The Evolution of Data Protection

Transcription

1 The Evolution of Data Protection White Paper, May 2016

2 The Evolution of Data Protection Executive Summary The last ~25 years have seen a significant evolution of IT applications driven by new socio-economic trends, evolving business requirements and next-gen technology innovations. The client-server era of the 1990 s was marked by the rise of enterprise applications that increased workforce productivity. The virtualization era of 2000 s was driven by improvements in hardware utilization and interactive web applications. Finally, the current big data era is rooted in improving operational efficiency through automation and real-time data-driven business insights. As enterprise applications have evolved, so, too, has the infrastructure stack (databases, storage, data management, et al) on which they are deployed and run. Specifically, data protection has kept pace with the IT application requirements and new data protection technologies have emerged. This cycle has also witnessed the rise and fall of several enterprise software and hardware vendors. Many start-ups have prospered by disrupting the traditional notions of storing, managing and leveraging data. This paper characterizes the last ~25 years into three eras and details the changes in next-gen applications and related data protection technologies. The Client-Server Era The period from was marked by client-server applications that were the key IT drivers of enterprise infrastructure. These applications aimed at improving productivity by integrating and automating all aspects of operations such as planning, development, manufacturing, sales, marketing and others. These early Enterprise Resource Planning (ERP) systems were deployed and used for standard business tasks such as forecasting demand, projecting inventory build-up and ordering raw materials. Towards the later half of 1990 s, Customer Relationship Manager (CRM) systems revolutionized sales automation. These applications were deployed mostly on relational databases, which went through a period of extensive growth to maturity.

3 The Evolution of IT Application Stack: 3rd Platform Era From a data protection perspective, this was an era of adoption and widespread growth for the first generation backup software products such as Veritas and Legato. The workloads that were protected were file systems and relational databases - small data set sizes and low-volume. The data was processed and indexed by backup media server and stored on tape devices. During the mid-1990s, storage vendors brought snapshot technology in their SAN and NAS products, bringing forward a new dimension to data protection. Recovery from snapshots was much faster than it was from tape, but more expensive as it consumed primary storage capacity. Snapshots complemented backups - giving customers a trade-off between RPO/RTO and budgets. Data protection products were able to meet the requirements of classical enterprise applications, but the rapid adoption of World Wide Web quickly began to test the limits of the underlying infrastructure. The Virtualization Era The period from was marked by digitization and Web 2.0 applications. These applications aimed at improving interaction with customers, collaboration across an organization and social interaction. These trends put tremendous pressure on relational databases as they hit their scale limits. There was a move towards sharded databases to meet the performance requirements, but cost and complexity also skyrocketed. Virtualization was broadly adopted to increase hardware efficiency.

4 As organizations became more agile and dependent on data, the data protection systems evolved to reduce data loss by reducing the recovery time objective and recovery point objective (RPO and RTO). Data Domain disrupted the backup storage market with block-based deduplication and disk-based backups. Data Domain also enabled corporate IT teams to meet low RTO requirements by recovering from disk instead of tape media. In addition, high availability became a key requirement for mission critical applications and replication solutions such as GoldenGate and RecoverPoint came to the rescue. Vendors such as Veeam leveraged the virtualization trend by focusing on VM level backup and replication solutions. However, ease of deploying a VM from a backup copy also resulted in VM sprawl and multiple copies of data. Generation 2 vendors such as Delphix and Actifio came to life in this era to solve the copy sprawl issue with the new paradigm of copy data management. By the end of this era, data protection included backups, snapshots, synchronous and asynchronous replication, and copy data management. The Big Data Era In the last 5 years, applications are again undergoing a paradigm shift. The applications now require more agility, scalability and availability. The key trends in this era are the use of social platforms, information access on mobile devices, and software as a service (SaaS). Being able to ingest large amounts of data from various sources, and then process it in real-time to deliver contextual information or business insights is a major competitive differentiator. To meet these application requirements, organizations are forced to look beyond traditional relational databases. This has resulted in a slew of new database systems that are distributed and scale-out in nature, can be deployed on commodity hardware and offer tunable consistency vs. performance tradeoffs. To cater to the agility requirements, database-as-a-service model in cloud is being adopted as well. Keyword Search Trend (Google Trends)

5 The requirements for data protection have changed forever, driven by this data-centric world (web scale applications and distributed databases). Organizations are collecting vast amounts of data and seek to drive more value from that data to make better and faster business decisions. Most distributed and cloud databases already provide replication capability and thus satisfy the availability requirements of data protection. However, data protection requirements for scalable point-in-time backup and recovery need to be addressed. Without point-in-time backups, organizations are at substantial risk of losing data due to human error, logical corruption and other operational failures. Traditional backup solutions were built to address the requirements of relational databases that used shared storage and had the ACID transaction model. Unfortunately, they fall well short in addressing the point-in-time backup requirements of distributed databases (local storage, eventual consistency, and the elastic nature of infrastructure). As database architecture has fundamentally changed to meet new application requirements, data protection needs to be redefined and re-architected as well. The following are the new requirements for data protection. Take a durable point-in-time backup copy of an eventually consistent database, we call it versioning the new paradigm of data protection for this new distributed era: backups to snapshots to replication to copy data management to versioning Minimize time to recover from failures (low RTO) Scale with the growing needs of application Enable easy refresh of test/dev environments for continuous development Provide operational resiliency in event of failures Provide deployment flexibility in public cloud or on-premise datacenter Most organizations are investing in enterprise-grade point-in-time backup and recovery products so they may deploy and scale their next-generation application on distributed databases with confidence. In the next 5 years, it will be exciting to watch companies redefine the data protection technologies to meet the requirements of next generation applications.