FIVE MISTAKES TO AVOID WHEN MOVING YOUR DATA TO THE CLOUD
Why do businesses move their data from on-prem to the cloud? Well, it saves them a ton of money—not just on infrastructure and hardware costs, but labor costs too. Moving your data to the cloud gives you the ability to automate your data operations and gain visibility to your data while keeping it organized and secure.
There’s a lot to consider when migrating your data to the cloud. Do I choose a hybrid or multi-cloud provider? How secure will my data be? Will this create more work for my team?
The path to the cloud has many twists and turns, and costly mistakes are easy to make if you’re not careful. But with the right preparation, the right tools, and the right partners, you can avoid making those mistakes, and set your data migration up for success.
Here are our Five Mistakes to Avoid when Migrating Your Data to the Cloud, along with advice on how to avoid them.
#1: Not using the right data storage classes and accessibility
Improperly stored data is a waste of time and money. The core structure of data storage begins with buckets. Each time you create a bucket, you assign it a globally-unique name, a geographic location where the bucket and its contents are stored, and a cloud storage class.
A cloud storage class is a classification of data based on how it’s accessed and where it resides. Google Cloud Storage offers four types of cloud storage classes—standard, nearline, cold line, and archive—and each has its own benefits and drawbacks.
Four types of storage classes:
- Standard storage: Best for frequently accessed data that’s available around the world and/or data stored for short periods of time. E.g. website content, data supporting your apps, and customer engagement.
- Nearline storage: A lower-cost service for data you plan to access once a month. E.g., Monthly analytic reports for stakeholders,
- Coldline storage: A very low-cost service for data accessed once a quarter. E.g., disaster recovery data or short-term data archiving.
- Archive storage: The lowest-cost service for storing data accessed less than once a year. E.g. legal data or disaster recovery data.
#2: Not co-locating your data in the same place where other tools are using it
When you’re storing data in the cloud, it’s important to make sure that your data is co-located with the tools and applications you’re using. This will help reduce latency and ensure that your data is always accessible when you need it.
There are a few different ways to do this:
- Use a storage class that’s specifically designed for the type of data you’re using. For example, if you’re using data for analytics, you might want to use a storage class that’s designed for fast access and low latency, such as Standard storage.
- Use a region that’s close to where your users are located. For example, if most of your users are in the US, you might want to use a storage class that’s designed for the US region. If you’re unsure which region(s) to store your data, the Google Cloud Region Picker tool helps you pick with considerations about carbon footprint, price, and latency.
- Use a bucket that’s in the same project as the tools and applications you’re using. This will help ensure that your data is always accessible and that you have the permissions you need to access it.
#3: Not creating scalable and resilient applications
When creating applications in the cloud, it’s important to make sure that they are scalable and resilient. Your apps should be able to handle increased traffic or data loads without issue and quickly recover from any outages or failures.
By removing under-utilized resources, you can also reduce cloud costs. Moving to the cloud also gives you the flexibility to adjust the resources consumed by an application. You can reduce cloud costs by removing under-utilized resources without compromising performance or user experience.
There are a few different ways to do this:
- Use managed services: Managed services, such as Google Cloud SQL, automate many of the complex tasks involved in running a database, such as encryption patching, monitoring, and backups. This can help free up time for you to focus on other aspects of your application.
- Use autoscaling: Compute Engine virtual machines and Google Kubernetes Engine (GKE) clusters integrate with auto scalers that let you grow or shrink resource consumption based on defined metrics. This can help ensure that your application is always available and can handle increased traffic or data loads.
- Set up predictive analytics: Products like BigQuery can deliver real-time data so you have up-to-date information on all your business processes and can securely share it with your team. With built-in machine learning, BigQuery is able to predict business outcomes without the need to move your data.
By following these best practices, you can make sure that your data is always available and that your applications are scalable and resilient. This will help you save time and money while ensuring that your users have a positive experience.
#4: Ignoring compliance and security needs
As data breaches become more commonplace, your business is at risk of hackers gaining access to valuable information. When storing data in the cloud, it’s important to make sure that your data is secure and compliant with any relevant regulations. Google Cloud offers built-in data protection to protect your business from intrusions, theft, and attacks. They also perform third-party audits and certifications, documentation, and legal commitments to help support your compliance.
Tips for securing your data:
- Monitor access to your data: Tools like Stackdriver Logging and Stackdriver Monitoring give monitor access to your data and help identify any potential security issues.
- Regularly back up your data: This prevents data loss in the event of an attack or outage. Google Cloud provides multiple options for backing up data, including Cloud Storage, Cloud Bigtable, and Spanner.
- Encrypt your data: Google Cloud provides multiple options for encrypting data at rest and in transit, including Cloud Storage encryption, BigQuery encryption, and Cloud Key Management Service.
Tips for having compliant data:
- Choose the right storage class: Some storage classes have additional features that can help with compliance, such as Object Lock for S3 Standard Infrequent Access (S3 Standard IA) and S3 One Zone IA. Object Lock allows you to configure retention dates and legal holds, which can help with data compliance.
- Add retention policies to buckets: Buckets in Cloud Storage require a data retention policy that governs how long objects in the bucket must be retained. Google Cloud offers a feature called BucketLock that helps you configure your data retention policies.
- Use compliance-enabled products: Products like Cloud Healthcare API and BigQuery help you comply with regulations such as HIPAA and GDPR. These products offer features such as data encryption, auditing, and access control to help you meet compliance requirements.
Following these tips will make sure that your data is secure and compliant with any relevant regulations. This will help you protect your business from data breaches and ensure that your user’s data is always safe.
#5: Ignoring Infrastructure as Code (IaC) approach
The Infrastructure as Code (IaC) approach is a way of managing cloud infrastructure that treats infrastructure resources as code. This means that infrastructure can be managed using the same tools and processes that are used for managing software code. IaC helped popularize the use of automation and configuration management tools like Puppet, Chef, and Ansible.
Benefits of using IaC:
- Easy to provision and manage cloud resources. This can help save time and money by reducing the need for manual Intervention.
- Ensures that resources are consistent across environments. This can help prevent errors and inconsistencies that can lead to downtime or data loss.
- Easy to version control infrastructure changes. This can help you track changes and roll back to previous versions if necessary.
- Improves collaboration among teams by allowing infrastructure changes to be reviewed and approved before they are implemented.
Google Cloud provides a number of IaC tools to help you manage your cloud infrastructure, including:
- Deployment Manager: Declarative templating tool that helps you create, manage, and deploy cloud resources.
- Cloud Shell: Interactive shell environment that gives you access to the Google Cloud Console and a pre-authenticated gcloud command-line interface.
- Cloud SDK: Command-line interface that you can use to manage your Google Cloud resources.
If you’re not using IaC to manage your cloud infrastructure, you’re missing out on the many benefits it has to offer. IaC can help save time and money, ensure consistency across environments, and make it easy to track and roll back changes. By adopting an IaC approach, you can make sure that your cloud infrastructure is always up-to-date and compliant.
Moving your data to the cloud doesn’t have to be complicated or risky. By following these best practices, you can make sure that your data is secure and compliant with any relevant regulations. This will help you protect your business from data breaches and ensure that your user’s data is always safe.
Manpreet Singh, Senior Data Engineer at Tensure