Welcome to The Long View—where we peruse the news of the week and strip it to the essentials. Let’s work out what really matters.
This week: Google complains to the FTC about Microsoft market abuses, and new graduates don’t know how to office. (more…)
Azure migration refers to the process of moving applications, data and other resources from on-premises or other cloud environments to Microsoft Azure, which is a cloud computing platform and service offered by Microsoft.
Azure migration can include migrating virtual machines, databases and storage to Azure, as well as re-architecting applications to take advantage of Azure services. Typically, the goal of Azure cloud migration is to take advantage of the scalability, security and cost benefits of the Azure platform.
Here are several tools provided by the Azure cloud which can help you migrate applications to the Microsoft cloud.
Azure Migrate is a service offered by Microsoft as part of Azure that helps customers discover, assess, and migrate their on-premises workloads to Azure. It provides a centralized hub for the discovery and assessment of on-premises workloads and helps customers plan and execute their migration to Azure. Azure Migrate includes the following features:
By using Azure Migrate, customers can move their workloads to Azure with confidence, knowing that they have a comprehensive plan and the right tools in place to ensure a successful migration.
Azure Database Migration Service (DMS) is a fully managed service offered by Microsoft as part of Azure that simplifies and accelerates the process of migrating on-premises databases to Azure. The service supports a variety of databases, including SQL Server, Oracle, MySQL, and PostgreSQL.
Azure DMS can perform both online and offline migrations, depending on the requirements and availability of the source database. Online migrations are performed while the source database is still in use, while offline migrations require the source database to be taken offline during the migration process.
The service supports several migration scenarios:
The Azure DMS provides a simple and efficient way to move your on-premises databases to Azure with minimal downtime, and it’s integrated with Azure Migrate for a holistic migration experience.
Azure Data Box is a service offered by Microsoft as part of Azure that allows customers to transfer large amounts of data to Azure for storage and processing. The service is designed for customers who have a large amount of data that needs to be transferred to Azure, but have limited network bandwidth or other constraints that make it difficult to transfer the data over the Internet.
Azure Data Box provides customers with a physical device (called an “Azure Data Box”) that they can use to transfer data to Azure. The device is shipped to the customer, who can then copy data to the device and ship it back to Microsoft. Microsoft will then transfer the data to the customer’s Azure storage account.
There are several different types of Azure Data Box, each with different storage capacities and data transfer speeds:
Azure Data Box is particularly useful for customers who have large amounts of data to transfer, and don’t have the network bandwidth or other resources to transfer the data over the Internet.
Azure Synapse Pathway is a new feature of Azure Synapse, which is a fully managed cloud-based data integration and analytics platform. Azure Synapse Pathway is designed to make it easy for customers to move their existing data integration and analytics workloads to Azure Synapse without requiring significant re-architecting or rewriting of their existing code.
Azure Synapse Pathway supports several migration scenarios, such as:
Azure Synapse Pathway also provides a migration tool that helps customers to move their existing data integration and analytics workloads to Azure Synapse, with minimal changes to their existing code. This allows customers to take advantage of the benefits of Azure Synapse without significant re-architecting or rewriting of their existing code.
Understanding your digital estate is an important part of creating an effective Azure migration strategy. A digital estate refers to the collection of digital assets and resources that an organization uses to run its business, including applications, data, and infrastructure. In order to migrate your digital estate to Azure, you need to understand what you have and where it’s running. This information can be used to create a migration plan that is tailored to your specific needs.
To understand your digital estate, you should start by creating an inventory of your applications, data, and infrastructure. This inventory should include information such as:
Once you have an inventory of your digital estate, you can use it to create a migration plan that takes into account the specific needs of each application, as well as any dependencies or constraints that need to be considered.
Best practices for inventorying your digital assets:
By understanding your digital estate and creating a migration plan that takes into account the specific needs of your applications and data, you can ensure that your migration to Azure is successful and that your business is able to continue to operate during and after the migration.
Estimating the monthly costs of your workloads is an important part of creating an Azure migration strategy. By understanding the costs associated with running your workloads in Azure, you can make informed decisions about how to migrate your workloads and how to optimize your cloud costs after migration.
To estimate the monthly costs of your workloads in Azure, you can use the Azure pricing calculator. The pricing calculator allows you to estimate the costs of running various Azure services, such as virtual machines, storage, and networking, based on the specifications of your workloads. You can also use the Azure TCO calculator to estimate the total cost of ownership of your workloads in Azure, taking into account costs such as data transfer, management, and support. There are multiple other Azure calculators you can use to estimate storage costs, networking costs, and more.
Image Source: Azure
When estimating the costs of your workloads in Azure, it’s important to consider the following factors:
It’s also important to consider how the costs of your workloads may change over time, such as how the number of users and usage patterns may change or how the costs of Azure services may change.
Best practices for estimating the monthly costs of your workloads in Azure:
By understanding the costs associated with running your workloads in Azure, you can create a migration strategy that is optimized for cost and that enables you to get the most value from your investment in Azure.
Migrating your workloads to Azure and optimizing them for the cloud environment is an important step in creating an Azure migration strategy. Once you have a clear understanding of your digital estate and have estimated the costs of running your workloads in Azure, you can begin migrating your workloads and optimizing them for the cloud.
There are several ways to migrate workloads to Azure, depending on the type of workload and the migration requirements. Some common migration methods include:
Once your workloads are migrated to Azure, you can optimize them for the cloud environment by:
Best practices for migrating your workloads and optimizing for the cloud environment:
By following these best practices, you can ensure that your workloads are migrated to Azure and optimized for the cloud environment, which will help you to get the most value from your investment in Azure.
Monitoring is an important part of creating an Azure migration strategy and ensuring that your workloads are running efficiently in the cloud. By monitoring your workloads, you can identify and address issues that may arise during or after migration and ensure that your workloads are meeting the needs of your business.
Azure provides a variety of tools and services for monitoring your workloads, including:
When monitoring your workloads in Azure, it’s important to consider the following factors:
It’s also important to consider how your monitoring needs may change over time, as your workloads and usage patterns may change.
Best practices for monitoring your workloads in Azure:
By monitoring your workloads in Azure, you can identify and address issues that may arise during or after migration, and ensure that your workloads are meeting the needs of your business. This will help you to get the most value from your investment in Azure and ensure a successful migration.
In conclusion, migrating to Azure is a great way to take advantage of the scalability, security, and cost benefits of the cloud. However, migrating your workloads to Azure requires a well-planned strategy that takes into account the specific needs of your business and your digital estate.
To create an effective Azure migration strategy, it is important to understand your digital estate, estimate the costs of running your workloads in Azure, choose the right strategy, and optimize them for the cloud environment.
Additionally, monitoring your workloads in Azure is crucial to ensure that they are running efficiently, and to address any issues that may arise during or after migration. By following best practices and using the tools and services provided by Azure, you can ensure a successful migration and get the most value from your investment in Azure.
Red Hat this week announced that a private preview of the Red Hat Ansible Automation Platform is now available on the Microsoft Azure Cloud.
Tom Anderson, vice president of Red Hat Ansible automation, said making the Red Hat instance of the open source automation framework available on Azure is the first step toward making it possible for IT teams to use the IT automation framework across multiple clouds.
The goal is to make it simpler for IT teams to bridge multiple IT environments using a common framework to automatically configure everything from operating systems to security platforms across a hybrid cloud computing environment.
Ansible is emerging as a de facto standard for automating IT environments largely because it provides an IT team with a declarative approach to automating IT processes. An IT team can write a playbook that describes their desired state for a platform without having to know anything about its current state.
Interest in IT automation has soared as the number of workloads being deployed in the cloud and on-premises IT environments have steadily increased. The simple truth is that many organizations can’t keep pace with the rate at which applications are built and deployed because they are unable to hire and retain enough IT staff. The challenge is that writing a playbook to automate any IT process requires a fair amount of expertise that many organizations lack. There are, however, now large numbers of existing templates that organizations can reuse.
Anderson also noted that security concerns will also force the IT automation issue. Many of the application workloads running in cloud computing environments are misconfigured because they were provisioned by developers that have little to no security expertise. A playbook greatly reduces the chances an application workload will be misconfigured in the cloud without having to turn every developer into a security expert, Anderson explained.
Ultimately, IT automation frameworks reduce the level of friction that often exists between developers and the rest of the IT operations team in a way that actually serves to increase developer productivity, added Anderson.
Regardless of how IT organizations automate IT processes, it’s now a question of the rate at which that goal will be achieved rather than if. DevOps teams, of course, have always been at the forefront of automation, but now it’s clear that as IT environments become more complex, IT organizations are embracing automation more aggressively. Most of those initial efforts are focused on repetitive, tedious and manual IT tasks, but the potential to automate IT processes at levels of unprecedented scale has never been greater.
In fact, many organizations may soon discover it’s difficult to retain IT professionals without investing in automation. After all, the most talented IT professionals will not want to work for an organization that requires them to always manually configure IT resources. Many IT teams might also discover that automation frameworks like Ansible are the gateway to embracing additional DevOps best practices. The challenge, of course, is finding the time to get started automating processes when there are so many immediate issues that IT teams can’t ignore.
A recent CloudBolt survey on IT sustainability finds that sustainability is no longer just a buzzword — the market is demanding real change, and it appears that environmental concerns finally are influencing large IT investments. For example, 67% say that a cloud provider’s sustainability initiatives are important in deciding whether to do business with them. A significant portion of organizations are even willing to pay a premium to support green initiatives!
Below, I’ll review the report to find its major takeaways. We’ll see how sustainability is directing real action in cloud IT and briefly compare how the market perceives current green initiatives among three top cloud providers: AWS, GCP and Azure.
In June and July 2021, CloudBolt polled 256 global CxOs and tech leaders on its Pulse platform, and found that 76% of respondents now consider climate change an existential threat. Not only are IT purchasers factoring compute and cost, but a sustainability conscience is now influencing executives to direct sweeping change. In fact, 79% of respondents indicate their IT departments are expected to help their companies achieve specific sustainability initiatives driven by the board of directors of the C-suite.
Interestingly, other studies found that a sustainability commitment results in tangible business outcomes. For instance, 88% of the research conducted by Oxford University and Arabesque showed that solid environmental, social and governance (ESG) practices result in better operational performance of firms and higher profits. This study also noted that 80% of the time, a company’s stock price is positively influenced by sustainability practices.
Most organizations now consider a cloud vendor’s sustainability initiatives when choosing whether to do business with that provider. A full 78% of respondents agree that the public/private cloud choices they make can materially affect the environment for better or worse. New environmental cloud commitments not only attempt to minimize carbon emissions from their data centers but factor in ecological ramifications and aim to erase companies’ historical carbon footprints, as well.
Cloud consumers also want to contribute to addressing these green initiatives. An impressive 79% of respondents indicate that they will pay a premium to work with vendors who incorporate sustainability into their business. And 41% of companies are willing to pay a premium of 11 % to 15% of their current bills. This shows that sustainability is now a vital factor within the marketplace, and companies are willing to pay the price to increase their own environmental standing.
Though this commitment is undoubtedly growing, the report did find that operational requirements such as security, cost and agility, still rank significantly higher than sustainability when comparing cloud providers. Though IT professionals recognize climate change as an existential threat, they still have day jobs and must keep operations moving.
Slightly more than half (51%) of respondents agree that the industry-wide green energy commitment is real and growing among all cloud providers. However, when comparing the top three—Amazon Web Services (AWS), Azure and Google, AWS appears to be emerging as an IT sustainability leader; 41% of respondents perceived AWS as doing the most to address green initiatives.
AWS is on track to power its entire operations with 100% renewable energy by 2025. With their solar plant investment in April 2021, Amazon became the largest corporate buyer of renewable energy in Europe. Around the globe, AWS has invested in a combination of on-site solar, solar farms and wind farms to power their data centers and Whole Foods divisions.
To their credit, both Microsoft and Google also committed to climate pledges that affect their cloud footprint. Azure supports a similar initiative to reach 100% renewable energy by 2025, in addition to further investments to improve water, waste disposal and surrounding local ecosystems. Google Cloud’s commitment is to operate on carbon-free energy 24 hours a day by 2030, and the company has already achieved 100% renewable every year since 2017.
Not only does AWS appear to be doing the most to address its environmental impact, it also retains the most market traction as a cloud leader. The majority of respondents (62%) said that AWS is winning the cloud wars while only 31% said Azure and just 7% said GCP.
It is heartening to see that ESG standards are having a measurable impact on a company’s cloud allegiances. The market now demands real change and is willing to pay the price for more ethical and sustainable cloud hosting.
But choosing a cloud provider is only one aspect of reducing IT’s impact. As I’ve covered before, there are many ways IT can curb its climate impact. Such actions include optimizing overall infrastructure, shuttering zombie VMs, avoiding over-provisioning resources, increasing performance visibility, refactoring code and other measures. What’s great is that most of these initiatives have the added benefit of reducing cost to the business.
The CloudBolt Industry Insights Report, The Truth About IT Sustainability: Paying More Green to Get More Green, surveyed 256 IT leaders on their perception of cloud sustainability. For additional insights, you can pick up a copy here.
As IT’s digital footprint grows, its cloud footprint is rising both in size and complexity. As a result, most organizations have matured into multi-cloud operators. A multi-cloud approach empowers different divisions with the autonomy to select the right computing environment for their needs. It also enables a lift-and-shift ability to port workloads across cloud service providers (CSPs) when needed. Adopting a multi-cloud model could bring performance benefits, cost savings or better scalability, all while encouraging a more vendor-neutral stance.
We’re in a multi-cloud world. A recent HashiCorp study found three out of every four organizations are already multi-cloud. This is a staggering increase from just a few years ago when mono-cloud was more accepted, and operators had zombie-like allegiance to AWS. The uptick in multi-cloud signals the maturity of offerings at other CSPs, like Azure and GCP. It also signals differentiation among clouds as each hones in their unique value propositions.
HashiCorp’s inaugural State of Cloud Strategy Survey offers some very clear results about the state of multi-cloud adoption. Below, I’ll review major takeaways from the report to better understand the state of multi-cloud adoption. To sum it up, large organizations tend to benefit most from multi-cloud adoption, as there are still significant roadblocks to truly reaping a sizable return from a multi-cloud status. Yet, more infrastructure automation may help companies of all sizes respond to multi-cloud complexities.
DevOps truly operates in a multi-cloud era. The report revealed 76% of organizations are already multi-cloud; that leaves only one in four companies leveraging a single cloud. And, that trend won’t stop—within two years, 86% predict they will be multi-cloud operators. The study also confirms that the larger a company is, the more likely it will adopt multi-cloud—94% of large enterprises with 5,000 or more employees are multi-cloud.
So, what’s driving this cloud fragmentation? Well, 34% of respondents cite digital transformation as a top driver for multi-cloud adoption. In the race to meet new digital innovation demands, multi-cloud has emerged as a strategic force. To enact this rapid change, many organizations are investing in a cloud center of excellence (CCoE) to guide cloud transformation efforts. A CCoE is most common within large companies with a cloud budget of $5 million or more.
Speaking of budgets, cloud spending is going through the roof. In 2020, only half of companies met their projected cloud spend, and 39% of companies overspent their allotted cloud budgets. As I’ve covered before, cloud-native costs are notoriously difficult to identify and trim. Without the proper guardrails to manage spending, surprise data egress fees or hidden server costs can strain the cloud checkbook. As it stands now, 40% of companies lie in the $100,000 to $2 million per year range, and 6% of enterprises are investing $50 million a year or more into multi-cloud. This spending will likely increase in the coming years as cloud reliance expands.
So, which clouds are companies using? If we compare cloud adoption, AWS is a clear market leader; 88% of companies use AWS, 74% use Azure and 61% use GCP. AWS’s hegemony is not expected to fade in the next two years. Yet, while AWS usage will remain the same, competing CSPs will experience modest increases. This is likely due to Azure and GCP making gains in geographical zones outside North America, such as Asia-Pacific and Africa.
In terms of technology used in cloud environments, open source software (OSS) is a popular choice. Cloud-native open source projects, such as Kubernetes, OpenStack and Terraform, have taken on a life of their own, with vibrant community support. However, not all shops build upon OSS and run it themselves. Somewhat ironically, we’re seeing more managed OSS emerge. One stand-out area is provisioning, where 42% of organizations build with open source and run it themselves.
On the whole, multi-cloud is working at most enterprises, with 53% of survey respondents saying multi-cloud has helped achieve their business goals. The top benefit of multi-cloud is digital transformation, at 34%. This is followed by avoiding lock-in (30%), reducing cost (28%) and scalability (25%). But multi-cloud does not treat all companies as equals; the likelihood of multi-cloud success increases as the company size increases. Less than half (42%) of small companies say they have multi-cloud success, which jumps to 64% for large enterprises. With fewer resources for support, multi-cloud may be less beneficial for startups and small to medium businesses. In fact, 41% of professionals say a lack of in-house skills inhibits their cloud success.
An ongoing talent gap is just one potential challenge to cloud success. Just over half (51%) say cost concerns are a top inhibitor to their cloud program success. Hybrid cloud complexity is another prominent challenge, with 35% of organizations citing it as a major cloud obstacle. Many enterprises are still grappling with the remnants of legacy on-premises estates. But technical debt is not the only reason for hybrid modalities. Surprisingly, large platforms even have constructed their own data centers or used colocation as an intentional strategy.
Security is a top cloud inhibitor, according to 47% of IT professionals. The leading cloud security concerns include data protection (40%), data theft (33%) and regulatory compliance (31%). The myriad cybersecurity threats evolve each day, and cloud technologies are not immune; for example, web APIs are now a significant threat vector. A separate report found a 300% increase in malicious API traffic in the past six months. Other issues, such as exposed keys, insecure defaults and misconfigurations are known to hamper cloud-native infrastructure.
Contrary to popular belief, nearly half (46%) of companies reported that COVID-19 has not quickened their cloud adoption. This reality could indicate that cloud migration has been planned for years, and recent adoption is only part of an ongoing trend. The study found that the pandemic did, however, accelerate things like infrastructure-as-code (IaC), container orchestration, compliance and governance and other operational factors.
Multi-cloud feels like an inevitable result of accelerating cloud adoption in a more diversified market. Rising multi-cloud use is also arguably in line with Conway’s Law. As organizations develop more and more digital experiences across new verticals, the platforms and backend processes to support these initiatives will inevitably grow more and more complex.
To mitigate some of the issues posed by multi-cloud, many organizations are turning toward increased infrastructure automation. In fact, 70% of those surveyed said infrastructure automation tools are extremely important to their organization. Of these tools, provisioning automation (75%) is the most popular kind in use. Automation for other areas, like networking (58%), security (50%) and app development (69%) follow.
Hashicorp’s State of Cloud Strategy Survey boldly announces, “Welcome to the Multi-Cloud Era,” and its findings back up that sentiment. For further insights, you can view the results freely on this website.
Multi-cloud is often framed from the perspective of “lift and shift.” In other words, an organization takes a computing environment previously running on one cloud and transfers it over to a different service provider. Cloud migration may make sense for cost savings or performance benefits and such a shift may be necessary when migrating on-premises data centers to a public cloud.
In theory, lift and shift sounds like it would empower cloud consumers with more choice in the marketplace. However, according to John Gentry, CTO of Virtana, lift and shift is quite rare in practice; it may not be the true driver behind multi-cloud strategies. Moving resources between clouds can result in costly egress fees. Plus, culturally-ingrained cloud preferences become challenging to shake. Unique configurations and add-on software-as-a-service (SaaS) make each cloud more nuanced, requiring new skills and procedures with every migration.
Instead, Gentry advocates for a “fit-for-purpose cloud” strategy. This attitude is less about moving similar workloads between clouds but, instead, pairing particular types of workloads with the appropriate cloud types. According to Gentry, using multiple clouds simultaneously could still help organizations strategically align their digital resources and reduce dependency on a single cloud service provider (CSP). But, the real value of a hybrid multi-cloud setup lies in matching computing environments to different business layers.
At first glance, the ability to move between clouds appears to be driving a new multi-cloud economy where cloud strategists can swiftly migrate resources and optimize intercloud utilization. However, when organizations attempt to shift, they usually experience many hidden costs, Gentry warned. These often pop up around data egress. Or, new data storage costs may take a surprising toll, Gentry added. “A lot of companies look at it from a computing perspective and they don’t account for the storage footprint.”
DevOps in the cloud also introduces new responsibilities and processes that may differ between clouds, continued Gentry. From unique storage operations to managing the life cycle of a virtual machine, each cloud carries unique configuration methods. This makes it more difficult to abandon established procedures in favor of a different computing arrangement.
Nevertheless, Gentry recognizes that we’re starting to see a maturing effect of the multi-cloud concept, especially among large enterprises. “Companies have a multi-cloud strategy—it’s less about moving between clouds than about picking a cloud that has specific advantages for a given workload,” he said. In a fit-for-purpose cloud approach, different workloads correspond to different layers of the business. For example, an organization may require a local data center or private cloud for high-security data. Certain applications may benefit from a distributed global public cloud, whereas other workloads could reap performance benefits and cost savings from a cloud-adjacent edge model. “These specific areas may not have anything to do with one another other than supporting the overall business,” explained Gentry.
So how do we match the workload at hand to the ideal computing arrangement? Gentry identified three emerging cloud types:
For example, Gentry described how a large health care company uses a hybrid multi-cloud setup to support various business divisions. The organization is keeping traditional patient care workloads exclusively on-premises; due to regulatory reasons, it will never see the inside of a cloud. Yet, they are simultaneously building the next generation of applications in a public cloud, using Google Cloud to scale a clinical trial division. Simultaneously they began using Microsoft Azure for their back office. This scenario highlights one peculiar advantage of late-stage cloud adoption, noted Gentry: “They had the advantage of being able to take a more thoughtful approach.”
Gentry described another case of an organization performing genomic sequencing. For data-heavy applications like this, where there is a high dependency on input and output, syncing with a public cloud could be extremely costly and introduce latency. For them, the most cost-effective method was to use a cloud-adjacent or edge model alongside a public cloud.
One situation that may warrant cloud migration is a complete replatforming, noted Gentry. He described one early cloud adopter that rushed into AWS, only to find it wasn’t cost-effective for their needs. Architects then had to make tough decisions to determine what would be repatriated back to local data centers and what should remain in the cloud. “Their only motive going from cloud to cloud was, ‘We made a bad choice and we want to move.’”
Clearly, to match cloud use with business requirements, you must choose the appropriate cloud. AWS is widely adopted for elastic computing and offers a wide product catalog. GCP is offering feature innovation and cost reduction to compete and is going after un- and under-penetrated regions. Azure, on the other hand, will offer licensing advantages if you are a Microsoft shop.
Secondly, to unite IT around a hybrid multi-cloud strategy, you must remove the adversarial state between traditional ops and cloud ops. Classic ops is typically very safety-oriented, using a slow approach with endless tests in pre-production. Traditional ops may produce yearly updates. This is directly opposed to the new cloud ops approach, which emphasizes agility, speed and constant deployment. “They sit in different silos,” Gentry explained.
To solve this dilemma, companies must share technical skillsets between the three main cloud types. “DevOps must become a continuum for all types,” Gentry said. In addition to cultural change, DevOps tools must evolve to monitor workloads across a hybrid multi-cloud estate. This will require integration to tie together tools and deeper observability.
HashiCorp today announced it has updated the instance of Terraform it created to automate the configuration of virtual machines on the Microsoft Azure cloud to give IT teams more granular control.
Version 2.0. of Terraform (TF) AzureRM Provider will allow IT teams to separately configure virtual machines by type for instance of both Windows and Linux.
In addition, version 2.0 of TF AzureRM Provider will allow users to specify custom timeouts for resources. Previously, timeouts were set for one hour by default.
Finally, TF AzureRM Provider 2.0 removes resources, data sources and fields that have been deprecated. TF AzureRM Provider currently provides access to 374 resources and 119 data sources.
Amith Nair, vice president of product marketing for HashiCorp, said the goal is to provide IT teams with a set of tools for automating the configuration of virtual machines on Azure that is more accessible than the tools currently provided by Microsoft.
Nair said HashiCorp is seeing increased adoption of Microsoft Azure, which in turn creates demand for tools that make it easier to deploy virtual machines at scale. In fact, Nair notes that as more workloads move into the public cloud the less resistance there is to IT automation as administrators look for ways to manage IT at what is now unprecedented scale. Of course, many organizations gain their first experience with tools such as Terraform when they first embrace a set of best DevOps practices.
Less clear is how many virtual machines are being configured on top of instances of Windows versus Linux. There is no doubt Microsoft has emerged as the strongest challenger to the dominance of Amazon Web Services (AWS) in the public cloud. Much of that success, however, comes from the fact that Microsoft supports distributions of Linux alongside Windows Server on the Azure cloud. There are, of course, many organizations, such as Walmart, that prefer to standardize on Azure simply because they view Amazon to be a competitor. At the same time, however, there are many companies that employ both AWS and Azure.
Nair said most organizations that have adopted more than one cloud tend to manage them in isolation from one another. However, it is expected that one day more organizations will seek to unify the management of multiple clouds within the context of a truly hybrid cloud computing environment as the total cost of cloud computing continues to rise with each additional workload deployed. Naturally, many of those organizations eventually will gravitate toward tools that can be employed across multiple clouds.
In the meantime, whether it’s IT administrators or developers themselves configuring virtual machines in the cloud, it’s thanks to tools such as Terraform that the amount of time and effort required to set up virtual machines in the cloud is now as negligible as it is. The challenge now is not so much finding tools to automate IT as much as it is navigating all the cultural changes that naturally ensue.
Teradici announced today it has made its Cloud Access Software (CAS) available on Microsoft Azure Stack, the version of the cloud operating system that Microsoft makes available for on-premises servers.
Ziad Lammam, vice president of product management for Teradici, said the availability of CAS on Azure Stack makes it possible to employ the PC-over-IP (PCoIP) remote display protocol developed by Teradici to access virtual desktops running in the Microsoft Azure cloud from Azure Stack platforms.
Virtual desktops have been around in one form or another for a couple of decades, but adoption has always been limited because of primarily the complexity associated with configuring virtual desktops on local servers. With the rise of public clouds, however, it has become easier to take advantage of virtual desktops that are made available as a cloud service.
The PCoIP protocol created by Teradici transfers pixels between the cloud and the desktop, which makes it feasible to deliver even high-performance 3D graphics applications running on graphical processor units (GPUs) via the cloud. While there are other protocols that can be employed to access remote desktops, Lammam said PCoIP has gained traction because of its ability to support such high-definition applications.
Microsoft, however, has thrown most of its weight behind its proprietary Remote Desktop Protocol (RDP).
It remains to be seen just how many virtual desktops might move to the cloud. Many organizations have resisted virtual desktops for a variety of technical concerns and cultural issues. Virtual desktops are difficult to set up on local servers, while connectivity to the cloud can be intermittent. At the same time, many internal IT teams responsible for managing local desktops have been reluctant to given up control of their fiefdom. In fact, it’s only been since the rise of Azure that Microsoft has been aggressively encouraging those IT teams to embrace virtual desktops.
However, now that connectivity to the cloud has become more reliable and more organizations are lifting and shifting workloads to the cloud, both technical concerns and cultural issues are becoming much less of a hurdle, said Lammam.
Less clear is to what degree IT organizations will embrace Azure Stack as a platform from which to access virtual desktops running in the Azure cloud. In general, Azure Stack requires organizations to acquire and deploy a modern server to run it. Many organizations are going to prefer to access virtual desktops running in the cloud without having to acquire a new local server running a new type of operating system. Teradici already provides access to virtual desktops running on public clouds without requiring organizations to have Azure Stack installed. However, there is a subset of Microsoft customers who will employ Azure Stack to build and deploy hybrid IT environments and will need to access virtual desktops running on a public cloud.
Whatever the path chosen, it’s clear more virtual desktops will be accessed via the cloud. Many organizations want to reduce the cost of labor associated with managing local instances of desktops that are usually deployed across multiple remote office locations. The challenge now is figuring out the best path to achieving that goal based on the characteristics of the workloads being accessed.
Talend has made its integration platform natively available on the Microsoft Azure cloud to provide DevOps teams employing Azure DevOps with an easier approach to creating pipelines and integrating data.
Vincent Lam, head of cloud product marketing for Talend, said the company is now making available 900 connectors and components to DevOps teams that use the continuous integration/continuous deployment (CI/CD) platform Microsoft offers as a service.
By providing deep hooks into the Azure platform, Lam says Talend is looking to make it easier for teams to build applications by relying on an integration platform-as-a-service (iPaaS) environment to access data stored in Microsoft cloud services such as Azure SQL Data Warehouse, Azure Databricks, Azure Data Lake Store and Azure HDInsight.
From a DevOps perspective, the Azure DevOps Orchestration engine has now been integrated with Talend’s zero-install continuous integration capability, which it created as part of an effort to integrate its integration service with CI/CD platforms such as Jenkins. That effort made it possible to leverage CI orchestration tools to automatically build unit tests and package Talend jobs in an artifact repository. That capability has now been extended to Azure DevOps.
Not every organization that uses Azure will employ Azure DevOps because they may have already standardized on another CI/CD platform, which they prefer to deploy and manage. However, because Azure lowers the barrier to entry for employing DevOps to build applications, Talend is now seeing a lot of demand for an iPaaS environment on Azure, Lam said.
Regardless of platform, as organizations start to build cloud-native applications based on microservices, many of them underestimate the integration challenges they will face. Each microservice has its own application programming interface that needs to be built and supported, which in turn is driving more convergence of DevOps platforms and iPaaS environments to help manage the APIs on which those microservices depend. As a result, IT organizations today need to apply more forethought to their overall API strategy, said Lam.
Talend is not the only provider of an integration platform to appreciate the role that DevOps processes and the rise of microservices are having on driving increased consumption of integration services. But it’s not clear whether access to integration services will become more democratized across IT organizations. Rather than continuing to rely on “centers of excellence” to centrally manage integration projects, many IT organizations have come to realize DevOps teams need to be able to access integration capabilities on demand. To facilitate that process, vendors such as Talend are making a concerted effort to couple integration platforms tightly with various DevOps platforms.
It remains to be seen to what degree integration platforms will remain standalone platforms versus becoming a capability to be invoked within the context of a CI/CD pipeline. Given the volume of monolithic applications that still depend on centrally managed integration platforms, it may be a while before the integration platform becomes subsumed in DevOps platforms. In the meantime, however, the line between DevOps and integration platforms will surely get more blurry.
Microsoft, at its recent Microsoft Build 2019 conference, launched a series of efforts intended to make it easier for organizations to embrace best DevOps practices, including making it possible to address both continuous integration and continuous delivery within the same YAML file using Azure Pipelines.
Microsoft also announced it will extend Azure Pipelines to provide tighter integration between GitHub, which Microsoft acquired last year, and Kubernetes. Via that integration, Azure Pipelines can be used to automate everything from creating container images and packaging them as Helm charts to generating Kubernetes deployment artifacts and then deploying the workload.
Continuing that Kubernetes theme, Microsoft also is launching the Kubernetes-based Event Driven Autoscaling (KEDA) project, which makes it possible to run Azure functions on top of Kubernetes clusters. Developed in collaboration with Red Hat, KEDA is available in developer preview for the Red Hat OpenShift platform based on Kubernetes.
In addition, Microsoft has extended the Azure IoT Edge runtime to Kubernetes to enable internet of things (IoT) applications to be deployed on Kubernetes and Azure SQL DB Edge, which is packaged as a container and makes it possible to deploy a database on ARM or x86 systems deployed at the network edge.
Also during the conference, Microsoft launched MLOps, which applies DevOps principles to deploying artificial intelligence (AI) models using the GitOps workflow; Azure SQL Database Serverless, which allows organizations to consume a database service on a per-second billing basis on the Azure cloud; and ML.net, a framework for building AI models.
Microsoft also announced it is now making available a full Linux subsystem within Windows 10 and the ability to link IoT devices to the Azure cloud without writing code.
Scott Guthrie, executive vice president for AI and cloud at Microsoft, told conference attendees Microsoft is squarely focused on making it easier to build applications that can be deployed in hybrid cloud computing environments anchored around the Microsoft Azure cloud.
Microsoft historically has focused on making it much easier to consume emerging technologies at the point in time they start to appeal to the broadest number of customers. As DevOps best practices continue to find mainstream adoption, that same philosophy is being applied to cloud services. Microsoft may not have invented the concept of CI/CD, but it is working to make it easier for organizations that have struggled to implement continuous delivery, for example, to master that challenge. The same concept applies to Kubernetes, which some argue is still too complex for the average IT organization to master and deploy.
It remains to be seen how much Microsoft’s efforts, most of which are only available as previews, will result in more applications being deployed on Azure. Because an application is built on a public cloud doesn’t always mean it will be deployed on that cloud. It does, however, increase the chances of that occurring. In fact, providing a better DevOps experience across a hybrid cloud computing environment is clearly key to Microsoft’s strategy as it seeks to gain ground on Amazon Web Services (AWS).