To deal with a growth in online demand and remote working, digital workplaces are transitioning to become more elastic. Numerous IT executives are attempting to migrate key enterprise apps to the public cloud. This involves a lot of effort and is definitely not a no-brainer deed.
If your company is trying to update mission-critical systems and is considering a cloud migration as part of the process, you don’t want to make the same mistakes as others. So, a 10-step cloud migration checklist of the important areas you should evaluate and address to optimize your chances of a successful cloud transfer will be quite insightful.
The following items are on the cloud migration checklist:
1. Create the job of migration architect.
2. Select the level of cloud integration you require.
3. Choose between a single cloud and several clouds.
4. Create cloud KPIs.
5. Set performance benchmarks
6. Sort migration components by importance.
7. Carry out any required refactoring.
8. Make a data-migration strategy.
9. Change over output
10. Examine the application’s resource allocation.
Create the job of migration architect.
Establish the migration architect function to oversee the project before you commence your cloud migration. The migration architect is a system architect-level position in charge of planning and completing all aspects of the migration; their primary responsibilities should include defining the necessary refactoring required to make the migration successful, designing data migration strategies, defining cloud-solution requirements, and determining migration priorities and production switchover mechanisms.
Many choices and technical plans must be made throughout the course of a big migration project, and having a migration architect who is accountable for all parts of the migration is important to the project’s success.
Select the level of cloud integration you require.
When migrating an application from an on-premises data centre to the cloud, you have two options: shallow cloud integration or deep cloud integration.
A shallow cloud integration (also known as “lift-and-shift”) occurs when you relocate an on-premises application to the cloud while making no—or limited—changes to the servers you instantiate in the cloud to execute the application. Any modifications to the program are only necessary to get it to run in the new environment. You do not utilise cloud-specific services. Because the application is lifted “as is” and relocated, or shifted, to the cloud intact, this paradigm is also known as lift-and-shift.
You adjust your application throughout the migration process to take use of important cloud features for deep cloud integration. This might be as simple as employing auto-scaling and dynamic load balancing, or as complex as leveraging serverless computing capabilities such as AWS Lambda for sections of the application. It might also include utilising a cloud-specific data store.
Choose between a single cloud and several clouds.
Before you begin your cloud migration, consider if you want to choose a single cloud provider and move your application so that it operates optimally in that single environment, or whether you want your application to function on several cloud providers.
It is quite straightforward to optimise your application to run with a certain cloud provider. Your development teams just need to master one set of cloud APIs, and your application can make use of all your chosen cloud provider has to offer.
The disadvantage of this method is vendor lock-in. Once your application has been changed to run with only that one provider, switching it to a new provider may entail just as much effort as the initial cloud migration. Furthermore, having a single cloud provider may limit your capacity to negotiate critical conditions with the cloud provider, such as price and SLAs.
But wait, things are about to get much more difficult. There are numerous models for utilising several cloud providers:
- One application on one cloud, another in a separate cloud The most basic multi-cloud strategy deploys one set of apps in one cloud provider and another set in another. This method provides you with improved business leverage with different providers as well as flexibility in the future placement of applications. It also allows you to optimise each application for the provider on which it is deployed.
- Distribute your application over several cloud providers. Some businesses opt to operate portions of an application in one cloud provider and others in another. This method allows you to take advantage of the primary benefits that each supplier provides (for example, one provider might have better AI capabilities than another, which is known for its database speeds). The danger is the fact that your app is coupled to the performance of both providers, and any issues with either provider might influence the consumer experience of your application.
- Make your application cloud-agnostic. Other businesses create programmes that can operate on any cloud provider. With this strategy, you might run your application on numerous providers at the same time or distribute your application load between them. Because you can simply change loads from one cloud provider to another, this architecture affords you the most flexibility in vendor negotiations. The disadvantage is that you may find it difficult to leverage each cloud provider’s core features, diminishing the benefits of hosting your application in the cloud. This method may also make your application development and validation procedures more difficult.
Create cloud KPIs.
Key Performance Indicators (KPIs) are measurements that you collect about your application or service in order to assess how well it is functioning in comparison to your expectations. You may have already defined some key performance indicators (KPIs) for your applications and services, but are they still appropriate for an application or service once it is in the cloud? The finest cloud migration KPIs reveal how your in-progress migration is progressing, highlighting apparent or unseen issues that may be hiding within your application. Perhaps most importantly, cloud migration KPIs can assist you in determining whether the move is complete and successful.
Set performance benchmarks
Baselining is the method of evaluating your application’s or service’s present (pre-migration) performance in order to decide if its future (post-migration) efficiency is appropriate. Baselines assist you in determining when your migration is complete and give confirmation of the projected post-migration performance improvements. Baselines can also be used to diagnose any difficulties that develop during a cloud migration.
Set a baseline statistic for each KPI that you intend to track. Decide how long you will gather data to establish a baseline. Selecting a short baseline time (such as a day) allows you to proceed more quickly, but you run the risk of not gathering a representative performance sample. A longer baseline period (such as a month) clearly requires more time, but it can yield more representative data.
You must also decide whether you want to gather simply average or representative baseline data or data collected during “peak” or “critical” periods. For example, if you run a news website, do you want to gather data on a day when there is a major news event, or do you want to avoid such days?
Whatever data-collection methodology is best for your industry, make sure to explicitly identify what sort of data you’ll gather and for how long.
Sort migration components by importance.
You must also select whether to move your complete program to the cloud at once or to transfer it component by component or service by service.
First, determine the links between your services and which services are dependent on which other services. Use an application performance monitoring tool that can produce dependency diagrams from service maps for bigger, more complicated applications. Determine which components should be moved and in what sequence using the dependency diagram. It is frequently best to begin with the services that have the fewest dependencies. In this situation, you would migrate your most internal services first, followed by your outermost services, which are often those closest to your consumers.
The alternative method is, to begin with, the services closest to your clients—the most external services—so that any influence on your customers may be controlled.
Carry out any required refactoring.
You might wish to perform additional work on your apps and services before migrating them to ensure that they run as effectively and efficiently as feasible in the cloud. For example, you may wish to restructure your application:
• It works effectively with a variable number of running instances to enable dynamic scaling, potentially saving you money on cloud service costs.
• Your resource utilisation can benefit from dynamic-cloud capabilities, such as the ability to dynamically allocate and de-allocate resources as needed, rather than statically allocating them ahead of time.
• Before the migration, transition to a more service-oriented design so that individual services may be moved more simply to the cloud.
Make a data-migration strategy.
One of the most difficult aspects of cloud migration is data movement. The location of your data can have a big influence on your application’s performance. Moving your data to the cloud while the primary data-access mechanisms remain on-premises can have a substantial impact on performance. The same is true if the data remains on-premises but the service that accesses it is hosted in the cloud.
Data migration options include:
• Implementing a bi-directional synchronising method between on-premises and cloud databases. Remove the on-premises database once all data consumers have been migrated to the cloud.
• Use an on-premises database with one-way synchronisation to a cloud-based database, and restrict consumer access to the on-premises version. When you’re finished, deactivate access to the on-premises version, making the cloud-based version the primary database, and allowing cloud-based consumers to use the new database.
• Make use of a cloud data-migration service, such as those provided by Amazon Web Services.
Don’t underestimate the necessity and complexity of data migration planning. Failure to pay strict attention to your data-migration plan before beginning a cloud migration might result in migrations failing or failing to meet expectations. Your migration architect should be heavily involved in data migration planning.
Change over output
When and how do you switch over the production system from the legacy on-premises solution to the new cloud version? The answer depends on the complexity and architecture of your application, and especially the architecture of your data and data stores.
There are two common approaches:
• Do it all at once. Wait until you’ve moved the entire application or service over to the cloud and validated that it works there, and then switch traffic from the on-premises stack to the cloud stack.
• Do it a little bit at a time. Move a few customers over, test that things are still working, and then move a few more customers. Continue this process until you’ve moved all your customers to the cloud-based application.
Examine the application’s resource allocation.
Even after you’ve completed your cloud migration, there are a few additional items to consider. The most crucial aspect is resource optimization. The cloud is designed for dynamic resource allocation, therefore allocating resources (servers, for example) statically does not make use of the cloud’s characteristics. As you migrate to the cloud, ensure that your teams have a strategy in place for allocating resources to your application. When you need to provide extra resources to a cloud-based application, they are frequently accessible from the vendor in nearly any number at any time. This implies that providing your teams have the application architecture in place to allow dynamic scaling, you can usually rely upon that you can scale as needed to meet demand.
A variety of variables impact an organization’s choice to explore whether or not to transfer an app or workload to the cloud.
In general, most digital transformation projects rely heavily on the cloud. Big data analytics is an enticing pull of cloud platforms, giving size and processing power that most on-premises solutions cannot match. And, as businesses grow their usage of cloud-native technology, they are looking for more uniform template-driven procedures rather than depending on assumptions and a small core of developers and architects.
Finally, cloud computing relieves a corporate IT staff of the task of managing uptime. Placing an application on the cloud is frequently the most natural step toward expansion.