Data center migration is ideal for businesses who are looking to exit or reduce on-premises data centers, migrate workloads as is, modernize apps, or leave another cloud. Executing migrations, however, is no small task, and as a result, there are many enterprise workloads that still run in on-premises data centers. Often technology leaders want to migrate more of their workloads and infrastructure to private or public cloud, but they are turned off by the seemingly complex processes and strategies involved in cloud migration, or lack the internal cloud skills necessary to make the transition.
Though data center migration can be a daunting business initiative, the benefits of moving to the cloud is well worth the effort, and the challenges of the migration process can be mitigated by creating a strategy, using the correct tools, and utilizing professional services. Data center migration provides a great opportunity to revise, rethink, and improve an organization’s IT architecture. It also ultimately impacts business critical drivers such as reducing capital expenditure, decreasing ongoing cost, improving scalability and elasticity, improving time-to-market, enacting digital transformation and attaining improvements in security and compliance.
What are Common Data Center Migration Challenges?
To ensure a seamless and successful migration to the cloud, businesses should be aware of the potential complexities and risks associated with data center migration. The complexities and risks are addressable, and if addressed properly, organizations can create not only an optimal environment for their migration project, but provide the launch point for business transformation.
Not Understanding Workloads
While cloud platforms are touted as flexible, it is a service-oriented resource, and it should be treated as such. To be successful in cloud deployment, organizations need to be aware of performance, compatibility, performance requirements (including hardware, software, and IOPS), required software, and adaptability to changes in their workloads. Teams need to run their cloud workloads on the cloud service that is best aligned with the needs of the application and the business.
Not Understanding Licensing
Cloud marketplaces allow businesses to easily “rent” software at an hourly rate. Though the ease of this purchase is enticing, it’s important to remember that it’s not the only option out there. Not all large vendors offer licensing mobility for all applications outside the operating system. In fact, companies should leverage existing relationships with licensing brokers. Just because a business is migrating to the cloud doesn’t mean that a business should abandon existing licensing channels. Organizations should familiarize themselves with their choices for licensing to better maximize ROI.
Not Looking for Opportunities to Incorporate PaaS
Platform as a service (PaaS) is a cloud computing model where a cloud service provider delivers hardware and software tools to users over the internet versus a build-it-yourself Infrastructure as a Service (IaaS) model. The PaaS provider abstracts everything—servers, networks, storage, operating system software, databases, development tools—enabling teams to focus on their application. This enables PaaS customers to build, test, deploy, run, update and scale applications more quickly and inexpensively than they could if they had to build out and manage an IaaS environment on top of their application. While businesses shouldn’t feel compelled to rewrite all their network configurations and operating environments, they should see where they can have quick PaaS wins to replace aging systems.
Not Proactively Preparing for Cloud Migration
Building a new data center is a major IT event and usually goes hand-in-hand with another significant business event, such as an acquisition, or outgrowing the existing data center. In the case of moving to a new on-premises data center, business will slow down as the company takes on a physical move. Migrating to the cloud is usually not coupled with an eventful business change, and as a result, business does not stop when a company chooses to migrate to the cloud. Therefore, a critical part of cloud migration success is designing the whole process as something that can run along with other IT changes that occur on the same timeline. Application teams frequently adopt cloud deployment practices months before their systems actually migrate to the cloud. By doing so, the team is ready before their infrastructure is even prepared, which makes cloud migration a much smoother event. Combining cloud events with other changes in this manner will maximize a company’s ability to succeed.
Treating and Running the Cloud Environment Like Traditional Data Centers
It seems obvious that cloud environments should be treated differently from traditional data centers, but this is actually a common pitfall for organizations to fall in. For example, preparing to migrate to the cloud should not include traditional data center services, like air conditioning, power supply, physical security, and other data center infrastructure, as a part of the planning. Again, this may seem very obvious, but if a business is used to certain practices, it can be surprisingly difficult to break entrenched mindsets and processes.
How to Plan for a Data Center Migration
While there are potential challenges associated with data center migration, the benefits of moving from physical infrastructures, enterprise data centers and/or on-premises data storage systems to a cloud data center or a hybrid cloud system is well worth the effort.
Now that we’ve gone over the potential challenges of data center migration, how do businesses enable a successful data center migration while effectively managing risk?
Below, we’ve laid out a repeatable high level migration strategy that is broken down into four phases: Discovery, Planning, Execution, and Optimization. By leveraging a repeatable framework as such, organizations create the opportunity to identify assets, minimize migration costs and risks using a multi-phased migration approach, enable deployment and configuration, and finally, optimize the end state.
Phase 1: Discovery
During the Discovery phase, companies should understand and document the entire data center footprint. This means understanding the existing hardware mapping, software applications, storage layers (databases, file shares), operating systems, networking configurations, security requirements, models of operation (release cadence, how to deploy, escalation management, system maintenance, patching, virtualization, etc.), licensing and compliance requirements, as well as other relevant assets.
The objective of this phase is to have a detailed view of all relevant assets and resources of the current data center footprint.
The key milestones in the Discovery phase are:
Creating a shared data center inventory footprint: Every team and individual who is a part of the data center migration to the cloud should be aware of the assets and resources that will go live.
Sketching out an initial cloud platform foundations design: This involves identifying centralized concepts of the cloud platform organization such as folder structure, Identity and Access Management (IAM) model, network administration model, and more.
As a best practice, companies should engage in cross-functional dialogue within their organizations, including teams from IT to Finance to Program Management, ensuring everyone is aligned on changes to support future cloud processes. Furthermore, once a business has migrated from a physical data center to the cloud, they should consider whether their data center team is trained to support the systems and infrastructure of the cloud provider.
Phase 2: Planning
When a company is entering the Planning phase, they are leveraging the assets and deliverables gathered in the Discovery phase to create migration waves to be sequentially deployed into non-production and production environments.
Typically, it is best to target non-production migration waves first, which helps identify the sequence of waves to migrate first. To start, consider the following:
Mapping the current server inventory to the cloud platform’s machine types: Each current workload will generally run on a virtual machine type with similar computing power, memory and disk. Oftentimes though, the current workload is overprovisioned, so each workload should be evaluated to ensure that it is migrated onto the right VM for that given workload.
Timelines: Businesses should lay out their target dates for each migration project.
Workloads in each grouping: Figure out what migration waves are grouped by i.e. non-production vs. production applications.
Cadence of code releases: Factor in any upcoming code releases as this may impact the decision of whether to migrate sooner or later.
Time for infrastructure deployment and testing: Allocate adequate time for testing infrastructures before fully moving over to the cloud.
Number of application dependencies: Migration order should be influenced by the number of application dependencies. The applications with the fewest dependencies are generally good candidates for migration first. In contrast, wait to migrate an application that depends on multiple databases.
Migration complexity and risk: Migration order should also take complexity into consideration. Tackling simpler aspects of the migration first will generally yield a more successful migration.
As mentioned above, the best practice for migration waves is to start with more predictable and simple workloads. For instance, companies should start with migrating file shares first, then databases and domain controlled, and save the apps for last. However, sometimes the complexity and dependencies don’t allow for a straightforward migration. In these cases, utilizing an experienced service provider who has experience with these complex environments will be prudent.
Phase 3: Execution
Once companies have developed a plan, they can bring them to fruition in the Execution phase. Here, businesses will need to be deliberate about the steps they take and the configurations they develop.
In the Execution phase, companies will put into place infrastructure components and ensure they are configured appropriately, like IAM, networking, firewall rules, and Service Accounts. Here is also where teams should test the applications on the infrastructure configurations to ensure that they have access to their databases, file shares, web servers, load balancers, Active Directory servers and more. Execution also includes using logging and monitoring to ensure applications continue to function with the necessary performance.
In order for the Execution phase to be successful, there needs to be agile application debugging and testing. Moreover, organizations should have both a short and long term plan for resolving blockers that may come up during the migration. The Execution phase is iterative and the goal should be to ensure that applications are fully tested on the new infrastructure.
Phase 4: Optimization
The last phase of a data center migration project is Optimization. After a business has migrated their workloads to the cloud, they should conduct periodic review and planning to optimize the workloads. Optimization includes the following activities:
Resizing machine types and disks
Leveraging a software like Terraform for more agile and predictable deployments
Improving automation to reduce operational overhead
Bolstering integration with logging, monitoring, and alerting tools
Adopting managed services to reduce operational overhead
Cloud services provide visibility into resource consumption and spend, and organizations can more easily identify the compute resources they are paying for. Additionally, businesses can identify virtual machines they need or don’t need. By migrating from a traditional data center environment to a cloud environment, teams will be able to more easily optimize their workloads due to the powerful tools that cloud platforms provide.
How do I take the first step in data center migration?
While undertaking a full data center migration is a significant project, it is worthwhile. The migration framework we’ve provided can help any business break down the process into manageable stages and move fully to the cloud.
When you’re ready to take the first step, we’re here to help to make the process even easier. Contact a 2nd Watch advisor today to get started with your data center migration to the cloud.
The demand for direct-to-consumer services and media content is continuously growing, and with that, audiences are raising their expectations of media and entertainment companies. Agile and innovative companies, such as Netflix, YouTube, and Amazon Prime, have arguably created and continue to enable the current viewership trends.
These streaming services have disrupted the traditional media landscape by empowering audiences to watch any content wherever and whenever they want. To accommodate new audience behaviors, relevant media companies use technologies to support the modern-day digital media supply chain, which has become increasingly complex to manage.
However, legacy media companies have something that audiences still want: content. Most of these institutions have massive budgets for content production and enormous existing media libraries that have latent revenue potential. For example, legacy media brands own nostalgic cult classics, like “The Office,” that viewers will always want to watch, even though they have watched these episodes multiple times before.
As the volume of content consumption and demand increases, media organizations will find that a traditional media supply chain will constrain their ability to grow and meet customers in their preferred venues, despite owning a broad range of content that viewers want to watch. In order to keep up with audience demand, media companies will need to transform their media supply chains, so that they can distribute their media quickly and at scale, or they risk falling behind. Cloud technologies are the key to modernizing digital asset management, metadata models, quality control, and content delivery networks.
The Challenges of a Traditional Media Supply Chain
There are a lot of moving parts and behind-the-scenes work for media and entertainment businesses to push media assets to audiences. The media supply chain is the process used to create, manage, and deliver digital media from the point of origin (creator, content provider, content owner, etc.) to the destination (the audience.) For the right content and best experience to reach users on devices and platforms of their choice, digital media files must pass through various stages of processing and different workflows.
Media supply chain management is challenging and if there are inefficiencies within this process, issues that will ultimately affect the bottom line will crop up. The following are top challenges of media supply chain management:
The content wars are in full swing, and as a result, the media and entertainment industry has seen an influx of divestitures, mergers, and acquisitions. Organizations are accumulating as much content as possible by bolstering their media production with media acquisition, but as a result, content management has become more difficult. With more content comes more problems because this introduces more siloed third-party partners. As companies merge, the asset management system becomes decentralized, and media files and metadata are spread across different storage arrays in different datacenters that are managed by different MAMs with various metadata repositories.
Reliance on Manual Processes
Legacy media companies have been around much longer than modern technologies. As a result, some of these organizations still do many media production and distribution tasks manually, especially when it comes to generating, reviewing, and approving metadata. Metadata is essential for sorting, categorizing, routing, and archiving media content, as well as making the content accessible to a global, diverse audience. Using manual processes for these functions not only severely slows down a business, but they are also susceptible to human-error.
Quality of Media Assets
Today, consumers have the latest technology (4K TVs, surround sound systems, etc.), which requires the highest quality version of content sources. With dispersed content libraries and team, working derivative edits to meet localization and licensing requirements and locating native frame rate masters can be a challenging and time-consuming problem to tackle.
Benefits of Using Cloud Technology to Modernize the Media Supply Chain
Cloud-based technologies can help manage and resolve the issues typically encountered in a media supply chain. If media organizations do not utilize cloud solutions to modernize their supply chain, they risk being less agile to meet global audience demand, incurring higher costs to deliver media, and eroding viewership.
Legacy media brands are recognizing the consequences of not adopting modern technology to support their media supply chains, and recently, we’ve seen established media corporations partnering with cloud service providers to undertake a digital transformation. A recent and newsworthy example of this is the MGM and AWS partnership. MGM owns a deep library of film and television content, and by leveraging AWS, MGM is able to distribute this content with flexibility, scalability, reliability, and security to their audiences. AWS offers services and tools to modernize MGM’s media supply chain to be able to distribute content across multiple platforms quickly and at scale.
Businesses don’t need to strike historic deals with cloud service providers to receive the same benefits. By transforming into a cloud-based framework, any media company can reap the following major benefits of modernizing their media supply chain:
Scale and Agility
This point cannot be repeated enough because, again, customer media consumption is rapidly increasing, and businesses must find a way to meet those demands in order to retain customers and remain competitive. With cloud computing, the media supply chain is no longer limited to the capacity of on-premise data centers or the capital expenditure budget that was forecasted a year earlier. Using cloud technology allows organizations to be dynamic and flexible to adjust for growing demand. Businesses can easily scale services up (or even down) based on audience demands by simply adding (or removing) more cloud resources, which is easier and more forgiving than having to add more infrastructure or being stuck with wasted databases.
Cloud services employ pay-as-you-go billing, which allows companies to pay for what they use rather than paying a fixed cost that may not fit their needs later on down the road. Most importantly, using the cloud removes the maintenance and operational costs associated with maintaining data center footprints. The costs of server hardware, power consumption, and space for traditional data centers can really add up, especially because these costs are inflexible based on actual consumption. Utilizing cloud technology provides flexibility in billing and trims down maintenance costs.
Automation and Efficiency
Cloud services offer tools that can handle abstract operational complexities, like metadata management, that were historically done manually. These automation and AI features can dramatically reduce the need to manually generate this metadata because it implements machine learning and video, audio, and image recognition to largely automate the generation, review, and approval of metadata. Harnessing the power of automation frees up teams’ resources and time and redirects that energy on impactful, business-differentiating activities.
Large audiences also means large amounts of data. Massive volumes of both structured and unstructured data requires increased processing power, storage, and more. Cloud computing has the scalable infrastructure to rapidly manage huge spikes of real time traffic or usage. Moreover, cloud service providers offer a variety of analytic tools that enable extract, transform, and loading of enormous datasets to provide meaningful insights quickly. Media companies can harness this data to improve user experiences and optimize supply chains, all of which greatly affects their bottom line.
How do I Get Started in my Media Supply Chain Transformation?
The process is less daunting than you think, and there are experienced cloud advisors and consulting firms who can point you in the right direction. At 2nd Watch, we embrace your unique modernization journey to help transform and modernize your business and achieve true business growth through cloud adoption. To learn more about our media cloud services, visit our Media and Entertainment page or talk to someone directly through our Contact Us page.
The Advantages of Cloud Computing for Media & Entertainment
We are living in a revolutionary era of digital content and media consumption. As such, media companies are reckoning with the new challenges that come with new times. One of the biggest changes in the industry is consumer demand and behavior. To adapt, M&E brands need to digitally transform their production, distribution, and monetization processes. Cloud solutions are a crucial tool for this evolution, and M&E organizations should prioritize cloud strategy as a core pillar of their business models to address industry-wide shifts and stay relevant in today’s ultra-competitive landscape.
The Challenge: Addressing Greater Audience Expectations and Volatility
Viewing behavior and media distribution has greatly impacted the M&E industry. Entertainment content consumption is at an all-time high, and audiences are finding new and more ways to watch media. Today, linear television is considered old-school, and consumers are favoring platforms that give them the power of choice and freedom. Why would you tune in to your cable television at a specific time to watch your favorite show when you can watch that same show anytime, anywhere, on any device or platform?
With new non-linear television services, media companies have less control over their audiences’ viewing experience. Before, viewers were constrained by broadcasting schedules and immobile, unconnected TVs. Now, audiences have taken viewership into their own hands, and M&E brands must discover ways to retain their viewers’ attention and loyalty in the era of endless options of content creators and streaming platforms.
The Cloud Has the Flexibility and Scalability to Handle Complex Workflows
OTT streaming services are the most popular alternative to linear television broadcasting. It is a solution that meets the audience’s expectation of access to content of their choosing whenever and wherever they want. However, OTT platforms require formatting multiple video files to be delivered to any device with varying connection speeds. As such, OTT streaming services need advanced video streaming workflows that encode and transcode, protect content, and possess storage capacities that continuously grow.
Because OTT broadcasting has complicated workflows and intense infrastructure needs, M&E companies need to consider scalability. OTT streaming that utilizes on-premises data centers will stymie growth for media organizations because legacy applications and software are resource and labor intensive. When OTT services are set up with on-premises streaming, it requires a group of configured live encoding and streaming services to deliver content to audiences.
The in-house services then need to have the computing capacity and capabilities in order to deliver content without interruptions. On top of that, technical staff are necessary to maintain the proprietary hardware, ensure its security, and continuously upgrade it as audiences grow. If companies opt for on-premises OTT streaming, they will not be able to achieve the scalability and quality of experience that they need to keep up with audience expectations.
A cloud-based infrastructure solves all of these issues. To reiterate, on-premises OTT platforms are very resource-intensive with complex ongoing maintenance and high upfront costs. Using cloud services for OTT streaming addresses the downfalls of on-premises streaming by leveraging a network for services dedicated to delivering video files. The benefits of cloud computing for OTT workflows immensely impact streaming latency and distribution, leading to a better end user experience. Cloud infrastructures have the following advantages to on-premises infrastructure:
Geography: Unlike in-house data centers, cloud servers can be located around the world, and content can be delivered to audiences via the closest data center, thereby reducing streaming latency.
Encoding and transcoding: Cloud services have the ability and capacity to host rendered files and ensure they are ready for quick delivery.
Flexible scalability: Providers can easily scale services up or down based on audience demands by simply adding more cloud resources, rather than having to purchase more infrastructure.
Cost optimization: Cloud cost is based on only the resources a business uses with none of the maintenance and upkeep costs, and the price adjusts up or down depending on how much is consumed. on-premises costs include server hardware, power consumption, and space. Furthermore, on-premises is inflexible based on actual consumption.
The Cloud Can Help You Better Understand Your Audiences to Increase Revenue
Another buzzword we hear often these days is “big data.” As audiences grow and demonstrate complex behaviors, it’s important to capture those insights to better understand what will increase engagement and loyalty. Cloud computing is able to ingest and manage big data in a way that is actionable: it is one thing to collect data, but it is another thing to process and do something with it. For M&E organizations, utilizing this data helps improve user experiences, optimize supply chains, and monetize content better.
Big data involves manipulating petabytes of data, and the scalable nature of a cloud environment makes it possible to deploy data-intensive applications that power business analytics. The cloud also simplifies connectivity and collaboration within an organization, which gives teams access to relevant and real time analytics and streamlines data sharing. Furthermore, most public cloud providers offer machine learning tools, which makes processing big data even more efficient.
From a data standpoint, a cloud platform is an advantageous option for those who are handling big data and want to make data-driven decisions. The compelling benefits of cloud computing for data are as follows:
Faster scalability: Large volumes of both structured and unstructured data requires increased processing power, storage, and more. The cloud provides not only readily-available infrastructure, but also the ability to scale this infrastructure very rapidly to manage large spikes in traffic or usage.
Better analytic tools: The cloud offers a number of instant, on demand analytic tools that enable extract, transform, and loading (ETL) of massive datasets to provide meaningful insights quickly.
Lowers cost of analytics: Mining big data in the cloud has made the analytics process less costly. In addition to the reduction of on-premises infrastructure, companies are reducing costs related to system maintenance and upgrades, energy consumption, facility management, and more when switching to a cloud infrastructure. Moreover, the cloud’s pay-as-you-go model is more cost-efficient, with little waste of resources.
Better resiliency: In cases of cyber-attacks, power outages or equipment failure, traditional data recovery strategies are slow, complex, and risky. The task of replicating a data center (with duplicate storage, servers, networking equipment, and other infrastructure) in preparation for a disaster is tedious, difficult, and expensive. On top of that, legacy systems often take very long to back up and restore, and this is especially true in the era of big data and large digital content libraries, when data stores are so immense and expansive. Having the data stored in cloud infrastructure will allow your organization to recover from disasters faster, thus ensuring continued access to information and vital big data insights.
The Cloud is Secure
There is a misconception that the public cloud is less secure than traditional data centers. Of course, these are valid concerns: media companies must protect sensitive data, such as customers’ personally identifiable information. As a result, security and compliance is crucial for an M&E business’s migration to the cloud.
We have read about cloud security breaches in news headlines. In most cases, these articles fail to accurately point out where the problem occurred. Usually, these breaches occur not due to the security of the cloud itself, but due to the policies and technologies for security and control of the technology. In nearly all cases, it is the user, not the cloud provider, who fails to manage the controls used to protect an organization’s data. The question for M&E business should not be “Is the cloud secure?” but rather “Am I using the cloud securely?”
Whether M&E organizations use a public cloud, private cloud, or hybrid cloud, they can be confident in the security of their data and content. Here is how the cloud is as secure, if not more secure, than in-house data centers:
Cloud architecture is homogenous: In building their data centers, cloud providers used the same blueprint and built-in security capabilities throughout their fabrics. The net effect is a reduced attack footprint and fewer holes to exploit since the application of security is ubiquitous.
Public cloud providers invest heavily in security measures: The protection of both the infrastructure and the cloud services is priority one and receives commensurate investment. Public cloud providers collectively invest billions in security research, innovation, and protection.
Patching and security management is consistent: Enterprises experience security breaches most often because of errors in configuration and unpatched vulnerabilities. Public cloud providers are responsible for the security of the cloud, which includes patching of infrastructure and managed services.
-Anthony Torabi, Strategic Account Executive, Media & Entertainment
In recent years, the adoption of cloud computing services has increased tremendously, especially given the onset of the pandemic. According to a report from the International Data Corporation (IDC), the public cloud services market grew 24.1% year over year in 2020. This increase in popularity is credited to the benefits provided by cloud including flexibility, on-demand capacity planning, cost reductions, and ability for users to access shared resources from anywhere.
No matter where you are in your cloud journey, understanding foundational concepts like the different types of cloud service models is important to your success in the cloud. These cloud computing service models provide different levels of control, flexibility, and management capabilities. With a greater understanding of the models, their benefits, and the different ways to deploy these infrastructures, you can determine the method that matches your business needs best.
What are the 3 Cloud Computing Service Delivery Models?
Different cloud computing service delivery models help meet different needs, and determining which model is best for you is an important first step when you transition to the cloud. The three major models are IaaS, PaaS, and SaaS.
Infrastructure as a Service (IaaS)
IaaS is one of the most flexible cloud computing models. The infrastructure and its features are presented in a completely remote environment, allowing clients direct access to servers, networking, storage, and availability zones. Additionally, IaaS environments have automated deployments, significantly speeding up your operations in comparison to manual deployments. Some examples of IaaS vendors include Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform. In these types of environments, the vendor is responsible for the infrastructure, but the users still have complete control over the Identity Access Management, data, applications, runtime, middleware, operating system, and virtual network.
Platform as a Service (PaaS)
Another cloud computing service delivery model is Platform as a Service (PaaS). PaaS is a subset of IaaS, except customers are only responsible for Identity Access Management, data, and applications and it removes the need for organizations to manage the underlying infrastructure. Rather than having the responsibility over hardware and operating systems as with IaaS, PaaS helps you focus on the deployment and management of your applications. There is less need for resource procurement, capacity planning, software maintenance, and patching. Some examples of PaaS include Windows Azure, Google AppEngine and AWS Elastic Beanstalk.
Software as a Service (SaaS)
Perhaps the most well-known of all three models is SaaS, where the deployment is redistributed to third party services. The customer’s only responsibilities are Identity Access Management, data, and the task of managing software. SaaS offers the entire package offered between IaaS and PaaS, as infrastructure, middleware, and applications deployed over the web can be seamlessly accessed from any place at any time, no matter the platform. Vendors of SaaS include CRM services like Salesforce and productivity software services like Google Apps. One major benefit of SaaS is that it reduces the costs of software ownership and eliminates the need for IT staff to manage the software so your company can focus on what it does best. Another benefit of SaaS that its relevance to businesses today, as SaaS is considered the best option for remote collaboration. With SaaS, your applications can be accessed from any geographical location and your company is not responsible for managing the hardware.
Choosing the Cloud Computing Model that is Right for You
Each cloud computing service model has different benefits to consider when determining the model that will work best for your business needs, projects, and goals.
While IaaS gives you complete control over your infrastructure, some businesses may decide they do not need to fully manage their applications and infrastructure on their own. IaaS is considered a good fit for SMEs and startups who do not have the resources or time to buy and build the infra for their own network. Additionally, larger companies may prefer to have complete control and scalability over their infrastructure, so they too may opt for IaaS for a pay-as-you go, remote option with powerful tools. One downside to IaaS is that it is more costly in comparison to PaaS and SaaS cloud computing models, yet it does minimize costs in the sense it eliminates the need to deploy on-premises hardware.
Reduced vendor lock-in
GUI and API-based access
Potential for vendor outages
The cost of training how to manage new infrastructure
PaaS is a good choice if you are looking to decrease your application’s time-to-market, because of its remote flexibility and accessibility. Thus, if your project involves multiple developers and vendors, each have quick accessibility to computing and networking resources through a PaaS. PaaS might also be used by a team of developers to test software and applications.
Rapid product development through simplified process
Eliminates need to manage basic infrastructure
Increased dependency on vendor for speed and support
SaaS is a feasible option for smaller companies that need to launch their ecommerce quickly or for short term projects that require quick, easy, and affordable collaboration from either a web or mobile standpoint. Any company that requires frequent collaboration such as transferring content and scheduling meetings will find SaaS convenient and accessible.
Automated provisioning/management of your cloud infrastructure
Allows for full remote collaboration
Reduced software costs
The 3 Cloud Computing Deployment Models
Another foundational concept of cloud are the deployment models. A deployment model is where your infrastructure resides and also determines who has control over its management. Like the cloud computing service delivery models, it is also important to choose the deployment model that will best meet the needs of your business.
There are three types of cloud computing deployment models:
A cloud deployment means your applications are fully run in the cloud and accessible by the public. Often, organizations will choose a public cloud deployment for scalability reasons or when security is not a main concern. For example, when testing an application. Businesses may choose to create or migrate applications to the cloud to take advantage of its benefits, such as its easy set-up and low costs. Additionally, a public cloud deployment allows for a cloud service provider to manage your cloud infrastructure for you.
An on-premises cloud deployment, or private cloud deployment, is for companies who need to protect and secure their data and are willing to pay more to do so. Since its on-premises, the data and infrastructure are accessed and managed by your own IT team. Due to in-house maintenance and fixed scalability, this deployment model is the costliest.
A hybrid cloud deployment connects cloud-based resources and existing non-cloud resources that do not exist in the cloud. The most common way to do this is between a public cloud and on-premises infrastructure. Through a hybrid cloud integration, you can segment data according to the needs of your business. For example, putting your highly sensitive data on-premises while putting less-sensitive data on the public cloud for accessibility and cost-effectiveness. This allows you to enjoy the benefits of the cloud while maintaining a secure environment for your data.
Determining the cloud computing service delivery model and deployment model best for your organization are both critical steps to the success of your company’s cloud computing journey. Get it right the first time by consulting with 2nd Watch. With a decade of experience as a managed service provider, we provide cloud services for your public cloud workloads. As an AWS Consulting Partner, Gold Microsoft Partner, and Google Cloud Partner, our team has the knowledge and expertise to efficiently guide you through your cloud journey. Contact us to learn more or talk to one of our experts.
During the COVID-19 pandemic, media and entertainment (M&E) organizations accelerated their need to undertake a digital transformation. As we approach a post-pandemic world, M&E companies are realizing that their digital transformation is no longer just a short-term solution, but rather, it is a long-term necessity to survive the increasingly competitive and saturated landscape of content distribution and consumption. Cloud service providers play a crucial role to M&E brands as they continue their digital evolution. Throughout the pandemic, cloud solutions allowed M&E companies to adapt efficiently and effectively. Beyond the landscape of COVID-19, a cloud-based framework will continue to facilitate agility and scalability in the M&E business model.
How COVID-19 Impacted the Media and Entertainment Industry
When COVID-19 created an unprecedented environment and altered our daily operations, people and businesses had to rapidly adjust to the new circumstances. In particular, the M&E industry faced a reckoning that was imminent before the pandemic and became more acute during the pandemic.
For M&E businesses, COVID-19 forced upon them an important pivotal point in their digital strategy. The pandemic didn’t present vastly new challenges for M&E organizations, it simply accelerated and highlighted the problems they had already begun experiencing in the last five or so years. Viewer behavior is one of the biggest shake-ups in the M&E industry. Prior to 2020, audiences were already hunting for new ways to consume content. Traditional linear broadcast was waning and modern digital streaming services were booming. Media content consumption was drastically changing, as audiences streamed content on different devices, such as their smartphones, tablets, connected TVs, PCs, and gaming consoles. Now, legacy M&E brands are no longer competing just against nimble new players in the streaming space, but they are also competing against music, gaming, and esport platforms. All of these trends that were in motion pre-pandemic became more apparent after society began sheltering-in-place.
With most of the United States going remote, industry giants, like Warner Brothers and Disney, pivoted their focus to streaming content to adjust to shelter-in-place orders. In an unprecedented move, Warner Brothers began releasing new movies in theaters and via streaming platforms simultaneously. Disney’s emphasis on its streaming service, Disney Plus, paid off: it exploded during quarantine and quickly accumulated 100 million subscribers. Additionally, Disney also followed a similar cinema distribution model to Warner Brothers by releasing new hits via streaming rather than just in theaters.
The need for digital innovation was crucial for the M&E industry to adapt to the new circumstances created by the pandemic, and this need will continue long into the post-COVID world. M&E organizations faced a catalyst in their structural transformation, and the digitization of content workflows and distribution became absolutely imperative as employees went remote and content consumption hit an all-time high. Moreover, certain market trends were felt more acutely during the pandemic and represented a paradigmatic shift for the M&E industry. These trends include the rise of direct-to-consumer, content wars via mergers and acquisitions, and wavering audience loyalty. Change is ever-present, and the consequences of not adapting to the modern world became obvious and unavoidable in the face of the pandemic. Ultimately, M&E incumbents who are slow to modernize their technology, production, and monetization strategies will be left behind by more agile competitors
How M&E Companies Can Use the Cloud to Innovate
As we return “back to normal,” we’ll see how the pandemic affected our societal structures temporarily and permanently. The M&E industry was particularly changed in an irrevocable manner: a new age of media has been fully realized, and M&E businesses will have to rethink their business models as a result. How the pandemic will continue to evolve from here is still unknown, but it is clear that media organizations will have to continue to innovate in order to keep up with the changes in working patterns and audience behavior.
To adapt to the accelerated changes driven by COVID-19, the modern media supply chain will require agility, flexibility, and scalability. Cloud solutions (such as Microsoft Azure, Amazon Web Services, and Google Cloud Platform) are the key enabler for M&E companies as they look to innovate. According to a Gartner report on digital transformation in media and entertainment, 80% of broadcasters and content creators migrated all or part of their operations to public cloud platforms as an urgent response to effects of quarantine in 2020. By switching to cloud-based infrastructures, M&E companies were able to collaborate and create remotely, better understand real-time audience behavior, and maintain a secure environment while supporting media production, storage, processing, and distribution requirements.
There is no one-size-fits-all cloud strategy, as it is dependent on the business. Some companies opt for a single cloud provider, while others choose a multi cloud strategy. A hybrid cloud solution is also an option, which utilizes data centers in conjunction with cloud service providers. Regardless of a company’s cloud strategy, the benefits of migrating to the cloud remain the same. Below we’ll dive into a couple of the pros of utilizing the cloud for morderning workflows, supply chains, and data analyses.
With a cloud platform, teams can now collaborate remotely and globally, which ultimately leads to greater productivity and efficiency in content creation. When it comes to media production, whether it is live or pre-filmed, massive teams of professionals are needed to make the vision come alive (editors, visual effects artists, production professionals, etc.) COVID-19 demonstrated that teams using cloud service providers could still work collaboratively and effectively in a remote environment. In fact, businesses realized that requiring teams to come on-site for content production can be more time consuming and costly than working remotely. Virtual post-production is a great example of how the cloud is more economical from a financial and time sense. Using a modern cloud infrastructure, M&E brands can create virtual workstations, which replaces physical workstations at the user’s desk. Unlike traditional workstations, virtual workstations do not have a capital expense. Virtual workstations are extremely customizable in terms of size and power to the exact specifications needed for a given task. Furthermore, the billing is flexible and you only pay for what resources you use. Lastly, with physical workstations, there are many “hidden costs.” Think about the electricity and staffing fees that businesses must pay in order to keep a workstation running. When you switch to a virtual workstation for post-production work, all of the aforementioned costs are managed by a cloud service provider.
Streamlining the Media Supply Chain
As media and entertainment shifts to direct-to-consumer, content management has become absolutely crucial in the media supply chain. Content libraries are only growing bigger and there is an influx of newly-produced assets as team workflows work more efficiently. Even so, most media companies store their library assets on-premise and within tape-based LTO cartridges. By doing so, these assets are neither indexable, searchable, or readily accessible. This slows down editing, versioning, compliance checking, and repackaging, all of which hurts an organization’s ability for rapid content monetization. By implementing a cloud-based infrastructure, M&E companies can utilize tools like machine learning capabilities to manage, activate, and monetize their assets throughout the content supply chain.
Capturing Real-time Data
Archaic and lagged metrics, such as overnight ratings and box office returns, will struggle today to produce actionable insights. Digital transformation for M&E organizations will require a technology and cultural transformation towards a data-driven mindset. To make data-driven decisions, you need to have the tools to collect, process, and analyze the data. Cloud platforms can help process big data by employing machine learning capabilities to deeply understand audiences, which can translate into monetization opportunities further down the funnel. By harnessing the cloud to redefine data strategy, businesses can make confident decisions using real-time data and use actionable insights to deliver real transformation.
Before the pandemic, 2020 was shaping up to be a pivotal year for the M&E industry as audience behavior was changing and new competitors were cropping up; however, the effects of the COVID-19 expedited these trends and forced organizations to transform immediately. In this new age of media, M&E companies must reckon with these unique and long-lasting challenges and seek to change their business models, cultures and technologies to keep up with the changing landscape.
-Anthony Torabi, Media & Entertainment Strategic Account Executive
The cloud market is maturing, and organizations worldwide are well into implementing their cloud strategies. In fact, a recent McKinsey survey estimates that, by 2022, 75% all workloads will be running in either public or private clouds. Additionally, according to VMWare, 72% of businesses are looking for a path forward for their existing applications, and it is important to consider an app modernization strategy as part of these migration efforts.
Whether it be a desire to containerize, utilize cloud-native services, increase agility, or realize cost savings, the overall goal should be to deliver business value faster in the rapidly changing cloud environment.
Application modernization has a focus on legacy or “incumbent” line of business applications, and approaches range anywhere between re-hosting from the datacenter to cloud, to full cloud native application rewrites. We prefer to take a pragmatic approach, which is to address issues with legacy applications that hinder organizations from realizing the benefits of modern software and cloud native approaches, while retaining as much of the intellectual property that has been built into incumbent applications over the years as possible. Additionally, we find ways of augmenting existing code bases to make use of modern paradigms.
Application Modernization Strategies
When approaching legacy software architecture, people often discuss breaking apart monolithic applications and microservices. However, the most important architectural decisions should be centered around how to best allow the application to function well in the cloud, with scalability, fault-tolerance, and observability all being important aspects. A popular approach is to consider the tenants of the 12-Factor App to help guide these decisions.
Architecture discussions go hand in hand with considering platforms. Containerization and serverless functions are popular approaches, but equally valid is traditional VM clustering or even self-hosting. Additionally, we start to think about utilizing cloud services to offload some application complexity, such as AWS S3 for document storage or AWS KMS for key management. This leads us to consider different cloud providers themselves for best fit for the organization and the applications overall, whether it be AWS, Azure, GCP (Google cloud platform), or hybrid-cloud solutions.
Another very important aspect of application modernization, especially in the cloud, is ensuring that applications have proper automation.
Strong continuous integration and continuous deployment (CI/CD) pipelines should be implemented or enhanced for legacy applications. Additionally, we apply CD/CI automation for deploying database migrations and performing infrastructure-as-code (IaaC) updates, and ensure paradigms like immutable infrastructure (i.e. pre-packaging machine images or utilizing containerization) are utilized.
Last, there is an important cultural aspect to modernization from an organizational to team level. Organizations must consider modernization a part of their overall cloud strategy and support their development teams in this area. Development teams must adapt to new paradigms to understand and best utilize the cloud – adopting strong DevOps practices and reorganizing teams along business objectives instead of technology objectives is key.