high_scalability high_scalability-2012 high_scalability-2012-1260 knowledge-graph by maker-knowledge-mining
Source: html
Introduction: In his blog post, Scaling WSO2 Stratos , Srinath Perera explains the scaling architecture of the WSO2 Stratos Platform as a Service (PaaS) infrastructure. It is explained as a series of solutions where every solution adds a new concept to solve a specific problem found in the earlier solution. Overall, WSO2 Stratos uses a combination of intelligent Load balancing and lazy loading to scale up the architecture. More details about Stratos can be found from the paper WSO2 Stratos: An Industrial Stack to Support Cloud Computing . Problem Stratos is multi-tenanted . In other words, there are many tenants. Each tenant generally represents an organization and isolated from other tenants, where each tenant has his own users, resources, and permissions. Stratos supports multiple PaaS services. Each PaaS service is actually a WSO2 Products (e.g. AS, BPS, ESB etc.) offered as a service. Using those services, tenants may deploy their own Web Services, Mediation logic, Workflows, a
sentIndex sentText sentNum sentScore
1 Overall, WSO2 Stratos uses a combination of intelligent Load balancing and lazy loading to scale up the architecture. [sent-3, score-0.393]
2 Each tenant generally represents an organization and isolated from other tenants, where each tenant has his own users, resources, and permissions. [sent-7, score-0.42]
3 Using those services, tenants may deploy their own Web Services, Mediation logic, Workflows, and Gadgets etc. [sent-13, score-0.57]
4 WSO2 Stratos runtime provides servers where each can support multiple tenants and provide a PaaS service. [sent-14, score-0.605]
5 Each server loads all tenants at the startup and can support any tenant when they receive a request. [sent-26, score-0.841]
6 So we started running multiple instances of each server and put a load balancer (LB). [sent-28, score-0.206]
7 When load on the server instances are high, LB starts new server instances and when the load is low, LB shuts down some instances. [sent-30, score-0.303]
8 Solution 3 When Stratos had several hundred tenants and many tenants with tens of services, it took a long time to load all tenants at the startup. [sent-32, score-1.77]
9 However, since each node has to hold all tenants, Stratos spends resources for inactive tenants as well. [sent-35, score-0.676]
10 To avoid above problems, solution 3 added lazy loading. [sent-36, score-0.289]
11 All information about tenants is stored in a central registry. [sent-37, score-0.608]
12 You can find more information about Lazy loading from Azzez’s blog entry “Lazy Loading Deployment Artifacts in a PaaS Deployment”. [sent-40, score-0.265]
13 Solution 4 When tenants have several artifacts, loading them takes time. [sent-41, score-0.749]
14 So if the tenant is accessed while it has not been loaded in solution 3, first request or two to the tenant will timeout. [sent-42, score-0.582]
15 As a result, loading a tenant has become a much simpler in Solution 4. [sent-46, score-0.389]
16 So this avoids requests from timing out while loading the tenant. [sent-47, score-0.216]
17 You can also find more information about Lazy loading from Azzez’s blog entry “Lazy Loading Deployment Artifacts in a PaaS Deployment”. [sent-48, score-0.265]
18 Due to lazy loading, all requests will work even through LBs route messages arbiterly. [sent-58, score-0.22]
19 To avoid this, in the solution 6, LBs are aware of tenants and allocate only a subset of tenants to each LB. [sent-60, score-1.302]
20 However, the next potential problem is that Registry which holds the configurations and resources of all tenants could not scale to handle a large number of tenants. [sent-63, score-0.641]
wordName wordTfidf (topN-words)
[('tenants', 0.57), ('stratos', 0.529), ('lb', 0.265), ('tenant', 0.21), ('lazy', 0.183), ('loading', 0.179), ('lbs', 0.173), ('artifacts', 0.139), ('bps', 0.122), ('solution', 0.106), ('paas', 0.105), ('esb', 0.099), ('azzez', 0.081), ('registry', 0.074), ('deployer', 0.074), ('inactive', 0.066), ('decision', 0.064), ('ghost', 0.064), ('load', 0.06), ('entry', 0.06), ('aware', 0.056), ('loaded', 0.056), ('deployment', 0.05), ('blog', 0.048), ('instances', 0.047), ('resources', 0.04), ('however', 0.038), ('metadata', 0.038), ('information', 0.038), ('requests', 0.037), ('perera', 0.037), ('srinath', 0.037), ('gadgets', 0.037), ('unloaded', 0.037), ('balancer', 0.035), ('rationale', 0.035), ('multiple', 0.035), ('explains', 0.034), ('solve', 0.033), ('adds', 0.033), ('service', 0.032), ('loads', 0.032), ('scale', 0.031), ('token', 0.031), ('shuts', 0.031), ('server', 0.029), ('placing', 0.029), ('balances', 0.028), ('industrial', 0.028), ('workflows', 0.028)]
simIndex simValue blogId blogTitle
same-blog 1 1.0000001 1260 high scalability-2012-06-07-Case Study on Scaling PaaS infrastructure
Introduction: In his blog post, Scaling WSO2 Stratos , Srinath Perera explains the scaling architecture of the WSO2 Stratos Platform as a Service (PaaS) infrastructure. It is explained as a series of solutions where every solution adds a new concept to solve a specific problem found in the earlier solution. Overall, WSO2 Stratos uses a combination of intelligent Load balancing and lazy loading to scale up the architecture. More details about Stratos can be found from the paper WSO2 Stratos: An Industrial Stack to Support Cloud Computing . Problem Stratos is multi-tenanted . In other words, there are many tenants. Each tenant generally represents an organization and isolated from other tenants, where each tenant has his own users, resources, and permissions. Stratos supports multiple PaaS services. Each PaaS service is actually a WSO2 Products (e.g. AS, BPS, ESB etc.) offered as a service. Using those services, tenants may deploy their own Web Services, Mediation logic, Workflows, a
2 0.086634494 1138 high scalability-2011-11-07-10 Core Architecture Pattern Variations for Achieving Scalability
Introduction: Srinath Perera has put together a strong list of architecture patterns based on three meta patterns: distribution, caching, and asynchronous processing. He contends these three are the primal patterns and the following patterns are but different combinations: LB (Load Balancers) + Shared nothing Units . Units that do not share anything with each other fronted with a load balancer that routes incoming messages to a unit based on some criteria. LB + Stateless Nodes + Scalable Storage . Several stateless nodes talking to a scalable storage, and a load balancer distributes load among the nodes. Peer to Peer Architectures (Distributed Hash Table (DHT) and Content Addressable Networks (CAN)) . Algorithm for scaling up logarithmically. Distributed Queues . Queue implementation (FIFO delivery) implemented as a network service. Publish/Subscribe Paradigm . Network publish subscribe brokers that route messages to each other. Gossip and Nature-inspired Architectures . Each
3 0.076468199 678 high scalability-2009-08-09-Writing about cisco loadbalancer?
Introduction: Guys, At one of my jobs I have to administer a CISCO ACE (application control engine) hardware load-balancer. I don't particularly love this beast, but it's very very powerful. There appears to be little real-world info out there, so it could be interesting writing an article on that. But I don't have other HW LB's to compare it to and I don't want to rehash the product page. What would interest you in a 'product review' of a loadbalancer? No replies means it's not an interesting topic, so no article then ;-)
4 0.069815159 1588 high scalability-2014-01-31-Stuff The Internet Says On Scalability For January 31st, 2014
Introduction: Hey, it's HighScalability time: Largest battle ever on Eve Online. 2,000 players. $200K in damage. Awesome pics . teaspoon of soil : hosts up to a billion bacteria spread among a million species. Quotable Quotes: Vivek Prakash : The problem of scaling always takes a toll on you. @ jcsalterego : See This One Weird Trick Hypervisors Don't Want You To Know Upgrades are the great killer of software systems. Do you really want a pill that would supply materials with instructions for nanobots to form new neurons and place them near existing cells to be replaced so you have a new brain within six months? Scary as hell. But there's an nanoapp for that. Ted Nelson has a fascinating series of Computers for Cynics vidcasts on YouTube. I'd ony really known of Mr. Nelson from his writings on hypertext, but he has a broad and penetrating insight into the early days of the computer industry. He's not really
5 0.068929486 1331 high scalability-2012-10-02-An Epic TripAdvisor Update: Why Not Run on the Cloud? The Grand Experiment.
Introduction: This is a guest post by Shawn Hsiao , Luke Massa , and Victor Luu . Shawn runs TripAdvisor ’s Technical Operations team, Luke and Victor interned on his team this past summer. This post is introduced by Andy Gelfond , TripAdvisor’s head of engineering. It's been a little over a year since our last post about the TripAdvisor architecture . It has been an exciting year. Our business and team continues to grow, we are now an independent public company, and we have continued to keep/scale our development process and culture as we have grown - we still run dozens of independent teams, and each team continues to work across the entire stack. All that has changed are the numbers: 56M visitors per month 350M+ pages requests a day 120TB+ of warehouse data running on a large Hadoop cluster, and quickly growing We also had a very successful college intern program that brought on over 60 interns this past summer, all who were quickly on boarded and doing the same kind of work a
6 0.068201348 1513 high scalability-2013-09-06-Stuff The Internet Says On Scalability For September 6, 2013
7 0.062749408 1543 high scalability-2013-11-05-10 Things You Should Know About AWS
8 0.062032655 1216 high scalability-2012-03-27-Big Data In the Cloud Using Cloudify
9 0.059238601 1002 high scalability-2011-03-09-Productivity vs. Control tradeoffs in PaaS
10 0.056874853 1508 high scalability-2013-08-28-Sean Hull's 20 Biggest Bottlenecks that Reduce and Slow Down Scalability
11 0.056801356 1424 high scalability-2013-03-15-Stuff The Internet Says On Scalability For March 15, 2013
12 0.056126796 775 high scalability-2010-02-10-ElasticSearch - Open Source, Distributed, RESTful Search Engine
13 0.05384995 1155 high scalability-2011-12-12-Netflix: Developing, Deploying, and Supporting Software According to the Way of the Cloud
14 0.052882925 1031 high scalability-2011-04-28-PaaS on OpenStack - Run Applications on Any Cloud, Any Time Using Any Thing
15 0.050442528 1240 high scalability-2012-05-07-Startups are Creating a New System of the World for IT
16 0.049502172 1596 high scalability-2014-02-14-Stuff The Internet Says On Scalability For February 14th, 2014
17 0.049081169 881 high scalability-2010-08-16-Scaling an AWS infrastructure - Tools and Patterns
18 0.048856683 1250 high scalability-2012-05-23-Averages, web performance data, and how your analytics product is lying to you
19 0.048134115 1565 high scalability-2013-12-16-22 Recommendations for Building Effective High Traffic Web Software
20 0.045839742 233 high scalability-2008-01-30-How Rackspace Now Uses MapReduce and Hadoop to Query Terabytes of Data
topicId topicWeight
[(0, 0.079), (1, 0.04), (2, 0.001), (3, -0.022), (4, -0.011), (5, -0.016), (6, 0.033), (7, -0.041), (8, -0.024), (9, -0.012), (10, 0.014), (11, 0.016), (12, 0.004), (13, -0.026), (14, -0.003), (15, -0.005), (16, 0.018), (17, -0.023), (18, 0.024), (19, 0.017), (20, 0.004), (21, 0.001), (22, -0.009), (23, 0.005), (24, 0.017), (25, 0.011), (26, -0.011), (27, 0.015), (28, -0.007), (29, -0.012), (30, 0.013), (31, 0.0), (32, -0.003), (33, 0.021), (34, -0.037), (35, 0.011), (36, 0.002), (37, -0.048), (38, -0.006), (39, -0.026), (40, 0.003), (41, 0.04), (42, -0.003), (43, -0.004), (44, 0.015), (45, 0.012), (46, 0.027), (47, 0.025), (48, 0.007), (49, -0.022)]
simIndex simValue blogId blogTitle
same-blog 1 0.93848222 1260 high scalability-2012-06-07-Case Study on Scaling PaaS infrastructure
Introduction: In his blog post, Scaling WSO2 Stratos , Srinath Perera explains the scaling architecture of the WSO2 Stratos Platform as a Service (PaaS) infrastructure. It is explained as a series of solutions where every solution adds a new concept to solve a specific problem found in the earlier solution. Overall, WSO2 Stratos uses a combination of intelligent Load balancing and lazy loading to scale up the architecture. More details about Stratos can be found from the paper WSO2 Stratos: An Industrial Stack to Support Cloud Computing . Problem Stratos is multi-tenanted . In other words, there are many tenants. Each tenant generally represents an organization and isolated from other tenants, where each tenant has his own users, resources, and permissions. Stratos supports multiple PaaS services. Each PaaS service is actually a WSO2 Products (e.g. AS, BPS, ESB etc.) offered as a service. Using those services, tenants may deploy their own Web Services, Mediation logic, Workflows, a
2 0.71252292 372 high scalability-2008-08-27-Updating distributed web applications
Introduction: Hi, we've got a web application, which runs without the common standalone application servers like tomcat or jboss, rather it runs with an embedded jetty server. Now we are planing to run instances of this application on multiple machines, with a load balancer serving the requests. The big question is: is there a common scenario on how to update these applications? Lets think of 10 instances on 10 machines (one instance per machine), where we want to update each of these applications version. The brute force approach would be, to stop all instances, update and then restart it. This is a lot of manual work ;) Another problem is down-time: so someone must only shutdown one server after another, but then there are multiple application versions around. Can someone please provide us with a hint for this problem? Perhaps papers, tools or something like that? Thanks a lot :)
3 0.71134692 906 high scalability-2010-09-22-Applying Scalability Patterns to Infrastructure Architecture
Introduction: Too often software design patterns are overlooked by network and application delivery network architects but these patterns are often equally applicable to addressing a broad range of architectural challenges in the application delivery tier of the data center. By Lori Mac Vittie, F5 Networks The “ High Scalability ” blog is fast becoming one of my favorite reads. Last week did not disappoint with a post highlighting a set of scalability design patterns that was, apparently, inspired by yet another High Scalability post on “ 6 Ways to Kill Your Servers: Learning to Scale the Hard Way. ” Credit:Michael Chow/azcentral.com This particular post caught my attention primarily because although I’ve touched on many of these patterns in the past, I’ve never thought to call them what they are: scalability patterns. That’s probably a side-effect of forgetting that building an architecture of any kind is at its core computer science and thus
4 0.70691693 1331 high scalability-2012-10-02-An Epic TripAdvisor Update: Why Not Run on the Cloud? The Grand Experiment.
Introduction: This is a guest post by Shawn Hsiao , Luke Massa , and Victor Luu . Shawn runs TripAdvisor ’s Technical Operations team, Luke and Victor interned on his team this past summer. This post is introduced by Andy Gelfond , TripAdvisor’s head of engineering. It's been a little over a year since our last post about the TripAdvisor architecture . It has been an exciting year. Our business and team continues to grow, we are now an independent public company, and we have continued to keep/scale our development process and culture as we have grown - we still run dozens of independent teams, and each team continues to work across the entire stack. All that has changed are the numbers: 56M visitors per month 350M+ pages requests a day 120TB+ of warehouse data running on a large Hadoop cluster, and quickly growing We also had a very successful college intern program that brought on over 60 interns this past summer, all who were quickly on boarded and doing the same kind of work a
5 0.69349682 1325 high scalability-2012-09-19-The 4 Building Blocks of Architecting Systems for Scale
Introduction: If you are looking for an excellent overview of general architecture principles then take a look at Will Larson's Introduction to Architecting Systems for Scale . Based on his experiences at Yahoo! and Digg, Will covers key concepts in some depth. A quick gloss on the building blocks: Load Balancing: Scalability & Redundancy . Horizontal scalability and redundancy are usually achieved via load balancing, the spreading of requests across multiple resources. Smart Clients . The client has a list of hosts and load balances across that list of hosts. Upside is simple for programmers. Downside is it's hard to update and change. Hardware Load Balancers . Targeted at larger companies, this is dedicated load balancing hardware. Upside is performance. Downside is cost and complexity. Software Load Balancers . The recommended approach, it's software that handles load balancing, health checks, etc. Caching . Make better use of resources you already have. Pr
6 0.68716371 138 high scalability-2007-10-30-Feedblendr Architecture - Using EC2 to Scale
7 0.68240833 1188 high scalability-2012-02-06-The Design of 99designs - A Clean Tens of Millions Pageviews Architecture
8 0.67360115 702 high scalability-2009-09-11-The interactive cloud
9 0.66528225 881 high scalability-2010-08-16-Scaling an AWS infrastructure - Tools and Patterns
10 0.65793031 897 high scalability-2010-09-08-4 General Core Scalability Patterns
11 0.65400189 1565 high scalability-2013-12-16-22 Recommendations for Building Effective High Traffic Web Software
12 0.65158099 1155 high scalability-2011-12-12-Netflix: Developing, Deploying, and Supporting Software According to the Way of the Cloud
13 0.64302498 1434 high scalability-2013-04-03-5 Steps to Benchmarking Managed NoSQL - DynamoDB vs Cassandra
14 0.6348123 620 high scalability-2009-06-05-SSL RPC API Scalability
15 0.63448399 118 high scalability-2007-10-09-High Load on production Webservers after Sourcecode sync
16 0.63216633 509 high scalability-2009-02-05-Product: HAProxy - The Reliable, High Performance TCP-HTTP Load Balancer
17 0.62534803 1517 high scalability-2013-09-16-The Hidden DNS Tax - Cascading Timeouts and Errors
18 0.62372774 1058 high scalability-2011-06-13-Automation on AWS with Ruby and Puppet
19 0.62120008 1296 high scalability-2012-08-02-Strategy: Use Spare Region Capacity to Survive Availability Zone Failures
topicId topicWeight
[(1, 0.074), (2, 0.177), (10, 0.027), (29, 0.013), (40, 0.012), (57, 0.011), (60, 0.379), (61, 0.044), (79, 0.055), (85, 0.04), (94, 0.032)]
simIndex simValue blogId blogTitle
1 0.87150049 49 high scalability-2007-07-30-allowed contributed
Introduction: buy cleocin
2 0.87060136 618 high scalability-2009-06-05-Google Wave Architecture
Introduction: Update: Good Vibrations by Radovan Semančík. Lot's of interesting questions about how Wave works, scalability, security, RESTyness, and so on. Google Wave is a new communication and collaboration platform based on hosted XML documents (called waves) supporting concurrent modifications and low-latency updates. This platform enables people to communicate and work together in new, convenient and effective ways. We will offer these benefits to users of Google Wave and we also want to share them with everyone else by making waves an open platform that everybody can share. We welcome others to run wave servers and become wave providers, for themselves or as services for their users, and to "federate" waves, that is, to share waves with each other and with Google Wave. In this way users from different wave providers can communicate and collaborate using shared waves. We are introducing the Google Wave Federation Protocol for federating waves between wave providers on the Internet. H
3 0.82118863 698 high scalability-2009-09-10-Building Scalable Databases: Denormalization, the NoSQL Movement and Digg
Introduction: Database normalization is a technique for designing relational database schemas that ensures that the data is optimal for ad-hoc querying and that modifications such as deletion or insertion of data does not lead to data inconsistency. Database denormalization is the process of optimizing your database for reads by creating redundant data. A consequence of denormalization is that insertions or deletions could cause data inconsistency if not uniformly applied to all redundant copies of the data within the database. Read more on Carnage4life blog...
same-blog 4 0.80899245 1260 high scalability-2012-06-07-Case Study on Scaling PaaS infrastructure
Introduction: In his blog post, Scaling WSO2 Stratos , Srinath Perera explains the scaling architecture of the WSO2 Stratos Platform as a Service (PaaS) infrastructure. It is explained as a series of solutions where every solution adds a new concept to solve a specific problem found in the earlier solution. Overall, WSO2 Stratos uses a combination of intelligent Load balancing and lazy loading to scale up the architecture. More details about Stratos can be found from the paper WSO2 Stratos: An Industrial Stack to Support Cloud Computing . Problem Stratos is multi-tenanted . In other words, there are many tenants. Each tenant generally represents an organization and isolated from other tenants, where each tenant has his own users, resources, and permissions. Stratos supports multiple PaaS services. Each PaaS service is actually a WSO2 Products (e.g. AS, BPS, ESB etc.) offered as a service. Using those services, tenants may deploy their own Web Services, Mediation logic, Workflows, a
5 0.72103918 249 high scalability-2008-02-16-S3 Failed Because of Authentication Overload
Introduction: Being an authentic human being is difficult and apparently authenticating all those S3 requests can be a bit overwhelming as well. Amazon fingered a lot of processor heavy authentication requests as the reason for their downtime: Early this morning, at 3:30am PST, we started seeing elevated levels of authenticated requests from multiple users in one of our locations. While we carefully monitor our overall request volumes and these remained within normal ranges, we had not been monitoring the proportion of authenticated requests. Importantly, these cryptographic requests consume more resources per call than other request types. Shortly before 4:00am PST, we began to see several other users significantly increase their volume of authenticated calls. The last of these pushed the authentication service over its maximum capacity before we could complete putting new capacity in place. In addition to processing authenticated requests, the authentication service also performs accou
6 0.63555324 655 high scalability-2009-07-12-SPHiveDB: A mixture of the Key-Value Store and the Relational Database.
7 0.63228792 1617 high scalability-2014-03-21-Stuff The Internet Says On Scalability For March 21st, 2014
8 0.60446239 1572 high scalability-2014-01-03-Stuff The Internet Says On Scalability For January 3rd, 2014
9 0.59557498 299 high scalability-2008-04-07-Rumors of Signs and Portents Concerning Freeish Google Cloud
10 0.58502704 1292 high scalability-2012-07-27-Stuff The Internet Says On Scalability For July 27, 2012
11 0.57779711 1630 high scalability-2014-04-11-Stuff The Internet Says On Scalability For April 11th, 2014
12 0.57680899 1129 high scalability-2011-09-30-Stuff The Internet Says On Scalability For September 30, 2011
13 0.54661185 789 high scalability-2010-03-05-Strategy: Planning for a Power Outage Google Style
14 0.54630291 1408 high scalability-2013-02-19-Puppet monitoring: how to monitor the success or failure of Puppet runs
15 0.48246399 1595 high scalability-2014-02-13-Snabb Switch - Skip the OS and Get 40 million Requests Per Second in Lua
16 0.48228297 1215 high scalability-2012-03-26-7 Years of YouTube Scalability Lessons in 30 Minutes
17 0.48215529 1204 high scalability-2012-03-06-Ask For Forgiveness Programming - Or How We'll Program 1000 Cores
18 0.48180109 1436 high scalability-2013-04-05-Stuff The Internet Says On Scalability For April 5, 2013
19 0.48172805 1063 high scalability-2011-06-17-Stuff The Internet Says On Scalability For June 17, 2011
20 0.48159704 1509 high scalability-2013-08-30-Stuff The Internet Says On Scalability For August 30, 2013