Crash Only Web Services
Upcoming SlideShare
Loading in...5
×
 

Crash Only Web Services

on

  • 1,246 views

Crash-Only Web Services: Failure Semantics in an SOA Environment

Crash-Only Web Services: Failure Semantics in an SOA Environment

Statistics

Views

Total Views
1,246
Views on SlideShare
1,244
Embed Views
2

Actions

Likes
0
Downloads
12
Comments
0

2 Embeds 2

http://www.slideshare.net 1
http://www.linkedin.com 1

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

Crash Only Web Services Crash Only Web Services Presentation Transcript

  • Crash-Only Web Services: Failure Semantics in an SOA Environment www.oasis-open.org Chris Hobbs and Abbie Barbir Nortel OASIS Symposium 2007, San Diego
  • The crash-only model
    • Software design approach
    • Easier to restart quickly in a known state than to clean up and rebuild to recover from an error
    George Candea and Armando Fox are key proponents of crash-only software
  • Two themes of this talk
    • Discuss issues of the behaviors of individual and composed services and their part in Web Services Service Level Agreements (WSLA)
      • Based on the behaviors of the individual services
      • Need a taxonomy or ontology of service behaviors
      • Need an approach to calculating behaviors of composed services
    • The “crash-only” model of operation as a simple failure behavior for a Web Service
      • Failure is one of many identified behaviors
  • Background: Orchestration as a New Programming Paradigm
    • SOA promotes the concept of combining services through orchestration - invoking services in a defined sequence to implement a business process
    • Orchestration compounds the difficulties of testing and managing the quality of the deployed services
    • Testing composite services in SOA environment is a discipline which is still at an early stage of study
    • Describing and usefully modeling the individual and combined behaviors - needed to offer Service Level Agreements (SLA) - is at an even earlier stage
    • We hope to stimulate additional research on these topics
  • Testing Composed Services
    • It’s fairly straightforward to test the operation of a device or system if we control all the parts.
    • When we start offering orchestrated services as a product, the services we are using may be outside our control.
    • For example consider well-known components:
      • Google mapping service
      • Amazon S3 storage service
      • Mobile operator’s location service
  • Testing Composed Services (2)
    • With orchestrated services, there is never a complete “box” we can test
    • With orchestration as the new programming paradigm, testing becomes a much bigger problem
    • Failures of orchestrated services are often “Heisenbugs” - impervious to conventional debugging, generally non-reproducible
    • Offering a WSLA based on testing alone, without reliable knowledge of component service behaviors, may be risky
  • Web Services SLA (WSLA)
    • Concerned with behaviors of the message flows and services spanning the end-to-end business transaction
    • Clients can develop testing strategies that stress the service to ensure that the service provider has met the contracted WSLA commitment
    • Composed services make offering a WSLA more risky
    Service Provider Z Provider X Service X Provider Y Service Y Client WSLA Network Packets Message flows Web Service
  • How can WSLAs be derived from behaviors of component services?
    • Need to develop a model of the behavioral attributes of the individual component Web Services which contribute to the overall behavior of an orchestrated or composed Web Service.
    • Need to model the combination of individual service behavioral models
  • Web Services behaviors
    • Behaviors may be described and quantified for each Web Service
    • May be combined by a “calculus of behaviors” when multiple services are composed
    • Behavior parameters may become a part of the service description, perhaps in WSDL.
    • Availability and Reliability
    • Performance
    • Management
    • Failure
    • Security
    • Privacy, confidentiality and integrity
    • Scalability
    • Execution
    • Internationalization
    • Synchronization
    • Etc., …
  • Web Services behaviors (2)
    • To develop a Service Level Agreement (SLA) for a composed service (Z), we need to have relevant behavior descriptions for the individual services (X and Y)
    • We also need a deep understanding of how to combine the descriptions of X and Y to calculate results for Z
    Z X Y
  • Web Services behaviors (3)
    • For each behavior, the challenges include the following:
    • 1. How may service X’s and service Y’s behavior be characterized?
    • 2. How may those characterizations be formalized and advertised by X and Y?
    • 3. How may Z incorporate X’s and Y’s characterizations and then advertise the result?
    • Z itself might become a component of an even larger service and therefore needs to advertise its own characteristics. It also needs this characterization to offer an SLA to consumers.
  • Web Services behaviors (4)
    • Each behavior may have its own ontology, measures, and calculus of combining those measures when services are composed.
    Local Ontology Local Ontology Local Ontology Abstracted Ontology Abstracted Ontology X Y Z Z – Specific Ontology ? Need this analysis for each behavior of services X, Y and Z
  • Web Services behaviors (5)
    • Ten behavior examples
      • Availability and Reliability
      • Performance
      • Management
      • Failure (Crash-only is one mode)
      • Security
      • Privacy, confidentiality and integrity
      • Scalability
      • Execution
      • Internationalization
      • Synchronization
    • Let’s focus on a few of these behaviors…
    Source: “Advertising Service Properties,” unpublished paper by C. Hobbs, J. Bell, P. Sanchez
  • Availability and Reliability
    • “ Availability” is the percentage of client requests to which the server responds within the time it advertised.
    • “ Reliability” is the percentage of such server responses which return the correct answer.
    • In some applications availability is more important than reliability
      • Many protocols used within the Internet, for example, are self-correcting and an occasional wrong answer is unimportant. The failure to give any answer, however, can cause a major network upheaval.
  • Availability and Reliability (2)
    • In other applications reliability is more important than availability
      • If the service which calculates a person’s annual tax return does not respond occasionally it’s not a major problem - the user can try again
      • If that service does respond but with the wrong answer which is submitted to the tax authorities, then it could be disastrous
  • Availability and Reliability (3)
    • Services are built with either availability or reliability in mind, with clients accepting that no service can ever be 100% available or 100% reliable.
    • In combining services X and Y into a composite service Z, it is necessary to combine the underlying availability and reliability models and predict Z’s model.
    • To do so without manual intervention, X’s and Y’s models must be exposed.
  • Availability and Reliability (4)
    • Availability and reliability models are often expressed as Markov Models or Petri Nets, which are easy to combine in a hierarchical way.
    • Major issues:
      • Agreeing upon the semantics of the states in the Markov model or places in the Petri nets
      • Finding a way for X and Y to publish the models in a standard form.
  • Availability and Reliability (5)
    • Currently, apart from raw percentage figures, there is no method for describing these models
      • Percentage time when the server is unavailable?
      • Percentage of requests to which it does not reply?
      • Different clients may experience these differently
      • A server which is unavailable from 00:00 to 04:00 every day can be 100% available to a client that only tries to access it in the afternoons.
  • Availability and Reliability (6)
    • If X and Y are distributed, then it is possible, following network failures, that for some customers, Z can access X but not Y and for others Y but not X.
    • The assessment of Z’s availability may be hard to quantify, so it may be difficult for Z to offer a meaningful WSLA.
  • Failure
    • The failure models of X and Y may be very different:
      • X fails cleanly and may, because of its idempotency, immediately be called again
      • Y has more complex failure modes
      • Z will add its own failure modes to those of X and Y
      • Predicting the outcome could be very difficult
    • The complexity is increased because many developers do not understand failure modeling and, even were models to be published, their combination would be difficult due to their stochastic nature.
  • Failure (2)
    • One approach to describing a service’s failure model:
      • Service publishes the exceptions that it can raise and associates the required consumer behavior with each
      • “ Exception D may be thrown when the database is locked by another process. Required action is to try again after a random backoff period of not less than 34ms.”
    • “ Crash-only” failure model is a simple starting point for building a taxonomy of failure behavior. This work is just beginning.
  • Scalability
    • A behavioral description and WSLA for the composite service Z must include its scalability
    • How many simultaneous service instances can it support?
    • What service request rate does it handle? etc.
    • These parameters will almost certainly differ between the component services X and Y, and will need to be published by those services.
    • X and Y are presumably not dedicated solely to Z, so the actual load being applied to X and Y at any given time is unknown to the provider of Z, making the scalability of Z even harder to determine.
  • Web Services behaviors (again)
    • Ten behavior examples
      • Availability and Reliability
      • Performance
      • Management
      • Failure (Crash-only is one mode)
      • Security
      • Privacy, confidentiality and integrity
      • Scalability
      • Execution
      • Internationalization
      • Synchronization
    • We described a few of these behaviors…
    • Can we use them to build WSLAs?
  • Web Service Level Agreement (WSLA)
    • Based on behaviors and descriptors for these behaviors.
    • Example: Failure model
      • Is transaction half-performed?
      • Is it re-wound?
    • These behaviors and descriptors are not available in the WS description, in WSDL
      • No performance info
      • Not even price!
  • Web Service Level Agreements (2)
    • Business acceptance of composed services for business-critical operations depends on a service provider’s ability to offer WSLA
      • Uptime, response time, etc.
      • Offering a WSLA depends on ability to compose the WSLA-related behaviors of the individual services
      • This information needs to be available via WSDL or similar source
      • Should include test vectors to test the SLA claims
    • The ability to determine and offer a WSLA commitment is a limiting factor for widespread acceptance of services based on orchestration
  • Web Service Level Agreements – conclusions
    • Need a more precise way to express the parameters of behaviors
      • Availability – What is 99.97% uptime?
        • Several milliseconds outage each minute?
        • Several minutes planned downtime each month?
      • Failure model – Crash-only as the simplest, lowest layer or level of failure in a future full failure model.
      • Eight other SLA-related behaviors listed here – each has a complex semantic for description and composition
    • More questions than answers now - many PhDs still to be earned in this area!
  • Back to the crash-only software model
    • Can it simplify service composition, testing, development of WSLA, and end world hunger?
  • Crash-only software (1)
    • Historically, developers have spent a lot of effort making software resilient
      • Put borders around it so it will not affect other things if it fails
      • Try to close it down cleanly
      • Save state
      • Reload the software component
      • Restart and replay
    • Trying to keep the client from becoming aware that a failure occurred
  • Crash-only software (2)
    • Years of work over last ten years on resilient software - which stays up all the time, and recovers from problems
      • For example, tutorials by Bev Littlewood
    • Crash-only software is the exact opposite
      • Client accepts that the server may crash
        • Power failure, network down, hardware, etc.
        • Client must be able to recover or restart the process by itself
  • Crash-only software (3)
    • Crash-only principles
      • Forget recovery - more trouble than it’s worth
      • When the server senses a problem, it will “crash” as cleanly as possible and may perform a “micro-reboot” to return to original state
        • Sometimes recover to a well-defined checkpoint
        • Client may initiate the crash
      • The server is back working sooner than if it tried to recover via logs and journals, etc.
    • Principles fit the Web Services paradigm nicely!
      • Loose coupling of services
      • Little state shared among services
  • Crash-Only Software (4)
    • Crash-only semantic has several advantages:
      • Simpler macroscopic behavior with fewer externally visible states
      • Reduces outage time by removing all shutting-down time
      • Simplifies failure model by reducing recovery state table size
      • Crashing can be invoked from outside the software of the provider
        • Recovery from a failed state is notoriously difficult and the crash-only paradigm coerces the system into a known state without attempting recovery
        • Reduce the complexity of the provider code
      • Simplifies testing by reducing the failure combinations that have to be verified. Consumer is assumed to be able to initiate the crash.
  • Crash-Only Web Services
    • Candea’s list of properties required for a crash-only system can be abstracted to match properties of Web Services:
      • Components have externally enforced boundaries. This is supported by the virtual machine concept used on many Web Service systems
      • All interactions between components have a timeout. This is implicit in any loosely-coupled Web Services interaction.
      • All resources are leased to the service rather than being permanently allocated. This is particularly useful in Web Services.
      • Requests are entirely self-describing. For crash-only services this requires that the request carries information about time-to-live and idempotency – will it return the same result if invoked again?.
      • All important non-volatile state is managed by dedicated state stores.
  • Crash-Only Reliable Web Service
    • For systems with hardware redundancy, by using crash only techniques, SOAP & WS-RM can be extended in order to produce an always available Web Service from the provider’s and consumer’s point of view
    • WSLA response time may be at risk if a service is forced to crash
    Crash-Only Application Server Stall Proxy Web Service Consumer Web Services Endpoint Recovery Agent Crash-Only Backend Crash-Only Backend Crash-only WSM Internet Reliable SOAP Protocol WS-ReliableMessaging
  • Conclusions
    • Testing Web Services in an SOA environment is a discipline that is still in its infancy
    • There are no standard models to describe or combine Web Services behavior information across various services and providers
    • Web Services SLAs (WSLAs) for composed services are problematic
      • Testing is only a partial solution
      • Behavioral composition needs work, but is promising
    • Crash-only Web Services can address some of these difficulties
    • There are many related areas for further work
  • Q & A