Lecture - 1 “Moving Ahead”
- from Clusters and Grids to Cloud computing
Salman Toor [email protected] Basic questions
• Why Cloud computing?
• What are the previous technologies?
• What was missing in the previous technologies?
• Will previous technologies be substituted?
• Can legacy applications run on Cloud platforms?
2 Were supercomputers the only source of large scale computing before Clouds?
ANSWER: NO
3 Distributed Computing Infrastructures (DCI) • Cluster Computing • Accessible via Local Area Network (LAN) • Grid Computing • Based on Wide Area Network (WAN) • Cloud Computing • Next generation computing model
• Desktop Computing • Utility Computing • P2P Computing • Pervasive Computing • Ubiquitous Computing • Mobile Computing
4 Contribution of large scale computing • Areas in which the role of large scale computing is inevitable:
• Particle Physics • Bioinformatics • Computational Mathematics • Quantum Chemistry • … • …
5 Computing model
• Most of the large scale applications both from academia and industry were designed for batch processing
• Batch Processing:
A complete set of batch or group of instructions together with the required input data to accomplish a given task (often known as job). No user interaction is possible during the execution.
6 Cluster computing
http://www.wikid.eu/index.php/Computer_Clustering Cluster computing
• A cluster is a type of parallel or distributed computer system, which consists of a collection of interconnected stand-alone computers working together as a single integrated computing resource
• First realised in 60’s but gained real momentum in mid 80’s
• The aim is to move away from the specialised supercomputing platform and build more general purpose computing environment based on commodity hardware http://www.cloudbus.org/papers/ic_cluster.pdf Cluster computing
• The concept of building computing clusters materialised with tremendous growth in computer hardware
• In a typical scenario (worker/slave/compute) cluster nodes are dedicated resources with no external peripherals attached
• Specifically designed for batch processing
• Cluster Types:
• Supercomputing clusters • Commodity hardware based clusters
9 Cluster computing
• Known Softwares of Cluster computing:
• HTCondor • Portable Batch System (PBS) • Load Sharing Facility (LSF) • Simple Linux Utility for Resource Management (SLRM) • Rocks • …. • ….
10 Cluster computing Advantages • Uniform access to available resources • Load balancing • Various job scheduling techniques • Cluster management tools • User interfaces • single job submission • complex workflows management • Fundamental level security (in typical cases) • Production quality softwares are available
11 Cluster computing Disadvantages • Applications need to adopt the way underlying infrastructure is designed • Cluster softwares are non-coherent • Steep learning curve • Less secure (improved significantly over the years) • Tightly coupled with the underlying resources • Difficult to port new applications • Applications need to stick with the available tools and libraries • Non standard interfaces
12 Cluster computing Current status • Cluster computing is one of the most established way of accessing limited amount of interconnected computational resources
• For example, hundreds of organisations in industry, government, and academia have used HTCondor
• Extension like Directed Acyclic Graph Manager (DagMAN) in HTCondor are still in use to define complex workflows
https://research.cs.wisc.edu/htcondor/description.html 13 https://research.cs.wisc.edu/htcondor/dagman/dagman.html Cluster computing Short falls
̣ Uniform access to large number of resources ̣ System that can handle complex and large workloads
• Possible next steps
• Explore ways to find more resources • Uniform access to distributed computational resources • A bigger system for batch processing
14 Grid computing
• Definition - 1 : (Computational Grid)
Grid is a type of parallel and distributed system that enables the sharing, selection, and aggregation of geographically distributed autonomous resources dynamically at runtime depending on their availability, capability, performance, cost, and users' quality-of-service requirements.
• Definition - 2 : (Computational Power Grids)
The computational power grid is analogous to electric power grid and it allows to couple geographically distributed resources and offer a consistent and inexpensive access to resources irrespective of their physical location or access point. http://toolkit.globus.org/alliance/publications/papers/chapter2.pdf The anatomy of the grid: Enabling scalable virtual organizations
The Grid 2: Blueprint for a new computing infrastructure 15 http://www.gridcomputing.com/gridfaq.html Grid computing Vision
16 Grid computing Actual picture
http://kekcc.kek.jp/service/cc/uguide_en/10_1.system_tokutyou.html 17 Grid computing System components
• Application execution tools • Information extraction • Multi-level scheduling • Runtime environments • Resource discovery • Security • Reliability • Data management • Quality of Services (QoS) • Interoperability • Resource allocation • Virtual Organisation • Metadata management Management System (VOMS) • …. • …. 18 Grid computing Virtual Organisation Management System (VOMS) • Virtual Organisation
An abstract entity grouping Users, Institutions and Resources in a same administrative domain.
• Virtual Organisation Management System
VOMS is a system for managing authorisation data within multi-institutional collaborations. VOMS provides a database of user roles and capabilities and a set of tools for accessing and manipulating the database and using the database contents to generate Grid credentials for users when needed.
Article: From gridmap-file to VOMS: managing authorization in a Grid environment http://toolkit.globus.org/grid_software/security/voms.php 19 Large Hadron Collider Grid (LCG)
20 http://www.isgtw.org/feature/isgtw-feature-mega-grid-mega-science Grid Computing Basic Workflow
UI Input sandbox JDL DataSets info Information Output sandbox Service Resource SE & CE info Input
Output voms-proxy-init Broker
sandbox Job Submit Event Submit Job sandbox Job QueryJob + Broker Info Publish
Expanded JDL
Job Status
Globus RSL Storage Element Job Submission Job Status Service Computing Job Status Element 21 Job workflow in gLite middleware: http://slideplayer.com/slide/2801198/ Grid computing at CERN
• Large Hadron Collider (LHC) experiment at European Organisation for Nuclear Research (CERN)
• The Grid runs more than two million jobs per day
• Till 2013, system had 100PB of data and its growing 27PB per year
• Expected to generate 400PB of data till 2023 https://www.youtube.com/watch?v=7k3VnWXOjP4 http://home.web.cern.ch/about/updates/2013/02/cern-data-centre-passes-100-petabytes http://www.hpcwire.com/2014/11/04/cern-details-openstack-journey/ 22 http://home.web.cern.ch/about/computing Grid computing Advantages
• Seamless access to geographically distributed resources
• Provide means to accelerate collaborative science
• The concept of virtual organisations (VO) evolved with Grids
• Each site in the Grid system is fully autonomous
• Transparent access to the heterogeneous resources
• Allows large scale batch processing capabilities
23 Grid Computing Disadvantages • Complex system architecture
• Steep learning curve for the end user
• Only allow batch processing, zero level interactivity
• Difficult to attach a comprehensive economic model
• The sites are autonomous but the softwares are tightly connected with the underlying hardware
• Mostly available for academic and research activities
• Lack of standard interface
• Static availability of resources 24 Grid computing Current status • European Middleware Initiative (EMI)
• Compute Resources: • gLite Middleware • Advanced Resource connector (ARC) • Unicore
• Storage Resources • DCache • Castor • DPM
25 Grid computing Current status • Advanced Resource connector (ARC)
26 Grid computing Current status • Nordic Data Grid Facility (NDGF)
• Storage/data grid based on DCache software stack
• Data is distributed over many computing centres across Scandinavia
• Secure data access using variety of protocols
http://neic.nordforsk.org/about/strategic-areas/tier-1 27 Grid computing Short falls ̣ Tight coupling with hardware resources ̣ User interfaces ̣ Limited user community ̣ Weak monitoring and billing system ̣ Limited user level access ̣ Complex software stack
̣ Security model ̣ users and project management system Possible next steps A system that can address these limitations 28 Cloud computing NIST definition
Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.
http://csrc.nist.gov/publications/nistpubs/800-145/SP800-145.pdf 29 Example from So ware Engineering Waterfall Model Spiral Model Grid Computing
Unified Modeling Language (UML) Cloud Computing
30 Strength of cloud computing
Cloud compu ng reduces the gap between the concept and the implementa on by defining roles and responsibili es that allows:
• level of abstrac on • Service Level Agreements (SLA) • paradigm shi from servers to *-as-a-service • possibility to a ach economic model • on-demand resource availability
31 Cloud computing Roles and responsibilities
• Infrastructure provider
• Platform provider
• Software provider
• Network provider
32 Cloud computing
Why Cloud Computing?
33 Cloud computing
A well-defined economic model
• Driving force behind Cloud concept
• Public Clouds • Private or Community • Amazon Clouds Smog • HP Helion Cloud • • ePouta • Intel Cloud • UberCloud 34 Cloud computing
Complete isolation, direct access and full control of allocated resources
35 Cloud computing
On demand resource allocation No job queues!
• No need of specialised static worker nodes
36 Cloud computing
Loose coupling with the underlying resources
• Live or block based VM migration
37 Cloud computing
“Standard” interface to interact with the cloud resources
• Amazon EC2 and S3 APIs could be used to connect to OpenStack based Cloud • RestAPIs based communication
38 Cloud computing
Orchestration of scalable services
• Amazon EC2 (Compute) • Amazon S3 (Storage) • Amazon Elastic MapReduce • OpenStack Sahara (virtual Hadoop cluster) • OpenStack Trove (Database)
39 Cloud computing
Minimal interaction with service providers
40 Cloud computing
Are legacy applications portable to Clouds?
ANSWER: Yes
41 Cloud computing Computing model • Together with batch processing, Cloud computing model provides interactive processing of complex applications
Wikipedia:
Interactive computing refers to software which accepts input from humans — for example, data or commands.
• Frameworks like; IPython or Jupyter notebooks extend web technologies for interactive computing
42 Cloud Computing
43 Introduction to SNIC Cloud (IaaS)
http://smog.uppmax.uu.se
44 Security on SNIC Cloud
45 What SNIC Cloud will provide?
• Resources – Compute – Storage – Network
• Users will have complete control over the allocated resources.
• Power comes with the responsibility!
46 Important
• Users can login as supper-user root, can install or uninstall whatever they want. • Question: What if for “connivance” I will create a user account on my VM with the name “XXX” and password “XXX123”… Can I ? • The answer is YES, you can. But it may have serious consequences!!!!
47 Consequences
• Since the VMs will be available via Internet and with weak password or sometimes even with strong passwords, systems can get hacked.
• The attacker can do varies things: – Destroy the data available on the VM – Corrupt the VM so it will not be usable – Generate an attack using your VM – Or even much more …
48 What should we do ?
• Don’t use password based logins!
• The convention is to use SSH key-pair login mechanism.
• For this course it is required that all the students always use SSH keys to access resources.
49 What is SSH key-pair?
• A public key based authentication system used to identify users on SSH enabled servers • based on pair of keys – private key (user’s personal key) – public key (world readable key) • User can generated RSA or DSA based keys – RSA (Rivest-Shamir-Adleman) keys have a minimum key length of 768 bits and the default length is 2048 – The key length of DSA (Digital Signature Algorithm) is always 1024
https://wiki.archlinux.org/index.php/SSH_keys https://help.ubuntu.com/community/SSH/OpenSSH/Keys 50 Key-Pair generation
• OpenStack based key
generation interface $ ssh-keygen or $ ssh-keygen -t rsa -b 2048 • Command-line interface
51