Unlock the value of your historical data by migrating to open format
Is your data is trapped in legacy systems? Shyft provides a clear path to liberation; offering seamless portability, robust formatting, and efficient transit to support your evolving business needs.
Petabytes of data has been ingested in vendor specific format across many Enterprise Security Organizations to their Security Data Lake. Data stored in some of these Data Lakes, are in proprietary format which can only be consumed by vendors, like Splunk, ElasticSearch etc.
In general, compared to open text compressed format, Stored Data in proprietary format are:
Organizations need a solution to address the portability of this historically ingested data. They require a robust solution that scales and provides proper flexibility to allow formatting, transiting, and seamless use of data exactly as it is required by security and compliance.
Open text format data lakes and vendor agnostic data lakes are very important for any public or private organizations. It gives flexibility for various groups/teams in the organization to be able to access the data and perform required analytics with their respective domain knowledge. This in turn helps drive business initiatives.
Shyft is the product that can help organizations with large size data exports from “Splunk SmartStore”, “Splunk Cold/Frozen Buckets” or other Security Data Products like ElasticSearch. Exporting data would reduce cost of storage by at least up to 70 percent on an average. There is no reason for any organization to lock petabytes of useful data in vendor proprietary format.
Shyft is a unique solution built with an embedded python distributed framework to scale and perform the tasks. Architecture diagram illustrates the workflow process as shown below
In essence, Shyft allows you to unlock the value of your historical data by freeing it from stringent and heavy proprietary formats. This helps organizations slash costs and utilize data efficiently in any tools they desire.
Building a cloud architecture involves several steps to design and implement an effective and scalable cloud infrastructure. Here is an overview of the general steps involved:
Determine your business needs, goals, and objectives for moving to the cloud. Identify the applications, services, and data that will be part of your cloud architecture.
Decide on the appropriate cloud model based on your requirements. This could be a public cloud, private cloud, hybrid cloud, or multi-cloud approach. Each model has its advantages and considerations.
Evaluate different cloud service providers based on factors such as reliability, performance, security, cost, and specific services they offer. Popular providers include Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), and IBM Cloud.
Plan the network infrastructure for your cloud environment. Define subnets, virtual private clouds (VPCs), security groups, and other networking components. Consider factors like scalability, availability, and data transfer requirements.
Define a robust security strategy to protect your cloud resources and data. Implement measures such as firewalls, encryption, access controls, intrusion detection and prevention systems, and regular security audits.
Determine how your data will be stored, organized, and accessed in the cloud. Choose appropriate storage options, such as object storage, block storage, or file storage. Consider data backup, replication, and disaster recovery mechanisms.
Determine the appropriate virtualization technologies, such as virtual machines (VMs) or containers, for your applications and services. Configure and deploy them in your cloud environment.
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