mpm + scalability   61

Design of a Modern Cache
Caching is a common approach for improving performance, yet most implementations use strictly classical techniques. In this article we will explore the modern methods used by Caffeine, an open-source Java caching library, that yield high hit rates and excellent concurrency.
caching  concurrency  memory  scalability 
7 weeks ago by mpm
Performance-Feedback Autoscaling with Budget Constraints for Cloud-based Workloads of Workflows
The growing popularity of workflows in the cloud domain promoted the development of sophisticated autoscaling policies that allow automatic allocation and deallocation of resources. However, many state-of-the-art autoscaling policies for workflows are mostly plan-based or designed for batches (ensembles) of workflows. This reduces their flexibility when dealing with workloads of workflows, as the workloads are often subject to unpredictable resource demand fluctuations. Moreover, autoscaling in clouds almost always imposes budget constraints that should be satisfied. The budget-aware autoscalers for workflows usually require task runtime estimates to be provided beforehand, which is not always possible when dealing with workloads due to their dynamic nature. To address these issues, we propose a novel Performance-Feedback Autoscaler (PFA) that is budget-aware and does not require task runtime estimates for its operation. Instead, it uses the performance-feedback loop that monitors the average throughput on each resource type. We implement PFA in the popular Apache Airflow workflow management system, and compare the performance of our autoscaler with other two state-of-the-art autoscalers, and with the optimal solution obtained with the Mixed Integer Programming approach. Our results show that PFA outperforms other considered online autoscalers, as it effectively minimizes the average job slowdown by up to 47% while still satisfying the budget constraints. Moreover, PFA shows by up to 76% lower average runtime than the competitors.
control-theory  scalability 
9 weeks ago by mpm
Random Slicing: Efficient and Scalable Data Placement for Large-Scale Storage Systems
The ever-growing amount of data requires highly scalable storage solutions. The most flexible approach is to use storage pools that can be expanded and scaled down by adding or removing storage devices. To make this approach usable, it is necessary to provide a solution to locate data items in such a dynamic environment. This article presents and evaluates the Random Slicing strategy, which incorporates lessons learned from table-based, rule-based, and pseudo-randomized hashing strategies and is able to provide a simple and efficient strategy that scales up to handle exascale data. Random Slicing keeps a small table with information about previous storage system insert and remove operations, drastically reducing the required amount of randomness while delivering a perfect load distribution.
storage  scalability 
june 2018 by mpm
How To Measure the Working Set Size on Linux
The Working Set Size (WSS) is how much memory an application needs to keep working. Your app may have populated 100 Gbytes of main memory, but only uses 50 Mbytes each second to do its job. That's the working set size. It is used for capacity planning and scalability analysis.
memory  linux  scalability 
january 2018 by mpm
How to Quantify Scalability
It's also an attempt to provide a quick overview of the USL methodology
scalability  architecture 
december 2017 by mpm
Efficient Distributed Coordination at WAN-Scale
Traditional coordination services for distributed applications do not scale well over wide-area networks (WAN): centralized coordination fails to scale with respect to the increasing distances in the WAN, and distributed coordination fails to scale with respect to the number of nodes involved. We argue that it is possible to achieve scalability over WAN using a hierarchical coordination architecture and a smart token migration mechanism, and lay down the foundation of a novel design for a flexible-consistent coordination framework, called WanKeeper. We implemented WanKeeper based on the ZooKeeper API and deployed it over WAN as a proof of concept. Our experimental results based on the Yahoo! Cloud Serving Benchmark (YCSB), Apache BookKeeper replicated log service, and the Shared Cloud-backed File System (SCFS) show that WanKeeper provides multiple folds improvement in write/update performance in WAN compared to ZooKeeper, while keeping the same read performance.
coordination  scalability 
july 2017 by mpm
We propose a novel class of algorithms called Join-Idle-Queue (JIQ) for distributed load balancing in large systems. Unlike algorithms such as Power-of-Two, the JIQ algorithm incurs no communication overhead between the dispatchers and processors at job arrivals
july 2017 by mpm
usl4j And You
In this post, I’ll introduce you to Little’s Law, the Universal Scalability Law, and usl4j, a Java library for modeling system performance given a small set of real-world measurements.
scalability  performance 
june 2017 by mpm
usl4j is Java modeler for the Universal Scalability Law, which can be used in system testing and capacity planning, as described by Baron Schwartz in his book Practical Scalability Analysis with the Universal Scalability Law. The model coefficients and predictions should be within 0.02% of those listed in the book.
april 2017 by mpm
Spanner vs. Calvin
I found it very difficult to find cases where an ideal implementation of Spanner theoretically outperforms an ideal implementation of Calvin.
consistency  consensus  database  performance  scalability 
april 2017 by mpm
Multileader WAN Paxos: Ruling the Archipelago with Fast Consensus
We present WPaxos, a multileader wide area network (WAN) Paxos protocol, that achieves low-latency high-throughput consensus across WAN deployments. WPaxos dynamically partitions the global object-space across multiple concurrent leaders that are deployed strategically using flexible quorums. This partitioning and emphasis on local operations allow our protocol to significantly outperform leaderless approaches, such as EPaxos, while maintaining the same consistency guarantees. Unlike statically partitioned multiple Paxos deployments, WPaxos adapts dynamically to the changing access locality through adaptive object stealing. The ability to quickly react to changing access locality not only speeds up the protocol, but also enables support for mini-transactions
paxos  consensus  scalability 
april 2017 by mpm
Stretching Multi-Ring Paxos
Internet-scale services rely on data partitioning and replication to provide scalable performance and high availability. Moreover, to reduce user-perceived response times and tolerate disasters (i.e., the failure of a whole datacenter), services are increasingly becoming geographically distributed. Data partitioning and replication, combined with local and geographical distribution, introduce daunting challenges, including the need to carefully order requests among replicas and partitions. One way to tackle this problem is to use group communication primitives that encapsulate order requirements. This paper presents a detailed performance evaluation of Multi-Ring Paxos, a scalable group communication primitive. We focus our analysis on "extreme conditions" with deployments including high-end 10 Gbps networks, a large number of combined rings (i.e., independent Paxos instances), a large number of replicas in a ring, and a global deployment. We also report on the performance of recovery under peak load and present two novel extensions to boost Multi-Ring Paxos's performance
paxos  scalability 
july 2015 by mpm
Socket acceptor pool for TCP protocols
erlang  scalability 
february 2015 by mpm
Building global and scalable systems with Atomic Multicast
The rise of worldwide Internet-scale services demands large distributed systems. Indeed, when handling several millions of users, it is common to operate thousands of servers spread across the globe. Here, replication plays a central role, as it contributes to improve the user experience by hiding failures and by providing acceptable latency. In this paper, we claim that atomic multicast, with strong and well-defined properties, is the appropriate abstraction to efficiently design and implement globally scalable distributed systems. We substantiate our claim with the design of two modern online services atop atomic multicast, a strongly consistent key-value store and a distributed log. In addition to presenting the design of these services, we experimentally assess their performance in a geographically distributed deployment
consistency  performance  scalability 
july 2014 by mpm
Achieving high-throughput State Machine Replication in multi-core systems
In this work, we show how to architect a replicated state machine whose performance scales with the number of cores in the nodes. We do so by applying several good practices of concurrent programming to the specific case of state machine replication, including staged execution, workload partitioning, actors, and non-blocking data structures.
distributed  consistency  paxos  performance  scalability 
april 2012 by mpm
Library for creating In-memory circular buffers that use direct ByteBuffers to minimize GC overhead
java  memory  scalability 
january 2012 by mpm
Generic Load Regulation Framework for Erlang
A robust way of managing high-load conditions is to regulate at the input edges of the system, and sampling known internal choke points in order to dynamically maintain optimum throughput
erlang  reliability  scalability 
february 2011 by mpm
Sheepdog Project
Sheepdog is a distributed storage system for KVM. It provides highly available block level storage volumes that can be attached to KVM virtual machines. Sheepdog scales to several hundreds nodes, and supports advanced volume management features such as snapshot, cloning, and thin provisioning.
filesystem  distributed  storage  scalability 
january 2011 by mpm
Benchmarking libevent against libev
describes the results of running the libevent benchmark program against both libevent and libev
networking  scalability 
november 2010 by mpm
S4 is a general-purpose, distributed, scalable, partially fault-tolerant, pluggable platform that allows programmers to easily develop applications for processing continuous unbounded streams of data. 
distributed  scalability 
november 2010 by mpm
Server Engineering Insights for Large-Scale Online Services
Our study is based on an in-depth analysis of three very large-scale production Microsoft services: Hotmail, Cosmos, and Bing that together capture a wide range of characteristics of online services
september 2010 by mpm
SRM (Scalable Reliable Multicast)
SRM is a framework for reliable multicast that is still in progress, with areas such as local recovery, congestion control, and ADU naming still under investigation
protocol  scalability 
may 2010 by mpm
Scalability and Performance in Modern Filesystems
This paper compares the XFS file system with three other file systems in widespread use today:
filesystem  scalability 
august 2009 by mpm
Needle in a haystack: efficient storage of billions of photos
The Photos application is one of Facebook’s most popular features. Up to date, users have uploaded over 15 billion photos which makes Facebook the biggest photo sharing website. For each uploaded photo, Facebook generates and stores four images of different sizes, which translates to a total of 60 billion images and 1.5PB of storage. The current growth rate is 220 million new photos per week, which translates to 25TB of additional storage consumed weekly. At the peak there are 550,000 images served per second. These numbers pose a significant challenge for the Facebook photo storage infrastructure.
storage  scalability 
may 2009 by mpm
The SHOP.COM Cache System is an object cache system that is an in-process cache and external, shared Cache
scalability  caching 
december 2008 by mpm
Scaling memcachd at Facebook
This ever increasing demand has required us to make modifications to both our operating system and memcached to achieve the performance that provides the best possible experience for our users.
networking  linux  scalability  caching 
december 2008 by mpm
Spock Proxy
Spock Proxy supports range-based horizontal paritioning of a large MySQL database. The proxy intercepts SQL queries from the client, sends queries to the correct databases based on how the database is partitioned, then aggregates the results from each database and returns them to the client as a regular MySQL result set.
database  proxy  mysql  scalability 
december 2008 by mpm
a web cache system base on nginx web server. faster and more efficient than squid.
proxy  http  scalability  caching 
december 2008 by mpm
Should I get a SAN to scale my site architecture?
using commodity hardware instead of proprietary solutions is about more than saving a few dollars on hardware, it’s also about minimizing the risks to your company
storage  scalability 
october 2008 by mpm
magent is a simple but useful proxy program for memcached servers.
proxy  scalability  caching 
september 2008 by mpm / talks
From time to time, I (Cal Henderson) talk at conferences and such about web things.
web  scalability 
september 2008 by mpm
Writing Java Multithreaded Servers - whats old is new
Thousands of Threads and Blocking I/O: The Old Way to Write Java Servers Is New Again (and Way Better)
java  concurrency  networking  scalability 
september 2008 by mpm
Highly Scalable Java
A collection of Concurrent and Highly Scalable Utilities. These are intended as direct replacements for the java.util.* or java.util.concurrent.* collections but with better performance when many CPUs are using the collection concurrently.
java  concurrency  scalability 
september 2008 by mpm
Scaling Out
Facebook: "So, Jason, we're going to open a new datacenter in Virginia by 2008. Do you think you can help?"
distributed  scalability 
september 2008 by mpm
A Scalable, Commodity Data Center Network Architecture
commodity Ethernet switches to support the full aggregate bandwidth of clusters
networking  cluster  scalability 
august 2008 by mpm
Shard Lessons
there are some other lessons to learn when applying the pattern to your data.
database  scalability 
august 2008 by mpm
scalable and fault-tolerant structured storage with strong data consistency for online databases or Web 2.0 services.
database  distributed  availability  dht  scalability 
july 2008 by mpm
high available and reliable coordination system
distributed  consensus  scalability 
july 2008 by mpm
the cassandra project
distributed storage system for managing structured data while providing reliability at a massive scale.
cluster  database  distributed  storage  dht  scalability 
july 2008 by mpm
The PIER Project
PIER is a massively distributed query engine based on structured overlay networks, which is intended to bring database query processing facilities to new, widely distributed environments.
database  dht  distributed  scalability 
july 2008 by mpm
Topics in High-Performance Messaging
The background information needed for successful deployment isn't widely available. In hopes of saving others a knock or two, we have tried to collect here background information and commentary on some of the issues involved in successful deployments
messaging  scalability 
june 2008 by mpm
Economies of Non-Scale
let's look at the amount of resources required to scale to a given level. We'll use Amdahl's Law as a method to measure the amount of required CPUs. This will provide us a proxy for hardware and software costs
concurrency  scalability 
june 2008 by mpm
Scalable Network Programming
The Quest For A Good Web Server (That Survives Slashdot)
networking  scalability 
june 2008 by mpm
LinkedIn Architecture
At JavaOne 2008, LinkedIn employees presented two sessions about the LinkedIn architecture
june 2008 by mpm
Linux HA
Provide a high availability (clustering) solution for Linux which promotes reliability, availability, and serviceability (RAS) through a community development effort.
cluster  distributed  linux  availability  reliability  maintainability  scalability 
may 2008 by mpm
Scalr is a fully redundant, self-curing and self-scaling hosting environment utilizing Amazon's EC2.
cluster  grid  scalability 
april 2008 by mpm
A Conversation with Michael Stonebraker and Margo Seltzer
A Conversation with Michael Stonebraker and Margo Seltzer
database  scalability 
march 2008 by mpm
Scale in Distributed Systems
This paper looks at scale and how it affects distributed systems
distributed  scalability 
march 2008 by mpm
The Linux Virtual Server Project
The Linux Virtual Server is a highly scalable and highly available server built on a cluster of real servers, with the load balancer running on the Linux operating system.
linux  cluster  availability  maintainability  scalability 
february 2008 by mpm
light-weight persistent queue server that speaks the MemCache protocol
messaging  scalability 
january 2008 by mpm
An Engineering Mantra: You Scaled Your What?
Let's look at the minimal set of scalability vectors that should be considered in every architecture
architecture  scalability 
october 2007 by mpm
Loadbalancer for horizontal web scaling
What questions to ask before implementing one.
web  scalability 
september 2007 by mpm
Set up a Web server cluster in 5 easy steps
Construct a highly available Apache Web server cluster that spans multiple physical or virtual Linux® servers in 5 easy steps with Linux Virtual Server and Heartbeat v2.
cluster  linux  scalability 
august 2007 by mpm
Scaling from 0 to 40 hits per second in 3 days
The thing about running a widget business is that you serve as many web server requests as all your users websites, combined. And if one of your users get’s Dugg or Slashdotted, you get Slashdotted too.
august 2007 by mpm
MySQL Proxy
MySQL Proxy is a simple program that sits between your client and MySQL server(s) that can monitor, analyze or transform their communication. Its flexibility allows for unlimited uses; common ones include: load balancing; failover; query analysis; query filtering and modification; and many more.
cluster  mysql  proxy  scalability 
july 2007 by mpm
Michael J. Radwin talks
Hacking Apache HTTP Server at Yahoo! etc.
web  http  scalability  caching 
october 2006 by mpm

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