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Increasing Your Cloud Footprint

The jump to the cloud can be a scary proposition.  For an enterprise with systems deeply embedded in traditional infrastructure like back office computer rooms and datacenters the move to the cloud can be daunting. The thought of having all of your data in someone else’s hands can make some IT admins cringe.  However, once you start looking into cloud technologies you start seeing some of the great benefits, especially with providers like Amazon Web Services (AWS).  The cloud can be cost-effective, elastic and scalable, flexible, and secure.  That same IT admin cringing at the thought of their data in someone else’s hands may finally realize that AWS is a bit more secure than a computer rack sitting under an employee’s desk in a remote office.  Once the decision is finally made to “try out” the cloud, the planning phase can begin.

Most of the time the biggest question is, “How do we start with the cloud?”  The answer is to use a phased approach.  By picking applications and workloads that are less mission critical, you can try the newest cloud technologies with less risk.  When deciding which workloads to move, you should ask yourself the following questions; Is there a business need for moving this workload to the cloud?  Is the technology a natural fit for the cloud?  What impact will this have on the business? If all those questions are suitably answered, your workloads will be successful in the cloud.

One great place to start is with archiving and backups.  These types of workloads are important, but the data you’re dealing with is likely just a copy of data you already have, so it is considerably less risky.  The easiest way to start with archives and backups is to try out S3 and Glacier.  Many of today’s backup utilities you may already be using, like Symantec Netbackup  and Veeam Backup & Replication, have cloud versions that can directly backup to AWS. This allows you to use start using the cloud without changing much of your embedded backup processes.  By moving less critical workloads you are taking the first steps in increasing your cloud footprint.

Now that you have moved your backups to AWS using S3 and Glacier, what’s next?  The next logical step would be to try some of the other services AWS offers.  Another workload that can often be moved to the cloud is Disaster Recovery.   DR is an area that will allow you to more AWS services like VPC, EC2, EBS, RDS, Route53 and ELBs.  DR is a perfect way to increase your cloud footprint because it will allow you to construct your current environment, which you should already be very familiar with, in the cloud.  A Pilot Light DR solution is one type of DR solution commonly seen in AWS.  In the Pilot Light scenario the DR site has minimal systems and resources with the core elements already configured to enable rapid recovery once a disaster happens.  To build a Pilot Light DR solution you would create the AWS network infrastructure (VPC), deploy the core AWS building blocks needed for the minimal Pilot Light configuration (EC2, EBS, RDS, and ELBs), and determine the process for recovery (Route53).  When it is time for recovery all the other components can be quickly provisioned to give you a fully working environment. By moving DR to the cloud you’ve increased your cloud footprint even more and are on your way to cloud domination!

The next logical step is to move Test and Dev environments into the cloud. Here you can get creative with the way you use the AWS technologies.  When building systems on AWS make sure to follow the Architecting Best Practices: Designing for failure means nothing will fail, decouple your components, take advantage of elasticity, build security into every layer, think parallel, and don’t fear constraints! Start with proof-of-concept (POC) to the development environment, and use AWS reference architecture to aid in the learning and planning process.  Next your legacy application in the new environment and migrate data.  The POC is not complete until you validate that it works and performance is to your expectations.  Once you get to this point, you can reevaluate the build and optimize it to exact specifications needed. Finally, you’re one step closer to deploying actual production workloads to the cloud!

Production workloads are obviously the most important, but with the phased approach you’ve taken to increase your cloud footprint, it’s not that far of a jump from the other workloads you now have running in AWS.   Some of the important things to remember to be successful with AWS include being aware of the rapid pace of the technology (this includes improved services and price drops), that security is your responsibility as well as Amazon’s, and that there isn’t a one-size-fits-all solution.  Lastly, all workloads you implement in the cloud should still have stringent security and comprehensive monitoring as you would on any of your on-premises systems.

Overall, a phased approach is a great way to start using AWS.  Start with simple services and traditional workloads that have a natural fit for AWS (e.g. backups and archiving).  Next, start to explore other AWS services by building out environments that are familiar to you (e.g. DR). Finally, experiment with POCs and the entire gambit of AWS to benefit for more efficient production operations.  Like many new technologies it takes time for adoption. By increasing your cloud footprint over time you can set expectations for cloud technologies in your enterprise and make it a more comfortable proposition for all.

-Derek Baltazar, Senior Cloud Engineer

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Storage Gateway with Amazon Web Services

Backup and disaster recovery often require solutions that add complexity and additional cost to properly synchronize your data and systems.  Amazon Web Services™ (AWS) helps drive this cost and complexity with a number of services.  Amazon S3 provides a highly durable (99.999999999%) storage platform for your backups.  This service backs up your data to multiple availability zones (AZ) to provide you the ultimate peace of mind for your data.  AWS also provides an ultra-low cost service for long-term cold storage that is aptly named Glacier.  At $0.01 per GB / month this service will force you to ask, “Why am I not using AWS today?”

AWS has developed the AWS Storage Gateway to make your backups secure and efficient.  For only $125 per backup location per month, you will have a robust solution that provides the following features:

  • Secure transfers of all data to AWS S3 storage
  • Compatible with your current architecture – there is no need to call up your local storage vendor for a special adapter or firmware version to use Storage Gateway
  • Designed for AWS – this provides a seamless integration of your current environment to AWS services

AWS Storage Gateway and Amazon EC2 (snapshots of machine images) together provide a simple cloud-hosted DR solution.   Amazon EC2 allows you to quickly launch images of your production environment in AWS when you need them.  The AWS Storage Gateway seamlessly orchestrates with S3 to provide you a robust backup and disaster recovery solution that meets anyone’s budget.

-Matt Whitney, Sales Executive

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AWS S3-Glacier Lifecycle Management

Not long ago, 2nd Watch published an article on Amazon Glacier. In it Caleb provides a great primer on the capabilities of Glacier and the cost benefits.  Now that he’s taken the time to explain what it is, let’s talk about possible use cases for Glacier and how to avoid some of the pitfalls.  As Amazon says, “Amazon Glacier is optimized for data that is infrequently accessed and for which retrieval times of several hours are suitable.”  What immediately comes to mind are backups, but most AWS customers do this through EBS snapshots, which can restore in minutes, while a Glacier recall can take hours.  Rather than looking at the obvious, consider these use cases for Glacier Archival storage: compliance (regulatory or internal process), conversion of paper archives, and application retirement.

Compliance often forces organizations to retain records and backups for years, customers often mention a seven year retention policy based on regulatory compliance.  In seven years, a traditional (on premise) server can be replaced at least once, operating systems are upgraded several times, applications have been upgraded or modified, and backup hardware/software has been changed.  Add to that all the media that would need to be replaced/upgraded and you have every IT department’s nightmare – needing to either maintain old tape hardware or convert all the old backup tapes to the new hardware format (and hope too many haven’t degraded over the years).  Glacier removes the need to worry about the hardware, the media, and the storage fees (currently 1¢ per GB/month in US-East) are tiny compared to the cost of media and storage on premise.  Upload your backup file(s) to S3, setup a lifecycle policy, and you have greatly simplified your archival process while keeping regulatory compliance.

So how do customers create these lifecycle policies so their data automatically moves to Glacier?  From the AWS Management Console, once you have an S3 bucket there is a Property called ‘Lifecycle’ that can manage the migration to Glacier (and possible deletion as well).  Add a rule (or rules) to the S3 bucket that can migrate files based on a filename prefix, how long since their creation date, or how long from an effective date (perhaps 1 day from the current date for things you want to move directly to Glacier).  For the example above, perhaps customers take backup files, move them to S3, then have them move to Glacier after 30 days and delete after 7 years.

Lifecycle Rule

Before we go too far and setup lifecycles, however, one major point should be highlighted: Amazon charges customers based on GB/month stored in Glacier and a one-time fee for each file moved from S3 to Glacier.  Moving a terabyte of data from S3 to Glacier could cost little more than $10/month in storage fees, however, if that data is made up of 1k log files, the one-time fee for that migration can be more than $50,000!  While this is an extreme example, consider data management before archiving.  If at all possible, compress the files into a single file (zip/tar/rar), upload those compressed files to S3 and then archive to Glacier.

-Keith Homewood, Cloud Architect

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Amazon Glacier: Your 1¢ Cloud-based Backup Solution

If you haven’t heard of Amazon Glacier, you need to check it out. As its name implies, you can think of Glacier as “frozen” storage. When considering the speed of EBS and S3, Glacier by comparison moves glacially slow. Consider Glacier as essentially a cloud-based archival solution that works similarly to old-style tape backup. In the past, backups first ran to tape, then were stored locally in case of immediate access requirements, and were then taken off-site once a certain date requirement was met (once a week, once a month, etc.). Glacier essentially works as the last stage of that process.

When a snapshot in S3, for instance, gets to be a month old, you can instruct AWS to automatically move that object to Glacier. Writing it to Glacier happens pretty much immediately, though being able to see that object on your Glacier management console can take between 3-5 hours. If you need it back, you’ll issue a request, but that can take up to 24 hours to be resolved. Amazon hasn’t released the exact mechanics of how they’re storing the data on their end, but large tape libraries are a good bet since they jive with one of Glacier’s best features: its price. That’s only $0.01 per gigabyte. Its second best feature is 11 nines worth of “durability” (which refers to data loss) and 4 nines worth of “reliability” (which refers to data availability). That’s 99.999999999% for those who like the visual.

Configuring Glacier, while a straightforward process, will require some technical savvy on your part. Amazon has done a nice job of representing how Glacier works in an illustration:

glacier1

As you can see, the first step is to download the Glacier software development kit (SDK), which is available for Java or .NET.  Once you’ve got that, you’ll need to create your vault. This is an easy step that starts with accessing your Glacier management console, selecting your service region (Glacier is automatically redundant across availability zones in your region, which is part of the reason for its high durability rating), naming your vault, and hitting the create button. I’m using the sandbox environment that comes with your AWS account to take these screen shots, so the region is pre-selected. In a live environment, this would be a drop-down menu providing you with region options.

glacier2

The vault is where you’ll store your objects, which equate to a single file, like a document or a photo. But instead of proceeding directly to vault creation from the screen above, be sure and set up your vault’s Amazon Simple Notification Service (SNS) parameters.

glacier3

Notifications can be created for a variety of operations and delivered to systems managers or applications using whatever protocol you need (HTML for a homegrown web control or email for your sys admin, for example). Once you create the vault from the notifications screen, you’re in your basic Glacier management console:

glacier4

Uploading and downloading documents is where it gets technical. Currently, the web-based console above doesn’t have tools for managing archive operations like you’d find with S3. Uploading, downloading, deleting or any other operation will require programming in whichever language for which you’ve downloaded the SDK. You can use the AWS Identity and Access Management (IAM) service to attach user permissions to vaults and manage billing through your Account interface, but everything else happens at the code level. However, there are third-party Glacier consoles out there that can handle much of the development stuff in the background while presenting you with a much simpler management interface, such as CloudBerry Explorer 3.6. We’re not going to run through code samples here, but Amazon has plenty of resources for this off its Sample Code & Libraries site.

On the upside, while programming for Glacier operations is difficult for non-programmers, if you’ve got the skills, it provides a lot of flexibility in designing your own archive and backup processes. You can assign vaults to any of the various backup operations being run by your business and define your own archive schedules. Essentially, that means you can configure a hierarchical storage management (HSM) architecture that natively incorporates AWS.

For example, imagine a typical server farm running in EC2. At the first tier, it’s using EBS for immediate, current data transactions, similar to a hard disk or SAN LUN. When files in your EBS store have been unused for a period of time or if you’ve scheduled them to move at a recurring time (like with server snapshots), those files can be automatically moved to S3. Access between your EC2 servers and S3 isn’t quite as fast as EBS, but it’s still a nearline return on data requests. Once those files have lived on S3 for a time, you can give them a time to live (TTL) parameter after which they are automatically archived on Glacier. It’ll take some programming work, but unlike with standard on-premises archival solutions, which are usually based on a proprietary architecture, using Java or .NET means you can configure your storage management any way you like – for different geographic locations, different departments, different applications, or even different kinds of data.

And this kind of HSM design doesn’t have to be entirely cloud-based. Glacier works just as well with on-premises data, applications, or server management. There is no minimum or maximum amount of data you can archive with Glacier, though individual archives can’t be less than 1 byte or larger than 40 terabytes. To help you observe regulatory compliance issues, Glacier uses secure protocols for data transfer and encrypts all data on the server side using key management and 256-bit encryption.

Pricing is extremely low and simple to calculate. Data stored in Glacier is $0.01 per gigabyte. Upload and retrieval operations run only $0.05 per 1000 requests, and there is a pro-rated charge of $0.03 per gigabyte if you delete objects prior to 90 days of storage. Like everything else in AWS, Glacier is a powerful solution that provides highly customizable functionality for which you only pay for what you use. This service is definitely worth a very close look.

-Caleb Carter, Solutions Architect

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Cloud Backup: More is Always Better

You’ve seen podcasts, blogs, whitepapers, and magazine articles all promoting backups, the concept, the benefits they provide, and the career crushing disasters that can happen when they’re ignored. Bottom line: You do it, and you do it now. Hey, do more than one, the more the merrier. Run at the right time (meaning low user load), and in a well maintained hierarchical storage process, they can only do good. A solid backup strategy can even get you business insurance discounts in some cases.

But backing up in-house servers is a relatively simple and time-ed process. Most operating systems have one or more backup utilities built-in, and then there are third-party options that take the concept to whole new level. But backup in or from the cloud is a new concept with new variables – data security, multi-tenant segregation, virtualized services, and especially cloud and internet bandwidth. That’s got to be difficult at the enterprise computing level. Wrong! Not for AWS customers.

For a while, cloud storage was mainly a backup solution on its own. But Amazon has matured its backup and data redundancy offerings over the years to a point where you’ll find a range of sophisticated options at your disposal, depending on your needs. Obviously, we start with S3.

S3 has been and still is a basic backup solution for many companies – some rely on it exclusively, since data in S3 gets additional redundancy and backup features in AWS’ datacenters, so customers can be fairly confident their data will be there when they need it. S3’s storage architecture is pleasantly simple to understand. You’ll find it revolves primarily around two key nouns: buckets and objects. Buckets are just ways to organize your objects, and objects represent every individual file that’s been backed up. Every object has its own secure URL, which allows easy organization and management of data using a number of homegrown tools like basic access control or Amazon prescribed bucket polices. But you’re also able to choose from new third-party solutions with even easier interfaces, like Symantec for enterprises or Dropbox for small businesses.

Recently, Amazon has fleshed out its backup solution even more with the introduction of Glacier, which doesn’t relate to melting polar ice caps as much as it does to slow data retrieval times. Glacier’s mission is to provide a much lower-cost backup solution (as little as a penny per gigabyte in some situations). The tradeoff is that because its low cost, it’s significantly slower than S3. But for long-term backup of important files, Glacier removes the need for repetitive backup operations, capacity planning, hardware provisioning and more. These are all time consuming tasks that add to the hidden costs of secure in-house backup. Glacier takes all that off your plate for very little money. Bottom line: use S3 if you’re storing data you’ll access often or that requires high-speed access; use Glacier for less frequently accessed data for which slow retrieval times (sometimes several hours) are acceptable.

That’s only a short glimpse into the S3 portion of Amazon’s backup capabilities. If we went into detail about all of AWS data protection features, we could publish this as a book. We’ll hit each of them in detail in future posts, but here’s a quick list of Amazon’s data protection solutions across their service portfolio:

  • Multi-zone and multi-region redundancy
  • AWS relational database service (RDS) bundled, automated back up
  • RDS backups you can control manually, like snapshots
  • AWS Import/Export
  • EC2 and S3
  • S3 and Elastic Block Store (EBS)
  • Route 53
  • Elastic Load Balancing (ELB)
  • Third-party backup platforms you can use to construct your own AWS storage hierarchy

Data safety has been a hot-button issue for folks still on the fence about adopting the cloud. But AWS has done an excellent job innovating sophisticated new data redundancy solutions that can make backing up to the cloud safer than in your own datacenter. Check it out.

-Travis Greenstreet, Senior Cloud Systems Engineer

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