the browser’s cache for a specific page, to force it to load the most recent version of a page. Sometimes, when changes are made to the website, they don’t register immediately due to caching. A hard refresh will usually fix this, though occasionally completely clearing the cache is necessary. How to do hard refresh on various browsers? Chrome: Quick hard refresh can be done by using the following short cut keys Windows/Linux: Hold down Ctrl and click the Reload button. Or, Hold down Ctrl and press F5. just open the Chrome Dev Tools by pressing F12. Once the chrome dev tools are open, just right click on the refresh button and a menu will drop down. This menu gives you the option of doing a hard refresh, or even clearing the cache and do a hard refresh automatically. Mac: Hold ⇧ Shift and click the Reload button. Or, hold down ⌘ Cmd and ⇧ Shift key and then press R. Mozilla Firefox and Related Browsers: Windows/Linux: Hold the Ctrl key and press the F5 key. Or, hold down Ctrl and ⇧ Shift and then press R. Mac: Hold down the ⇧ Shift and click the Reload button. Or, hold down ⌘ Cmd and ⇧ Shift and then press R. Internet Explorer: Hold the Ctrl key and press the F5 key. Or, hold the Ctrl key and click the Refresh button.

An API is short for Application Programming Interface The term API is an acronym, and it stands for “Application Programming Interface.” Think of an API like a menu in a restaurant. The menu provides a list of dishes you can order, along with a description of each dish. When you specify what menu items you want, the restaurant’s kitchen does the work and provides you with some finished dishes. You don’t know exactly how the restaurant prepares that food, and you don’t really need to. Similarly, an API lists a bunch of operations that developers can use, along with a description of what they do. The developer doesn’t necessarily need to know how, for example, an operating system builds and presents a “Save As” dialog box. They just need to know that it’s available for use in their app. This isn’t a perfect metaphor, as developers may have to provide their own data to the API to get the results, so perhaps it’s more like a fancy restaurant where you can provide some of your own ingredients the kitchen will work with. But it’s broadly accurate. APIs allow developers to save time by taking advantage of a platform’s implementation to do the nitty-gritty work. This helps reduce the amount of code developers need to create, and also helps create more consistency across apps for the same platform. APIs can control access to hardware and software resources. APIs Make Life Easier for Developers Let’s say you want to develop an app for an iPhone. Apple’s iOS operating system provides a large number of APIs—as every other operating system does—to make this easier on you. If you want to embed a web browser to show one or more web pages, for example, you don’t have to program your own web browser from scratch just for your application. You use the WKWebView API to embed a WebKit (Safari) browser object in your application. If you want to capture photos or video from the iPhone’s camera, you don’t have to write your own camera interface. You use the camera API to embed the iPhone’s built-in camera in your app. If APIs didn’t exist to make this easy, app developers would have to create their own camera software and interpret the camera hardware’s inputs. But Apple’s operating system developers have done all this hard work so the developers can just use the camera API to embed a camera, and then get on with building their app. And, when Apple improves the camera API, all the apps that rely on it will take advantage of that improvement automatically. This applies to every platform. For example, do you want to create a dialog box on Windows? There’s an API for that. Want to support fingerprint authentication on Android? There’s an API for that, too, so you don’t have to test every different Android manufacturer’s fingerprint sensor. Developers don’t have to reinvent the wheel over and over. APIs Control Access to Resources APIs are also used to control access to hardware devices and software functions that an application may not necessarily have permission to use. That’s why APIs often play a big role in security. For example, if you’ve ever visited a website and seen a message in your browser that the website is asking to see your precise location, that website is attempting to use the geolocation API in your web browser. Web browsers expose APIs like this to make it easy for web developers to access your location—they can just ask “where are you?” and the browser does the hard work of accessing GPS or nearby Wi-Fi networks to find your physical location. However, browsers also expose this information via an API because it’s possible to control access to it. When a website wants access to your exact physical location, the only way they can get it is via the location API. And, when a website tries to use it, you—the user—can choose to allow or deny this request. The only way to access hardware resources like the GPS sensor is through the API, so the browser can control access to the hardware and limit what apps can do. This same principle is used on modern mobile operating systems like iOS and Android, where mobile apps have permissions that can be enforced by controlling access to APIs. For example, if a developer tries to access the camera via the camera API, you can deny the permission request and the app has no way of accessing your device’s camera. File systems that use permissions—as they do on Windows, Mac, and Linux—have those permissions enforced by the file system API. A typical application doesn’t have direct access to the raw physical hard disk. Instead, the app must access files through an API. APIs Are Used For Communication Between Services APIs are used for all kinds of other reasons, too. For example, if you’ve ever seen a Google Maps object embedded on a website, that website is using the Google Maps API to embed that map. Google exposes APIs like this to web developers, who can then use the APIs to plop complex objects right on their website. If APIs like this didn’t exist, developers might have to create their own maps and provide their own map data just to put a little interactive map on a website. And, because it’s an API, Google can control access to Google Maps on third-party websites, ensuring they use it in a consistent way rather than attempting to messily embed a frame that shows the Google Maps website, for example. This applies to many different online services. There are APIs for requesting text translation from Google Translate, or embedding Facebook comments or tweets from Twitter on a website.

What are the advantages of using Kong for API management? Kong has several advantages compared to other API management platforms and tools. Community favorites include: Open-Source: No black box. For enterprise or free usage, Kong is entirely open-source, always. Based on Nginx: Kong is embedded in Nginx and benefits from its amazing proxying performances. Customizable: Write plugins to cover all your architecture use-cases. Data Ownership: Kong and its underlying datastore run on your servers. Easy to scale: All Kong nodes are stateless. Spawning new nodes in your cluster is very easy. Integrations: Many plugins integrate with popular third-party services in the microservices world. Because Kong is open-source and highly customizable, you’ll have full control over your architecture. It’s perfectly suited for managing internal microservice traffic as well as partners or public entities. Internal Internal API traffic that connects microservices built inside your organization can originate from teams in different geographic regions, but belong to the same entity. Internal microservices and APIs can be deployed either on bare metal or a cloud provider. Partners Partners usage is when your software has to communicate with a mission critical third party microservice to offer its key features (and vice-versa). For example a credit card company relies on at least one bank to offer its service. In the past most of those connections would happen via an ESB, nowadays all you need is an API Gateway. Public Public is when you offer your API with a self-serve onboarding process. Any developer can get a key and access/consume your services. An example of this model is Facebook’s Graph API. Common features are authentication, rate limiting, and billing tiers if it’s a paid API. For more info visit - https://konghq.com/

Containerisation is a method for efficiently deploying applications – with the overall aim being to enable applications to run anywhere on any machine. The concept is inspired by the shipping industry, where the introduction of standardised shipping containers and handling equipment simplified the transportation of everything from coffee beans to clothing. Goods can now be loaded, transferred, shipped over distance and then unloaded efficiently using a single process. Software containerisation uses these same underlying principles. A container is a standardised structure which can store and run any application, and can be transported from server to server. Each application is stored within its own container, which holds an image of all components required for it to run – the code, settings, systems tools and libraries etc. This creates an isolated operating environment which can run on any server.

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Kubernetes is a vendor-agnostic cluster and container management tool, open-sourced by Google in 2014. It provides a “platform for automating deployment, scaling, and operations of application containers across clusters of hosts”. Above all, this lowers the cost of cloud computing expenses and simplifies operations and architecture. Before we explain what Kubernetes does, we need to explain what containers are and why people are using those. A container is a mini-virtual machine. It is small, as it does not have device drivers and all the other components of a regular virtual machine. Docker is by far the most popular container and it is written in Linux. Microsoft also has added containers to Windows as well, because they have become so popular. The best way to illustrate why this is useful and important is to give an example. Suppose you want to install the nginx web server on a Linux server. You have several ways to do that. First, you could install it directly on the physical server’s OS. But most people use virtual machines now, so you would probably install it there. But setting up a virtual machine requires some administrative effort and cost as well. And machines will be underutilized if you just dedicate it for just one task, which is how people typically use VMs. It would be better to load that one machine up with nginx, messaging software, a DNS server, etc. The people who invented containers thought through these issues and reasoned that since nginx or any other application just needs some bare minimum operating system to run, then why not make a stripped down version of an OS, put nginx inside, and run that. Then you have a self-contained, machine-agnostic unit that can be installed anywhere. Now containers are so popular than they threaten to make VMs obsolete, is what some people say. Docker Hub But making the container small is not the only advantage. The container can be deployed just like a VM template, meaning an application that is ready to go that requires little or no configuration. There are thousands of preconfigured Docker images at the Dockerhub public repository. There, people have taken the time to assemble opensource software configurations that might take someone else hours or days to put together. People benefit from that because they can install nginx or even far more complicated items simply by downloading them from there. For example, this one line command will down, install, and start Apache Spark with Jupyter notebooks (iPython): docker run -d -p 8888:8888 jupyter/all-spark-notebook As you can see it is running on port 8888. So you could install something else on another port or even install a second instance of Spark and Jupyter. On the Need for Orchestration Now, there is an inherent problem with containers, just like there is with virtual machines. That is the need to keep track of them. When public cloud companies bill you for CPU time or storage then you need to make sure you do not have any orphaned machines spinning out there doing nothing. Plus there is the need to automatically spin up more when a machine needs more memory, CPU, or storage, as well as shut them down when the load lightens. Orchestration tackles these problems. This is where Kubernetes comes in. Kubernetes Google built Kubernetes and has been using it for 10 years. That it has been used to run Google’s massive systems for that long is one of its key selling points. Two years ago Google pushed Kubernetes into open source. Kubernetes is a cluster and container management tool. It lets you deploy containers to clusters, meaning a network of virtual machines. It works with different containers, not just Docker. Kubernetes Basics The basic idea of Kubernetes is to further abstract machines, storage, and networks away from their physical implementation. So it is a single interface to deploy containers to all kinds of clouds, virtual machines, and physical machines. Here are a few of Kubernetes concepts to help understand what it does. Node A node is a physical or virtual machine. It is not created by Kubernetes. You create those with a cloud operating system, like OpenStack or Amazon EC2, or manually install them. So you need to lay down your basic infrastructure before you use Kubernetes to deploy your apps. But from that point it can define virtual networks, storage, etc. For example, you could use OpenStack Neutron or Romana to define networks and push those out from Kubernetes. Pods A pod is a one or more containers that logically go together. Pods run on nodes. Pods run together as a logical unit. So they have the same shared content. They all share the share IP address but can reach other other via localhost. And they can share storage. But they do not need to all run on the same machine as containers can span more than one machine. One node can run multiple pods. Pods are cloud-aware. For example you could spin up two Nginx instances and assign them a public IP address on the Google Compute Engine (GCE). To do that you would start the Kubernetes cluster, configure the connection to GCE, and then type something like: kubectl expose deployment my-nginx –port=80 –type=LoadBalancer Deployment A set of pods is a deployment. A deployment ensures that a sufficient number of pods are running at one time to service the app and shuts down those pods that are not needed. It can do this by looking at, for example, CPU utilization. Vendor Agnostic Kubernetes works with many cloud and server products. And the list is always growing as so many companies are contributing to the open source project. Even though it was invented by Google, Google is not said to dominate it’s development. To illustrate, the OpenStack process to create block storage is called Cinder. OpenStack orchestration is called Heat. You can use Heat with Kubernetes to manage storage with Cinder. Kubernetes works with Amazon EC2, Azure Container Service, Rackspace, GCE, IBM Software, and other clouds. And it works with bare-metal (using something like CoreOS), Docker, and vSphere. And it works with libvirt and KVM, which are Linux machines turned into hypervisors (i.e, a platform to run virtual machines). Use Cases So why would you use Kubernetes on, for example, Amazon EC2, when it has its own tool for orchestration (CloudFormation)? Because with Kubernetes you can use the same orchestration tool and command-line interfaces for all your different systems. Amazon CloudFormation only works with EC2. So with Kubernetes you could push containers to the Amazon cloud, your in-house virtual and physical machines as well, and other clouds. In Conclusion So we have answered the question what is Kubernetes? It is an orchestration tool for containers. What are containers? They are small virtual machines that run ready-to-run applications on top of other virtual machines or any host OS. They greatly simplify deploying applications. And they make sure machines are fully-utilized. All of this lowers the cost of cloud subscriptions, further abstracts the data center, and simplifies operations and architecture. To get started learning about it, the reader can install MiniKube to run it all on one machine and play around with it.

Elasticsearch is a distributed, real-time, search engine/document store. Elasticsearch is built on an open source foundation (Apache Lucene) and allows users to gather data from a wide variety of sources and in numerous formats, analyze this data, and then uses Kibana to visualize it in real time. Elasticsearch + Kibana can help with business insights throughout an organization.

Kibana is a dream come true for any entrepreneur or business that wants to visualize data in a fast, efficient, accurate manner. The program offers a great deal of freedom by allowing users to select the manner in which data is displayed. Even those who aren’t sure of the best way to display data can easily figure out an ideal configuration thanks to the interactive visualizations this program offers. Kibana offers histograms, line graphs, pie charts, sunbursts, geospatial map displays, and other common visualization options along with the option for one to create his or her own unique visualization option. Kibana also makes it possible for users to spot and analyze relationships in Elasticsearch data and detect and explore anomalies in Elasticsearch data with machine learning features. As an added benefit, those who are responsible for analyzing and compiling data can easily share the information they have gathered with supervisors, colleagues, and customers thanks to Kibana’s dashboard sharing options and the program’s ability to allow dashboards to be inserted into internal wiki or website pages. Alternatively, one can send out the URL to the dashboard in question or even export important data in PDF or CSV format. It comes with its own Node.js server so users don’t have to install additional code or invest in new, updated infrastructure to run the program. Kibana’s open source nature ensures that the program will continue to improve and evolve with the times, providing business owners with new features and amenities as and when needed. As the program has been downloaded millions of times, it has also been carefully analyzed by users from all walks of life, providing ObjectRocket with valuable insight into glitches, bugs, and improvement ideas.

Unfortunately, many database programs don’t provide the high-quality visualization a modern company needs in order to stay on the cutting edge of its field. MySQL Mongo and other popular alternatives either don’t offer the tools needed to visualize the data provided by the programs, are too expensive, or require large changes to your data. Thankfully, there is a reliable, open source program that specializes in providing great data visualization in various convenient formats. Kibana, a tool for visualizing data in Elasticsearch, is great at providing visualization of every bit of data that a business would need to see at any given time.

Life is busy and a result, people forget to do things sometimes. However, some tasks should not be delayed and that includes renewing a website’s SSL/TLS certificate(s). SSL certificates allow a person, computer or organization to securely exchange information, such as bank account details, logins, and credit card numbers, over the web. So you can imagine why having up-to-date certificates are particularly important for businesses such as retailers – and the problems that can arise when companies let them lapse. This includes sites being marked as unsecure and blocked by browsers, leading to reduced visitor trust and, of course, abandoned shopping carts. Example site with expired SSL Certificate in Chrome. But do you really want to run that risk? The answer is no, and yet forgetting to renew certificates happens more frequently than you think, and it’s not restricted to any one industry.