A denial of service attack is probably the most well known kind of attack using botnets. But for $200, you can put 10,000 computers around the world to work on whatever nefarious purpose you prefer.
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When you log into a site like an online bank or Facebook, you are connecting to a secure web application—a piece of code that runs on the web and handles the secure transfer of information such as a password. With an application installed on a phone or computer, hackers would need to reverse-engineer (i.e. figure out how it works from what it does) the code to learn how it works. But a web app’s code is visible to anyone who looks so web browsers can run them. Hackers seeking to crack systems can look at that code and write scripts to exploit it—maybe they purchased some of the credit card info stolen from Target, for instance, and want to exploit the code at an online shopping site to make as many online purchases as fast as they can. Or perhaps, unbeknownst to you, some malware is tracking your keystrokes as you log into your bank account.

Read more at http://qz.com/168264/this-start-up-turned-hackers-greatest-trick-around-on-the-to-make-botnets-obsolete/

 

“By preventing automation against any website’s user interface, Shape’s technology allows enterprises to block dozens of attack categories, such as account takeover, application DDoS, and Man-in-the-Browser, with a single product. This is not only a powerful new tool for enterprises but a potentially disruptive technology for multiple sectors of the cybersecurity industry.”

Robert Lentz, former Chief Information Security Officer of the United States Department of Defense

Often times, huge web projects use multiple programming languages and even multiple databases. While relational database management systems (RDBMS) are common, they have limitations when it comes to the management of highly variable data. For such applications, NoSQL databases are a better alternative. The PostgreSQL RDBMS now provides Foreign Data Wrappers (FDW) that let PostgreSQL query non-relational external data sources.

FDWs are drivers that allow PostgreSQL database administrators to run queries and get data from external sources, including other SQL databases (Oracle, MySQL), NoSQL databases(MongoDB, Redis, CouchDB), text files in CSV and JSON formats, and content from Twitter. A few of the wrappers, such as the one for Kyoto Tycoon, allow PostgreSQL to handle both read and write operations on remote data.

Read full article on http://www.openlogic.com/wazi/bid/331001/how-to-use-postgresql-foreign-data-wrappers-for-external-data-management

SUMMARY: The answer will surprise you. Colocation can be a much better option than cloud for certain types of applications. Read on to see why

Colocation, which means buying your own hardware up front and running and managing it in a third-party site,  is not usually seen as a cheaper alternative to cloud. But, oddly enough, it can be.

Last week I compared cloud instances against dedicated servers showing that for long running uses such as databases, it’s significantly cheaper if you go with dedicated servers, but that’s not the end of it. Since you are still paying for those server resources every month, if you project the costs out 1 or 3 years, you end up paying much more than if you had just bought the hardware outright. This is where buying your own hardware and colocating it becomes a better option.

Continuing the comparison with the same specs for a long running database instance, If we price a basic Dell R415 with x2 processors each with 8 cores, 32GB RAM, a 500GB SATA system drive and a 400GB SSD, then the one-time list price is around $4000 – more than half the price of the SoftLayer server at $9,468/year we came up with in our previous analysis.

Remember, again, that this is a database server so while with Rackspace, Amazon and SoftLayer you pay that price every year, after the first year with colocation the annual cost drops to $1932 because you already own the hardware. Further, the hardware can also be considered an asset which has tax benefits.

Source: http://gigaom.com/2013/12/07/want-to-reduce-your-cloud-costs-70-percent-heres-how/

Lessons Learned

This is a mix of lessons taken from Jeff and Joel and comments from their posts.

• If you’re comfortable managing servers then buy them. The two biggest problems with renting costs were:
  1) the insane cost of memory and disk upgrades
  2) the fact that they [hosting providers] really couldn’t manage anything.

• Make larger one time up front investments to avoid recurring monthly costs which are more expensive in the long term.

• Update all network drivers. Performance went from 2x slower to 2x faster.

• Upgrading to 48GB RAM required upgrading MS Enterprise edition.

• Memory is incredibly cheap. Max it out for almost free performance. At Dell, for example, upgrading from 4G memory to 128G is $4378.

• Stack Overflow copied a key part of the Wikipedia database design. This turned out to be a mistake which will need massive and painful database refactoring to fix. The refactorings will be to avoid excessive joins in a lot of key queries. This is the key lesson from giant multi-terabyte table schemas (like Google’s BigTable) which are completely join-free. This is significant because Stack Overflow’s database is almost completely in RAM and the joins still exact too high a cost.

• CPU speed is surprisingly important to the database server. Going from 1.86 GHz, to 2.5 GHz, to 3.5 GHz CPUs causes an almost linear improvement in typical query times. The exception is queries which don’t fit in memory.

• When renting hardware nobody pays list price for RAM upgrades unless you are on a month-to-month contract.

• The bottleneck is the database 90% of the time.

• At low server volume, the key cost driver is not rackspace, power, bandwidth, servers, or software; it is NETWORKING EQUIPMENT. You need a gigabit network between your DB and Web tiers. Between the cloud and your web server, you need firewall, routing, and VPN devices. The moment you add a second web server, you also need a load balancing appliance. The upfront cost of these devices can easily be 2x the cost of a handful of servers.

• EC2 is for scaling horizontally, that is you can split up your work across many machines (a good idea if you want to be able to scale). It makes even more sense if you need to be able to scale on demand (add and remove machines as load increases / decreases).

• Scaling out is only frictionless when you use open source software. Otherwise scaling up means paying less for licenses and a lot more for hardware, while scaling out means paying less for the hardware, and a whole lot more for licenses.

• RAID-10 is awesome in a heavy read/write database workload.

• Separate application and database duties so each can scale independently of the other. Databases scale up and the applications scale out.

• Applications should keep state in the database so they scale horizontally by adding more servers.

• The problem with a scale up strategy is a lack of redundancy. A cluster ads more reliability, but is very expensive when the individual machines are expensive.

• Few applications can scale linearly with the number of processors. Locks will be taken which serializes processing and ends up reducing the effectiveness of your Big Iron.

• With larger form factors like 7U power and cooling become critical issues. Using something between 1U and 7U might be easier to make work in your data center.

• As you add more and more database servers the SQL Server license costs can be outrageous. So by starting scale up and gradually going scale out with non-open source software you can be in a world of financial hurt.

  Copied from http://highscalability.com/blog/2009/8/5/stack-overflow-architecture.html