Here’s how AWS lists the three broad job descriptions covered by the certs:

• Solutions Architect: a technical individual who is skilled at designing distributed applications and systems on the AWS platform. A Solution Architect generally has knowledge across a broad array of disciplines, including distributed application architecture, networking, infrastructure, and security.
• SysOps Administrator: a technical individual who is responsible for the operational health of an application on the AWS cloud. A SysOps Administrator has in-depth knowledge of the application or service they operate, including how the application is constructed, deployed, and automated, as well as the controls and monitoring points available.
• Developer: a technical individual who has designed and built an AWS-based application. A Developer has involvement with or responsibility for operating the application on the AWS platform.

Older tech companies — Microsoft, IBM, VMware, Cisco Systems — have long relied on certifications as a way for people — either those inside IT shops or at third-party VARs and integrators (and those seeking jobs in either camp) — to show that they have what it takes to succeed working with specific technologies. As with those programs, AWS candidates must pass an exam to get their credentials. Testing will be administered by Kryterion.

Some of the more valuable certs in recent years include the VMware Certified Professional (VCP), Cisco Certified International Expert (CCIE) and Microsoft Certified IT Professional (MCITP). And Certified Information Systems Security Professional (CISSP), a more vendor-agnostic certification, is also a top draw for potential hiring companies.

In another nod to the IT concerns of enterprise accounts, AWS also launched a security blog this week. The news comes just after Microsoft opened up Infrastructure-as-a-Service capabilities in Azure that are more directly competitive with AWS and Google gears up for the public release of Google Compute Engine, which I expect will happen at Google I/O in May. While AWS dominates public cloud infrastructure by virtue of its head start, many enterprise customers in particular will likely test out these rivals as well — nobody wants cloud lock-in.

Still, given the traction AWS has among startups and increasingly at bigger businesses, I’d expect to see these certifications cropping up in lots of job postings going forward.

Photo courtesy of Shutterstock user Mega Pixel

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At Scalr, we’ve been happy customers of Amazon’s infrastructure service, EC2, since 2007. In fact, we’ve built our tools for EC2 because we saw an opportunity to leverage its flexibility to help AWS customers easily design and manage resilient services. But as competitors spring up, we always test them to see how they compare, especially in regards to io performance.

On a warm June day in San Francisco, the Scalr team attended Google I/O 2012. Google was rumored to be launching a EC2 competitor, which we were interested in for our multi-cloud management software. It launched. And boy did it sound good. You see, EC2 and GCE offer pretty much the same core service, but Amazon has been plagued by poor network and disk performance, so Google’s promise to offer both higher and more consistent performance struck a real chord.

Not ones to be fooled by marketing-driven, hyped-up software, we applied for early access and were let in so we could start testing it ourselves. Once we got in, we felt like kids in a candy store. Google Compute Engine is not just fast. It’s Google fast. In fact, it’s a class of fast that enables new service architectures entirely. Here are the results from our tests, along with explanations of how GCE and EC2 differ, as well as comments and use cases.

A note about our data: The benchmarks run to collect the data presented here were taken twice a day, over four days, then averaged. When a high variance was observed, we took note of it and present it here as intervals for which 80 percent of observed data points fall into.

API

First off, GCE’s API is beautifully simple, explicit and easy to work with. Just take a look at it. Their firewalls are called “firewalls,” vlans are “networks,” and kernels are “kernels” (AKIs, anyone?). Anyone familiar with Unix will feel right at home.

Fast boot

Second, VMs are deployed and started with impressive speed (and we’ve extensively used 10 clouds). It routinely takes less than 30 seconds to login as root after making the insert call to launch a VM. As a reference point, this is the amount of time it takes AWS to get to the running state, after which you still need to wait for the OS to boot, for a total of 120 seconds on a good day, and 300 on a bad one (data points taken from us-east-1).

Boot times are measured in seconds.

We don’t know what sort of sorcery Google does here, but they clearly demonstrate engineering prowess. That’s 4-10x faster.

Volumes

Those of you familiar with Amazon’s EBS volumes know that you can attach and detach volumes to any instance, anytime. On GCE, you can’t (at least not yet). This precludes you from switching drives to minimize downtime: attaching a volume on a running server allows you to skip the boot and configure stages of bringing a new node up, which is useful when promoting an existing mysql slave to master and you just need to swap out storage devices.

While GCE’s “disks” (as they call them) have that one disadvantage, they offer some unique advantages over Amazon volumes. For example, disks can be mounted read-only on multiple instances, which makes for more convenient fileserving than object stores, especially for software such as WordPress (see disclosure) or Drupal that expect a local filesystem. Disks are really fast too, and don’t seem to have the variable performance that plagued EBS before the introduction of Provisioned IOPS. See for yourself in the following benchmarks.

As you can see, GCE and EC2 are equivalent on reads, but GCE is 2-4x faster on writes.

Read/write speeds are measured in MB/s. Higher numbers mean faster throughput.

Network

A short note about multi-cloud. I’m talking here about services that span multiple clouds, such as replicating a database from us-east-1 to us-west-1, for disaster recovery or latency-lowering purposes, not the multi-cloud management capabilities widely used in the enterprise. I believe that first kind of multi-cloud is a myth driven by the industry’s less tech-savvy folks. I’ve seen too many people attempt it unsuccessfully to recommend it: what usually happens is the slave database falls behind on the master, with an ever-increasing inconsistency window, because the load on the master exceeds the meager bandwidth available between master and slave. Our friends at Continuent are doing great work with Tungsten to accelerate that, but still.

Google’s network is so fast, however, that this kind of multi-cloud might just be possible. To illustrate the difference in speeds, we ran a bandwidth benchmark in which we copied a single, 500 Mb file between two regions. It took 242 seconds on AWS at an average speed of 15 Mbit/s, and 15 seconds on GCE with an average speed of 300Mbit/s. GCE came out 20x faster.

Higher bandwidth is better and means faster up and downlinks.

After being so very much impressed, we made a latency benchmark between the same regions. We got an average of 20ms for GCE and 86ms for AWS. GCE came out 4x faster.

Lower latency is better and means shorter wait times.

This might allow new architectures, and high-load replicated databases might just become possible. Put a slave in different regions of the US (and if/when GCE goes international, why not different regions of the world?) to dramatically speed up SaaS applications for read performance.

Of course, unless Amazon and Google work together to enable Direct Connect, bandwidth from GCE to EC2 will still be slow. I also hear that Amazon is working on creating a private backbone between regions to enable the same use cases, which would be an expected smart move from them.

Multi-region images

We’re not quite sure why AWS doesn’t support this, but images on GCE are multi-region (“multi-zone” in their terms), that is to say when you snapshot an instance into an image, you can immediately launch new instances from that image in any region. This makes disaster recovery that much easier and makes their scheduled region maintenance (which occurs a couple of times a year) less of a problem. On that note, I’d also like to add that it forces people to plan their infrastructure to be multi-region, similar to what AWS did for instance failure by making local disk storage ephemeral.

So should you switch?

AWS offers an extremely comprehensive cloud service, with everything from DNS to database. Google does not. This makes building applications on AWS easier, since you have bigger building blocks. So if you don’t mind locking yourself into a vendor, you’ll be more productive on AWS.

But that said, with Google Compute Engine, AWS has a formidable new competitor in the public cloud space, and we’ll likely be moving some of Scalr’s production workloads from our hybrid aws-rackspace-softlayer setup to it when it leaves beta. There’s a strong technical case for migrating heavy workloads to GCE, and I’ll be grabbing popcorn to eagerly watch as the battle unfolds between the giants.

Sebastian Stadil is the founder of Scalr, a simple, powerful cloud management suite, and SVCCG, the world’s largest cloud computing user group. When not working on cloud, Sebastian enjoys making sushi and playing rugby.

Note: Data scientists from LinkedIn, Continuuity, Quantcast and NASA will talk about their hardware and software stacks at our “guru panel” at Structure:Data next week, March 20-21, in New York City.

Disclosure: Automattic, maker of WordPress.com, is backed by True Ventures, a venture capital firm that is an investor in the parent company of this blog, GigaOM. Om Malik, founder of GigaOM, is also a venture partner at True.

Update: This story was updated at 7:34 a.m. PDT on May 15, 2013 to note that Scalr is working on a new set of benchmarks and will publish those results soon.

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While public cloud services, including content delivery networks (CDNs), are usually very reliable, no one is perfect. Outages happen, and as a result some companies find themselves looking into multi-cloud strategies to ensure redundancy (and to optimize performance and cost). The issue is that cloud costs and resource allocation are complex — hence the emergence of a new breed of cloud mediation services such as Rightscale and Cedexis.

DT is preparing two complementary services in this space. The first is NetAnalyze, which draws on the billion network measurements that DT’s “community” takes every day, spanning 32,000 networks in 230 countries. Webmasters can put the NetAnalyze tag on their site and visiting customers will then automatically generate anonymized measurement for metrics like throughput and response time.

Then NetOptimize kicks in. When a customer requests the website from wherever they are located, NetOptimize will use the NetAnalyze metrics to determine which provider will deliver the content most quickly, and automatically route the content accordingly. Pricing for this load-balancing service is pay-per-use. The result, in theory, is better performance and lower risk of outages, and also better price-to-performance ratios, given the ability to hop between different providers according to needs.

DT’s website also touts the fact that such multi-sourcing approaches make it easier to avoid vendor lock-in. The company says NetAnalyze and NetOptimize make it possible to “form a unified strategy across multiple platforms (cloud, data center or CDN)”.

A glance at the NetOptimize portal (which appears to default to Japanese, at least from my end) shows that the service covers numerous clouds and CDNs. On the cloud side, we have locations for Amazon EC2, Google App Engine, GoGrid, InstaCompute, Internap AgileCLOUD, Joyent, PhoenixNAP, Profitbricks, Rackspace Cloud, Softlayer and Windows Azure. For CDN, there’s Akamai, Azure, BitGravity, CacheFly, CDN77, CDNetworks, CDNVideo, ChinaCache, ChinaNetCenter, CloudFlare, Cloudfront, Edgecast, Fastly, Fastweb, Highwinds, Internap AgileCAST, Internode, Level3, Limelight, NetDNA, Ngenix, OnApp, Pacnet, UPX CloudCache and Yacast.

I’ve asked DT for further details of the service, such as when they intend to officially take the wraps off it, and will add their response when I get it.

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Pinterest Operations Engineer Ryan Park had the stage to himself for a session on Wednesday, while Flipboard Chief Architect Greg Scallan and Yelp Engineering Manager Jim Blomo teamed up with Kleiner Perkins Caufield Byers Partner Ray Bradford to form a trifecta of wisdom on Thursday.

Know — and measure — your costs

Flipboard’s Scallan had a paradoxical lesson for the audience when it comes to managing cloud-based infrastructure: Embrace the cloud, but be afraid of the cloud. Yes, it’s flexible and affordable if done right, but all it takes is poor planning or a handful of servers left running ad infinitum, and the costs can begin to grow out of control. That’s why Flipboard assigns members of its engineering team the title of “chief miser,” which means they’re the ones who decide that applications are using the right resources and using them wisely.

Thanks to a variety of practices, including its miserly ways, Scallan said Flipboard is now running about 900 instances at any given time. That’s down from a peak of about 1,500.

Some stats on Flipboard’s AWS usage

One way to help ensure this sort lean operation is to understand your business inputs and outputs, Kleiner Perkins’s Bradford explained. He suggests companies ask, for example, what it costs them to serve a free user on their platform and how does that change with scale or affect the experience they can offer premium users. Pick metrics that really matter, he said (e.g., infrastructure cost per user per month) and then consider how long your current  architecture can sustain that cost before it’s time to retool.

The secret weapon: Source your instances wisely

Pinterest, Yelp and Flipboard all swear by AWS’s pre-paid Reserved Instances in order to save money over the long haul. In fact, Flipboard’s Scallan said, the e-reading startup sees cost savings of about 80 percent over three years by using heavy-duty Reserved Instances instead of on-demand instances for its base workloads, and the break-even point might be only eight or nine months. Pinterest’s Park cited savings of about 70 percent over three years using them.

The trick is queuing another job to take up the waste.

Yelp’s Blomo said his company is a heavy Elastic MapReduce (EMR) user, peaking at more than 350 Elastic MapReduce instances when many developers run their Hadoop jobs simultaneously or when it’s doing nightly analysis of its log files. In order to keep costs in check, Yelp uses Reserved Instances whenever possible to save on hourly bills and has implemented a job-flow pooling system to keep Hadoop jobs running continuously as resources become available. This helps avoid the situation where a job completes in 61 minutes, for example, thus triggering the charge for a full hour of resources even though it only used a minute worth of the second hour.

In order to best gauge when it should use what type instance, Yelp created a tool called EMRio that analyzes past usage to determine what resources are the most-efficient choice for any given job.

The results of EMRio

When it comes to optimizing costs on AWS, though, Pinterest appears to have it all figured out — even how to make use of the somewhat tricky Spot Instances that are priced based on demand and can be terminated without notice if the market price outgrows a user’s bid. Park explained how Pinterest uses the heck out of Reserved Instances and created its own auto-scaling “watchdog” service that decides whether to use Spot Instances or on-demand instances when more resources are required.

Ryan Park dropping knowledge — and graphs

Although Spot Instance prices occasionally spike through the roof, Park’s experience is that they typically remain stable and can result in “massive” savings if you know how to use them effectively. Using Spot Instances to power Pinterest’s approximately 80 front-end servers costs only about $20 per hour, he said. All told, Pinterest has reduced its daily computing bill to about $440 from about $1,200.

All this being said, though, Park, Blomo and Scallan all acknowledged that the flexibility of being able to mix on-demand, reserved and spot servers might not be all it’s cracked up to be if you don’t understand how they all work. Reserved Instances are inflexible in terms of size and region once you reserve them, and Spot Instances must be used wisely for jobs or applications that can handle their easy come, easy go nature. And now there’s even more to consider because Reserved Instances can be resold via AWS’s spot marketplace.

“It gets a little tricky,” Blomo said.

Pick your challenges

Although decisions such database type and structure are largely architectural, there might be elements of cost efficiency at play, as well. Maybe Kleiner Perkins’s Bradford put it best while leading off the session with Scallan and Blomo. Bradford presented a slide containing a simple quote from Instagram Founder Mike Krieger: “Your users around the world don’t care that you wrote your own database.” Sometimes, Bradford added, it might be best to use what works — maybe even a managed service — rather than whatever’s trending highest on Hacker News.

Pinterest’s Park expressed a similar sentiment during his session, citing a lesson his team learned about trying out too many new databases. The site used to use MongoDB, Cassandra, Redis and other databases simultaneously, but learning all the new technologies and managing them became burdensome. Now, he said, Pinterest uses good, old-fashioned MySQL (granted, it sharded MySQL 4,000 times) and memcached — as well as Redis — because they have strong communities and new engineers are more likely to know how to work with them.

After explaining EMRio and some other custom-built Hadoop tools to the crowd, Yelp’s Blomo noted that companies should carefully consider whether the time and money it takes to build stuff will actually result in commensurate savings once those tools or systems are in production. That can require some tough balancing of criteria such as cost, performance, flexibility and user experience.

But it’s important to use human resources wisely. As Bradford said during his presentation, “There’s no free lunch when it comes to developer time.”

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But then again, Amazon knows a bit about cloud computing and a lot about online marketplaces, so things may go better. For companies that may have over stocked Amazon EC2 reserved instances, there’s now a way out: You can sell off your excess capacity on a new Amazon marketplace.

Amazon  reserved instances are less expensive than on-demand instances , but they’re sold on 1- and 3-year commitments and, as we all know, computing needs can change dramatically. This marketplace will facilitate reserved instance transactions between buyer and seller. Amazon will charge the seller a 12 percent service fee, according to the Amazon Web Services blog.

Here’s the deal, according to the blog:

If you have excess capacity, you can list it on the marketplace and sell it to someone who needs additional capacity. If you need additional capacity, you can compare the upfront prices and durations of Reserved Instances on the marketplace to the upfront prices of one and three year Reserved Instances available directly from AWS. The Reserved Instances in the Marketplace are functionally identical to other Reserved Instances and have the then-current hourly rates, they will just have less than a full term and a different upfront price. Transactions in the Marketplace are always between a buyer and a seller; the Reserved Instance Marketplace hosts the listings and allows buyers and sellers to locate and transact with each other.

The marketplace might be of interest to companies who booked reserved instances in one AWS Region, but needs to move them to another. Or perhaps the application has (in AWS terms) put on a little weight and needs a larger instance type.

Amazon is seeing increased competition on many fronts — from new OpenStack clouds coming online from Rackspace and others, from ProfitBricks, which just launched in the US and lets companies pay for their compute resources by the minute rather than the whole hour. In  addition there’s a flock of companies – Newvem, Cloudability, Cloudyn, etc.– offering services to help companies better plan their use of AWS computing, cutting back on over provisioning.  Amazon is nothing if not proactive when new competition comes online.

Feature photo courtesy of  Flickr user Will Merydith

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According to co-founder Alex Loddengaard, Levy began building MemCachier as a side project in mid-2011, and he hosted a private beta version in the Heroku add-on market so a friend could easily access the service. The team at Heroku saw the service, liked it and encouraged Levy to pursue it for real. Levy, who’s still in the middle of getting a Ph.D. from Stanford, called Loddengaard (who taught Levy while a teaching assistant at the University of Washington) and fellow Stanford Ph.D. candidate David Terei for help, and MemCachier launched in April 2012.

Alex Loddengaard

Landing Loddengaard wasn’t too tough. He had quit his job at software-development firm Atlassian, after beginning his career at Google and then following his boss Christophe Bisciglia to Hadoop pioneer Cloudera, where Loddengaard was a pre-funding employee. (MemCachier, by the way, now shares office space with Bisciglia’s new company, WibiData, in the former Atlassian headquarters.) He was living off his savings, had “built a bunch of stupid web apps that you never heard of” and was trying to figure out what to do next, he told me. And then Levy called.

Memcached, and MemCachier, are everywhere

Memcached is a popular open-source key-value system that speeds up web applications by caching certain data in the memory of distributed systems rather than on disk in the database itself. Facebook is widely cited as the largest user for the hundreds of terabytes it’s now storing in memcached, but, Loddengaard said, “Every company that needs to scale uses memcached.”

Aside from the core open source version, developers might choose the Couchbase’s eponymous NoSQL database (into which the popular memcached implementation Membase Server has been integrated) or its hosted Membase service called Memcache, which is available on Heroku. Another hosted option is AWS’s ElastiCache, a membased-compliant service available to developers building web applications on the Amazon EC2 cloud.

Since starting off on Heroku, MemCachier has already expanded to the AppHarbor and Cloud Control platforms, but Wednesday’s expansion represents  the company’s first real introduction to the public, Loddengaard said. Now, MemCachier is also available on AppFog, CloudBees and DotCloud — three popular PaaS offerings — as well as Amazon EC2.

Growing isn’t always easy

Moving to Amazon’s cloud, in particular, also meant a change in pricing to reflect a different class of user (e.g., AWS mega-user Netflix) than most PaaS offerings attract. Whereas MemCachier’s options on Heroku range from 100MB to 10GB in size, Amazon users can get up to a 100GB instance. Loddengaard said most Amazon EC2 users use more than a gigabyte of RAM for memcached, and ElastiCache actually starts out at 1.3GB.

MemCachier’s architecture, simplified.

Loddengaard acknowledges that trying to woo developers away from ElastiCache service on Amazon’s own platform won’t necessarily be easy, but he thinks the difference in approach between the two services favors MemCachier for a particular class of developers — those who don’t want to manage their infrastructure too closely. Whereas ElastiCache still requires users to manage their instances, as is the norm with Amazon’s lower-level infrastructure-as-a-service platform, MemCachier is about “no operations whatsoever,” he said. “Developers shouldn’t spend any time operating servers over developing software.”

That mindset has proven effective so far. Thanks to word of mouth alone, the bootstrapped MemCachier has been growing steadily in terms of revenue and users, now claiming more than 1,500 developers, but its broader footprint and some proactive marketing should mean sharp upticks in both areas. However, a jump in users — especially the larger ones that might come from Amazon EC2 — will probably require MemCachier to grow beyond its current three-person team. Of course, there are worse problems to have.

Feature image courtesy of Shutterstock user optimarc.

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