Hello my folks, welcome to the fascinating world of Gitlab. Nowadays, this has become a real use of every programmer/developer. You know every programmer needs some space to situate their projects and code which have been made by them. Today, in this Gitlab mainstream, we are going to elaborate on the SSH key in this you will learn about the fact of how can you create, manage with the SSH key.

What is an SSH key?

Let’s get started with SSH. SSH stands for secured shell and now, comes to the place of uses what is the use? This is used for authentication, by setting SSH you can connect to the Gitlab server without using a username and password each time. Once, you will set the SSH key so, you may skip using your username and password each time to connect your Gitlab server.

How to set up an SSH key in Gitlab?

Let see, what will have to do here?

Step 1: Run command SSH- keygen

You will have to run this command. If you are on MacBook, you can put terminal and will run the command SSH-keygen. You may enter the location or file where you have to save the key and press the enter key. So, you will have your ssh key created. This was on mac.

On mac. – run command on terminal

On windows – use putty or Git bash

If you are on windows then you can use an application or a client called putty, it is ssh client that you can use on windows or you can also use Git bash to run the command. If you will have installed it before, you will go to your windows system and search for Git bash. And you will adjust fonts if you will need them. So, you will run $ ssh-keygen then it will ask you to enter the file do you want to save it then again, you will press the enter so, it will have been created. You will go to your folder from local disk to .ssh in that two files will be created in the id_rsa and id_rsa.pub

Now, step no.2 will be

Step 2: log in to Gitlab account

                        Go to an account >> Settings >> SSH keys

So, you will go to your Gitlab and log in. you will sign in to your account if you will go to your account or profile at the top right. You would find settings there and if you will go in that. So, you will find an option for SSH key then you will click on that. You would add the content of your file id_rsa.pub. If you will go to the file and open it with any text editor like notepad and notepad++, you can copy the entire thing from there. And you will paste it to the SSH key. Suppose, you want to give a name to your key then you can add that name in the title option and switch to add key. So, you will see that everything would be edited there. There would be a key that you can use to authenticate and log in to the Gitlab server.

Now, here step no.3 is

Step 3: copy contents of id_rsa.pub and add key

Step 4: verify SSh key is added

 You have been seen. This is how you can add an SSH key to your Gitlab. I wish this all will be very useful for you.

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Welcome to the introductory part of Gerrit. In this article, we would cover all the prominent spaces regarding Gerrit, why use Gerrit? About a code review, and some basic Gerrit terminology.

What is Gerrit?

Let’s start with the introduction of Gerrit? Now, take a brief action on Gerrit, it is a source code management (SCM) platform that is like a GitHub, bit bucket, or team foundation server in that it manages multiple repositories, tags, branches, and other git resources for multiple projects. Its version control system is GIT. It provides you with an optional code review workflow and access control on git repositories that store changes before they are committed to repository branches. It is a free open-source development and is used by Google to develop an android operating system. So, it’s free and available, you can easily download it from google.

Why use Gerrit?

Now, we have a second option that comes one after the other why are we using it? There are several patterns or behaviors through which you can judge and manage your possibilities. It provides a lightweight framework for reviewing commits before they are accepted into the GIT repository. One more thing, it is performing that captures the team discussion on code changes through change reviews and is persistent and auditable. It allows flexibility to control team workflows to ensure all code changes go through quality assurance checks. And it manages access controls for GIT repositories, and its web-based interface. After this kind of advancement, developers don’t need any additional tools to interact with Gerrit.

What is a code review?

A code review is a process of quality assurance that involves other reading and checking source code to offer suggestions, recommendations, or approvals performing a code review into two stages the first is the latest commit pushed as a change, and the second is kept in a staging area for a review. And under the second stage that will be merged into the repository when approved. Along with code review consist of various functions like comments, approvals/rejections, code quality verification, additional patches to fix issues, the difference between versions, dependencies, and the changing status.

Gerrit terminology

Here is some Gerrit terminology that may come up:

• Change: A change represents a single commit that is under review. Particular change is identified with a change-Id.

• Patch set: Patch sets are subsequent commits that are attempting to amend an existing change.

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Hello folks, welcome to the world of computer programming. So, if you’re a software engineer and either student or fresher. And you do anything work-related to computer, doing any coding. So, you will have listened must about the GIT. What is GIT? Today, we talk about that stuff. Without doing any further delay, let’s start this from my article.

Who is the developer of GIT?

Let’s see the first thing, the developer of that GIT whose name was “Linus Torvalds”. This is an individual who’s made our Linus kernel. It is also open-source. Right, it is our open source and in that, anybody can give their contribution. Linus is open-source that means anyone can contribute to it, so there are thousands of people who are contributing to it.

What is the Linux kernel?

 You will have listened in that for this you shouldn’t want any license, doing download any source code in this. After that, you have to do modification, do modification, and put any features in that. You can deploy this on the server. If they feel good then will add in features. You can do like as. GIT is also our open-source. Now, what is the need of GIT?

Importance of GIT

 If the talks come of about git so, what is the need of it? Suppose you’re doing a project, we are five people that are doing projects. After that, suppose we have to do code exchange then we will do mail to code, mailed it, or uploaded in drive. First, drive where we will have put all codes. Suppose, there is a place where any other person has sent code to me then will happen far away. We will do a download and set of it. Like be any system, whose every code do automatically, everything sets itself to happen. Automatically code merge on that place. Therefore, our use of git. If we use of git then that difficulties are coming, even five people come difficulty in working, they things will happen far away. How much no. of employees and teams can use. Our task will be easy. It is also doing our communication and code management easy. our GIT is based on source code management (SCM). It means that those manages of our source code, keep code in the right way. Therefore, we say distributed version control system to this.

What is distributed version control system?

What does it mean? Distributed version control system means that every one version of, you have made the first file then the second file, all of these versions those we will do changes in the file that changes they do keep save. We can return to the previous change. we see this in more detail, suppose we do a project in that some features or chat application, we make of that. So, what will we do, when first happens start, for starting we will release it put some minimum features. I have in forward, some changes come in that code. Suppose, we have to add new features then new features come.   

Importance of version control system

Those my previous software such as chat application in that new features drops then something version will make, you will have listened to some version like version 1.2, 1.3 and 2.0. What is it happens? This is updation in code, we make that code or even any software are making so, that in time to time updation happens. The responsibility to keep care of all updations of GIT. Like new features read and after, read some more features. The version in that they will be changing. Like some more features have been released, while in that time version 1.1 will have made, again read some more features then version 1.2 has come and read more features so, version 1.3 has come. Suppose, these all are codes of mine, all have been put in my local machine. For saving all of them, we shall have stored to them so, what we will do? We will store of all in storage. Now, that will store in that when we will do updations then suppose we are running version v1.3, my client says to me that we shouldn’t want version v1.3, we should want version v1.2. So, we will move in storage then we will download that file from there and after this, we will upload it. Nothing like as it doesn’t practical. Suppose, one huge project of mine then we will don’t like it as continuously we will move in storage, dropbox, or google drive, we will download from there and after that upload it. It is so long process and doesn’t practically exist, Codes can be misguided. Now, you, whenever little bit changes come to like even semicolon problems come then how much errors come. Therefore, for this, we will use GIT. We use GIT because it will have to care of all these versions. Suppose, one of my machines, we’re working on that machine, and the server is situated nearby you and there will place in that we will say repository or remote repository. Those on the server, we call him remote repository because they’re put in the server, there we don’t do changes and we do changes when we do download. That repository will have made in sever, we will do download. Those we will do download in the machine, we will call him remote repository and same as another user has downloaded it, they will also work. They all will upload their own changes, again they will upload changes in the server. Repository, you can understand like as it is the only folder in which we have some projects.

What is trunk-based development?

Our GIT runs on trunk-based development. Who says trunk-based development? Trunk-based development means we can make branches. So, what do branches means? Suppose, mine has version v1.3. That is one of the stable versions and has been uploaded, software is running then our team will work in the latest version, my team is working on version v2.0. Now, those of your stable version comes any bug, one user says that something bug in this. When the bugs come in this so, it will report. When it will report then what will we do? We will not do like as we will not leave version 2.0, we will also work on that. Now, through GIT, we can make branches, we can work simultaneously on GIT through the branch.

What is the master branch?

Let’s look, how we do this. Like one of mine branch, by default we take changes, it happens in master branch. Suppose, doing changes, commit it. We are doing in the master branch, again doing changes, commit it. When we do commit then we add any version or features, again doing changes, commit it. Your version is similar there. Suppose, there is version v1.3, the bug has come in this. We are working own in what, we are also working on version v2.0. Definitely, we have to do work on the latest version and we also have to do fixes bugs of v1.3. So, what we will do? We will make a branch on there, there will make one branch where we can manage version 2.0 and coding also. This 1.3 version will move to differ. Like a tree, you can work on different versions through branching.

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New Delhi, June 24 (IANS) Amazon Web Services on Thursday expanded its partnership with Salesforce making it easy for users to use the full set of Salesforce and AWS capabilities together to quickly build and deploy powerful new business applications that accelerate digital transformation.

The partnership will drive customer value through new and enhanced unification between AWS and Salesforce products.

“For more than five years, our customers have benefitted from a tight relationship between AWS and Salesforce,” Andy Jassy, CEO of Amazon Web Services, said in a statement.

“Now, we are taking the partnership to the next level by integrating our offerings so developers using both AWS and Salesforce can build unified applications much faster and simpler than ever before,” Jassy added.

Developers will now be able to build and launch custom applications that extend the power of both platforms by connecting Salesforce data and workflows natively into their solutions running on AWS and make it easy for Salesforce developers to integrate AWS data and workflows into their Salesforce applications.

Salesforce will also embed AWS services for voice, video, artificial intelligence (AI) and machine learning (ML) directly in new applications for sales, service, and industry vertical use cases.

With these new offerings, customers can purchase out-of-the-box solutions directly from Salesforce and then consume the integrated AWS services on a pay-as-you-go basis.

“With this partnership, we are significantly simplifying developers’ lives and empowering them to develop applications however they want, from wherever they want globally, at any scale,” Jassy said.

Previously, significant custom integration code was often required for customers that wanted to combine AWS and Salesforce capabilities for their applications.

These new offerings will enable customers to use AWS and Salesforce services together seamlessly through new, unified platforms.

The companies have also collaborated on new low-code tools to help customers innovate and build applications that connect data in real-time between Salesforce applications and AWS services.

Customers can now innovate faster with pre-built applications that combine AWS and Salesforce Customer 360, making it easier for organisations to seamlessly deploy AWS’s voice, video and AI services natively with Salesforce business applications.

Amazon Web Services (AWS), an Amazon.com company and Salesforce, has announced a significant expansion of their global strategic partnership that will make it easy for customers to use the full set of Salesforce and AWS capabilities together to quickly build and deploy powerful new business applications that accelerate digital transformation.

The partnership will drive customer value through new and enhanced unification between AWS and Salesforce products. Developers will now be able to build and launch custom applications that extend the power of both platforms by connecting Salesforce data and workflows natively into their solutions running on AWS and make it easy for Salesforce developers to integrate AWS data and workflows into their Salesforce applications.

Salesforce will also embed AWS services for voice, video, artificial intelligence (AI) and machine learning (ML) directly in new applications for sales, service, and industry vertical use cases. With these new offerings, customers can purchase out-of-the-box solutions directly from Salesforce and then consume the integrated AWS services on a pay-as-you-go basis.

“For more than five years, our customers have benefitted from a tight relationship between AWS and Salesforce. Now, we are taking the partnership to the next level by integrating our offerings so developers using both AWS and Salesforce can build unified applications much faster and simpler than ever before,” said Andy Jassy, CEO, Amazon Web Services.

“With this partnership, we are significantly simplifying developers’ lives and empowering them to develop applications however they want, from wherever they want globally, at any scale,” added Jassy.

“This is a milestone partnership for the technology industry, and one that will enable our customers to experience an even more powerful Salesforce Customer 360 and achieve a new level of success in their business. With a more strongly unified Salesforce and AWS platform, our customers around the world can create a single source of truth across sales, service, marketing, and commerce, and achieve success from anywhere,” said Marc Benioff, Chair and CEO, Salesforce.

As Kermit the Frog famously sang, “it’s not easy being green,” yet it’s critical for our planet’s survival that we figure it out.

Ironically, the very tech we’re using to help in that effort could be making things worse. A 2019 survey conducted by Informa revealed that while datacentres use 3 percent of the world’s electricity, energy efficiency was only number four on IT leaders’ priority lists when creating a new datacentre. Yet those datacentres run the artificial intelligence and machine learning being used to understand and combat greenhouse gas emissions.

The price of AI
A 2019 report from the University of Massachusetts found that training and tuning a deep neural network can create the equivalent CO2 emissions of those produced in anything from just over two years of an average American’s life to more than seventeen years’ worth (depending on the model). Another study, also from 2019, found that the computations needed for deep learning research increased by 300,000x (no, that is not a typo!) between 2012 and 2018.

Going green
In an effort to combat the runaway emissions, at the Microsoft BUILD virtual conference last week, Microsoft, Accenture, GitHub, and ThoughtWorks announced that they have teamed up as founding members of the Green Software Foundation, a non-profit organization with the mission of creating an ecosystem of people, standards, tools, and best practices for building green software. It is part of the Joint Development Foundation Projects, an affiliate of the Linux Foundation.

What is green software
So what is green software? Sajay Podder, technology sustainability innovation lead at
Accenture explained. “The term green software relates to the design, development and use of software, and is a term we use to help companies consider the carbon emissions related to software with the intent to keep emissions as low as possible. It is important because while digital technologies are key to protecting the environment, that proliferation is also resulting in software’s growing carbon footprint,” he said. “But we also realize that it’s a new field, requiring new skills, new standards, new training and new tooling.” He said that when he discovered that a team at Microsoft was also looking at the issues, they began discussions about a collaboration, and the Green Software Foundation was born.

It’s all about the community, added Jeff Sandquist, corporate vice president of developer relations at Microsoft. Developers want to build apps that consider their impact on the

climate, and no one company or individual can do it alone. “For that to happen, we need to understand how to build green software, and folks need tools, and they need the knowledge to become qualified wherever they are in the world, on a really important matter,” he said. “And so our goal with this is to really establish best practices, set up standards, really work together. We’ll work together to be able to make sure that we create a great community of green software practitioners.”

Erica Brescia, chief operating officer at GitHub, said that GitHub joined with the goal to make it easier for developers to use and contribute to the global climate solution by empowering them with the right visibility and the right tools, so they can create and maintain green software themselves.

For ThoughtWorks, said Elise Zelechowski, global head of diversity, equity and inclusion, sustainability and social

change, sustainability and climate change mitigation is a priority. “We believe that the tech sector has a really important role to play here in taking action on climate,” she said. “We’re increasingly seeing our clients coming to us for thought leadership tools and advice on this. And while there’s a desire to take action, it’s not always clear where to start for them. ThoughtWorks is very excited to be joining the foundation to help define these standards to help organizations adapt and implement new tools, and to work with government, academia, nonprofits, and all of you and build this community to shape the vision of the work.”

Cloud identity access management company Okta Inc. today revamped its developer experience with features that include new integrations and documentation in a general release that’s free for up to 15,000 monthly active users.

The updates are part of Okta’s new Starter Developer Edition that will provide developers tools to embed the company’s Okta authentication, authorization and user management into enterprise cloud applications at scale.

The company announced the product revamps during the first day of Oktane21, the company’s three-day virtual developer conference.

“Okta’s vision is to enable everyone to safely use any technology,” said Diya Jolly, chief product officer at Okta. “Developers are foundational to bringing that vision to life, and it’s our goal to make every piece of the development process easier with Okta. Developers can ramp up at no cost with the Starter Developer Edition.”

Okta Identity Cloud plays an instrumental role in the secure deployment and use of applications in the cloud, especially when it comes to role- and permission-based management. Knowing who is accessing information, how it’s being accessed and controlling how it’s being accessed is critical for security.

“Our reimagined developer experience delivers tools that seamlessly work with developers’ toolchains across whatever hybrid, cloud, or multicloud environment they’re building on,” said Jolly. “If developers need to do something with identity, they can do it with Okta.”

With new application programming interfaces, developers will find their footing with Okta faster than before, and this can be done with a redesigned console for all Okta customers that the company says will help deliver a faster time to market and full application lifecycle support.

The company has provided what it calls “Auth For All,” secure applications support and further identity infrastructure across a multitude of popular languages so that developers can get running in their preferred code faster than ever before with enhanced documentation.

Sample applications are also included in the developer portal with highly detailed documentation including Go, Java, JavaScript, Python, VueJS, React Native and Spring Boot.

In addition, Okta has included integrations for DevOps, SecOps and API Security tooling. This means that developers can quickly prototype Okta’s identity capabilities across numerous use cases including continuous integration and delivery or roles and management when securing applications, APIs and infrastructure.

New integrations include Heroku to automate identity across CI/CD pipelines, Kong to protect APIs and an updated Okta Terraform provider, which can replicate Okta configurations across environments.

The new Okta Starter Developer Edition and integrations are generally available starting today on Okta’s developer portal page along with enhanced documentation, sample applications and implementations.

Ready to start a brand new career path? Whether you lost your job during the COVID-19 pandemic or you’re just hoping to make a big change in 2021, if you’ve been thinking about transitioning into a developer career The Complete Git and GitHub for Beginners Bootcamp Bundle can help. The three courses included would typically set you back $600, but they’re available now in this bundle for 95 percent off at just $24.99.

You can master the essentials and tricky parts of Git and GitHub from the comfort of your couch with The Complete Git and GitHub for Beginners Bootcamp Bundle. Web developer and coding instructor Kalob Taulien, an instructor with a 4.6 out of 5 star rating who has over two decades of experience developing websites and working with startups, will walk you through the first course that’s included, Git Essentials: The Step-by-Step Guide to Git and GitHub Mastery. This 4.6 out of 5 star course will school you on the daily git workflow that all big developers use, teaching you how to create and use a remote repository, learn staging, committing and pushing files and resolve rebase conflicts and learn how to rebase on GitHub.

Shubham Sarda, a developer and digital marketer with a 4.3 out of 5 star rating, is the next instructor included in the bundle, teaching you the course Git and Github for Beginners: Practical Bootcamp. Learn hands-on, practical ways to work with Git and GitHub with Git Commands, Collaboration, Cheat-Sheet and more within this hour of instruction in this 4.2 out of 5 star course. And finally, the 4.4 out of 5 star rated Zenva Academy will walk you through the last course, Git and GitHub Version Control and Collaboration. This class will teach you about the uses of version control and how to use Git commands to change a project’s ecosystem.

After a year of full-time remote work, software engineers and team leaders are perfecting daily work routines developed in this solitary setting and simultaneously looking ahead to what the future will bring. Managers say that building new communication habits was key to making the shift to remote work. Development teams had to make adjustments to daily work flows as well, all while working longer hours and dealing with an increased risk of burnout as a result.

Jacqui Vreeland, recruiting manager at Emergent Software, noticed that the pandemic forced many developers to think about the long-term stability of their job.

“Too many people were working in a way that was, frankly, unsustainable before and when the world switched to being fully remote, many people have had to reevaluate what they truly love about their job in the first place when so many in-person benefits have been stripped away,” she said.

Meanwhile, for recruiters and hiring managers, filling open positions is as challenging as ever, even when the candidate pool now reaches worldwide.

Here’s a look at how the job landscape, daily routines and communication skills have changed over the last 12 months as well as what the future may look like.

How the pandemic has changed the job market
David Moise, president of Decide Consulting, is a software developer who now runs an IT staffing and recruiting firm. He said he noticed that managers, directors and vice presidents in IT were let go at a higher rate than other roles while hands-on engineers were not. He said some companies expected the developer to suddenly do their job plus the former manager’s job while other companies realized that the extra load had to be dispersed among everyone.

Moise said that letting go of managers meant that making decisions about digital transformation strategies was that much harder. Many companies threw out the old technology roadmap to adapt to the demands of the pandemic, but in some cases there were no managers to make decisions about software and tech stacks, he said.

Moise said that hiring is harder now in part because required skill sets are longer and more specific.

“Just a couple of years ago if you are looking for a developer, you had 20 options on skills and you needed to match 10,” he said. “Now you have 75 and you need to match 25.”

Mary Lee Olson, head of talent at Rollbar, said that companies should expand their hiring scope to the entire world.

“Expanding your geographical reach to find talent presents its own, new challenges but it’s a pivot companies must make,” she said.

Rollbar helps fix critical errors by using real-time alerts and AI-assisted workflows.

Gabrielle Hendryx-Parker, CEO of software consultancy company Six Feet Up, said hiring has become somewhat easier thanks to a truly global job market. She has employees in 15 time zones. One disadvantage is that such a large pool puts stress on compensation packages as smaller developer teams compete in a global marketplace, creating discrepancies based on company size, reputation and location.

“Over time, I expect compensation differences to level out, but for now, it’s common to see candidates asking for up to 3 times what you are expecting to pay for a technical position,” she said.

Adjusting the daily routine
For some development teams, the overnight shift to 100% remote work was a catalyst for improvements. Jay Leaf-Clark, head of IT at Dashlane, said the shift to remote work forced his company to change support and maintenance models within IT.

“We’ve rapidly adapted to an already incoming, and frankly, welcomed new way of managing IT that has up until now, been slowed in most organizations due to the battle between IT leaders and leadership on allocating the budget and time to make these dreams a reality,” he said.

Leaf-Clark said that this transformation will have long-term benefits as this new display of agility proves that his department can handle whatever the future has in store.

Alberto Giorgi, director of engineering at Tray.io, a low-code workflow automation company, said that remote work inspired his team to take a new look at internal processes from prioritizing asynchronous and written communication, ensuring a strong meeting etiquette to finding new ways to collaborate more effectively and increase the team’s overall productivity.

Giorgi said that demand for proper IT support for DevOps practitioners in particular increased significantly in the early days of the pandemic as companies faced a growing backlog in their deployment and development processes.

Another challenge was that the spike in Zoom meetings meant that developers lost time that would have been dedicated to writing code, which reduced overall efficiency, he said.

“To combat these challenges, many development teams took to the dual strategy of using API integrations and workflow automation to increase productivity,” he said.

The key to this approach is making sure that tools for important use cases such as source code control, continuous integration and delivery, and issue tracking can seamlessly pass data to each other.

“To streamline processes, smart devops teams looked to API integrations to connect their tech stack to avoid having to copy and re-copy issue logs and other data across multiple platforms,” he said.

Giorgi said automation has allowed his team to focus more resources on strategic projects while streamlining away time-consuming manual work.

Building new communication habits
Many workers miss the spontaneous chats in the breakroom or taking lunch with colleagues. For developers, not being able to walk over to a colleague’s cube to ask a question was a more serious problem. Alex Yelenevych, co-founder and chief marketing and product officer at CodeGym, an online platform for learning Java, said that developers had to adjust to the lack of in-person communication.

“Sometimes teammates didn’t understand some tasks in writing without further explanation, even a video call didn’t help,” he said. “We just started to formulate our tasks more precisely.”

Hendryx-Parker of Six Feet Up said that the pandemic has made internal communication critical.

“Having to deal with isolation made it all the more obvious that soft skills are actually essential in development to keep high performing teams going,” she said.

Yelenevych said that as people started to work longer hours, professional burnout began to manifest itself much earlier and deeper.

Hendryx-Parker said that by the fall, she saw developer burnout due to lopsided work/life balance.

“Working at home was especially challenging for developers with children, as they were putting longer hours while at the same time acting as educators and caretakers,” she said.

Yelenevych sees a hybrid schedule with some days at home and some days at the office as the optimal approach.

Red Hat, Inc., the world’s leading provider of open source solutions, and GitHub, the software collaboration platform home to more than 50 million developers, today announced extended collaboration between the two companies, emphasizing Red Hat OpenShift through GitHub Actions and more. Red Hat is adding Red Hat GitHub Actions to the GitHub Marketplace, bringing GitHub’s DevOps, continuous integration/continuous development (CI/CD) and developer workflow automation tools to Red Hat OpenShift. This further refines the application development capabilities of the world’s leading enterprise Kubernetes platform with GitHub Actions, adding greater freedom to how developers can build and deploy applications on Red Hat OpenShift across the open hybrid cloud.

GitHub has become nearly synonymous with developer tools and serves as the home for many popular software projects, including open source communities like the Linux kernel and Kubernetes. Using GitHub’s built-in powerful, flexible CI/CD solution, GitHub Actions puts automation directly in the developer path, making it possible for nearly any event in a GitHub repository, like a pull-request or issue comment, to trigger workflows that can build and deploy applications across an IT environment and automate nearly any process in the software lifecycle. Organizations often want to bring the familiar, collaborative experience of GitHub to their developers, as well as provide a more secure, common platform for working with open source communities. This makes the availability of tooling like Actions on enterprise Kubernetes platforms a crucial component for the future of IT.

Red Hat OpenShift now supports GitHub Actions, enabling organizations to standardize and scale their use of open, standardized developer toolchain components like Quay, Buildah, or Source-to-Image (s2i). This helps to meet developers where they are and provides greater choice and flexibility to OpenShift customers in how they build and deploy applications. The new GitHub Actions for Red Hat OpenShift, along with existing actions on GitHub Marketplace and action workflows, make it possible to achieve simple as well as complex application workflows on Red Hat’s enterprise Kubernetes platform using an extensive array of standards-based tools.

As part of the collaboration, GitHub has also joined OpenShift Commons, a community that helps drive connections and collaboration across the OpenShift ecosystem. Beyond Actions and GitHub Marketplace, Red Hat and GitHub are also exploring self-hosted GitHub runners for OpenShift. A runner is the combined application and server that hosts a job and carries out the steps for an Action workflow. Self-hosting runners gives IT teams more control and flexibility over the hardware and software included as part of their environment. This means that end users can increase memory size, enable GPUs, or install software that may only be available locally as part of a tailored application development experience.

The addition of GitHub Actions builds on Red Hat OpenShift’s robust developer experience, which includes OpenShift GitOps (based on ArgoCD) and OpenShift Pipelines (based on Tekton). OpenShift is now able to provide a complete solution for DevOps and GitOps practitioners as they seek to build, deploy, and maintain cloud-native applications.

Availability

GitHub Actions on Red Hat OpenShift are available now via GitHub Marketplace.

Supporting Quotes

Joe Fernandes, vice president, Products, Cloud Platforms, Red Hat

“Red Hat OpenShift is more than a Kubernetes platform for deploying cloud-native applications; it’s a powerful, flexible foundation for developers to build the latest and greatest applications. By adding GitHub Actions to our existing set of DevOps and GitOps capabilities and by working with GitHub to further refine and expand the developer experience, we aim to make Red Hat OpenShift the most complete cloud-native development platform available, one built on the open standards of Kubernetes and Linux containers and backed by the vast expertise of Red Hat.”

Jeremy Epling, vice president of Product Management, GitHub

“GitHub is the home for all developers, and we’re excited to expand our collaboration with Red Hat to accelerate software development within the enterprise. Combining Red Hat OpenShift with GitHub Actions will help our customers more securely automate nearly all their cloud-native development and DevOps workflows, providing a unified experience across the hybrid cloud that is exceptionally friendly to developers, security and operations teams. We’re looking forward to working more closely with Red Hat, and helping our customers deliver better and faster with open source software and standards.”

2020 has brought a seemingly endless amount of problems, but software developers have responded with solutions. Despite all of this year’s change, one thing remains true: Software is being used in a multitude of ways to tackle some of the world’s most pressing challenges. And developer creativity is helping to progress exciting new areas of technology innovation; specifically, internet of things (IoT) and edge computing, 5G and autonomous vehicles.

The barriers to entry for development in these new areas has lowered in recent years. It’s now just as cost-effective to get started on an IoT hardware project as it is to build a web or mobile application and learning how to get started with the hardware is as easy as searching for “how to raspberry pi” on YouTube. The issue is, once you get started and begin shipping units, you’ll come to realize that developer tooling for emerging areas of technology is lagging behind the curve. The market for tools that monitor and test web and mobile applications is healthy and diverse, but tooling for IoT/edge, 5G and autonomous vehicles has yet to see the same surge. And as projects become more complex, how do you keep up with both automated and manual testing? How do you ensure that firmware updates don’t “brick” devices out in the field? Fixing a bug in a website can be deployed in a few minutes, and in some cases, customers won’t even notice. Shipping new versions of software to devices is a little more tricky.

One of the biggest areas of change in this sector is innovation in CPUs. For the longest time, engineers could write software that worked on either Intel- or AMD-based CPUs—and the majority of software that exists today can run on either of those platforms. However, IoT devices make heavy use of the newest player in the CPU space: Arm. Most people don’t realize it, but anyone with either an Android or iPhone smartphone in their pocket already has a device running an Arm processor. Arm processors work especially well in low-power environments, such as those you find in IoT. The biggest problem that engineers face with this new CPU is that the majority of developer tooling isn’t suited for them. It’s all been built with either Intel or AMD CPUs in mind.

We are only beginning to realize the possibilities of these emerging technologies—and developers will be the ones paving the way, building the solutions that will power our future. As they continue to evolve and create new unstructured data sources, companies will need to invest in the tools that enable developer teams to not only keep pace but also innovate.

The tools I’m referring to will be the ones that let developers seamlessly deliver software across any environment—from IoT devices to private or public cloud to embedded systems to 5G. CI/CD platforms are one way to accomplish this. But there’s a misconception when it comes to selecting CI/CD providers: that developers must choose between the security of on-premises environments and the scale of public cloud. A hybrid cloud approach to CI/CD is an effective way to test and deploy software at scale without compromising the security of a company’s most valuable resource: its source code.

For so many teams and companies, this was the year of throwing out the playbook and rewriting the road map. The window of opportunity for true software innovation has never been more open. Whether it be in IoT, 5G or autonomous vehicles, developers are moving fast to change the world. They need developer tooling that will help them deliver on those ambitions.

Let’s face it, as the demands of writing software increase, more pressure is put on devs to be as productive as humanly possible. And with this demand, the landscape for being a developer has never been more challenging.

With increased responsibilities and technology options, developers are asked to not just worry about the code they write, but all other aspects of the application development life cycle.

The plethora of tools at a developer’s disposal has also made developer responsibilities even more challenging. Determining what tools and platforms to develop on and with have caused a “too many options” scenario in lots of cases.

GitHub To The Rescue
As challenging as this landscape is, there are solutions. One thing that’s abundantly clear, GitHub is the place where developers go to learn and collaborate with the community.

GitHub has enabled developers to have the power of the entire Open-Source community at their disposal and the freedom to learn from the work of others to better themselves as a developer. GitHub has unveiled many tools aside from hosting source code to make the ecosystem as comfortable as possible.

One of those tools I am fired up about is “GitHub Actions”. Look, as you all know, I’m a DevOps guy , and I think about DevOps every time I put on my developer hat. I believe that no matter the app, if you are going to send it somewhere that isn’t your local machine, that app deserves to have some continuous integration and continous delivery (CI/CD), simple as that.

The question becomes, if my code is already in GitHub, what is the easiest way to hook CI/CD into my app? The answer is GitHub Actions.

GitHub Actions allow us to easily configure custom workflows, using a bounty of existing community-created workflows to fulfill the needs of our app. It isn’t just starting from scratch as there are workflows to do nearly everything, and your goal is to just build your Action in the way YOU need it. With GitHub Actions, getting your app to the Cloud is super easy.

But What About Developing My App?
Talking about where it goes before I write and compile my app seems non-sensical, but I believe that thinking about these things early will allow us to choose the technology/tools we need to be most productive.

In my opinion, one of the best tools to write the code that powers our software is Visual Studio Code. Visual Studio Code is a cross-platform, multi-language editor that provides extensive extensibility to create the perfect environment to write code.

Whether you are writing express apps in Node.js, multi-thread highly scalable applications in Go, or writing cutting-edge modules on your Raspberry Pi with Python, VS Code gives you the ability to work in the way that benefits you the most.

The best part, VS Code offers deep integrations with GitHub, which allows you to clone/pull/push your repositories as well as manage your work on issues and pull requests, without leaving the editor, HOW COOL IS THAT! Once you have your repo in VS Code, the editor gives you access to an oversupply of Open-Source extensions to do everything from configure your experience, down to your font and background of choice. Nearly anything is possible with VS Code, and with first-class GitHub support, it truly is one of the best options.

What Should Host My App?
With our code being built in VS Code and stored in GitHub and DevOps’d with GitHub Actions, the last thing we need to think about is now what?

Personally, I think Azure is the ultimate Cloud for GitHub. There is no other Cloud that best enables developers to be the most productive, and with integrations to VS Code AND GitHub, you truly have “best of breed” capabilities at your disposal.

Let’s start with VS Code Integrations, and boy there are a ton of them. Existing extensions enable developers to seamlessly connect to their Azure tenants and have full management capability of the resources in their subscriptions, including creation, scaling, configuration, debugging and if we want, even deployment!

Microsoft has built an extension pack called “Azure Tools” which includes extensions to manage every major Azure resource type as well as Azure CLI support AND Docker. There are also other extensions published by Microsoft that connect and manage nearly every Azure Resource. This means when new features come to the platform, they will be coming to the Microsoft published extensions.

Azure Loves GitHub
Finally, it is safe to say that Azure loves GitHub and the integrations are plentiful. From Azure Portal authentication with GitHub Ids, to individual services interfacing with GitHub (one great example of this is Azure Static Web Apps, which allow CI/CD to be configured on creation of the resource).

There is no better integration story between GitHub and Azure than “GitHub Actions for Azure” a set of pre-built GitHub Action workflows that helps you automate your app’s story on Azure, from deployment to monitoring and everything in between.

The team has built over 30 of these workflows and they are documented in a way that you will be able to use them without hesitation. One of my favorite examples is container image scan which allows you to scan the container images you are using for known vulnerabilities as well as linting to ensure you are using best practices.

GitHub + Visual Studio Code + Azure ensures you as a developer can just trust the tools and get your work done. There are tons of more features that I didn’t talk about here, so please take a look at some of the resources below to get started enhancing your developer productivity.

Background: Two Announcements from Redis

Towards the end of 2019, Redis made two announcements aimed squarely at its developer community. The first was the release of RedisInsight, a free GUI tool that lets developers manipulate, visualise, and analyse data stored in Redis without leaving a graphical interface. The second was the launch of a Redis Developer Certification Programme, designed to formally recognise proficiency in building applications with Redis.

Howard Ting, Redis’s CMO at the time, spoke to DevOps Online about the reasoning behind both initiatives and shared his broader views on database architecture trends and the DevOps mindset.

Why a Developer Certification?

The certification was conceived as a way to bring consistency and credibility to the Redis ecosystem. Ting explained the core motivation:

“It’s about bringing more consistency and credibility for Redis developers. When someone is looking to hire a developer, they will know that with this certification, they have at least a bare minimum level of credibility and expertise.”

Howard Ting, CMO, Redis

The exam covers the topics Redis considers foundational for effective development:

• Data structures – understanding Redis’s native types (strings, hashes, lists, sets, sorted sets, streams, and more)
• Data modelling – how to structure data appropriately for Redis rather than forcing relational patterns onto a key-value store
• Best practices – patterns for reliability, key naming, eviction policies, and client usage
• Database setup and optimisation – configuration tuning for a given use case

The exam is 90 minutes long, taken online, and is proctored to ensure the credential carries genuine weight. Redis indicated the programme would evolve based on community feedback over time.

Industry Trend: From One Database per Thousand Apps to One App with Many Databases

Ting offered a striking framing of how the database landscape has changed in the microservices era:

“20 years ago we had one database supporting 1,000 applications. Now we have one application that might have 1,000 databases.”

Howard Ting, CMO, Redis

This inversion reflects the polyglot persistence approach that has become common in cloud-native architecture. As microservices decompose monolithic applications into independent, loosely coupled services, each service can—and often should—choose the database type best suited to its specific data access patterns. A session store might use Redis, a product catalogue might use a document database, and financial ledger data might live in a relational database, all within a single application.

The explosion of Kubernetes as a deployment platform has accelerated this trend, making it operationally feasible to run many different stateful services side by side at scale.

Performance Engineering: Design for Elasticity First

On the question of performance and debugging, Ting’s advice centred on understanding the elasticity profile of an application before choosing where data should live:

• Highly elastic applications – workloads with large, unpredictable usage spikes need databases that can absorb sudden load. In-memory databases such as Redis are well-suited here because reads and writes happen at memory speed.
• Predictable, steady-state applications – workloads with consistent throughput have more flexibility in storage tier selection, and the cost advantages of disk-backed storage become more relevant.

Ting also pointed to an emerging two-tier data model that he expected to become standard:

• Hot tier – fast-moving, frequently accessed data stored in DRAM or fast SSDs. Persistent memory (technologies that behave close to DRAM speed at lower cost per GB) was highlighted as a growing option here.
• Cold/archival tier – slower-moving or historical data stored on traditional disk or flash-backed databases in the back end.

The practical takeaway for developers designing data-intensive, highly personalised, or real-time reactive applications is to start with an in-memory database as the primary data layer rather than retrofitting one later.

Optimising Data Management: Pick the Right Tool and Plan Long Term

Ting distilled data management advice into two principles:

1. Pick the right tool for the job. No single database is optimal for every access pattern. Evaluate whether your data’s characteristics—size, access frequency, query complexity, latency requirements—align with the database you are considering.
2. Plan for where the application is going, not just where it is today. Ting warned against choosing a solution that creates a dead end, forcing a complete application refactor once scale or data model requirements change. He encouraged thinking in multi-year horizons when evaluating platforms.

DevOps and Automation: The Core Infrastructure Must Be Stable

Asked how Redis itself was applying DevOps principles internally, Ting’s answer was grounded in the relationship between automation and developer velocity:

“It’s just not intuitive of the DevOps mindset to continue to deploy new features and capabilities quickly [without stable infrastructure]. You want to have the core infrastructure be as stable, solid, robust, and resilient as possible.”

Howard Ting, CMO, Redis

The argument is straightforward: if teams are manually handling routine operational tasks—sizing, deployment, upgrades, scaling, and recovery—those are human cycles that cannot be spent on higher-value work. Automating the mundane creates the headroom that allows continuous delivery to function sustainably.

This is a commonly cited principle in the DevOps community, and it aligns with the broader industry push towards infrastructure as code, self-healing systems, and operator patterns for managing stateful workloads in Kubernetes environments. Redis has invested in managed cloud offerings and Kubernetes operators to push operational complexity down the stack, away from application developers.

Key Takeaways for DevOps and Platform Engineers

• Polyglot persistence is not a trend to resist—it is a natural consequence of microservices decomposition. Plan your platform to support multiple database types.
• Design your data tier around your application’s elasticity profile. High-variability workloads benefit disproportionately from in-memory storage.
• A two-tier hot/cold data architecture is a pragmatic way to balance cost against latency requirements as persistent memory options mature.
• Automating infrastructure operations (scaling, recovery, upgrades) is a prerequisite for sustainable continuous delivery, not an optional enhancement.
• Developer certification programmes can raise hiring confidence in communities built around open-source tools—but verify what a specific certification actually tests before treating it as a proxy for seniority.

1. Access Control

Granular access control is the foundational reason most teams move to a private registry. Rather than exposing every image to anyone with a Docker Hub account, you can define exactly which users or service accounts can read from or write to a given repository.

Practical access control typically includes:

• Role-based permissions — assign read-only, push, or admin rights per repository or namespace.
• Team-scoped repositories — let the frontend team see their images without exposing the payment-service images.
• Rapid revocation — if a contractor’s engagement ends or credentials are compromised, access can be removed immediately without affecting other users.
• Audit logging — track who pulled or pushed which image and when, supporting compliance and incident response.

Solutions such as Harbor, Nexus Repository, and GitLab Container Registry all expose role-based access control. Docker’s own open-source registry image supports token-based authentication that you can wire to your existing identity provider.

2. Custom Workflows and Image Scanning

A private registry is more than a storage bucket — it is a policy enforcement point. Most enterprise-grade private registries let you configure custom workflows that trigger automatically when an image is pushed.

Common workflow customizations include:

• Vulnerability scanning — integrations with scanners such as Trivy, Clair, or Snyk can block a promotion pipeline if a CVE above a defined severity is detected.
• Custom storage paths and ports — host the registry on an internal domain with a non-standard TLS port and mount storage to a dedicated volume or object-storage bucket.
• Certificate and mutual-TLS enforcement — require clients to present a certificate before they can authenticate, reducing the blast radius of stolen credentials.
• Webhook notifications — fire a Slack message or trigger a CI job whenever a new image tag lands in a watched repository.

Embedding scanning into the registry rather than into individual CI pipelines ensures that no image—regardless of how it was built—reaches production without a security check.

3. Pulling Existing Images Efficiently

Over time, a registry accumulates dozens or hundreds of images across multiple versions and tags. Without a reliable pull mechanism and a sensible tagging strategy, teams waste time hunting for the right image.

A private registry improves image retrieval in several ways:

• Searchable catalog — a UI or API lets you query by name, tag, or label metadata.
• Pull-through cache — proxy requests to Docker Hub or another upstream registry and cache the result locally, reducing external bandwidth and protecting against upstream outages or rate limits.
• Deterministic tagging conventions — combining semantic version tags with immutable digest references (e.g., myapp:1.4.2@sha256:abc123) makes it straightforward to pull exactly the image you intend.

# Pull a specific image by tag from a private registry
docker pull registry.internal.example.com/myteam/myapp:1.4.2

# Pull by digest for strict reproducibility
docker pull registry.internal.example.com/myteam/myapp@sha256:abc123...

4. Building Images Directly in the Registry Environment

Some private registry platforms — and the CI/CD systems that integrate with them — support building container images within the same secured environment where they will be stored. This pattern has meaningful security benefits.

• No round-trip to a public registry — the image never leaves your network boundary during the build phase.
• Immediate availability — once the build completes, the image is already in the registry; no separate push step is required.
• Consistent build context — base images used during the build are pulled from your curated, scanned registry rather than directly from an upstream source that could change between builds.
• Reduced attack surface — build secrets and intermediate layers remain inside your controlled infrastructure.

GitLab’s built-in container registry and Harbor’s integration with CI tools are common examples of this pattern. Kaniko and BuildKit running inside a Kubernetes cluster can push directly to a private registry without requiring a Docker daemon on the build host.

5. Uploading Containers for Team Collaboration

A private registry creates a single source of truth that the whole team—and downstream systems—can rely on. When every developer pushes to the same internal registry, the following collaboration benefits emerge:

• Shared base images — platform teams publish hardened base images; application teams extend them, knowing the base has already been scanned and approved.
• Consistent environments — developers, CI runners, staging, and production all pull from the same registry, eliminating the classic “works on my machine” problem caused by image drift.
• Permission-gated collaboration — external contractors or partner teams can be granted scoped, time-limited access to specific repositories without exposing the entire registry.
• Faster incident response — when a vulnerability is found, the team can identify every image that uses the affected layer by querying the registry’s metadata, rather than manually auditing individual developer laptops.

# Tag a locally built image and push it to the private registry for teammates
docker tag myapp:latest registry.internal.example.com/myteam/myapp:feature-auth
docker push registry.internal.example.com/myteam/myapp:feature-auth

Choosing a Private Registry Solution

There is no single “right” private registry for every team. The decision typically comes down to hosting model, feature requirements, and existing tooling:

• Self-hosted open source: Docker’s official registry image is lightweight but minimal; Harbor adds a full-featured UI, RBAC, scanning integration, and replication.
• Platform-integrated: GitLab Container Registry, GitHub Packages, and Gitea’s built-in registry are good choices if your source code already lives on those platforms.
• Cloud-managed: Amazon ECR, Google Artifact Registry, and Azure Container Registry offload operational overhead while remaining within your cloud provider’s IAM model.
• Enterprise on-premises: JFrog Artifactory and Sonatype Nexus Repository support container images alongside other artifact types (Maven, npm, PyPI) from a single platform.

Summary

Private Docker registries are not simply a more secure version of Docker Hub. They are active participants in the software delivery pipeline. The five functions covered here — access control, custom scanning workflows, efficient image pulls, in-environment builds, and collaborative uploads — collectively reduce risk, improve reproducibility, and accelerate delivery. Any team running containers in production should evaluate which of these functions would have the highest immediate impact on their workflow and deploy accordingly.

That maturity, however, comes with a caveat: the threat landscape has shifted. A series of high-profile data breaches in recent years has pushed security to the top of every boardroom agenda, and regulatory frameworks such as the EU’s General Data Protection Regulation (GDPR) have introduced real legal consequences for organisations that fail to protect their data. Security is no longer optional — and neither is compliance.

The Security Challenge Specific to Cloud Environments

For development and operations teams, the cloud’s flexibility and speed are clear advantages. For security teams, those same qualities introduce a new class of problems. Traditional security practice involved carefully controlled, relatively static environments. In the cloud, infrastructure can be spun up, modified, and torn down within minutes — often without the security team’s direct involvement.

The tight integration between cloud platforms and application code means that security requirements can no longer be bolted on at the end of a project. They must be incorporated into the code and infrastructure definitions themselves. When cloud platform configurations can change daily, the window for misconfiguration to go undetected is wide open.

This risk is well-recognised in the industry. Gartner has projected that by 2020, the majority of cloud security incidents would be attributable to customer misconfiguration, mismanaged credentials, or insider threats — not to vulnerabilities in the cloud provider’s own infrastructure. The implication is clear: the responsibility for securing cloud environments lies overwhelmingly with the organisations that use them.

Translating Security Policy into Developer Workflow

A growing category of cloud security posture management (CSPM) tools addresses this problem by bridging the gap between security policy and development practice. These tools allow security teams to define their compliance requirements — mapped to standards such as PCI-DSS, CIS Benchmarks, NIST, or HIPAA — and then surface violations to development teams in an actionable, concise format.

The practical benefit is significant. When security guardrails are codified and enforced automatically, developers no longer need to manually cross-reference pages of written policy every time they make a change to cloud infrastructure. They work within well-defined boundaries, reducing the risk of misinterpretation and human error while freeing them to focus on building features rather than auditing configurations.

A Practical Continuous Security Workflow

The following workflow illustrates how continuous cloud security can be integrated into the development lifecycle in a structured, repeatable way. It is based on a real-world implementation built to address gaps found in existing multi-cloud security tooling:

• Deployment: Stand up a new cloud subscription or account (for example, an Azure subscription or an AWS account).
• Permission: Create the necessary IAM controls and grant the security team the access they need to configure the security inspection tool for that new environment.
• Definition: The security team defines or applies the compliance policies that the cloud environment must meet. These policies can be updated as the environment grows or as compliance requirements evolve.
• Building: Development teams begin deploying cloud resources into the environment. For early-stage deployments, developers can focus on functionality, knowing that security compliance will be evaluated in real time by the tooling.
• Consumption: Query the security tool via API to identify exactly where a deployment fails to meet the defined security policy. If it passes, the tool generates a report to serve as evidence of compliance.
• Remediation: Where violations are found, fixes can be applied programmatically. A corrected infrastructure template can be pulled back into the repository, or the API can return the necessary JSON for independent integration. GUI-based alert review and remediation is also available for teams that prefer it.
• Reporting: As the project progresses, compliance reports are shared with stakeholders. These reports support risk analysis and inform sprint planning by clearly identifying which areas carry the greatest security risk.

Security Visibility Across the Entire Delivery Pipeline

Embedding security checks throughout the integration cycle — rather than only at the end — means that risk can be surfaced and addressed at the most appropriate stage. Early in the pipeline, the tooling can flag risks in smoke testing. In UAT, quick remediations can be applied. In staging, deployments can be validated before they reach production. Once in production, the same tooling can be handed over to operations teams to monitor for manual configuration changes or for configuration drift over time.

For security teams, continuous cloud security tooling provides an immediate, centralised view of the security posture across all cloud environments — including short-lived environments that might otherwise go unmonitored. With full visibility of the infrastructure and how its components interconnect, security teams can identify weak points proactively rather than reactively.

The audit trail is equally valuable. Every configuration change can be monitored in real time, with alerts routed to communication and logging platforms such as Slack, Sumo Logic, or email whenever a resource falls out of compliance. This creates a continuous, auditable record of security posture — something that is increasingly required for regulatory compliance and internal governance alike.

Why Continuous Cloud Security Benefits Both Security and Development Teams

The traditional model — where security reviews happen at the end of a development cycle — is poorly suited to the pace of cloud-native development. Continuous security integrates compliance into the cloud lifecycle itself, allowing security and development teams to work in parallel rather than in sequence.

Security teams gain the tooling to define, enforce, and audit policy at scale. Development teams gain clear guardrails and automated feedback that let them move quickly without inadvertently introducing compliance risk. Both teams operate on the same infrastructure, using the methods best suited to their respective roles.

As cloud adoption continues to deepen in regulated industries, the organisations that treat continuous security as a first-class part of their developer journey — not an afterthought — will be better positioned to move fast, stay compliant, and respond to an evolving threat landscape.

Originally sourced from cloudcomputing-news.net (2019).

What Are Transient Faults?

In electrical engineering, a transient fault is an error condition that disappears once power is disconnected and restored — the same principle behind the instinctive fix of turning a frozen device off and on again. In cloud computing, the equivalent faults are far harder to contain.

Distributed systems face increased complexity: known unknowns, unknown unknowns, infrastructure you will never physically touch, and technology that evolves faster than any single team can track. Today’s users have zero tolerance for unresponsive or unreliable services. With competitors a single click away, any measurable downtime risks permanent loss of users.

Two real-world incidents illustrate how quickly transient faults can become serious outages:

• A Rough Patch (Azure DevOps): Microsoft’s corporate VP of cloud developer services Brian Harry described weeks of sleepless nights tracing a storm of requests to the access control service (ACS) that exhausted Source Network Address Translation (SNAT) ports, blocked authentications, and impacted thousands of users.
• 503 Errors (Azure Functions): Cellenza’s Mikael Krief documented on the ALM DevOps Rangers blog how a refactored extension spawned a storm of connections and threads, overwhelming an Azure service and returning 503 Service Unavailable errors to end users. The incident reinforced the critical importance of monitoring from the very beginning of any implementation.

While failure and disaster recovery strategies can minimize the impact of infrastructure outages, solutions that rely on remote resources or services also need built-in sensitivity to transient faults. Well-designed systems detect these faults and attempt to self-correct before escalating an alert — or worse, becoming completely unresponsive.

Three patterns address the majority of transient fault scenarios in distributed systems: retry, throttling, and circuit breaker.

1. Retry Pattern

The retry pattern is the simplest of the three and mirrors what humans do instinctively — try again. It is effective for transient faults caused by brief network latency spikes, momentary service overloads, or short-lived connectivity interruptions across distributed networks.

How It Works

The core logic uses an incrementally increasing delay (exponential back-off) between successive attempts, and a maximum retry limit to prevent infinite loops:

Set failure_count = 0
CALL the [micro] service
If (fail) failure_count++
If (failure_count > retry_limit) OR (not a transient failure) → FAIL
DELAY (delay_time)
Increase delay_time by a factor of failure_count
RETRY from step 2

The back-off delay is critical: retrying too aggressively can compound the original problem and push a struggling service into the throttling or circuit-breaker territory described below.

When to Use It

• Short-lived, self-resolving network errors
• Temporary service overloads expected to clear within seconds
• Idempotent operations where repeating the call is safe

Open-source implementations to explore include java-design-patterns and Microsoft’s Transient Fault Handling Application Block.

2. Throttling Pattern

Throttling protects your services from clients that are overutilising resources — whether due to a logic bug, a misconfigured consumer, or a sudden traffic surge. Think of it as a four-lane tunnel managing traffic from a six-lane freeway: the tunnel sets the maximum throughput, and excess flow must be managed at the entry point.

How It Works

Increment request_count
// limit  = maximum requests permitted within a time interval
// degrade = return a "slow down" error or temporarily pause the operation
If (request_count > limit) → DEGRADE service
CALL the [micro] service

When to Use It

• Enforcing service-level agreements (SLAs) on throughput
• Preventing a single consumer from monopolising shared resources
• Smoothing bursts of unexpected traffic
• Complementing the retry pattern — back-off delays in retries help avoid accidentally triggering throttle limits

Open-source implementations include WebApiThrottle and Core.Throttling.

3. Circuit Breaker Pattern

Like a circuit breaker in a home’s electrical panel, this pattern is your last line of defence. Where the retry pattern handles brief, self-resolving faults, the circuit breaker is designed for faults that persist over a longer period. Continuously retrying a failing service operation under these conditions can worsen the situation, cascade failures across dependent services, and ultimately bring down the entire system.

The core hypothesis: a failed service call is more likely to succeed if retried only after a significant delay — giving the downstream service time to recover before new load arrives.

How It Works

The circuit breaker maintains a state — open (normal operation) or closed (tripped). When failures exceed a threshold, the breaker trips and subsequent calls are blocked until a timer expires and a probe call succeeds.

// Circuit breaker has NOT tripped (open state = normal flow)
If (circuit_state == open)
    CALL the [micro] service
    If (fail) fail_count++
    If (fail_count > limit) circuit_state = closed   // trip the breaker

// Circuit breaker IS tripped (closed state = blocking calls)
Else
    If (circuit_state == closed) Start recovery Timer

// Probe call when timer fires
On Timer timeout
    CALL the [micro] service
    If (success) circuit_state = open                // reset the breaker

States at a Glance

• Open: Calls flow normally; failures are counted.
• Closed (tripped): Calls are blocked; a timer runs to allow the downstream service to recover.
• Half-open (implied in most implementations): A single probe call tests whether the service has recovered before fully reopening.

Open-source implementations include Netflix’s Hystrix, circuit-breaker libraries, and Polly for .NET.

Combining the Patterns: A Microservices Example

In practice, these three patterns work together. Consider a microservices architecture where service #7 fails under load:

• Upstream callers first attempt retries with exponential back-off.
• If traffic to healthy services spikes as a result, throttling prevents resource exhaustion across the mesh.
• If service #7 remains unavailable beyond the retry limit, circuit breakers trip, halting cascading failures while the service recovers.

The complexity of managing these interactions grows rapidly — especially when feature flags are involved. A single flag flip can alter traffic patterns, expose previously hidden failure modes, and invalidate assumptions baked into your retry and throttle configurations.

Testing Your Fault-Handling Logic

Implementing these patterns is only half the work. You must validate them:

• Unit tests should verify that your fault-handling logic triggers correctly — confirm that retries fire the expected number of times, throttle limits return the right error codes, and circuit breakers transition state as designed.
• Integration tests should simulate resilient faults across your collective services to confirm that the system as a whole responds appropriately.
• Service virtualisation tools such as Hoverfly can simulate transient faults, slow responses, and degrading services in a controlled environment without requiring a real downstream dependency to misbehave on cue.

Stakeholders will not forgive fault-handling logic that itself fails under pressure. Treat resilience patterns as first-class features and test them accordingly.

Faults Are a Feature, Not a Failure

In a blameless DevOps culture, faults — like failures — are learning opportunities rather than indictments. The goal is not to eliminate faults entirely, which is impossible in distributed systems, but to build systems that detect, contain, and self-correct them before users are impacted.

Applying the retry, throttling, and circuit breaker patterns is a concrete, measurable step toward raising the quality bar of your infrastructure — continuously delivering business value and maintaining the trust of your stakeholders even when the unexpected happens.

As September 2019 got underway, Microsoft announced a wave of Azure updates spanning AI services, developer tooling, compliance blueprints, infrastructure, and partner ecosystem news. Here is a structured breakdown of the most significant changes.

Azure Form Recognizer: Handwritten Text and Mixed-Mode Support

Principal program manager Neta Halby outlined new capabilities added to Azure Form Recognizer. Previously, the service could extract tables, plain text, and key-value pairs from structured documents such as W-2 tax forms. The update added two significant capabilities:

• Handwritten text recognition — extending extraction beyond printed characters to include handwritten content.
• Mixed-mode processing — enabling a single application to handle documents that contain both printed and handwritten text, targeting sectors such as healthcare, finance, insurance, and manufacturing.

The stated value proposition includes reducing manual data entry, extending digitization workflows back to older handwritten records, and consolidating handling of multiple document types into a single pipeline. Consulting firm Avanade was cited as an early adopter, using the feature to automate capture of handwritten contact information collected on paper at trade shows.

Azure Logic Apps: Features Added in July and August 2019

Over the summer sprint cycle, the Logic Apps team shipped a number of developer-facing updates:

• Support for internal access endpoints to restrict Logic App triggers to internal network traffic.
• Inline code support for embedding JavaScript snippets directly within workflows.
• Fixed IP addresses for connector deployment endpoints, simplifying firewall allowlisting.
• Use of Azure on-premises data gateways across subscriptions.
• Visibility into canceled webhook actions in the portal.
• Portal themes for improved developer experience.

Azure DevOps: Sprint 157 Highlights and Deprecation Notices

During Sprint 157, the Azure DevOps team shipped rollup columns for backlogs, enabling teams to track progress across work item hierarchies. Smaller improvements were also delivered for Repos, Boards, and Artifacts.

Deprecation notices issued around this time included:

• Kubernetes 1.10.x clusters: Users were asked to upgrade to one of the four supported versions by October 25, 2019. Following the release of Kubernetes 1.14 in August 2019, version 1.10.x was scheduled to be removed from the Azure CLI and Azure portal.
• Media Encoder Standard and Premium Workflow: Both encoder capabilities were set to be retired on November 30, 2019.
• JavaScript SDK v1.x for Cosmos DB: Scheduled for deprecation on August 30, 2020.

Azure Blueprint Compliance Samples: NIST SP 800-53 R4

Microsoft expanded its library of Azure Blueprint compliance samples. The most recent addition at the time was NIST SP 800-53 R4, which maps Azure Policy controls directly to NIST control identifiers. This blueprint is primarily targeted at US government customers and agencies with regulatory compliance requirements under the NIST framework.

Infrastructure and Database Updates

Several infrastructure updates were made available around this period:

• M-series VMs became available in the France Central region.
• Cross-region read replicas for Azure Database for MySQL went live.
• Monthly payment options for Azure Reservations were introduced, lowering the upfront commitment barrier.
• Azure SQL Database instance pool entered preview, allowing pre-planning of vCore compute resources across multiple instances.
• An integration between DevTest Labs and Azure Bastion was introduced, enabling SSL-based VM connections directly from the Azure portal.

SQL Server Data Tools in Visual Studio 2019 Preview

SQL Server Data Tools (SSDT) became available as part of the Visual Studio 2019 preview release. The integration supports stable change management and deployment workflows when building solutions that target Azure SQL Data Warehouse.

Azure Stack: Government Secret Cloud Integration and Edge AI

Azure Stack gained integration with the Government Secret cloud, enabling hybrid cloud scenarios for highly regulated government workloads. Billing options include Pay-As-You-Go and marketplace billing models.

Additional Stack updates included:

• General availability of diagnostic log collection, allowing operators to share logs directly with Microsoft Customer Support Services.
• Work in progress on solution patterns for AI inferencing on video streams at the network edge, aimed at developers building intelligent edge applications.

Vision AI Developer Kit: General Availability

Principal PM Anne Yang covered the Microsoft and Qualcomm partnership around the Vision AI Developer Kit, which was announced the previous year and reached general availability around this time. The kit combines:

• A purpose-built camera module
• Azure IoT Edge runtime
• Azure Machine Learning integration
• Qualcomm’s Vision Intelligence 300 Platform

The kit is designed to accelerate deployment of computer vision models to intelligent edge devices, with Microsoft claiming vision models can be deployed in minutes. Development options include Visual Studio Code and no-code pathways through Azure Machine Learning, Cognitive Services, and Custom Vision.

Azure Site Recovery: Simplified Failover Mapping

Rajani Janaki Ram, program manager for R&D Compute, discussed improvements to Azure Site Recovery. Enhanced integrations aim to reduce the number of manual steps required during disaster recovery planning, making it easier to map resources between a source region and a target region. The update also improves handling of:

• Public IP addresses
• Network Security Groups (NSGs)
• Internal load balancers

These networking resources can now be more readily incorporated into site recovery plans rather than requiring post-failover manual reconfiguration.

Partner and Ecosystem News

Several partner announcements accompanied the product updates:

• MongoDB Atlas on Azure Marketplace: MongoDB expanded its partnership with Microsoft through the Partner Reported ACR co-sell program. MongoDB Atlas, already integrated with Power BI, Databricks, and Sitecore, became available through Azure Marketplace with billing integrated into Azure invoicing.
• Logicalis acquires Orange Networks in Germany: British IT firm Logicalis acquired Orange Networks, a Microsoft partner operating in Munich, Hamburg, Offenbach, and Düsseldorf. The acquisition grants Logicalis Germany Microsoft Gold Partner status.
• SES extends Azure ExpressRoute via satellite: Luxembourg-based satellite operator SES announced it would extend Azure ExpressRoute connectivity through its fleet of 50 geostationary satellites, delivering the service to maritime and offshore oil platform environments.
• Infosys and JG Summit Holdings in the Philippines: Infosys announced a collaboration with JG Summit Holdings to build a platform based on Azure and SAP S/4HANA.

This article is based on reporting originally published by msdynamicsworld.com in September 2019. Some features and timelines described here reflect the state of Azure services as of that date and may have changed significantly since.

What Is the GitHub Student Developer Pack?

The GitHub Student Developer Pack is a program run by GitHub Education that gives verified students free access to a curated set of professional tools and services. It includes GitHub Pro (normally a paid tier) plus free or heavily discounted access to tools from GitHub’s partner ecosystem, covering everything from cloud hosting and CI/CD pipelines to domain names, IDEs, and design assets.

The program launched several years ago and has grown steadily. As of the August 2019 announcement that prompted this article, 21 new partners had joined the pack, bringing the total partner count to over 35 and raising GitHub’s stated savings figure to approximately $45,000 USD in combined tool value over the course of a student’s enrollment.

Who Is Eligible?

Any student aged 13 or older who is currently enrolled at an accredited educational institution can apply. GitHub accepts the following as proof of enrollment:

• A school-issued email address (e.g., a .edu domain)
• A valid student ID
• Other official documentation of current academic enrollment

Applications are reviewed by GitHub. Once approved, access is typically granted for the duration of your studies and must be renewed periodically.

What Tools Are Included?

The partner list spans a wide range of categories useful to developers, DevOps practitioners, and designers. The following tools were listed as part of the pack at the time of the August 2019 update. Note that partner availability changes over time — always check the official GitHub Student Developer Pack page for the current list.

Cloud Platforms & Hosting

• Microsoft Azure — Cloud services for building, managing, and deploying applications
• AWS Educate — Cloud compute, free training, and collaboration resources from Amazon Web Services
• DigitalOcean — Simple cloud hosting built for developers
• Heroku — Flexible platform-as-a-service for deploying and managing apps
• Netwise — Turnkey data centre services for hosting critical IT infrastructure

IDEs & Development Environments

• JetBrains — Professional desktop IDEs including IntelliJ IDEA, PyCharm, WebStorm, and more
• Gitpod — Online IDE integrated with GitHub for instant, browser-based workspaces
• Next.tech — Browser-based computing environments for hands-on learning

DevOps, Monitoring & CI/CD

• Travis CI — Continuous integration platform for open-source and private projects
• Datadog — Cloud-based infrastructure monitoring and observability
• Sentry — Real-time error reporting and crash monitoring for applications
• LogDNA — Log management and aggregation platform
• Better Code Hub — Online source code analysis and quality assessment service

Domain Names & Web Infrastructure

• Namecheap — Affordable domain registration, hosting, and management
• Name.com — Domain name registrar and web host
• .TECH Domains — Domain registration for tech startups, businesses, events, and communities

APIs & Developer Services

• Stripe — Web and mobile payment APIs built for developers
• Algolia — Hosted search API with support for frontend and backend frameworks
• Sendgrid — Cloud-based email delivery platform
• TransloadIt — File uploading and media processing service
• PushBots — Scalable push notification system for mobile applications
• ConfigCat — Feature flag and configuration management service
• Cryptolens — Cloud-based software licensing platform

Git Clients & Project Management

• Axosoft (GitKraken) — Cross-platform Git GUI client and GitKraken Glo task boards with GitHub Issues sync
• Working Copy — Git client for iOS supporting cloning, editing, committing, and pushing
• Termius — SSH client for desktop and mobile devices

Learning & Courses

• Frontend Masters — In-depth JavaScript, Node.js, and front-end engineering courses
• Thinkful — Project-based courseware and mentoring to launch a developer career
• Flatiron School — Coding bootcamp focused on launching developers into the industry
• SymfonyCasts — Symfony and PHP video tutorials with code challenges

Localization & Data

• Transifex — Localization platform with codebase integration
• Phrase — Cloud-based localization and translation management
• Carto — Spatial data analysis, visualization, and mapping application platform

Design & Productivity

• Icons8 — Design resources including icons, UI illustrations, and photos
• Bootstrap Studio — Desktop application for building responsive websites using the Bootstrap framework
• PomoDone — Pomodoro-based time-tracking app to improve focus and reduce burnout
• SQL Smash — Productivity plugin for SQL Server Management Studio

Why This Matters for Student Developers

The practical value of the pack extends beyond cost savings. Having access to production-grade tools — real CI/CD pipelines, cloud infrastructure, professional IDEs, and monitoring systems — lets students build and deploy projects that reflect actual industry workflows. This hands-on experience is significantly more valuable on a résumé or portfolio than toy projects built in isolated learning environments.

For DevOps and platform engineering students in particular, free access to tools like Travis CI, Datadog, Sentry, AWS Educate, Azure, DigitalOcean, and Heroku means you can practice the full software delivery lifecycle — build, test, deploy, monitor, and iterate — without spending a cent.

How to Apply

To apply for the GitHub Student Developer Pack:

1. Sign in to your GitHub account (or create one if you don’t have one).
2. Visit education.github.com/pack.
3. Click Get your pack and follow the verification steps.
4. Submit proof of enrollment — school email, student ID, or equivalent documentation.
5. Wait for GitHub’s review, which typically takes a short time but may vary.

Once approved, you can access each partner offer directly from the pack dashboard. Individual partner offers have their own redemption steps, but most are straightforward — often a promo code or an OAuth connection to your GitHub account.

Keep an Eye on the Current Partner List

The partner list in this article reflects the state of the pack as of August 2019. GitHub regularly adds and removes partners, updates offer terms, and adjusts credit amounts. Before applying for any specific tool, verify current availability and offer details on the official GitHub Student Developer Pack page. The $45,000 savings figure cited by GitHub is also a combined, theoretical maximum across all offers — actual value depends on which tools you use and for how long.

What Is the GitHub Student Developer Pack?

The GitHub Student Developer Pack is a program offered by GitHub to verified students at accredited educational institutions. At its core, it provides:

• GitHub Pro at no cost for as long as you remain a student — giving you unlimited private repositories, advanced code review tools, and insights.
• Free access or deep discounts on tools from GitHub’s partner ecosystem, spanning cloud hosting, monitoring, CI/CD, IDEs, domain registration, and more.

GitHub periodically updates the partner list. The 2019 edition added 21 new partners, bringing the theoretical combined value of all benefits to approximately $45,000 — though in practice most students will take advantage of a targeted subset of the offers.

Why It Matters for DevOps and Developer Learners

Many of the tools in the pack are the same ones used by professional engineering teams every day. Getting hands-on access as a student means you can:

• Build and deploy real projects to cloud infrastructure (DigitalOcean, Heroku, Microsoft Azure, AWS Educate) without paying out of pocket.
• Set up continuous integration pipelines (Travis CI) on private repositories.
• Monitor application performance and infrastructure (Datadog) the way production teams do.
• Use professional IDEs (JetBrains IntelliJ IDEA, PyCharm, and others) rather than free-tier alternatives.
• Handle transactional payments in test and live environments (Stripe) to understand commerce integrations.
• Track errors in your deployed apps (Sentry) and learn incident response practices early.

Partner Tools Included in the Pack

The following tools were listed as part of the GitHub Student Developer Pack at the time of the 2019 announcement. Partners and benefit details change over time, so always verify current offers on the official GitHub Education page.

Cloud Infrastructure & Hosting

• Microsoft Azure — Cloud services for building, managing, and deploying applications.
• DigitalOcean — Developer-focused cloud hosting with straightforward pricing.
• Heroku — Platform-as-a-service for deploying and managing web applications.
• AWS Educate — AWS cloud training, credits, and collaboration resources for students.
• Netwise — Turnkey data centre colocation and managed hosting services.

CI/CD & Code Quality

• Travis CI — Continuous integration platform supporting both open source and private projects.
• Better Code Hub — Automated source code analysis that scores your codebase against maintainability guidelines.
• Sentry — Real-time error tracking and crash reporting for applications.

Monitoring & Logging

• Datadog — Cloud-based infrastructure and application performance monitoring.
• LogDNA — Centralised log management platform for aggregating and searching logs.

IDEs & Development Environments

• JetBrains — Professional cross-platform IDEs including IntelliJ IDEA, PyCharm, WebStorm, and more.
• Gitpod — Browser-based IDE with full GitHub integration for instant, reproducible dev environments.
• Next.tech — Browser-based computing environments for coding without local setup.

Git Clients & Workflow Tools

• Axosoft (GitKraken) — Cross-platform Git GUI client and GitKraken Glo boards for task tracking synced with GitHub Issues.
• Working Copy — Full-featured Git client for iOS: clone, edit, commit, push, and more.
• Termius — SSH client for desktop and mobile, useful for managing remote servers.
• SQL Smash — Productivity plugin for SQL Server Management Studio.

APIs & Back-End Services

• Stripe — Payment processing APIs built for developers, covering web and mobile.
• Algolia — Hosted search API with front-end and back-end framework support.
• SendGrid — Cloud-based transactional and marketing email delivery platform.
• TransloadIt — File uploading, encoding, and processing service.
• PushBots — Scalable push notification system for mobile applications.
• ConfigCat — Feature flag and configuration management service.
• Cryptolens — Cloud-based software licensing platform.

Domain Names & Web

• Namecheap — Affordable domain registration and hosting.
• Name.com — Domain registration and web hosting.
• .TECH Domains — .tech TLD for startups, communities, and tech projects.

Localization & Internationalization

• Transifex — Localization platform that integrates with your code repository.
• Phrase — Cloud-based localization and translation management.

Design & Front-End

• Bootstrap Studio — Desktop application for building responsive websites with the Bootstrap framework.
• Icons8 — Design resources: icons, UI illustrations, stock photos, and more.
• Frontend Masters — In-depth video courses on JavaScript, Node.js, and front-end engineering.

Data & Analytics

• Carto — Platform for spatial data analysis, visualization, and location-based application development.

Learning & Courses

• Flatiron School — Coding bootcamp curriculum for aspiring developers.
• Thinkful — Mentored online courseware for launching a developer career.
• SymfonyCasts — Symfony and PHP video tutorials with code challenges.

Productivity

• PomoDone — Pomodoro-based time-tracking app designed to improve focus and reduce burnout.

How to Apply

To claim the Student Developer Pack you need a verified student status. GitHub typically accepts one or more of the following as proof:

• A school-issued email address (e.g., a .edu address).
• A photo of a dated student ID or enrolment document.

Once verified, benefits are accessible through the GitHub Education portal. Individual partner offers may require you to connect your GitHub account or create a separate account with that partner.

Key Takeaways

• The GitHub Student Developer Pack provides GitHub Pro for free during enrolment.
• Partner benefits cover the full DevOps and development stack: cloud hosting, CI/CD, monitoring, IDEs, APIs, and more.
• The combined advertised value of all benefits was approximately $45,000 as of the 2019 announcement — partners and amounts change over time.
• Applying requires proof of student status through the GitHub Education portal.
• The pack is an excellent opportunity to gain practical experience with the same tools used by professional engineering teams.

Original coverage sourced from Lifehacker. For the current list of partners and up-to-date benefit details, visit the official GitHub Student Developer Pack page.

The Cloud Security Perception Gap Has Closed — But New Risks Have Opened

Cloud computing’s early reputation for being inherently less secure than on-premises data centres has largely been put to rest. For most critical business functions, well-configured cloud environments now meet or exceed the security posture of traditional infrastructure. However, “well-configured” is doing a lot of heavy lifting in that sentence.

The profile of cloud adopters has shifted dramatically. Early adopters were often technology-native companies with relatively flexible security requirements. Today’s wave of cloud entrants comes predominantly from finance, healthcare, and government sectors — industries where compliance is not optional and the consequences of a breach extend well beyond reputation damage.

Regulatory pressure has intensified this shift. The introduction of GDPR in Europe, along with sector-specific regulations such as PCI-DSS, HIPAA, and NIST frameworks, has made compliance a board-level concern. Security is no longer a post-launch checkbox; it is a continuous operational requirement.

Why Misconfiguration Is the Real Threat Vector

The threat model for cloud environments is fundamentally different from that of traditional data centres. Security teams previously worked with relatively static, controlled environments they could carefully assess and manage. Cloud platforms change constantly — new services are released, IAM policies are updated, storage buckets are created, and networking rules are modified, often daily or even hourly.

Gartner has projected that the overwhelming majority of cloud security failures would be attributable to customer misconfiguration, mismanaged credentials, or insider threats — not vulnerabilities in the cloud provider’s own infrastructure. This projection aligns with what security practitioners observe in real-world incidents: the cloud provider’s perimeter holds; it is the customer’s configuration that creates the exposure.

This reality places a significant new burden on development teams. Because cloud platform configuration and application code are now tightly integrated — infrastructure-as-code, Terraform modules, CloudFormation templates, and Kubernetes manifests all encode security decisions directly — security can no longer be treated as a separate discipline applied after the fact.

The Structural Problem: Security Policies Don’t Translate Automatically to Cloud Configurations

Security teams typically define their requirements in terms of compliance frameworks: PCI-DSS, CIS Benchmarks, NIST 800-53, HIPAA. These are written documents. Cloud environments, however, are defined by API calls, configuration files, and policy JSON. There is no automatic translation between a written compliance policy and a correctly configured S3 bucket or Azure Storage account.

The result is a recurring failure mode: developers make configuration decisions in good faith, unaware that a specific setting violates a compliance requirement they have never read in full. Security teams, meanwhile, struggle to audit cloud environments at the speed at which they change.

Reducing the overhead of maintaining and interpreting security policies benefits everyone involved. It lowers the risk of misinterpretation, narrows the margin for human error, and allows development teams to work confidently within guardrails established by the security team — without needing to be experts in every compliance framework or track every cloud platform change themselves.

A Practical Continuous Cloud Security Workflow

One approach to solving this problem is to implement a continuous security tool that sits between the security team’s policy definitions and the development team’s cloud deployments. The following workflow illustrates how this can be structured in practice, based on a real implementation pattern using a tool the original author called Cloud Security Guardian (CSG):

• Deployment: Provision a new cloud account or subscription — for example, a new Azure subscription or AWS account — as the starting point.
• Permission: Create the necessary IAM controls and grant the security team access to configure the continuous security tool to inspect the new environment.
• Definition: The security team defines or applies the compliance policies the environment must meet — for example, CIS Benchmarks, PCI-DSS, or HIPAA controls. These definitions can be updated as the environment evolves or as regulatory requirements change.
• Building: Developers begin making cloud deployments into the environment. In early iterations, they can focus on functional correctness; policy compliance is evaluated continuously and in real time rather than as a gate they must pass before writing any code.
• Consumption: Query the security tool via its API to identify exactly where a deployment diverges from the defined security policy. If the deployment is fully compliant, the tool generates a report confirming this — useful for audits and stakeholder communication.
• Remediation: Where violations exist, fixes can be applied directly. The corrected infrastructure template can be pulled back into the repository, or the tool can provide the corrected JSON for independent integration. Teams that prefer a visual interface can review alerts and remediate through a GUI.
• Reporting: As the project progresses, compliance reports can be shared with stakeholders, used for risk analysis, and incorporated into sprint planning to prioritise remediation work.

Continuous Security Across the Entire Delivery Pipeline

The value of this approach is that it provides security information throughout the entire integration cycle rather than only at specific review gates:

• In smoke testing: Surface security risks early, when they are cheapest to fix.
• In UAT: Apply quick remediations before issues carry forward.
• In staging: Validate the full configuration against policy before production promotion.
• In production: Hand monitoring off to the operations team to detect manual changes and configuration drift over time.

Configuration drift — where a production environment gradually diverges from its originally approved state due to manual changes or platform updates — is one of the most common sources of compliance failures in cloud environments. Continuous monitoring in production catches this as it happens rather than at the next scheduled audit.

Benefits for Security Teams

Continuous cloud security tooling is not only a developer productivity concern — it fundamentally changes what security teams can do. With a centralised view of all cloud environments, security teams can:

• Maintain an up-to-date compliance status for all cloud accounts without manual audits.
• Monitor short-lived environments — feature branches, ephemeral test stacks — that would otherwise be invisible to traditional audit processes.
• Understand how infrastructure components interconnect and identify weak points in the overall architecture.
• Generate on-demand compliance reports at any point in time, with a full audit trail of every change.
• Receive real-time alerts via communication channels such as Slack, email, or SIEM tools when something falls out of compliance.

Making Continuous Security a Shared Responsibility

The broader principle here is one of shared ownership. Security cannot be a function performed exclusively by a separate team working in isolation from development and operations. In cloud-native environments, the speed of change makes that model unworkable.

By embedding continuous security checks into the development workflow — providing developers with clear, actionable feedback rather than pages of policy documentation — organisations can allow each team to operate in the way that suits them best while still converging on a shared compliance standard.

Development teams move faster because they have guardrails rather than gates. Security teams gain broader visibility without needing to manually review every deployment. Operations teams catch drift in production rather than discovering it in an audit. That alignment, achieved through tooling and process rather than org-chart restructuring alone, is what sustainable cloud security looks like in practice.

Key Takeaways

• Cloud misconfiguration and mismanaged credentials — not provider vulnerabilities — are the leading sources of cloud security failures.
• Compliance frameworks such as PCI-DSS, HIPAA, CIS, and NIST must be translated into enforceable cloud configuration policies, not just written documents.
• Continuous security tooling should sit in the CI/CD pipeline and provide feedback at every stage: development, testing, staging, and production.
• Security teams benefit from centralised visibility and real-time alerting; development teams benefit from clear, code-level remediation guidance.
• Configuration drift in production is as significant a risk as initial misconfiguration — continuous monitoring is required, not just pre-deployment checks.