Unlike other shifts in IT, the broad view of uptime is well understood. What has many IT pros confused is the myriad of options that exist to ensure the availability of their applications and achieve faster recovery times, consistent performance, and business continuity. From backup and disaster recovery, to high availability, to fault tolerance and more, a lot of confusion surrounds the differences between each type of availability solution and how IT teams can determine the best option for their business.
This gets even more complex when each category has a very broad definition within the industry. Take "high availability" for instance. Last year, a highly respected analyst firm issued a survey that said the majority of respondents believed that high availability meant having a disaster recovery plan in place. To someone who lives and breathes availability solutions, these are two very different things. The definitions will also fluctuate from person to person based on their history with different computing platforms – the IT guys working in the mainframe will define high availability very differently than those working in dev/ops. On top of this, for years research firm IDC has been using its own set of availability levels (AL1-AL4), but these are very broad as most technologies fall within just one of the availability levels and the levels haven't changed over time as technology has evolved.
In this slideshow, Jason Andersen, vice president of business line management, Stratus Technologies, will demystify the seven key types of availability solutions by clarifying what each one actually means. Keep in mind, when evaluating what you need, it is important that you consider not only what data is specifically being protected, but also the recovery time and infrastructure costs – mainly processing and networking – that your business can support.
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