If you are reading this, chances are that your business has finally decided to shift to the cloud. We won’t say you are late because there are so many businesses out there still reluctant to migrate to possibly the only technology that can assuredly secure their future – the cloud.

Stats show that organizations that have already invested in the cloud is likely to increase their use of it in the next few years.

Last year, Forbes forecasted that 80% of all IT budget would be spent on cloud solutions by the summer of 2018.

Though the present stats aren’t out yet, we suppose it’s safe to assume that Forbes was right for such is the momentum of the cloud today.

Though companies have generally seen a lot of blog posts and articles about the benefits of the cloud, they still might find it challenging to determine what cloud service they should use in their organization. For many organizations, this choice comes down to three of the biggest cloud platforms in the world – Microsoft Azure, Amazon Web Services, and the Google Cloud Platform.

Comparing the three to find the best of the bunch is rather pointless. All three are popular and widely adopted for more than one reason. They all have their fair share of pros and cons. The truth is that it’s the organization that needs to choose the right kind of cloud service that matches their business strategy and goals.

To make it easier for you, this blog will explore the characteristics of these 3 cloud platforms.

But before we begin, here are a few things to keep in mind.

The cloud provider should understand your business and its objectives – The cloud service provider that’s right for you should understand your business, its objectives, and what it aims to achieve with the cloud.

Your current architecture – Your business architecture should be compatible with your cloud provider’s. Their architecture needs to be integrated into your workflows. So compatibility should be given top priority. For instance, if your business already uses Microsoft tools, Microsoft Azure is the way to go. At the end of the day, you want seamless, hassle-free integration.

Data center locations – This factor is important if the app your business is going to host on the cloud is sensitive when it comes to data centers and their locations. For a great user experience, the geographical location of the data center hosting the app is pivotal especially if the business has branches across the globe. Your service provider should have data centers in various locations that are far from each other ideally.

With that, let’s get down to the main topic at hand starting with…

Compute services

Microsoft Azure – Azure is widely preferred for its ‘Virtual Machines’ service. Its key offers include excellent security, an array of hybrid cloud capabilities, and support for Windows Server, IBM, Oracle, SAP, Linux, and SQL Server. Azure also features instances optimized for AI & ML.

AWS – AWS’ main service is the Elastic Compute Cloud with a plethora of options including auto-scaling, Windows & Linux support, high-performance computing, bare metal instances etc. AWS’s container services support Docker and Kubernetes as well as the Fargate service.

Google Cloud – Though Google Cloud’s compute services don’t come close to its two biggest competitors, its Compute Engine is still turning heads with its support for Windows and Linux, pre-defined/custom machine types, and per-second billing. Google’s role in the Kubernetes project and considering the fact that Kubernetes adoption is increasing rapidly gives the Google Cloud an edge over others when it comes to container deployment.

Cloud tools

Microsoft Azure – Microsoft’s heavy investment in AI reflects on Azure as the platform provides impressive machine learning and bot services. Other major Azure cognitive services include Text Analytics API, Computer vision API, Face API, Custom vision API etc. Azure also offers various analytics and management services for IoT.

AWS – AWS competes with acclaimed services like the Lex conversational interface for Alexa, Greengrass IoT messaging service, SageMaker service for ML, Lambda serverless computing service etc. Amazon also unveiled AI-related services like DeepLens and Gluon.

Google Cloud – The services and tools for Google Cloud seem to mainly focus on AI and ML. We can also assume that since Google developed TensorFlow – a huge open source library to develop ML apps, the Google Cloud has a slight edge over its rivals when it comes to AI and ML. Other great features include natural-language APIs, translation APIs, speech APIs, IoT services etc.

Making the choice

Though all three are dominant in the cloud services industry, Google Cloud still seems to be trailing behind the other two. But the tech giant’s partnership with Cisco, the company’s hefty investment in cloud-computing services, and focus on machine learning may give the Google Cloud more traction very soon.

Microsoft Azure, on the other hand, initially lagged behind AWS but is now considered the most dominant cloud service provider in the world. If your business relies on Microsoft platforms and tools, it’s going to pair well with Azure. But Azure’s focus on Microsoft’s own Windows puts Linux on the backseat despite Azure’s compatibility with the open source OS. So if your business is associated with Linux, DevOps, or bare metal, Azure may not be a safe bet.

This leaves us with AWS. With its massive scale and a broad array of services and tools, AWS can easily give Azure a run for their money. Though Microsoft’s efforts are starting to pay off catapulting Azure to new heights, AWS is consistently growing every year. However, if your business is looking for a personal relationship with your cloud provider and expecting an attentive service, you may find AWS disappointing. Amazon’s massive size itself makes offering such a service practically impossible.

Conclusion

These providers can help your business with pretty much every type of digital service it needs to stay ahead of the curve in today’s dynamic market conditions. If you think these providers don’t match your business objectives, you can still seek assistance from smaller boutique cloud providers. The bottom-line is that modern businesses are going to need the cloud backing them to efficiently adapt to a technologically advanced future.  If you require assistance regarding cloud adoption and migration, the experts here at AOT can help make it easier for you. Give us a ring to learn more.

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The cloud kept evolving over the years, and ‘Multi Cloud’ is widely anticipated to be its next evolution. Public and hybrid clouds have become much more important in modern IT infrastructure owing to the rising prominence of Software-as-a-service (SaaS). Multi cloud is expected to fill more gaps in the coming years.

Multi cloud

It’s not to be confused with hybrid cloud, and is basically a combination of a number of cloud technologies from multiple public clouds to meet the changing needs of businesses in the modern age. Multi cloud typically is not specific to a single vendor. Hybrid cloud, on the other hand, is a cloud architecture that blends public and private clouds.

The rise of multi cloud began when enterprises tried to avoid dependence on a single public cloud provider, and instead choosing specific services from each public cloud provider.

Last year IDC predicted that over 85% of IT organizations will adopt multi-cloud architectures by 2018.

One of the biggest benefits of adopting a multi cloud approach is that it boosts innovation. The right combination of cloud technologies enable different departments in an IT organization to adopt cutting-edge applications both to balance workloads and to accelerate digital transformation. The cloud is known for the flexibility it grants an enterprise. When multiple cloud technologies are combined, the same flexibility would be present while offering optimal conditions for the best performance.

If it’s an eCommerce business, there can be a highly scalable cloud platform and a different cloud technology to balance as well as meet the large storage demands of a data-intensive workload.

Behind the multi cloud trend

Cloud computing, with each evolution, became more sophisticated as well. Back when it began, the vision for the technology was to place workloads on a single cloud be it private or public. Times have changed. Today, hybrid cloud architecture grants more flexibility and benefits to businesses in addition to many choices that augment how the business digitally operates in more ways than one.

There are many viable public cloud options now including Amazon Web Services and Microsoft Azure. Tech corporates like Google and Oracle have joined the fray, presenting enterprises with many options. With so many options available, many enterprises started experimenting by combining various cloud technologies either through architectural processes or through ‘shadow IT’ where groups in an enterprise used public cloud services without explicit organizational approval. Regardless of the method adopted, many organizations today use multi cloud infrastructures.

However, managing multi cloud environments presents a lot of challenges and complexity that many organizations may struggle to tackle. With help from cloud service brokers or using cloud management tools, they can somewhat reduce the complexity though they will only be able to use a subset of features from each cloud instead.

Multi cloud management and deployment

Though multi cloud provides more flexibility, control, and security, the downside is that there would more to manage as well. The cloud may have grown out of its infancy, but multi-cloud is still relatively new. There’s so much more to explore which makes the management and deployment of multi-cloud environments a hassle despite its benefits.

Here are a few expert tips to keep in mind when adopting a multi cloud strategy for your enterprise.

  • Map the network to see where the multi cloud can fit – Different lines of businesses are best served by different cloud vendors. So it’s important to have a clear picture of your overall system and its management to figure out where the cloud can fit in and make things better.
  • Devise a flexible purchase process – To avoid cost impediments to using different cloud services from different vendors, it’s wise to come up with a purchase process that’s flexible as the cloud services that would be used. It’s also important to analyze whether each service is delivering value that’s worth its cost.
  • Use cloud management tools to keep track of costs – Cost optimization should have top priority when leveraging multi cloud for the enterprise. There are tools available that can perform accurate cost analysis of workloads when placed in different clouds.
  • Automate policy across your multi cloud ecosystem – When using multiple cloud services, especially from different vendors, an efficient approach is to have a single standard of policies. They should be applied automatically to each environment covering various areas including virtual servers, workloads, data storage, traffic etc. Such a configuration also makes it easier to apply updates so that they propagate seamlessly across the environments.

Conclusion

Public, private, hybrid, multi, pragmatic hybrid: the cloud comes in many forms today. And it’s not their names you should be focused on. The key is to understand what each offers, and learn how each benefits your enterprise. If you require help implementing the right kind of cloud strategy to your business, AoT offers our vast expertise. We can help your business get the best out of cloud computing with innovative, custom cloud solutions. Want to learn more? Give us a call.

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According to the dataset from Redmonk and Bitnami, about 30% of container deployments are in production environments.

The impact of the open source Docker on DevOps and virtualization is evident from how developers discuss the prospects all over the internet, and from its increased use in production environments of both SMBs and large-scale enterprises.

Last year, Datadog published a report on Docker adaption among their users, which showed a 30% increase in Docker adoption in just a single year. 

Docker’s growth momentum is still consistently rising, and along with the capability it gives developers to create, deploy, and run applications easier makes it a vital element in a DevOps ecosystem. Though DevOps pretty much covers the entire delivery pipeline, Docker optimizes the production environments.

Before Docker made a name for itself

Before Docker came into being, developers, testers and the ops team relied on a plethora of tools for configuration management. In addition, they had to deal with the complex integrations and other issues inevitably delaying the project not to mention making it more complex in most cases.

The team will have to make use of various environments that should be optimally aligned to meet the project’s goals. Achieving that alignment requires a lot of effort as well. Conclusively, development wasn’t efficient or fast then compared to how it is with Docker now.

The need for Docker arose primarily due to the evolution of application complexity over the years.

Relief for DevOps teams

Software developers in a DevOps environment are well aware of what Docker can do as a reliable environment for development. It allows the team to configure both development and test environments efficiently, subsequently resulting in successful release management.

With major cloud platforms like Microsoft Azure and Amazon Web Services offering support to the open source container system, Docker allows DevOps teams to deploy to any platform without concern for the underlying complexities. Add to that an extensive collection of official language stacks and repositories from DockerHub, and they have one of the most powerful tools to get the job done quickly.

Ops teams can package an entire application as a Docker image without compromising the build version before it gets added to a central registry. They don’t have to individually deploy EXE and JAR files to the target environment. The Docker image can then be taken by the various environments (development, testing, production etc.) for final deployment.

While the developers are relieved from worrying about setting up and configuring specific development environments every time, the ops team or system administrators become capable of setting up environments (thanks to Docker) akin to a production server, allowing anyone to work on the project with the same settings. 

Docker’s role in DevOps

To begin with, let’s take Wikipedia’s definition of DevOps.

DevOps is a culture, movement or practice that emphasizes the collaboration and communication of both software developers and other information-technology (IT) professionals while automating the process of software delivery and infrastructure changes.

That said, in such an environment, Docker finds its use both as a platform and as a tool. Developers can use it as a platform to run applications while the operations staff can use it as a tool to facilitate integration with the workflow.

With Docker as a platform, the developers can focus on building good quality code. Despite being isolated, Docker containers share the same kernel and OS files. This makes them lightweight and pretty fast; enough to make it one of the best ways to easily and efficiently build distributed systems by allowing applications to run on either a single machine or across many virtual machines. It comes with a cloud service to share applications and automate workflows.

Generally, once development and testing of an application are done, the ops team will take up the responsibility to deploy that app. Before Docker, this phase was quite challenging as issues that didn’t occur during development might show up, giving sleepless nights to the team. Docker eliminates this friction allowing the ops team to deploy the application seamlessly.

Docker-based pipeline in a DevOps environment considerably reduces risks associated with software delivery and deployment. In addition, it ensures timely delivery at a cheaper cost. It effectively unifies the DevOps community as well, supporting the use of popular provisioning and configuration tools like Chef, Ansible, and Puppet etc. From a technical standpoint, Docker facilitates seamless collaboration which is the core essence of a DevOps ecosystem.

The present state of Docker

With Jenkins, another open source tool, becoming more popular thanks to its efficiency in orchestrating complex workflows, developers have started exploring the results of combining it with Docker.

Docker, Inc. decided to invest in build automation last year, and the community behind Jenkins developed many plugins for effective Docker-Jenkins integration. This ended up expanding the capabilities of Docker at the hands of developers, allowing them to create and implement build pipelines on Docker.

Word soon got out, and now many startups have finally started seizing the opportunity to leverage the potential of Docker-based build automation.

CloudBees, one of the first companies, embraced Jenkins and Docker’s build automation to evolve from being just a PaaS player, by offering professional support and services for enterprises planning to adopt Jenkins and Docker.

Shippable, another company, adopted Docker for software build automation.

All these facts and more emphasize the dominating presence of Docker in today’s development realm whether it’s being used in a DevOps system of a simple, small startup or an enterprise with large teams.

Conclusion

According to Datadog’s report,

Docker adopters quintuple (5x) the container count within 9 months after initial deployment. 

Because it’s open source, it brings more perks to the table. Its ability to maintain consistency, productivity, and compatibility while providing reliable security and support for multi-cloud platforms in addition to major corporate backing makes Docker a valuable tool for companies putting their faith on DevOps.

With support from a huge and growing community, Docker will most likely be enhanced in the immediate future providing more out-of-the-box features and more integration choices.