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Tag: Microsoft Azure

Dynatrace expands strategic collaboration with Microsoft
Access to Dynatrace’s Software Intelligence Platform through the Microsoft Azure Marketplace empowers global organizations to accelerate digital transformation
WALTHAM, MASS, March 16, 2021 – Software intelligence company Dynatrace (NYSE: DT) announced today an expanded strategic collaboration with Microsoft. As part of this, Dynatrace now delivers its observability platform for purchase through the Microsoft Azure Marketplace. This means Microsoft customers can now easily implement Dynatrace’s automatic and intelligent observability for their Microsoft Azure and hybrid-cloud environments through a streamlined process covering everything from procurement to automated deployment and configuration.

The collaboration also includes joint go-to-market activities, including:

Microsoft Azure customers can now use their committed Azure spend to purchase Dynatrace®.

Microsoft and Dynatrace are engaging in joint marketing, including events, sponsorships, and customer solutions workshops.

Microsoft and Dynatrace will provide their sales representatives with co-selling incentives to encourage a simple, unified go-to-market motion.

“We are pleased that Dynatrace has made their observability platform available in the Azure Marketplace, so customers can easily implement automatic and intelligent observability for their Azure and hybrid-cloud environments,” said Casey McGee, Vice President of Global ISV Sales at Microsoft. “The Dynatrace platform enables customers’ business transformation by providing real-time information about application performance and security, underlying infrastructure, and user experiences, so they can focus on driving innovation and delivering new value.”

“We designed the Dynatrace platform to enable the largest organizations in the world to accelerate their digital transformations,” said Mike Maciag, Chief Marketing Officer at Dynatrace. “Together with Microsoft, we’re making it even easier for our joint customers to build, deploy, and grow applications in Azure and hybrid environments at scale. In addition to the metrics, logs, and traces of observability, our unique approach unifies AIOps and continuous automation to help organizations innovate faster and achieve better business results with greater efficiency and confidence.”

Visit the Microsoft Azure Marketplace to get started with Dynatrace today. To learn more about how Dynatrace complements and enhances Microsoft Azure, visit the Dynatrace website.

About Dynatrace

Dynatrace provides software intelligence to simplify cloud complexity and accelerate digital transformation. With automatic and intelligent observability at scale, our all-in-one platform delivers precise answers about the performance and security of applications, the underlying infrastructure, and the experience of all users to enable organizations to innovate faster, collaborate more efficiently, and deliver more value with dramatically less effort. That’s why many of the world’s largest enterprises trust Dynatrace® to modernize and automate cloud operations, release better software faster, and deliver unrivalled digital experiences.

Curious to see how you can simplify your cloud? Let us show you. Visit our trial page for a free 15-day Dynatrace trial.

To learn more about how Dynatrace can help your business, visit www.dynatrace.com, visit our blog and follow us on Twitter @dynatrace.
March 16, 2021
Barracuda Networks Partners With Microsoft on SD-WAN Service

Barracuda Networks today launched a software-defined wide area network (SD-WAN) service that runs natively on the Microsoft Azure cloud.

Klaus Gheri, vice president of network security for Barracuda Networks, said Microsoft has made it possible to launch an SD-WAN service using Azure Virtual WAN Hubs, a networking service based on a hub-and-spoke architecture that unifies networking services such as security and routing under a common interface. Those services span branch connectivity, multiple types of virtual private networks, cloud interconnects, firewalls and encryption services.

Gheri said rather than having to replicate all those networking services, Barracuda Networks is layering a Barracuda CloudGen WAN service on top of the Azure Virtual WAN Hubs to provide a service that, like any other cloud service, can be consumed per billable hour.

Developed in collaboration with Microsoft, the Barracuda CloudGen WAN service provides the management framework needed to convert Azure Virtual WAN Hubs into an SD-WAN service that IT teams can employ to securely connect remote offices to cloud applications or on-premises IT environments, he said.

SD-WAN services today come in four basic forms. IT teams can deploy and manage their own SD-WAN appliances. Alternatively, telecommunications carriers make SD-WAN services available on their networks or a managed service provider (MSP) can create its own SD-WAN service by deploying the appliance on points of presence (PoP) on a global network it manages. More recently, cloud service providers have been making SD-WAN services available via the networks they built to connect all their data centers.

Gheri said Microsoft is now taking that SD-WAN capability a step further by adding a management portal created by Barracuda Networks.

A recent survey of 750 business and IT professionals conducted by Vanson Bourne on behalf of Barracuda Networks finds more than half (52%) are looking to employ SD-WAN services delivered via the cloud. In comparison, the survey finds 16% prefer to get SD-WAN from an independent vendor, 15% would opt for a telecommunications partner and 12% would rely on a value-added reseller.

With more application workloads moving into the cloud, the way networks are deployed and managed is evolving rapidly. Instead of connecting branch offices to local data centers to access cloud applications, more organizations are employing SD-WANs to provide direct access to cloud applications without having to backhaul network traffic through a local data center. That approach significantly improves overall application latency and, in many cases, reduces the need to rely on leased MPLS lines from a telecommunications carrier.

Rather than build those SD-WANs themselves, many IT organizations want to be able to access and manage them via a portal through which they can allocate bandwidth to applications as they best see fit. It’s not clear to what degree IT organizations will continue to prefer to deploy appliances versus consuming SD-WAN as a service. However, given the complexity of managing SD-WANs, there’s a high probability that SD-WAN services delivered via existing cloud networking infrastructure will soon become a widely employed alternative.

July 16, 2020
AWS Looks to Accelerate Windows Migrations to the Cloud

Amazon Web Services (AWS) is ratcheting up pressure on Microsoft by devoting more resources to enable IT organizations to migrate Windows workloads to the cloud.

Fred Wurden, general manager for enterprise engineering at AWS, said a Migration Acceleration Program (MAP) for Windows, now generally available, provides IT teams with prescriptive guidance, consulting support, tools, training and service credits to help reduce the risk and cost of migrating to the cloud.

The service is being delivered in collaboration with partners including Rackspace, 2nd Watch, Accenture, Cloudreach, Enimbos Global Services, Onica and Slalom. Wurden said AWS has been migrating Windows workloads to the cloud for more than a decade now and claims to have more than half of all Windows workloads deployed in the cloud.

Microsoft has clearly been making strides in recent years to close the gap between it and AWS by running both Windows and Linux workloads on its cloud alongside instances of Microsoft Office 365. Microsoft most recently reported a 39% year-over-year growth in commercial cloud revenue, reaching $13.3 billion for its fiscal third quarter. However, Microsoft does not break out Azure revenue from Microsoft Office 365 revenue or disclose what percentage of the workloads running on Azure is based on Windows versus Linux.

At the same time, Microsoft now charges more for instances of SQL Server that run on other clouds. AWS contends that decision will only accelerate the rate at which organizations are transitioning to open source databases deployed on Windows or Linux.

Competition for Windows workloads is growing in ferocity in the wake of the COVID-19 pandemic because more workloads are being lifted and shifted into the cloud as organizations realize that on-premises IT environments can be rendered inaccessible. IT staffs in many geographies will be working from home at least through the end of the year. Many organizations are also moving workloads to the cloud in anticipation of a second potential outbreak of the pandemic.

At the same time, the rate at which new workloads are being deployed in the cloud is also accelerating. Many of those cloud-native workloads are based on containers running on Kubernetes. Support for containers on Windows platforms is still relatively nascent when compared to Linux platforms.

AWS and Microsoft, along with a host of rival cloud service providers, are focusing on legacy workloads because the expectation is that monolithic workloads running on Windows will be re-engineered to run as a set of microservices that can be updated more flexibly within the context of a larger digital business transformation initiative. It may be a while before that transformation fully manifests; however, it’s clear the battle for control over millions of workloads in anticipation of that transition is reaching a higher level of intensity.

There’s no doubt many of those workloads will run on the Microsoft Azure cloud. However, the degree to which Microsoft might be winning in the cloud era may not be as great when everything that is being lost to AWS and other cloud service providers is taken into consideration.

June 4, 2020
Nerdio Unfurls Management Tools for WVD on Azure

Nerdio has launched a management tool that makes it easier to provision large numbers of virtual desktops on the Microsoft Azure public cloud.

Company CEO Vadim Vladimirskiy said that now that Microsoft is finally encouraging organizations to embrace desktop virtualization in the form of its Windows Virtual Desktop (WVD) service, there is a need for tools to manage all those desktops.

Nerdio Manager for WVD fills that gap by providing support for, among other things, dynamic host pools that automatically grow and shrink depending on workload and desktop images that can be employed across thousands of users.

Vladimirskiy said Nerdio Manager for WVD runs natively on Azure, which among other things allows all the data it collects to remain within the geo-boundaries of the selected Azure region. No additions to an Azure subscription are required to store that data, he noted.

Fresh off raising an additional $8 million in funding, Nerdio is riding the coattails of a relatively newfound enthusiasm at Microsoft for virtual desktops. While the concept of a virtual desktop has been around for the better part of two decades, Microsoft has only been encouraging IT organizations to embrace virtual desktops since the WVD Service became available on Azure in the last several months. Previously, Windows licensing restrictions tended to make virtual desktops less economically attractive.

Rather than organizations relying on Citrix or VMware for virtual desktops, Microsoft is now making a case for employing its Azure cloud service to subscribe to virtual desktops as a less complicated alternative that also supports both Windows 10 and Windows 7. That means IT teams that embrace Windows 7 on Azure will be supported by Microsoft.

It’s not clear to what degree Windows desktops will move into the cloud now that Microsoft has embraced the concept. In addition, it’s also worth noting that rivals such as Amazon Web Services (AWS) now provide similar desktop virtualization services. What is clear is many fewer instances of Windows will be running locally as more organizations determine it might be easier for them to manage Windows desktops via the cloud than on each individual machine. At the same time, many organizations are also looking at ways to more easily enable remote computing to help limit potential employee exposure to the COVID-19 virus.

Whatever the path forward, it’s not likely large enterprise IT organizations will make the jump to WVD or any other cloud service all at once. IT administrators may find themselves managing a hybrid desktop computing environment for many years to come. There are also, of course, organizations operating in highly regulated industries where virtual desktops running on a public cloud are simply not an option.

Nevertheless, it’s apparent the time when IT administrators had to spend time visiting individual desktop machines is coming to an end. The management of both virtual desktops and physical endpoints is becoming more automated with each passing day. The only real question is what degree of automation can be achieved based on where the desktop actually resides.

— Mike Vizard

March 11, 2020
Datadog Adds Support for Microsoft Azure DevOps

Datadog has added support for Microsoft Azure DevOps to its namesake monitoring and analytics platform.

Ilan Rabinovitch, vice president of product and community for Datadog, said Microsoft Azure DevOps, formally known as Visual Studio Team Services, is gaining traction as a continuous integration/continuous delivery (CI/CD) platform that can be deployed on-premises or in the cloud.

Via this integration DevOps teams that have adopted Microsoft Azure DevOps can now pull in events to create metrics from their continuous integration pipelines, and then correlate that information in real-time against Datadog is pulling from their entire stack in Datadog. DevOps teams can also configure to monitor gates in their Azure DevOps deployment pipelines, enabling them to detect and abandon bad releases automatically, said Rabinovitch.

Finally, DevOps teams can also employ Datadog to measure the efficiency of their processes by tracking, for example, how often builds are completing or failing or the frequency of code commits, added Rabinovitch.

Microsoft has been pouring significant resources into building out Microsoft Azure DevOps over the course of the last year. At the recent Microsoft Ignite 2019 conference, the company released Azure DevOps Server update 1.1 release candidate to address some bug issues before organizations deployed the platform in production environments. Microsoft also has added previews of auditing tools, extended reporting capabilities, enhanced the user interface for the repositories page to be more mobile device friendly and added more billing options.

Microsoft Azure DevOps in time will play a much larger role in the company’s bifurcated approach to hybrid cloud computing. On the one hand, the company is driving an increasingly larger portfolio of Azure public cloud services. In on-premises IT environments there is a massive base of Windows servers coupled with a nascent Azure Stack platform that provides organizations with the option to deploy the same IT environment Microsoft employs on its public cloud. The long-term goal is to make it easier for organizations to build and deploy applications across hybrid cloud computing environments using the same DevOps pipeline.

Of course, Microsoft Azure DevOps is not the only CI/CD platform that might be employed to achieve that goal. As rival CI/CD platforms continue to extend their reach into Azure and Windows environments, Microsoft will find itself competing with a small army of rival DevOps platforms that span not only Azure, Windows and Linux platforms but also rival cloud platforms such as Amazon Web Services (AWS) and Google Cloud Platform (GCP).

In the meantime, IT organizations should expect to see a host of third-party tools becoming available for Microsoft Azure DevOps as the CI/CD platform gains traction. In some cases, organizations will standardize on Microsoft Azure DevOps. In other cases, Microsoft Azure DevOps will become one of several CI/CD platforms that different teams within an organization are employing. Regardless of the CI/CD platform adopted, however, organizations that do wind up employing multiple CI/CD platforms are likely to want to consolidate as many as the monitoring tools they rely on as possible.

— Mike Vizard

January 3, 2020
How Serverless Is Impacting the IT Landscape

Although most users will never realize it, with every digital data entry and exchange servers are consuming substantial quantities of energy to file, store and sustain that data’s availability.

While the average consumer or office worker doesn’t consider the economic or environmental impact they have, IT and C-Suite teams are awakening to the problem and the awareness among energy concerns, legislators and thought leaders is growing. From the expanding troves of transactional data for AI to each video streamed on a smartphone or to a social media platform, hyperconnected companies are hungry to collect, understand, feed and leverage data on our digital habits. In today’s infrastructure models, data centers continuously burn through processing power to be ever-ready to those workloads—even when demand falls during regular off-peak periods.

That’s one of the two real pushes behind the shift from legacy to new serverless infrastructures: waste, both environmental and economic.

The world is waking up to the realization that the digital economy is consuming disproportionate levels of energy, putting new pressures on their organizations, their region’s energy infrastructures and, ultimately, on the planet.

A recent report from Climate Change News predicts billions of internet-connected devices could produce 3.5% of global emissions within 10 years and the communications industry could use 20% of all the world’s electricity by 2025. In fact, data from statistics portal Statista notes the energy consumption of Facebook usage alone amounted to about 2.46TW hours in 2017, compared to 532GW hours in 2011.

In the U.S. alone, data centers consume an astounding 90 billion kWh of electricity per year, the approximate annual output of 34 (500MW) coal-burning power plants. The data center consumption costs are baked in—organizations pay for always-on computing power to meet peak need regardless of how demand may fluctuate.

The Promise and Potential of Serverless

Cutting Energy Consumption: Serverless compute technology such as Amazon’s AWS Lambda or Microsoft’s Azure Functions are native cloud architectures designed to decrease consumption and increase agility and innovation.

It provides a more efficient function-as-a-service (FaaS) consumption model that enables organizations to pay for what they use, rather than constant peak demand charges.

Some of the economic impacts of serverless are obvious: Organizations that host their own servers have reconciled themselves to paying for those servers running at full power while sitting idle for much of the time. It’s like keeping your car constantly running, regardless of whether you’re going anywhere.

In contrast, serverless not only promises far greater energy efficiency from the macro-infrastructure perspective, it also is event-driven. Organizations pay by the computing power consumed, so their costs reflect their actual server usage rather than paying for always-on capacity.

The Shift Is On, From Managing Infrastructures to Solving Problems

Reduced energy consumption and cost efficiencies are important for organizations and the planet. Two other major promises serverless offers are the ability to let organizations focus on creating applications and services without chaining them to infrastructure and innovation opportunities.

Organizations shift the focus of their IT resources away from infrastructure maintenance—the provisioning, patching, operating system maintenance, managing runtimes and capacity planning overhead—to solving business problems. This means the focus of the organization’s IT resources can shift from managing infrastructure maintenance burdens to doing what IT was always meant to do: solve actual business problems.

But there’s another aspect to serverless that’s even more exciting.

Unlocking ‘Vendor Lock’ and Unleashing Innovation

Every great technology breakthrough inevitably tears through old barriers and accelerates innovation. Serverless is no different.

Furnace is a good example. It’s a new open source, serverless, streaming data processing platform for building big data solutions that are cloud platform and language-agnostic.

It supports the use of applications that run natively in AWS Lambda, Microsoft Azure and Google Cloud, passporting data between platforms. Using coding languages including JavaScript, Node, Python and Golang, a growing community of developers are creating constructs to connect cloud-based applications.

Some of the most urgently needed application construct types we’re likely to see in the near term will be for extracting and anonymizing old proprietary data for GDPR compliance, and for honeypot data collection and manipulation, with Elasticsearch and Redshift. Other application foundational on-ramps are in development.

According to Danny Waite, CTO for the Furnace Ignite organization, the Serverless Furnace source platform was architected to allow deployment and data traversal into and across various cloud, on-premises and hybrid environments, putting the underlying efficiencies of serverless to work on practical applications.

The application development platform is optimized to ingest massive volumes of data from different sources and in various formats. The Furnace open source community is soliciting feedback and community developers are working on various projects, with plans for constructs to harness and tap into the massive stores of now-untouched IoT data, among other sources.

Greener, Cleaner, Streamlined Computing

Serverless is a driver for ecologically greener, operationally cleaner and innovation-driving new computing. Its reduced data-center energy consumption, pay-per-use event-driven model, openness to innovation and seemingly unique ability to help align historical data with new regulatory requirements are all arguments for a shift in thinking and embrace of serverless. The improved economics are another compelling reason, though likely not a primary one for data-driven organizations.

Serverless communities such as Furnace Ignite are emerging with tools and techniques for adoption. The Furnace application development platform has been architected in a way that allows it to be deployed into various infrastructures, such as cloud, on-premises or within hybrid environments, with the ability to ingest huge volumes of data from different sources, in various formats, so developers can take that data and make it useable. The whole process can be done with speed and agility and removes all the nuances normally associated with working with streaming data.

Serverless platforms such as Furnace will continue to be developed to drive DevOps and meet the needs of the opensource community.

— John Blamire

July 23, 2019
RDX Eases Oracle Database Migration to PostgreSQL on AWS

RDX this week launched a set of tools designed to make it easier to convert applications running on an Oracle database to Amazon Aurora, an instance of an open source PostgreSQL database running on the Amazon Web Service (AWS) cloud that is compatible with Oracle databases.

Announced at the AWS Summit event in Washington D.C., the clckwrk Refactoring Service for Oracle promises to reduce the amount of manual effort associated with refactoring applications for the Amazon Aurora platform by automating as much as 60% of the database schema conversion process.

James Ball, chief strategy officer for RDX, said in addition to reducing costs, many organizations want to shift applications to open source databases in the cloud to further their DevOps ambitions. Each time an application needs to scale, an organization will incur additional Oracle licensing fees. In contrast, an open source database enables DevOps teams to scale database instances as required automatically, he said.

AWS has been making a concerted effort to convince customers to give up proprietary databases in favor of open source databases running on its cloud platform. That competitive pressure is a driving force behind new alliances that previously would have been considered unimaginable. Oracle, for example, recently partnered with Microsoft to promote the integration of the Oracle Cloud platform with the Microsoft Azure cloud. Oracle would prefer its database run on its cloud, but through the alliance is signaling its willingness to work with Microsoft to deploy Oracle database on Azure, a cloud platform that is the leading industry alternative to AWS. Microsoft, of course, has its proprietary database to adopt in the form of Microsoft SQL Server.

Ball said RDX not only provides tools to accelerate the conversion to Amazon Aurora, but it also provides managed services for customers that want to outsource the management of Amazon Aurora to RDX.

It takes most organizations several months to migrate a legacy application on to a public cloud. AWS has a vested interested in helping accelerate that process whenever possible. But many organizations that have embraced best DevOps practices find their efforts are hampered by reliance on proprietary databases. In fact, one of the reasons so many developers tend to favor open source databases is to avoid all the headaches associated with getting approvals for new database licenses.

It’s unclear to what degree the rise of DevOps in the enterprise will ultimately shift database allegiances. Oracle is trying to maintain as much control as possible by making its databases available as a managed service that eliminates some of the purchasing overhead associated with spinning up new instances. However, the cost of an Oracle database license is still buried in the cost of the managed service.

Not every organization is looking to transition away from a proprietary database, but there is now enough momentum around the “open source first” movement to make it worthwhile to build tools that automate the refactoring of legacy databases not just to reduce costs, but also to make IT a lot more agile.

— Mike Vizard

June 13, 2019
Pre-Commit Job Workflow in Azure DevOps
Many organizations use a combination of open so Many organizations use a combination of open source and commercial tools and Azure DevOps (formerly called VSTS) and an application lifecycle management (ALM) tool that includes features such as Azure pipelines. This article talks about how to achieve an end-to-end DevOps setup in Azure

Pre-requisites:
1. Subscription
2. Project created with version control selected
3. Process template selected (Agile/Scrum)
4. Code repo–one on VSTS and one on GitHub/cloud GitLab
5. Build server–Use credits from MSDN subscription
6. Deploy–Azure subscription from MSDN
7. Other tools–tools supported by VSTS/Azure DevOps
- The objective of a pre-commit job is to reduce the risk of complexities, duplications and potential bugs in the code to get deployed directly into production.
- In usual workflows, the build will be generated on regular intervals and released for testing. However, there is a chance of several code quality issues and building deployment issues.
- With the help of pre-commit job, we can configure triggers to generate builds for every pull request made by developers. Also, this enables the development team to create pull request releases that deploy your pull request code or pull request builds, which help to detect deployment/release issues before the code changes are merged.
- Pre-commit deployments also help catch deployment/release issues early in the cycle, maintain better code quality and release with higher confidence.
Configuring Agile Board in Azure DevOps for Project Management, and Tracking Steps to Do It

Steps:

With Azure Boards we can plan, track and discuss work across different teams. With Azure Boards, we can swiftly and simply start tracking tasks, features and bugs of our project.

For every project we have to create on sprint, go to Boards and select Work Items to create a new user story and provide the acceptance criteria. Select Boards and create New Work Items, then under Epic select User Story and click on Task and provide the task description.

Setting Up Branches, Version Control and Branch Policies

Steps:
- Import the code from VCS.
- Under Repos, create branches such as dev or test.
- Set up the branches policies to improve code quality.
Improve Code Quality With Branch Policies

Branch policies help teams protect their important branches of development. Branch policies enforce a team’s change management standards and code quality.

Setting up Branch Policies for Review Code

Code reviews are good practice for the most successful software development projects. We have to configure the minimum number of reviewers to review the code and complete the pull request.
- The code review done in a pull request is simply to find obvious bugs.
- Code reviews help protect the team from bad commits or merges and broken builds that hinder team’s productivity.
The review will help to catch these kind of problems before the merge, protecting our important branches, such as the release branch, from undesirable changes.

Pre-Commit, Enabling Pull Request

Steps:

Workflow to complete the pull request:
- Create a pull request
- Complete a pull request
Benefits of pull request:
- Peer review
- Enough testing and better stability
- Reducing conflicts
- Continuous delivery
- Clearer responsibility
Create a pull request:
- Pull requests combine the review and merge the code into a single collaborative process.
- For every bug fix or new feature in a branch, we have to create a new pull request.
- Add the members of the team to the pull request once the development branch build is completed without issues. Then members can review and vote on your changes.
Link work items to your pull request:

Select the Overview tab in Azure DevOps. Select the add link button “+” in the Work Items to relate your current pull request.

Complete Pull Request:
- The basic policy requires that some reviewers approve the code with no rejections.
- If Allow users to approve their own changes is not selected, the creator of the pull request can still vote Approve on their pull request, but their vote won’t count toward the Require, least reviewers policy.
- If any reviewer rejects the changes, the pull request cannot be completed unless the allow users selection is completed, even if some reviewers select Waiting or Reject.
- To reset code reviewer votes when new changes are pushed to the source branch, check Reset code reviewer votes when there are new changes.
Nightly CI Build

Steps:

Build Triggers:
- We can configure the build triggers to generate war package for every code commit made to the branch.
- Under Build select Triggers to enable CI and include master branch.
- One can enable the build trigger for every commit made to the branch.
- Configure two builds—one for dev branch and one for master branch.
- If the developer executes the code, the dev branch build is triggered automatically with help of dev branch polices.
- Once the dev branch build is completed, reviewers approve the pull request and the master branch build is triggered. Once the build is completed, it moves to the release part.
- The code quality analysis and unit test/Junit test is configured in the dev branch. The code quality gateways such as code review and find bug have been enabled.
Continuous Deployment (Release) through Azure Kubernetes Services (AKS)

Pre-requisites:
- Any source code management tool such as Git/SVN or Azure Repo
- Microsoft MSDN account
- Azure account creation and VSTS/Azure DevOps account creation
- Dockerfile to be created and placed along with source code in Git
- YAML file to be created and placed along with source code in Git
- Kubernetes cluster to be created in Azure portal
- Docker hub account or Azure Container Registry
- Build definition–Docker build image
Docker File Creation for Application to Deploy

Create the Service Principle to provide the access to the application/Docker image to deploy on Azure Kubernetes services. Select the Deploy to Kubernetes task and make the following configurations:
- Create new Kubernetes service connection
- Select the command option for deployment
- Provide the configuration file location i.e, Deployment.yaml
- Select the container registry type
- Select the subscription
- Select the Replace Tokens task to append the tag number for an image automatically while pushing it to container registry
- Perform the deployment and view the logs
Test plans:

Load testing:

Pipeline History

Azure Pipelines is used to automatically build and test your code project and make it available to other users. Azure Pipelines integrates CI and CD to continuously test and build your project and ship it to any target server. It provides the full-stack end-to-end flow of CI and CD through various tools integrated as tasks in Azure DevOps.

Conclusion

With Azure DevOps, you can set up end-to-end DevOps with tracebility, pre-commit, CI and deployment to Kubernetes.

This article was co-authored by Srinivasa Rao Guntupalli, lead engineer at HCL Technologies Ltd. He works on various DevOps technologies such as Git, maven, Jenkins and cloud technologies including AWS, Azure, Azure DevOps/VSTS.

— Naveen Manchem
June 5, 2019
Logz.io Unveils Azure Open Source ELK Monitoring Solution

Needless to say, DevOps as a practice is largely fueled by open source. The growth and popularity of open source tools such as Elasticsearch, Kubernetes and others are driven largely by the increased flexibility, innovation and familiarity of options. While this isn’t news for developers (65% of which are active open source contributors), leading cloud providers are taking notice, as they try to increase their appeal to DevOps engineers to finally win the cloud wars.

Currently, AWS is the leading cloud provider. However, with Azure gaining more and more momentum, all three major cloud providers are scrambling to offer their customers the best open source options and empower them to use the tools they know and love in a manner that is convenient and native to their cloud environments.

Going Big on Open Source

Today, Logz.io and Microsoft Azure announced that our ELK-as-a-service will now be offered on Microsoft Azure. Logz.io offers an intelligent machine data analytics platform built on ELK and Grafana, two of the most popular open source monitoring and troubleshooting tools. Our platform enables engineers to easily deploy, run and scale ELK without the hassle and pain of maintaining and managing the stack themselves.

Now, with Logz.io for Azure, users can use open source ELK as a highly integrated experience in Azure. The new offering includes seamless integrations to various Azure services, out-of-the-box Azure dashboards, built-in alerting and crowdsourced machine learning capabilities.

The integration between Logz.io and Azure is not only significant in the context of the cloud wars, but in the culture of Microsoft itself. While the company was previously associated with a more proprietary structure, they have made tremendous strides in recent years toward empowering open source by opening its .NET framework and Azure SDK, as well as their acquisition of GitHub.

According to Julia Liuson, corporate vice president of Microsoft’s developer division: “At Microsoft, we see open source as a major driver of innovation within the engineering community. Since we strive to empower our customers and facilitate their success, it is important to us to meet them where they are by making it easy to access and use open source tools. Our partnership with Logz.io will strengthen Microsoft Azure ties with the developer community, enabling teams to easily build and monitor their products using ELK.”

AWS vs. Google Cloud

Microsoft’s investment in ELK comes just in time to provide an answer to its competitors, AWS and Google Cloud. Just two months ago, AWS announced Open Distro for Elasticsearch, which in their own words “is a value-added distribution of Elasticsearch that is 100% open source (Apache 2.0 license) and supported by AWS.” The new offering includes managed Elasticsearch and Kibana along with features such as built-in alerting, security and more. This was AWS’ most recent appeal to the engineering community, offering one of the most popular monitoring tools as a managed service on AWS.

Following this release, Google Cloud announced its own open source offering featuring integrations with leading companies such as Elastic, MongoDB, Confluent and more. According to Google, the purpose of these integrations was to “provide users with a seamless user experience and the ability to easily leverage these open-source technologies in Google’s cloud.”

Is Open Source the Future?

If what’s happening between cloud vendors is any indication of future trends in the engineering space, it seems imperative that all organizations targeting DevOps teams must consider how they’ll fuel open source and empower its vast user community. At Logz.io, we are proud to be part of this initiative.

Overall, it is great to see the strides large organizations are taking in furthering the interests of the developer community and enabling them to work using the tools, methodologies and strategies that best suit their workflows and ideals.

— Daniel Berman

May 7, 2019
Deploying into Azure App Service using Azure DevOps CI/CD Pipeline
This article demonstrates how to deploy an application into Azure App Service using Azure DevOps (VSTS) continuous integration/continuous delivery (CI/CD) pipeline.

In this article, you’ll create a sample environment to:
- New build based on code commit to your Azure DevOps Repo.
- Automatically deploy your app into Azure.
Prerequisites:
- Azure Portal Account, Azure subscription and Azure DevOps (VSTS) account.
- Azure Resource Group.
- Create a web app in Azure. Make note of the app service URL—you need it later.
What is Azure App Service?

Azure App Service enables you to build and host web apps, mobile backends and RESTful APIs in the programming language of your choice without managing infrastructure. It offers auto-scaling and high availability, supports both Windows and Linux, and enables automated deployments from GitHub, Azure DevOps or any Git repo.

Creating Resource Group in Azure

Once you have a subscription in Azure, you need to create a resource group to manage resources in Azure. The best practice is to maintain a separate resource group for each environment (DEV, INT, QA, STAG, PERF, PROD) and follow the proper naming conventions. To create a resource group, select Resource Group from left-side blade, click on +Add, then select Subscription, give a proper name to the resource group and click on Review + Create.

Creating App Service

Click on All resources from the left-side blade of the panel and click on Add, then select Web App and give a proper name to your app service. Then select Subscription and select the existing resource group. Keep the remaining option as default. and click on Create.

Once you have created the app service, click on that app service and go to Overview. There you can identify all the details that belong to this app service, including status, resource group, subscription and URL (please make a note of this; you’ll need it later).

Creating Service Principal

When an application needs access to deploy or configure resources through ARM or VSTS in Azure, you’ll need to create a service principal, which is a credential for your application.

Go to Azure Active Directory -> App registrations -> New application registration, then give a name to the service principle, select application type and give it a URL of your choice. After creating the app registration, go to Settings from that service and make note of application ID, then go to Keys create a key and copy the secret value. (Note: It doesn’t appear later, so please store it in safe place.)

Create a New Project in VSTS

The first step is to create an account in Azure DevOps (VSTS), then follow the steps below to start an application deployment. Here I’m taking sample open source java-based code from GitHub repository and importing it to Azure DevOps repo. (You can push your own source code into repo.) It is a simple multi-module Maven project. The application is a very simple online version of Conway’s “Game of Life.”

To create a new project, click on Create new project, give a proper name to your project and select create. Then go to Repos, click on Import, then select source type, type in the above URL in the Clone URL tab and select Import. The source code will import into your repository.

We need give service connections to our project, so go to project settings from the bottom of blade in our project home directory and then select Service Connections -> New Service connection -> Azure Resource Manager. Click on “Use the full version of the service connection dialog” from the pop-up, then paste the Application ID into the Service principal client ID tab and the secret key value into the Service principal key tab (which you saved during app registration creation). Then click OK.

Creating a Continuous Integration (CI) Build

Go to Pipelines -> Build -> New Build Pipeline, then click on “Use the visual designer.” It will ask source code repo details, so select Azure Repos Git and select Team project, which you created at the start of the project, select Repository and branch name, then click Continue.

Next, select a template Maven, type in the pipeline name and select Hosted VS2017 for the Agent pool, and click on pom.xml in the Maven POM file. There you can list the goal(s) as Clean Package and select Copy Files. At the contents section please enter **/*.war then go to Publish Artifact: drop, list the artifact name as Gameoflife and keep all remaining options as default values. Then, under Triggers, select Enable continuous integration and give branch filters listed at right, which enables the continuous integration feature. Once a developer commits their changes into master, the CI build will trigger automatically.

Once the configuration is complete, click on Save and Queue from top of pipeline to trigger a CI build. (Every commit into master will trigger a new build.)

Creating Continuous Delivery (CD) Pipeline

Go to Pipelines -> Releases -> New Release Pipeline, then select the template Azure App Service deployment, list the stage name as DEV and click on Add an artifact. Select project and source (build pipeline), then select default version as Latest, click on Add. Cick on Task (below the DEV), select Run on agent and select agent pool as Hosted VS2017, then click on the plus(+) symbol, search for template File Rename and select the .war file from source file and give it the new name ROOT.war.

In the Display name box, list Azure App Service Deploy. In the Azure subscription field, you need to select a service principal name to authorize the resources. Then choose the App type and App Service name. In the Package or folder selection, select war file and rename it ROOT.war, because for java-based applications we need to deploy our app into a proper directory structure.

Finally, select the template Azure App service manager and select the Restart option, making sure to select the same subscription and app service name you selected in the Azure app service deploy window. Click on Save, then click on Release -> Create a release -> select artifact build number -> create. Build will then trigger and deploy into the app service.

Now, your code is successfully deployed into Azure App Service.

You can access using app service URL from any browser (e.g., https://xyz-abc-webjob-01.azurewebsites.net) and you can check whether code is deployed successfully or not using below URL: https://xyz-abc-webjob-01.scm.azurewebsites.net.

— Srinivas Kudipudi
February 19, 2019