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This Edureka “AWS DevOps vs Azure DevOps” video will give a detailed comparison of how AWS and Azure fare in handling and supporting DevOps approach on the respective cloud platforms along with latest trends and numbers in the domain.
The following topics are covered in the video:
#aws #azure #cloud #devops
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In the midst of this pandemic, what is allowing us unprecedented flexibility in making faster technological advancements is the availability of various competent cloud computing systems. From delivering on-demand computing services for applications, processing and storage, now is the time to make the best use of public cloud providers. What’s more, with easy scalability there are no geographical restrictions either.
Machine Learning systems can be indefinitely supported by them as they are open-sourced and within reach now more than ever with increased affordability for businesses. In fact, public cloud providers are increasingly helpful in building Machine Learning models. So, the question that arises for us is – what are the possibilities for using them for deployment as well?
Model building is very much like the process of designing any product. From ideation and data preparation to prototyping and testing. Deployment basically is the actionable point of the whole process, which means that we use the already trained model and make its predictions available to users or other systems in an automated, reproducible and auditable manner.
#cyber security #aws vs azure #google vs aws #google vs azure #google vs azure vs aws
1610609488
This Edureka “AWS DevOps vs Azure DevOps” video will give a detailed comparison of how AWS and Azure fare in handling and supporting DevOps approach on the respective cloud platforms along with latest trends and numbers in the domain.
The following topics are covered in the video:
#aws #azure #cloud #devops
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Site Reliability Engineering is a fast-evolving engineering discipline, under the realms of DevOps, that is focused on ensuring desirable levels of reliability for any system, solution, or service offered or used by an organization.
As the solution footprint grows, both the DevOps and the SRE teams face the same challenges that are mostly related to performance, scalability, availability, observability, security, and process documentation. The organizations define their SLAs around the same set of attributes. Some of the standard SLAs are:
Such SLAs can be met by setting up appropriate SLOs and identifying the correct services from the cloud provider.
Managing site reliability helps organizations to improve their customer experience, provide quick support, reduce application outages, and positively impact the overall business. We dive into the services provided by Azure to understand the SLOs better below.
Microsoft Azure is an extremely mature cloud platform that has a lot of services for handling every concern of a solution. While building your solution on the Azure cloud, you need to choose the correct services that serve your SRE requirements.
Azure Monitor is a modern monitoring solution that can collect data from your solution, cloud platform, and on-premises environment, analyze it, and visualize it. It allows rules-driven alerts as well as ML-based insights to proactively identify issues with the reliability of the solution.
It can easily integrate with solutions of all modern technology stacks, viz. .Net, Java, Node.js, Python, and Ruby. It is a unified intelligent service that can serve your entire solution.
A load balancer plays the critical role of distributing the load across multiple application instances so that the performance of the solution is optimal. Azure Traffic Manager is a DNS-based load balancer that distributes the traffic to multiple Azure regions globally based on the routing policies and health of the services.
This ensures high availability, redundancy as well as failover. It has the capability to distribute the load amongst internet-based services hosted within or outside Azure platform.
The availability, reliability, and security of a solution are as good as that of the network it is operating on. Azure Network Watcher allows you to monitor and diagnose networking issues remotely by capturing data packets and analyzing them. Apart from performance and issues, it also lets you audit your network traffic and detect security vulnerabilities and threats.
Most of the applications on the cloud are not yet containerized. SRE teams need tools that can help them spawn new instances, monitor existing instances, throttle service access, and perform other resource management tasks.
Azure Resource Manager is the perfect tool for doing all these things from a single place. It allows you to create declarative templates that can be used to deploy the entire solution along with its dependencies in the correct order.
As the footprint of the solution grows, it is important to monitor all integration points and vendor actions. Azure Lighthouse is the tool that provides you ways for controlling access and monitoring the activities.
SRE teams can leverage it to reduce the risk exposure of the solution. It also provides just-in-time access, real-time insights, and auditing features.
Enforcing the organizational policies related to security, privacy, and data governance is another key challenge that SRE teams face while maintaining the reliability of the solution.
Azure Policy works as the guardrails for governing existing and future resource deployments. It can automatically remediate any non-compliant resources.
A must for the SRE teams is to automate all the frequent, time-consuming, and error-prone cloud management tasks.
Azure Automation helps in orchestrating processes using runbooks created in PowerShell and Python. It helps you to scale up and down all your resources automatically and consistently.
#azure #microsoft-azure #azure-devops #aws-vs-azure #devops
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DevOps and Cloud computing are joined at the hip, now that fact is well appreciated by the organizations that engaged in SaaS cloud and developed applications in the Cloud. During the COVID crisis period, most of the organizations have started using cloud computing services and implementing a cloud-first strategy to establish their remote operations. Similarly, the extended DevOps strategy will make the development process more agile with automated test cases.
According to the survey in EMEA, IT decision-makers have observed a 129%* improvement in the overall software development process when performing DevOps on the Cloud. This success result was just 81% when practicing only DevOps and 67%* when leveraging Cloud without DevOps. Not only that, but the practice has also made the software predictability better, improve the customer experience as well as speed up software delivery 2.6* times faster.
3 Core Principle to fit DevOps Strategy
If you consider implementing DevOps in concert with the Cloud, then the
below core principle will guide you to utilize the strategy.
Guide to Remold Business with DevOps and Cloud
Companies are now re-inventing themselves to become better at sensing the next big thing their customers need and finding ways with the Cloud based DevOps to get ahead of the competition.
#devops #devops-principles #azure-devops #devops-transformation #good-company #devops-tools #devops-top-story #devops-infrastructure
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Collaboration is a crucial element in software development; having the right collaboration tools can make a difference and boost the entire team’s productivity. Microsoft introduced its Application Lifecycle Management product with Team Foundation Server (aka TFS) on March 16th, 2006. This software had to be installed on a server within your network and had a user-based license. To reduce the complexity of setting up and maintaining the server, Microsoft released Visual Studio Online–an Azure-based, server-hosted version of TFS. Microsoft manages and administers the servers as well as taking care of backups. To clarify its commitment to agile and DevOps, Microsoft rebranded Visual Studio Online in 2015 as Visual Studio Team Services and later as Azure DevOps in 2018.
Since its beginning, this platform has changed significantly. For example, it introduced a customizable, task-based build service, release gates, and much more. Many organizations across the world made a significant investment to run their businesses on Azure DevOps. For this reason, after Microsoft announced the acquisition of GitHub in mid-2018, GitHub announced its automated workflow system, which is much like Azure Pipelines. It’s called GitHub Actions. Due to the switch, some companies became afraid of having to migrate their practices again. In the past few months, I have gotten several questions about whether it is still worth starting new projects on Azure DevOps, especially after the release of features like GitHub Advanced Security and GitHub Codespaces (similar to Visual Studio Codespaces). In this article, I’ll clarify the differences between these two platforms, and I’ll give you some advice on how you should be using them to your advantage.
To meet the needs of companies that want to keep their data within their network, both GitHub and Azure DevOps provide a server version of their platform. GitHub version is called GitHub Enterprise Server, and the Azure DevOps version is called Azure DevOps Server. Both versions require the client to install and maintain both software and machine.
On the other hand, there is a critical difference between their cloud-hosted version. While Azure DevOps Service allows you to choose the Azure region, which is closes to your organization’s location, to decrease the eventuality of networking latency during the creation of your organization (collection of projects). GitHub doesn’t provide this feature.
At the core of GitHub project management, we can find the issues. This task can be used to track any work item, from feature to bugs, and can be sorted into a Kanban-style board for easy consultation. The issue’s description also supports markdown syntax. Adding a specific keyword #issue-number (ex: #3) can associate the issue with another one. Each issue can be assigned to multiple developers, be linked to pull requests, and have various labels assigned to it. One can link a pull request to an issue to show that a fix is in progress and automatically close the issue when someone merges the pull request.
GitHub Kanban board
#azure-devops #microsoft #azure #github #azure devops #azure devops and github