Yelp.com provides consumers with crowd-sourced reviews about local businesses. It connects its data centers to the cloud using AWS Direct Connect to access a range of AWS services for its Dev & Test, Automated Testing systems, staging areas, and production workloads. Using AWS, Yelp dramatically improved its development productivity by reducing test-run times by as much as 90 percent.
AWS OpsWorks for Windows now supports custom AutoScaling based on Amazon CloudWatch Alarms and custom AMIs.
Amazon CloudWatch alarms can be used as thresholds for AWS OpsWorks Automatic Load-based Scaling. For example, you can use ‘Disk Reads’ or ‘Network In’ as metrics to scale up or down your load-based instances.
Custom AMI support gives you the ability to use your own AMIs based on a Windows Server 2012 R2 base that have software such as Microsoft Windows Server 2012 R2 with SQL Server Express, SQL Server Standard or SQL Server Web preinstalled.
These additions to AWS OpsWorks Windows support benefit customers that want to start with custom built AMIs and customers that have the need to scale their infrastructure based on any metric available in Amazon CloudWatch alarms.
Read our Product Page to learn more and our Documentation to get started with AWS OpsWorks.
Biologists around the world use DNA sequencers created by California-based Illumina for a broad range of genomics applications including whole-genome sequencing. The company built its BaseSpace tool on AWS to allow researchers to upload massive data sets directly to the cloud for analysis and to store the results long-term with Amazon Glacier.
By Jeff Bercovici, San Francisco bureau chief, Inc. as written on Inc.com. The ECT-1. IMAGE:
Hardly a week goes by in Silicon Valley without someone launching a new food-delivery or ride-sharing app. Meanwhile, we're running out of antibiotics that work. What's going on here? Why is new drug development so comparatively torpid when app development is so torrid?
The founders of Emerald Therapeutics, D.J. Kleinbaum and Brian Frezza, think it comes down to the difficulty of running experiments in the life sciences. A typical new experiment takes a month to set up -- a month during which a scientist with a decade of education might find herself lugging around jugs of reagent or pipetting. And that's when nothing goes wrong.
"There are these major roadblocks to doing research that all involve the energy you have to sink into the lab itself," said Frezza on Tuesday evening, speaking at the opening of the new Emerald Cloud Laboratory in South San Francisco. The ECL is Frezza and Kleinbaum's solution to the friction they believe is holding back progress in their field.
Dubbed ECL-1, because it's intended to be the first of many, the gleaming warehouse-like space is filled with state-of-the-art instruments for DNA sequencing, gas chromatography, nuclear magnetic resonance and other standard types of experiments. It's also filled with robots that prep and carry out the trials, with minimal oversight from human operators. Thanks to the high degree of automation, a team of two or three technicians can carry out up to 50 experiments simultaneously. "It's all about each experiment being 'push a button, walk away,'" Kleinbaum said during a tour of the facility.
The protocols themselves are uploaded to ECL's servers remotely by clients. (Hence the "Cloud" part.) Frezza and Kleinbaum liken the arrangement to Amazon Web Services, which triggered an explosion in the number of new internet startups by removing the need to own one's own servers as a barrier to entry.
Running experiments over the cloud is cost-competitive and far more time efficient; in Emerald's old lab, average setup time was a mere 25 minutes. But it's also superior in terms of standardization and reproducibility, with the environment engineered to control for and measure a host of variables, from ambient air temperature to the length of rubber tubing, that often get overlooked. Capturing so much more data this way gives investigators what Kleinbaum calls "full computational closure," and it's a big part of the ECL's value proposition. "If we're asking people to experiment out of place and out of time, it's not enough to just give them an equivalent experience," he says. "We have to give them a richer experience."
If Kleinbaum and Frezza are sensitive to the needs of researchers, it's because it was in that role that they started Emerald Therapeutics in 2010. Attempting to raise funding for their effort to develop a novel therapy for persistent viral infections, the co-founders, who've been best friends since they grew up together in Philadelphia, were on the verge of giving up and heading back to the east coast when Peter Thiel personally persuaded them to stay in town. A few weeks later, his Founders Fund wrote them their first check. They've raised more than $13 million to date.
Work on their viral cure is ongoing but deep in stealth mode. Frezza says it will be perhaps a year before they're ready to talk about it publicly. Meanwhile, in the next 18 months they plan to invest another $7 million in the ECL, more than doubling the number of different experiments it's capable of carrying out.
AWS Elastic Beanstalk simplifies the process of deploying and scaling Java, .NET, PHP, Node.js, Python, Ruby, Go, and Docker web applications and services on AWS. Today we are making Elastic Beanstalk even more useful by adding support for enhanced application health monitoring.
To understand the benefit of this new feature, imagine you have a web application with a bug that causes it to return an error when someone visits the /blog page but the rest of your application works as expected. Previously, you could detect such issues by either monitoring the Elastic Load Balancers HTTPCode_Backend_5XX metric or going to the URL yourself to test it out. With enhanced application health monitoring, Elastic Beanstalk does the monitoring for you and highlights such issues by changing the health status as necessary. With this new feature, Elastic Beanstalk not only monitors the EC2 and ELB health check statuses but also monitors processes (application, proxy, etc.) and essential metrics (CPU, memory, disk space, etc.) to determine the overall health of your application.
At the core of the enhanced health monitoring feature are a set of rules that allow Elastic Beanstalk to detect anomalies in your running application and flag them by changing the health status. With every change in health status, Elastic Beanstalk provides a list of causes for the change. In the example above, the system would detect an increase in 500 errors as visitors visit the /blog page and flag it by changing the health status from “Ok” to “Warning” with a cause of “More than 1% of requests are failing with 5XX errors”.
Here’s what the status looks like in the AWS Management Console:
And from the command line (via eb health --refresh):
As you can see, this makes it much easier to know when your application is not performing as expected, and why this is the case (we are working on a similar view for the Console). For further details on how enhanced application health monitoring works, see Factors in Determining Instance and Environment Health.
As part of this feature we have also made some other changes:
Health monitoring is now near real-time. Elastic Beanstalk now evaluates application health and reports metrics every 10 seconds or so instead of every minute.
Rolling deployments require health checks to pass before a version deployment to a batch of instances is deemed successful. This ensures that any impact due to regressions in application versions is minimized to a batch of instances.
The set of values for the health status has been expanded from three (Green, Yellow, and Red) to seven (Ok, Warning, Degraded, Severe, Info, Pending, and Unknown). This allows Elastic Beanstalk to provide you with a more meaningful health status.
We have added over 40 additional environment and instance metrics including percentiles of application response times, hard disk space consumption, CPU utilization, all of which can be published to Amazon CloudWatch as desired for monitoring and alarming.
To begin using this feature, log in to the AWS Elastic Beanstalk Management Console or use the EB CLI to create an environment running platform version 2.0.0 or newer.
— Abhishek Singh, Senior Product Manager, AWS Elastic Beanstalk
Source: AWS Official Blog
Nordstrom, a Seattle-based fashion retailer, is going all in on AWS by running its websites, mobile application, security management tools, ecommerce platform, internal development tools and recommendation engine on the AWS Cloud.
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About Pinterest
Pinterest is no stranger to rapid growth, expanding from 50,000 users to 17 million in 9 months. Now at 48 million users, Pinterest was able to scale its business because it was built on Amazon Web Services (AWS). With a company of fewer than 12 employees, Pinterest didn’t want to dedicate staff time to managing a data center. Instead, Pinterest uses AWS to manage a high-performance social application that stores more than 8 billion objects and 400 terabytes of data in the AWS Cloud using Amazon Simple Storage Service (Amazon S3), and 225,000 instance hours a month with Amazon Elastic Compute Cloud (Amazon EC2).
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