What are common mistakes to avoid when scaling your cloud storage?

Common mistakes in scaling cloud storage include underestimating future needs, neglecting data architecture optimization, overlooking security, failing to monitor costs, and ignoring redundancy and disaster recovery. Accurate forecasting and scalability planning are crucial. Optimizing data architecture ensures efficiency, while robust security measures protect against breaches. Monitoring costs prevents surprises, and implementing redundancy and disaster recovery ensures data availability and resilience.

Underestimating Data Growth: Many businesses fail to adequately forecast the rapid growth of their data. This can lead to a shortage of storage space or an insufficient infrastructure to manage the increasing volume. Neglecting Backup and Recovery Strategy: Not having a robust data backup and recovery strategy can be catastrophic. Regular backups and a recovery plan in case of data loss are essential.

The biggest mistake is to only compare prices. Most of the time, we have to fit the solution to the budget, but the solution chosen should be oriented to your requirements. In this context, it is important to note that object storage is ideal for storing a large amount of static files. Block storage is better suited for frequently accessed and dynamic data. File storage is a good option for sharing files on multiple machines and users.

Data type and workload: Understand the nature of your data and the applications that will access it. Determine if you need object storage for unstructured data, block storage for I/O-intensive applications, or file storage for shared file access. Scalability and durability: Assess your data growth requirements and evaluate the scalability and durability features offered by different storage options. Object storage usually excels in scalability and durability. Performance requirements: Consider the performance needs of your applications. If low latency and high performance are crucial, block storage might be the best fit. However, if slightly higher latency is acceptable, object storage can offer excellent scalability and durability.

Choosing the Wrong Cloud Storage Service: Mistake: Selecting a cloud storage service without considering specific business requirements, performance needs, and cost implications. Consideration: Assess the features, performance, pricing models, and data durability of different cloud storage options to choose the one that aligns best with your use case.

If you don't automate your lifecycle management you can be sure that it'll become unmanageable very quickly. If you are using it as a backup repo' it's easy as typically that software will manage it for you. Other use cases again look for a tool to automate. Moving data between tiers needs to be carefully considered finding a happy middle ground can be the best option or look for a provider who can meet your needs better. For most providers as you go down a tier costs for the storage decrease but interacting with it (egress and API fees) increases. We have worked with many clients who have moved to COLD or ARCHIVE only to find that their costs have actually gone up, so make sure you understand the differences and implement accordingly.

Data retention policies: Define clear policies for how long different types of data should be retained based on legal, regulatory, or business requirements. Identify data that needs to be retained for specific periods and establish mechanisms to enforce retention rules. Data archiving: Archive data that is no longer actively used but still needs to be retained for compliance or historical purposes. Archiving allows you to move data to cheaper storage tiers or cold storage options, reducing costs while ensuring data accessibility when needed. Backup and recovery: Implement a robust backup strategy to protect against data loss or corruption. Regularly back up your critical data and test the recovery process to ensure data integrity.

Ignoring Data Lifecycle Management: Mistake: Neglecting to implement a comprehensive data lifecycle management strategy can result in increased costs and inefficiencies. Consideration: Define policies for data retention, archiving, and deletion. Utilize automated tools to manage data lifecycle efficiently based on access patterns and business needs.

Neglecting to properly manage data throughout its lifecycle can result in increased costs, compliance risks, and storage inefficiencies. Implementing a comprehensive lifecycle management strategy ensures that data is stored, accessed, and archived in accordance with business requirements and regulatory standards. By proactively managing data from creation to deletion, organizations can optimize storage resources, reduce risks, and enhance overall data governance.

Not having a lifecycle management policy means you are exposing your data to risks, leakage. It is harder to track archival data structures. One of the most common mistakes!

Encryption: Implement encryption mechanisms to protect your data both at rest and in transit. Access controls and authentication: Implement robust access controls to restrict data access to authorized users. Utilize strong authentication mechanisms such as multi-factor authentication (MFA) to ensure only legitimate users can access your data. Authorization and role-based access: Implement granular authorization policies and role-based access controls (RBAC) to ensure users have appropriate access permissions based on their roles and responsibilities. Auditing and monitoring: Implement auditing mechanisms to track user activities, data access, and modifications.

Neglecting Data Security and Privacy: Mistake: Failing to prioritize security measures, encryption, and access controls can lead to data breaches and compliance issues. Consideration: Implement robust security measures, including encryption in transit and at rest, access controls, and regular security audits. Ensure compliance with relevant regulations.

With cyber threats on the rise and regulatory compliance becoming stricter, protecting sensitive data is paramount. Ensure robust encryption, access controls, and regular security audits are in place to safeguard data from unauthorized access or breaches. Additionally, prioritize compliance with data privacy regulations like GDPR or CCPA to avoid hefty fines and reputational damage. Don't compromise on security – it's an investment that pays off in safeguarding your valuable assets.

Not encrypting the data or not using redaction strategies to mask sensitive data. It is important that your data is exposed to right personal and you are adding right access to the right data sets

When you're expanding your cloud storage, don't forget about performance and availability! You want your data to be fast and always accessible, right? Take some time to check if your systems can handle the increased load. Make sure there's a backup plan in case something goes wrong. Trust me, it'll save you a lot of headaches later on. Keep your data flowing smoothly and your users happy!

Understand the service level agreements provided by your cloud storage provider.Pay attention to metrics such as uptime, response times, and data durability. Choose a storage service with SLAs that align with your business requirements. Leverage redundancy and replication options provided by your cloud storage provider to enhance availability and data durability. Redundancy involves storing data across multiple storage devices or data centers to ensure availability in case of hardware failures. Replication allows data to be copied across geographically distributed regions, improving both availability and data resilience. Implement load balancing mechanisms to distribute data access across multiple storage resources.

Overlooking Performance and Availability Issues: Mistake: Ignoring performance considerations and failing to design for high availability can lead to service disruptions and slow data access. Consideration: Choose storage solutions with the right performance characteristics for your workloads. Implement redundancy and failover mechanisms to ensure high availability.

Object storage in the cloud can be used to create a pipeline for moving data to different storage tiers based on its lifespan. This is important for data lakes, as it can help organizations to reduce costs for files that are not being accessed but need to be retained for compliance. However, this can be challenging to implement, as it requires a project-oriented multi-bucket strategy.

Forgetting to Automate and Orchestrate: Mistake: Manual management of storage resources can be error-prone and time-consuming, hindering scalability. Consideration: Implement automation and orchestration tools to manage scaling, provisioning, and configuration changes. This ensures efficiency, consistency, and rapid response to changing demands.

One big mistake to avoid when scaling your cloud storage is forgetting to automate and orchestrate. Manual processes can slow you down and cause errors. By automating tasks and orchestrating workflows, you can save time and ensure everything runs smoothly. Take advantage of tools and scripts to automate repetitive tasks, and use orchestration platforms to coordinate complex processes. Trust me, it'll make your life a whole lot easier!

Failing to Plan and Test: Mistake: Scaling without proper planning and testing can lead to unexpected issues, including performance bottlenecks and resource constraints. Consideration: Develop a comprehensive scaling plan that includes testing in realistic scenarios. Monitor performance during testing and be prepared to adjust strategies based on results.

A failing cloud storage solution is almost always a failure of planning. That's not to say it's easy to plan and the big 3 providers make actually calculating your needs very difficult. My core advice is the cloud is different and needs to be treated as such, it's a different billing model, different scalability, different performance and different responsibilities of ownership, so when migrating or implementing a cloud solution ensure you have considered and optimised for both your needs and the capabilites of the platform to ensure maximum value.

I'd just like to highlight choice. Azure / AWS / GCP all have their place and they all provide a service which MAY be right for your use case but there are so many others out there, ensure you have explored all options before commiting to one or more of the obvious ones. The price differential can be huge >80% and the support and performance can be on par or better, often clients don't consider anything else and write off "cloud storage" as too expensive, less secure, lacking scalbility or too limited in features after looking at one or two providers... there are loads out there (yes some are rubbish) but with a small amount of detective work normally there are alternatives to consider within both budget and requirements.

Underestimating Costs: Cloud storage provider -Wasabi gives predictable pricing without egress fees, but it’s still important to regularly review usage to manage costs effectively. Monitor storage consumption to ensure you’re using resources efficiently.Also, unlike traditional cloud storage providers that have multiple tiers (e.g., hot, cold, and archival storage), Wasabi's uniform tier ensures that even archival data can be accessed quickly without the need for rehydration or additional delays associated with transitioning between tiers. This is particularly beneficial for archival use cases where infrequent but potentially urgent access to data is required.

With the advancement of AI you should also consider automating some of the data rules through AI or use AI in built in the tools you are using