high_scalability high_scalability-2007 high_scalability-2007-21 knowledge-graph by maker-knowledge-mining
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Introduction: Google Talk is Google's instant communications service. Interestingly the IM messages aren't the major architectural challenge, handling user presence indications dominate the design. They also have the challenge of handling small low latency messages and integrating with many other systems. How do they do it? Site: http://www.google.com/talk Information Sources GoogleTalk Architecture Platform Linux Java Google Stack Shard What's Inside? The Stats Support presence and messages for millions of users. Handles billions of packets per day in under 100ms. IM is different than many other applications because the requests are small packets. Routing and application logic are applied per packet for sender and receiver. Messages must be delivered in-order. Architecture extends to new clients and Google services. Lessons Learned Measure the right thing. - People ask about how many IMs do you deliver or how many active users. Turns out not
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1 Interestingly the IM messages aren't the major architectural challenge, handling user presence indications dominate the design. [sent-2, score-0.787]
2 They also have the challenge of handling small low latency messages and integrating with many other systems. [sent-3, score-0.38]
3 The Stats Support presence and messages for millions of users. [sent-8, score-0.42]
4 Handles billions of packets per day in under 100ms. [sent-9, score-0.214]
5 Architecture extends to new clients and Google services. [sent-13, score-0.201]
6 - People ask about how many IMs do you deliver or how many active users. [sent-15, score-0.198]
7 - Hard part of IM is how to show correct present to all connected users because growth is non-linear: ConnectedUsers * BuddyListSize * OnlineStateChanges - A linear user grown can mean a very non-linear server growth which requires serving many billions of presence packets per day. [sent-17, score-0.61]
8 - Have a large number friends and presence explodes. [sent-18, score-0.379]
9 - Simulate presence requests and going on-line and off-line for weeks and months, even if real data is not returned. [sent-22, score-0.297]
10 - Google Talk backend servers handle traffic for a subset of users. [sent-25, score-0.189]
11 - Servers can bring down servers and backups take over. [sent-29, score-0.192]
12 Then you can bring up new servers and data migrated automatically and clients auto detect and go to new servers. [sent-30, score-0.396]
13 Add Abstractions to Hide System Complexity - Different systems should have little knowledge of each other, especially when separate groups are working together. [sent-31, score-0.187]
14 Can change at anytime without cascading changes throughout the system. [sent-33, score-0.225]
15 This is architectural implications as you can have separate system failing independently. [sent-40, score-0.202]
16 - What happens when servers restart with an empty cache? [sent-45, score-0.269]
17 - Add ability to profile live servers without impacting server. [sent-56, score-0.19]
18 - Log end-to-end so you can reconstruct an entire operation from beginning to end across all machines. [sent-60, score-0.225]
19 Software Development Strategies - Make sure binaries are both backward and forward compatible so you can have old clients work with new code. [sent-61, score-0.31]
20 This is very different than many companies who have completely separate OP teams in their data centers. [sent-65, score-0.202]
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