Podcast
Questions and Answers
What are the root causes for scalability problems with centralized solutions?
What are the root causes for scalability problems with centralized solutions?
Computational capacity, storage capacity, network capacity
Define the Utilization (U) of a service in the context of scalability.
Define the Utilization (U) of a service in the context of scalability.
Fraction of time that the service is busy
What happens to the response time when Utilization (U) approaches 1?
What happens to the response time when Utilization (U) approaches 1?
The system comes to a grinding halt
Why is it challenging to scale geographically from LAN to WAN?
Why is it challenging to scale geographically from LAN to WAN?
What is the average number of requests in the system used for in scalability analysis?
What is the average number of requests in the system used for in scalability analysis?
How can the system avoid coming to a grinding halt when Utilization (U) is close to 1?
How can the system avoid coming to a grinding halt when Utilization (U) is close to 1?
What is a practical digital signature used for?
What is a practical digital signature used for?
What are the three components of scalability mentioned in the text?
What are the three components of scalability mentioned in the text?
What is a common solution to size scalability?
What is a common solution to size scalability?
Where do most systems fall short in terms of scalability?
Where do most systems fall short in terms of scalability?
What is the main issue highlighted about modern distributed systems and scalability?
What is the main issue highlighted about modern distributed systems and scalability?
What is computationally impossible according to the text?
What is computationally impossible according to the text?
What are the design goals of scalability?
What are the design goals of scalability?
How can communication latencies be hidden in scaling systems?
How can communication latencies be hidden in scaling systems?
What is the problem with replication when trying to achieve scalability?
What is the problem with replication when trying to achieve scalability?
How can replication and caching help in scaling systems?
How can replication and caching help in scaling systems?
What is a challenge associated with global synchronization in scaling systems?
What is a challenge associated with global synchronization in scaling systems?
How can scaling solutions facilitate by moving computations to clients?
How can scaling solutions facilitate by moving computations to clients?
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Study Notes
Scalability Introduction
- Scalability refers to the ability of a system to handle increased load without a decrease in performance.
- Centralized solutions face scalability problems due to limitations in computational capacity, storage capacity, and network bandwidth.
Design Goals
- Formal analysis of a centralized service can be modeled as a simple queuing system with infinite capacity.
- The queue has an arrival rate of requests (λ) and a processing capacity of µ requests per second.
- Utilization (U) is the fraction of time the service is busy, and it affects response time and throughput.
Formal Analysis
- The average number of requests in the system is a key factor in scalability.
- Average throughput is affected by the utilization rate (U).
- Response time is the total time taken to process a request after submission, and it increases as U approaches 1.
Problems with Scalability
- Geographical scalability is a challenge due to the limitations of synchronous client-server interactions in distributed systems.
- Simply increasing the number of users or processes is not enough to achieve scalability.
Scale in Distributed Systems
- Scalability in distributed systems involves at least three components: size scalability, geographical scalability, and administrative scalability.
- Most systems only account for size scalability, leaving geographical and administrative scalability as ongoing challenges.
Techniques for Scaling
- Hide communication latencies by using asynchronous communication and separate handlers for incoming responses.
- Facilitate scaling by moving computations to clients (e.g., Java applets and scripts).
- Partition data and computations across multiple machines.
- Use replication and caching to make copies of data available at different machines.
The Problem with Replication
- Applying replication is easy, but it leads to inconsistencies between multiple copies of data.
- Modifying one copy makes it different from the rest, resulting in inconsistencies.
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