How To Migrate PB/TBs Of Data To The Cloud Seamlessly?

If your organization is migrating PB/TB’s of data into the cloud. The most common procedure is to load the data into a physical appliance with data, then ship the appliance to a cloud provider. There’s an old-school principal.

Any large-scale data migrations can incur high network costs. They would take unrealistically long transfer times. No matter how fast is your networks can take months and years to move terabytes and petabytes of data from an on-premises data center to a public cloud provider.

We have a simple method that reduces the transfer time in the most cost-effective manner. This blog gives you AWS Snowball a shippable storage device for migrating petabyte-scale data sets into the cloud. How Minfy helped a media company to migrate their TB’s of data into the cloud

Manually migrating large-scale data is a time-consuming undertaking. Most wide area networks suffer from extended delays transmitting thousands of terabytes of data, stretching from hours to months.

On-premise workloads are predicted to shrink from 37% today to 27% of all workloads by 2020. 

Migrating huge amounts of both structured and unstructured data involve detailed planning, expensive software purchases, effective execution roadmap, proper cleanup and error corrections, speedy and seamless access transfer, data elimination from existing storage facility and validation. Streaming data brings in a new dimension of higher velocity and real-time processing constraints into the picture. Velocity differs based on the type of application and quality of data to be transferred.

Transferring petabytes amount of data in itself takes a long time, in addition, computing and performing analytics takes even longer threatening agility of the organization. This also affects the organizations to innovate and embrace emerging trends like IoT, Artificial Intelligence and Edge Computing.  Another issue is having a centralized management location for diverse infrastructures, having defined access roles (RBAC)  at the project level and BU level is imperative in the current global working space. Diverse teams, multiple sites, different infrastructure requirements increase operational costs to large scale as developing, deploying and operating take a long time and increase overhead costs to a large scale.

Snowball from AWS is a petabyte-scale data transport solution that is used to transfer large amounts of data into and out of the AWS cloud. It is designed to intelligently address common large-scale data transfer challenges. Snowball is simple, fast, more secure, and can be as little as one-fifth the cost of transferring data via high-speed Internet.

You can opt to use a single AWS Snowball device to transport multiple terabytes of data, or use multiple devices in parallel to transfer petabytes of data. Additionally, AWS Snowmobile truck-size option can help you in transforming exabyte data into the cloud.

Seamless migration

AWS Snowball is being used by enterprises for migrating huge volumes of data – regardless of complexities and types across uses and sizes. Genomics data, analytics, backups, migration projects, video libraries, and image repositories – what you want to migrate, you can effortlessly do so without expecting the vulnerabilities and barriers of migration.

Time 

Transferring 100 terabytes of data, for example, may take more than 100 days over a dedicated 100

Mbps connection

Moreover, it may so happen that if the connectivity breaks the transfer may start all over again. With Snowball devices, the desired activity can be completed within a week or less without a data loss guarantee.

Highly compatible and scalable

The Snowball device is very easy to connect to your existing systems, and provides endless scalability advantages.

AWS Snowball is cost effective

It is very affordable when compared with the cost associated with data for high-speed Internet transfers. With obvious benefits, it delivers seamless migration facility at a cheap price It also offers easy data retrieval benefits

AWS Snowball is a service that expedites the transfer of large amounts of data into and out of cloud using physical storage devices, bypassing the internet. These physical storage devices transfer data at faster-than internet speed over the regional carriers, complete with E Ink shipping labels. This data is then transferred into the Amazon Simple Storage Service (S3).

The Snowball appliances and provides powerful interfaces that you can use to create jobs, transfer data, and track the status of your jobs through to completion. Since the devices can be directly sent to the customers, it is easy to receive and share volumes of business data with stakeholders.

It has an 80TB model for all regions and the 50TB only for the USA. It transfers data to S3 in an encrypted format, protecting the data. Jobs are managed through a management console or programmatically through the job management API. AWS Snowball Management Console and the job management API for creating and managing jobs.

The media company is headquartered in Kolkatta. had a massive inventory of data in TB.  Managing and migrating such large streams of rich content required for them to use huge volumes of manpower expertised in the implementation of cloud migration.

The company continuously uploads new digital content on its platform and anticipates seamless media consumption for its target audience. The tape drive backup system, because of its portability and adaptability limitations made it relatively challenging to provide its audience with instant and endless access to content-rich programs. The company wanted to achieve cost-effective outcome while retaining their expectations in performance, stability, compatibility, and compliance

Minfy extracted 100 TB data out of the Tape Drives and moved on to AWS using AWS Snowball. Files transferred using Snowball were also moved directly to Glacier for archival. AWS File Gateway was configured to move daily delta files directly on to AWS S3 Files stored on AWS S3 as the primary storage with Intelligent Tier enabled. The Intelligent storage class is a low cost and optimizing it by the data access patterns, not compromising with the performance or operational overhead. It moves data between two access tiers – frequent and infrequent access tiers – when access pattern changes, ideal for data with changing access patterns.

The data is moved to Glacier from Amazon S3 based on lifecycle policies via the AWS Management Console, which set rules to configure the movement of data to Glacier. It can be either transition or expiration which decides the cost of data management.

This is applied to the S3 buckets, by selecting the appropriate bucket and going to the Management tab to Add Lifecycle Rule. Here the rules are added with a name and selecting what versions of data are transferred, after how many days. Later an expiration date can be specified, which will permanently delete data from S3 after a given number of days. The files can be restored from Glacier to be moved to S3 by specifying how long to be accessible on S3 and retrieval types – Bulk, Standard and Expedited.

The lifecycle rules are highly useful when the data only needs to be available on S3 for a specified amount of time like periodic logs or some those need to be archived like digital media as in the case of our project. Broadly there are GET bucket lifecycle, PUT bucket lifecycle and DELETE bucket lifecycle.