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000-998 WebSphere Message Broker V6.0, System Admin

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000-998 exam Dumps Source : WebSphere Message Broker V6.0, System Admin

Test Code : 000-998
Test title : WebSphere Message Broker V6.0, System Admin
Vendor title : IBM
braindumps : 102 actual Questions

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IBM WebSphere Message Broker V6.0,

Correlsense broadcasts SharePath for IBM WebSphere Message broker, Improves carrier-stage administration, mistake Identification and Bottleneck Isolation | killexams.com actual Questions and Pass4sure dumps

FRAMINGHAM, MA--(Marketwired - Jun 11, 2013) - Correlsense, a number one IT monitoring software business, nowadays added SharePath for IBM® WebSphere Message broker (WMB). This latest enhancement to SharePath 3.0, the company's business-category APM reply for managing complicated interconnected purposes, is most effectual for any company relying on IBM middleware for its transactional spine.

As functions become increasingly connected, groups are employing enterprise provider Buses (ESBs) to deal with the communications between disparate applications and functions. the usage of an ESB, besides the fact that children, introduces fresh management challenges. They are often decoupled from the core application and execute company worthy judgment and code which provides complexity while expanding the time to notice and isolate efficiency concerns. unlike other middleware management options that hub of attention on infrastructure monitoring, SharePath for IBM WebSphere Message broker presents greater granular visibility into the finished journey of particular person message flows into, inside and out of the ESB. This gives indisputable proof about where performance complications and mistakes happen, even if within message broking service, in which node, or in the backend features or applications.

SharePath follows every message circulation via its nodes and external features, and logs every lone this special tips in a scalable immense statistics repository, including parameters, values and exception blunders of each and every execution. besides huge constructed-in logging, auditing, and monitoring of every lone messages, SharePath offers trending and change analysis to track performance over time.

SharePath for WebSphere Message broking service offers middleware owners, IT operations and production champion groups the potential to without detain rob into account dependencies and establish middleware bottlenecks. Most particularly, SharePath for IBM WebSphere Message broking service:

  • enables IT operations teams to simply ascertain "misplaced messages" by any search standards via an easy full-text search.
  • gives essentially the most accurate bottleneck detection available on the market nowadays with the aid of monitoring and logging each message movement throughout its execution, including utilization of exterior features and supplies, and suggests no matter if bottlenecks are within WMB or outside of it.
  • immediately detects every lone message flows and their exterior dependencies to give an always up to date dependency mapping. No manual configuration is required when message flows are updated or fresh message flows are deployed.
  • "SharePath for IBM WebSphere Message broking service empowers agencies to benefit wield over a faultfinding enterprise element," observed Nir Livni, VP of products. "companies the usage of SharePath now not should build wide, costly and mistake-inclined logging and tracking mechanisms to preserve in intellect what took status to a selected message and no matter if it succeeded or failed."

    SharePath for IBM WebSphere Message broking service is purchasable instantly as a standalone offering or as a Part of an entire conclusion-to-conclusion APM solution in response to SharePath 3.0. more counsel will likewise subsist discovered at http://www.correlsense.com/options/enterprise-want/sharepath-for-ibm-websphere-message-broker/

    About Correlsense Correlsense develops utility performance management and IT monitoring software. it is the APM made of selection for traffic and IT operations managers that depend on complicated and significant traffic functions. Correlsense paints a complete and dynamic image of IT carrier levels and performance for applications that span mobile, SaaS, cloud, information middle and legacy mainframes. Correlsense was centered in 2005, is privately held and SharePath consumers comprehend some of the world's biggest monetary, telecom and retail enterprises. For greater assistance, consult with www.correlsense.com.


    IBM App connect XML information XML external Entity [CVE-2018-1801] | killexams.com actual Questions and Pass4sure dumps

    A vulnerability became present in IBM App join, Integration Bus and WebSphere Message broking service (software Server application) and categorised as important. This challenge influences a Part of the component XML information Handler. The manipulation with an unknown input leads to a privilege escalation vulnerability (XXE). using CWE to declare the problem ends up in CWE-611. Impacted is confidentiality, integrity, and availability.

    The decrepit point was launched 02/04/2019. it is workable to read the advisory at change.xforce.ibmcloud.com. The identification of this vulnerability is CVE-2018-1801 when you account that 12/13/2017. The assail can subsist initiated remotely. The technical particulars are unknown and an get the most isn't publicly obtainable. The pricing for an exploit could subsist around USD $25k-$100k at the minute (estimation calculated on 02/05/2019).

    There isn't any assistance about workable countermeasures time-honored. It could subsist advised to substitute the affected object with an selection product.

    CPE CVSSv3 VulDB Meta base rating: 6.3VulDB Meta Temp rating: 6.three

    VulDB base score: ≈6.3VulDB Temp rating: ≈6.3VulDB Vector: 🔒VulDB Reliability: 🔍

    CVSSv2 VulDB base score: 🔒VulDB Temp score: 🔒VulDB Reliability: 🔍Exploiting classification: Privilege escalation / XXE (CWE-611)native: NoRemote: yes

    Availability: 🔒

    cost Prediction: 🔍latest rate Estimation: 🔒

    chance Intelligence chance: 🔍Adversaries: 🔍Geopolitics: 🔍economic climate: 🔍Predictions: 🔍moves: 🔍 Countermeasures advised: no mitigation known0-Day Time: 🔒 Timeline 12/13/2017 CVE assigned02/04/2019 Advisory disclosed02/05/2019 VulDB entry created02/05/2019 VulDB closing update resourcesAdvisory: change.xforce.ibmcloud.comConfirmation: 🔒

    CVE: CVE-2018-1801 (🔒)

    accessCreated: 02/05/2019Complete: 🔍

    Lien vers l'article supply


    SOA software proclaims integrated SOA Governance for IBM WebSphere Message broking service | killexams.com actual Questions and Pass4sure dumps

    by means of SOA information Desk

    Article rating:

    March 17, 2008 02:45 PM EDT

    Reads:

    6,328

    SOA software introduced that it has licensed IBM WebSphere Message broking service as a ruled provider Platform. This certification enables valued clientele to exercise IBM WebSphere Message broking service to Put into consequence and implement governance policies for enterprise internet services providing reporting information to permit a closed-loop audit routine as a Part of their traffic SOA.

    certified ruled service Platform popularity capacity that customers can subsist confident that their platforms might not compromise the allegiance of the governance techniques and structures described in an traffic SOA program.

    SOA application's Workbench and service manager subsist certain that IBM WebSphere Message broking service can facilitate and benefit from the integrated SOA Governance Automation finest practices:

  • have faith & administration mediation
  • service virtualization
  • Governance Automation
  • continual compliance and validation
  • Metadata federation
  • change believe an consequence on mitigation
  • Uniform coverage management
  • SOA software provides a custom palette for the IBM WebSphere Message broker Toolkit. The nodes can subsist dragged and dropped into the acceptable points in a manner journey and provide the gross performance of the Agent for ultimate-mile coverage enforcement, and the Delegate for first-mile policy implementation.

    "we're snug to announce the mixing of their integrated SOA Governance Automation products with IBM WebSphere Message broking service," mentioned straightforward Martinez, executive vp of SOA application. "The certification of IBM WebSphere Message broking service as a ruled carrier Platform gives customers self credence that their present investments in IBM WebSphere Message broking service hold the allegiance of the governance fashions, constructions and mechanisms helping their commercial enterprise SOA application."

    SOA application and IBMIBM valued clientele leverage SOA software for seamless, heterogeneous SOA Governance, safety and management integration with their IBM Middleware infrastructure to ensure interoperability across disparate companions and systems. SOA application's items give uniform lifecycle and policy governance across every lone latest platform investments with requisites aid for Governance automation and dependence enablement and mediation.

    SOA software's products toil seamlessly with IBM's WebSphere product family unit together with WSRR, DataPower, process Server, utility Server, and Message broking service.

    SOA World magazine information Desk trawls the district of disbursed computing and SOA-connected developments for the newest keep on technologies, standards, products, and capabilities and brings key suggestions to you in a well timed and convenient summary kind.

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    WebSphere Message Broker V6.0, System Admin

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    MESSAGING: WHAT TO pick AND WHEN | killexams.com actual questions and Pass4sure dumps

    XavientBlockedUnblockFollowFollowing

    Oct 18, 2016

    In the previous blog, they gave an overview of the different messaging protocols available to us (AMQP & JMS) and listed each one’s benefits and issues. In this blog, they intend throwing light on the different messaging solutions available in the market such as Kafka, RabbitMQ, Cloud Messaging solutions such as Amazon SQS and Google Pub Sub, Container built in messaging such as Oracle M)M in Oracle Weblogic and IBM MQ in WebSphere and which should subsist used for what situation

    Apache Kafka

    Apache Kafka is a message broker that was originally developed by LinkedIn before going open source under the Apache umbrella. Kafka’s main focus was speed and efficiency. It can maintain a message throughput rate of 100k+ msgs/sec which is significantly higher than most other alternatives. However, other basic features create in other brokers are eschewed in favor of efficiency. Features dote message acknowledgments, routing rules and an admin UI are not available as standard. Even though Kafka is defined as ‘stable’ and ‘production-ready’, deploying Kafka in HA mode is tougher than it is with other providers. It is highly contingent on the Zookeeper module in order to maintain synchronization between multiple Kafka nodes and client apps.

    RabbitMQ

    RabbitMQ is an open source message broker software managed by Pivotal. It implements the Advanced Message Queuing Protocol (AMQP) which they described in detail in the earlier blog. Unlike Kafka, RabbitMQ comes with a built-in management dashboard for easy configuration and monitoring of message queues. It likewise supports requests for message acknowledgements and is easily deployed in HA mode with minimal effort. With a message rate of about 20k+ msgs/sec which is much less than Kafka, it’s sufficient enough for most exercise cases. Due to it’s platform-independent framework and ease of use, RabbitMQ is a very age message broker offering with a lot of extended champion from the community.

    Amazon SQS

    Simple Queue Service (SQS) is Amazon’s cloud-based message queuing system made available as Part of Amazon Web Services (AWS). Unlike the other brokers mentioned here, there is barely any setup/deployment required for an application to exercise SQS. every lone you exigency is AWS credentials to subsist able to exercise it. Since it is a SaaS (Software-as-a-service), this makes it a much lower-cost option since there is no infrastructure cost. You only pay for what you use. SQS likewise has the notion of in-flight messages. This means that the message is pulled off the queue but never deleted until the ‘delete‘ command is sent for that message ID. So if you lose your worker mid-processing of the event, that event isn’t lost for good.

    One drawback of the SQS implementation is the exigency for polling of a message queue to determine if fresh messages believe appeared. This is a bit of an issue being as you must now model your application to accomplish a polling cycle in order to determine if fresh messages are available. While the SQS costs are reasonable, Amazon places a restrict on the message rate which can subsist increased on request and likewise charges extra based on the overall message rate.

    Google Cloud Pub/Sub

    Google’s Cloud Pub/Sub is a fully-managed real-time messaging service that allows you to transmit and receive messages between applications or server. It is developed specifically to faciliate messaging among applications deployed on the Google Compute Engine (GCE) cloud. It’s basic features are very similar to that of Amazon’s SQS in that there are no infrastructure costs and you pay for what you use. The major inequity from SQS is that Google charges based only on volume and not transacation speed i.e. you will not subsist charged extra for a sudden multiply in message rate.

    IBM MQ & Oracle WebLogic JMS

    Both IBM MQ and Oracle WebLogic JMS are very similar in features to benchmark JMS. You would pick one over the other based on what framework your app is using i.e. if your app is deployed on IBM Websphere, it will subsist much easier to integrate it with IBM MQ than any other provider.

    Similarly, it would subsist simpler to integrate an app running on Weblogic with the JMS server that it provides instead of an external provider.

    For in-detail comparisons , read more here — https://techblog.xavient.com/messaging-what-to-choose-and-when/

    Implementing Retries with a MDB or an MQ Batch Job? (WAS 7, MQ 6) | killexams.com actual questions and Pass4sure dumps

    We exigency to listen for messages distributed via Websphere MQ to collect informed when an employee joins or leaves IBM. And because the resources used in the processing (a database, a webservice) may subsist temporarily unavailable, they must subsist able to deal with such outages, which may sweep from minutes to hours, by repeatedly retrying the processing after some delay. And they must subsist likewise able to deal with “poison messages”, that means messages whose processing always fails either because their content is invalid or because their data isn’t consistent with the database.

    The question is whether this would subsist better implemented as a Message-Driven Bean (MDB) or a batch job regularly checking its queue given that they believe Websphere Application Server 7 (and thus Java EE 5) and Websphere MQ 6, which both believe some notable changes compared to the previous versions. It turns out that it depends – both approaches believe some advantages and disadvantages and so it’s a question of the likelihood of particular problems and traffic requirements and priorities.

    Setting the scene MDB vs. a batch job: the decision factors

    Whether they should select the MDB or the batch job approach depends on a number of factors, some of them are:

  • Requirements
  • Quantity: What quantity of messages accomplish they exigency to handle?
  • Error likelihood: What’s the probability that a resource will subsist temporarily unavailable or that a message will contain data that can’t subsist processed correctly and how soon such a problem needs to subsist resolved? I.e. can they wait to another day or shall they collect going as soon as the resource is up again? This will order us how often they exigency to retry and whether a manual handling of an issue is sufficient.
  • Support for mistake handling/retrial logic
  • Ease of use/development/maintenance
  • Performance: They exigency to wield every lone the incoming messages and to believe minimal negative impact on the  performance of the target system
  • Speed of processing of the incoming messages (immediate vs. once or few times per day)
  • Integration with their operations monitoring (logging, their Operations Dashboard webapp)
  • The problems to deal with

    There are three types of problems that can occur:

  • A failure to communicate with MQ, for instance because a network connection got interrupted
  • Inability to process a message due to a resource (a DB or a WS) being temporary unavailable
  • A poison (invalid) message (wrong data type, unexpected content) leading to an exception during its processing
  • The two approaches Approach 1: A Message-Driven Bean (MDB)

    A MDB is hosted by an application server that does a lot of toil on behalf of the bean (such as transaction and concurrency management) thus simplifying its development and configuration. It may subsist as simple as writing

    @javax.ejb.MessageDrivenpublic class SimpleMessageBean implements javax.jms.MessageListener { public void onMessage(javax.jms.Message inMessage) { final javax.jms.TextMessage msg = (javax.jms.TextMessage) inMessage; final String msgBody = msg.getText(); // wield the msgBody ... }}

    and configuring the ActivationSpecification for the MDB in JNDI via the app. server’s administration UI.

    The question is, of course, how well it can wield poison messages and retrial when resources are temporarily unavailable.

    MDB mistake handling and configuration in Websphere 7

    Let’s believe a spy how Websphere deals with various kinds of errors related to MDBs and how they accomplish configure a MDB in this application server, especially with regard to mistake handling.

    MDB mistake handling in Websphere

    What happens when an mistake occurs?

    Normally an Application Server starts an MQ transaction before it invokes a MDB and it either commits it when the MDB finishes or rolls it back when it throws an exception. If the transaction succeeds then the message is removed from the MDB’s queue otherwise it will subsist returned there and processed again in the future. This is the default behavior corresponding to configuring container-managed transactions (tx) with the kind of ‘required’. Notice that likewise DB operations can participate in this transaction and thus subsist committed/rolled back as well, which might subsist useful.

  • In the case of an MQ communication/connection failure, WAS logs the exception and retries the connection later based on its configuration. It’s likewise workable to set an ExceptionListener that would subsist called with the exception as a parameter in such a case.
  • In the case of an exception during message processing (or due to a manual setRollbackOnly invocation) the current transaction is rolled back, the message is Put back to the queue and the MDB is restarted. When the queue is re-checked, the message is create again and passed to another MDB. If the intuition of the problem persists, this will fail again – and so on.
  • We believe two ways how to deal with a failed message:

  • Remove the message from the queue either by discarding it or by affecting it to the queue’s “back-out queue”. This is commandeer when the message itself is the problem (e.g. contains data incompatible with the DB …).
  • Stop processing messages from the queue (pause the Activation Specification) and restart it later when the problem is resolved. This is commandeer when a necessary resource is temporarily unavailable.
  • Messaging provider and JMS resources configuration related to mistake handling

    We will exercise JCA 1.5 Activation Specification (and not Listener Ports that are deprecated since WAS 7) with Websphere MQ as the provider, which limits their configuration options to those described below.

  • Disabling (temporarily) the gross queue, more exactly shutting down the MDB
  • “Number of sequential delivery failures before suspending endpoint” – on an MQ Activation Specification
  • “Stop endpoint if message delivery fails” – if true, message delivery suspended when the Number of sequential delivery failures… exceeded
  • Removing problematic messages (this is done by Websphere MQ itself, not WAS)
  • “Backout threshold” (BOTHRESH; a property of a queue, configured via MQ) specifies the maximum number of times a message can subsist Put onto a queue before it is moved to the specified backout requeue queue.  Default: 0 or unset?! => never re-delivered
  • “Backout requeue queue” (BOQNAME; a property of a queue, configured via MQ) – the queue where to Put the failed messages; default: SYSTEM.DEAD.LETTER.QUEUE
  • WARNING: This seems to apply only to a queue, not to a topic. But underneath topics exercise (likely dynamic) queues anyway so it should subsist workable somehow.
  • Other related settings
  • Interesting resources:

    Design of the MDB approach Error handling design

    The main problem with the MDB approach is that it doesn’t champion retrying an operation after a detain (either for a lone failing message or for the gross queue, if a resource is temporarily unavailable). There are some workarounds, but not very nice.

  • For a lone message I couldn’t find a pass to implement retrials after some, preferably increasing, delay; the only thing they can accomplish is to retry it few times with the default Websphere’s delay, which seems to subsist 5s, and if it noiseless doesn’t succeed then journey it into a special queue that would subsist processed manually while perhaps likewise sending an email notification.
  • If there is some global problem, such as an unavailable resource, indicated by several consecutive failures of one or more messages (depending on the content of the queue), they could let WAS desist the MDB and re-enable it later either automatically after a detain or manually when the problem gets fixed.
  • MDB design
  • When resource unavailability is detected, let WAS desist the MDB automatically via the setting “Number of sequential delivery failures before suspending endpoint”. It will exigency to subsist re-enabled either manually or automatically.
  • Manual re-activation of the MDB: They believe to to a certain degree detect that the MDB was disabled (the only option is perhaps by watching the log), find out why it failed, and re-enable it via the Websphere Administration Console.
  • Automated re-activation: Implement a scheduled stateless EJB, which re-enables the MDB after few tens of minutes – preferably accomplish this few times with increasing delay, if noiseless failing, give up and notify an admin.
  • When there is a poison message, journey it to the backout queue and notify somebody to wield it (e.g. via email)
  • If the queue contains only one message there is no generic pass how to find out whether the problem is within the message or in some resource, the MDB would exigency to find this out and communicate it. If there are multiple messages and only one fails, they know it’s a poison message and it could subsist automatically removed by means of the “Backout threshold”. (Beware of the interaction between the message’s redelivery count/backout threashold and the “Number of sequential delivery failures…” – the letter is reset when either a message processing succeeds or when the MDB is stopped/restarted.)
  • (Perhaps they could exercise JMS selectors on JMS header properties (e.g. JMSRedeliveredto, JMSXDeliveryCount) but the possibilities are rather limited because both the selector query and the properties are static (e.g. something dote MyRetryTime >= now() isn’t possible). Note: MQ V7 has a major rewrite of the selectors champion and their handling was moved from the Java client directly to the queue manager.)
  • MDB approach evaluation Key MDB issues
  • Permissions to accomplish a WAS administration operation required.
  • Difficult to distinguish a poison message from a resource outage without additional logic when the queue contains only one element.
  • But observe the batch job design below, which likewise requires to subsist able to distinguish these two types of problems.
  • Inefficient determination of MDB’s status for the detain reactivation logic: either polling its status regularly or watching the log with many unrelated messages that can’t subsist filtered out.
  • Key MDB advantages and disadvantages
  • Advantages
  • The data is processed and reaches the destination system soon after it is published
  • Key characteristics are configurable via UI (Number of sequential delivery failures, Backout threshold, MQ connection data, MQ security/SSL, processing concurrency, DataSource configuration/injection, …). Actually this is likewise a drawback due to needing an admin, observe below
  • Logging configurable at the runtime (Java logging, levels can subsist set in WAS console)
  • Disadvantages
  • Any configuration requires a WAS administrator and thus lot of time due to the IBM bureaucracy and ceremony
  • Difficult to collect and communicate statistics for their Operations Dashboard because (a) there are frequent fine-grained changes instead of 1/day batch changes and (b) there is no champion for the Job logging framework of ours (a workable but laborious solution is to gather statistics in an instance variable and log them in regular intervals into the job tables using JDBC and some code extracted from the job framework)
  • Necessary to to a certain degree configure the reactivation EJB (the reactivation delay, number of attempts before giving up)
  • MDB design questions:

  • Do they exigency automated reactivation of a disabled MDB? Perhaps not if: (1) a resource outage happens rarely and/or (2) the administration team spots this automatically and can wield it automatically without any bureaucracy and consumption of their resources.
  • MDB resources

    Essential docs

    Other (not every lone docs available for their version, namely MQ v6 and WAs v7)

    Approach 2: A batch job checking MQ regularly

    A batch job is a command-line application that is regularly, for sample once a day, escape by cron and actively scans its incoming queue/topic for fresh messages and processes them every lone at once. every lone the JMS communication and management and configuration must subsist implemented from scratch. (Though utilities such as Spring JMS template may simplify it.)

    Job mistake handling and configuration Error handling

    The problems and ways to deal with errors are the same as when running in an application server, only they believe to accomplish everything ourselves. That means they exigency to manually start a transaction, snare exception and commit/roll back and configure the topic/queue for poison messages.

    We would exigency to implement a problem intuition detection logic to distinguish whether there is a temporary resource outage or whether there is a problem with the message itself (either incorrect data kind or data incompatible with the target DB ). There is no other worthy pass to deal with these part kinds of problems without really knowing which of them it is.

    We would deal with the problems as follows:

  • For a resource outage, retry few times with an increasing delay, then quit and postpone the processing till the next scheduled execution
  • For a poison message, journey it to the backout queue and notify an administrator
  • JMS configuration in a batch job

    We believe two ways to configure the JMS resources (a Topic and a (Topic)ConnectionFactory) and their options related to mistake handling:

  • Use MQ provider-specific APIs to create the objects and configure them. observe this JMS + MQ API example.
  • Configure the provider-specific resources in JNDI and exercise only the standardized JNDI and JMS APIs. This is very easy with Sun’s filesystem-based JNDI provider (fscontext.jar and providerutil.jar) and vendor-supplied tools for generating the JNDI .bindings file for existing JMS resources . In the case of MQ you can accomplish it in the MQ Explorer GUI or with the command-line utility JMSAdmin (a JMSAdmin example, another one).
  • You can create the JNDI configuration via the MQ Explorer wizards – after having added a fresh JNDI “context” using fscontext and a local directory – either by first creating the JMS resource and then letting the wizard generate an MQ resources for it and adjusting it as needed:

    Or by creating the JMS resource from an existing MQ resource:

    Provided that the FsContext configuration file .bindings produced by JMSAdmin/MQ Explorer is in the folder /etc/mqJndiconfig, they would connect to the MQ as follows:

    final Hashtable<String, String> env = fresh Hashtable<String, String>();env.put(Context.INITIAL_CONTEXT_FACTORY, "com.sun.jndi.fscontext.RefFSContextFactory");env.put(Context.PROVIDER_URL, "file:/etc/mqJndiconfig");final InitialContext context = fresh InitialContext(env);ConnectionFactory qcf = (javax.jms.ConnectionFactory) context.lookup("MyConnectionFactory"); // Note: I set the channel property MCAUSER so it actually isn't necessary to supply credentials below:final Connection connection = qcf.createConnection("anna", "password ignored");// Client ID is necessary for a durable subscr.// They could alternatively set in on the ConnectionFactory - the CLIENTID propertyconnection.setClientID("MyCoolApplication");final Session session = connection.createSession(true, -1); // the param 2 is ignored for durable subscr.final Topic destination = (Topic) context.lookup(JNDI_PREFIX + TOPIC);final MessageConsumer receiver = subscribe(session, destination);try {connection.start();} snare (javax.jms.JMSException e) {throw fresh RuntimeException("Failed to start the JMS connection", e);}

    We would then read the messages via:

    while ((msg= receiver.receiveNoWait()) != null) {handleMessage(msg);}

    The dependencies comprehend jms.jar, fscontext.jar and providerutil.jar. You can find them either in the WMQ installation or on the web.

    You may want to believe a spy at Writing a simple publish/subscribe application connecting through WebSphere MQ in WMQ help, which discusses some of the code above in more detail.

    Job design
  • Set a reasonable backout threshold and a suitable backout queue on the queue used by the Topic so that problematic messages are removed automatically after few failed attempts
  • Some monitoring of the backout queue would subsist necessary. If the MQ infrastructure doesn’t provide it then they can implement another MQ/JMS reader that would transmit an email when there are some fresh messages in the queue.
  • Regarding the kind of the topic queue:
  • Either they can exercise the shared JMS queue (SYSTEM.JMS.D.SUBSCRIBER.QUEUE) for the topic
  • Or they can exercise a non-shared queue unique for their application, which would subsist actually better and more aligned with IBM standards. It’s achieved by setting a broker durable subscription queue pattern in the shape “SYSTEM.JMS.D..*” (notice the trailing *) on the JMS ConnectionFactory when defining it in JNDI or in the Java code. Upon the first connection a permanent dynamic queue is generated for the client. They can then set the backout options on it (or the administrators may define a model queue for these dynamic queues with this setting already applied).
  • Read and process each message in a fresh MQ transaction so that if the processing fails it will subsist Put back into the queue (and its delivery weigh will subsist increased, thus making it perhaps eligible for the backout queue)
  • Batch job approach evaluation
  • Advantages
  • Simple implementation offlexibledelayed retrials – upon a resource outage, discontinue the job and try again during the next scheduled escape or, perhaps, retry first after a manual detain (Thread.sleep(); beware connection timeouts).
  • Simple integration into their monitoring/logging framework incl. the Operations Dashboard.
  • Disadvantages
  • More coding to set up/clean the resources and wield errors, which is not trivial, and thus likewise more bug prone.
  • Concurrent processing of the messages would subsist considerably more difficult to implement correctly if workable at every lone (if MQ JMS does implement the necessary optional methods). They would exigency to exercise the advanced methods targeted at app. server vendors – there is a non-MQ sample of a multithreaded (non-durable subscription) consumer. Hopefully it could subsist modified for a durable one using Connection.createDurableConnectionConsumer with the same simple implementation of ServerSessionPool.
  • Impl. details: The “pool” would always create a fresh custom ServerSession implementation. instance, whose getSession() would simply create a fresh transacted TopicSession, set its MessageListener, and escape the session in a fresh Thread when start() called. Notice that (Topic)Session implements Runnable, whose run() invokes the provided listener sequentially for available messages. The listener would process a message and call commit/rollback on its owning session (see this transactional listener example).
  • Important: Handling of failed messages would exigency to subsist considered carefully as returning a message to the queue would lead to its immediate re-processing and likely rejection by one of the other threads, exceeding its backout treshold in a few seconds and thus subverting the delayed retrial processing. On the other hand, as mentioned above, they should anyway subsist able to distinguish resource outage, in which case they would desist processing immediately, and a problematic message, which would anyway discontinue up in the backout queue so this is perhaps not a actual issue.
  • Note: When using MessageListeners, it’s notable to set an ExceptionListener on the connection because some errors can only subsist communicated this way.
  • Summary and conclusion

    The version and fixpack flush of WMQ/WAS is very important.

    Both the approaches believe some pros and cons and it depends on the requirements and their priority which one would subsist more suitable.

    MDB: It’s more difficult to implement delayed retrial if it is required – it may subsist implemented via a scheduled EJB automatically re-enabling the MDB stopped by WAS after a number of failures (one issue is that we’d exigency WAS admin rights for the EJB to accomplish that; another is performance due to the exigency to either monitor logs or check the MDB’s status regularly). On the other hand, concurrent processing is available out of the box and likewise implementing a bean notifying about problematic messages in the backout queue is simpler thanks to the injection of the mail API resources. This solution may thus require some JMX and Java EE (scheduled EJB) magic and there may subsist unexpected problems with that.

    JOB: Concurrency: it’s more difficult to implement processing of the messages in parallel, there is even a slight desultory that it’s impossible. Also  more coding is required and thus there will subsist more bugs. On the other hand they can implement delayed retrials as they want. Thus if concurrent processing isn’t faultfinding while the automatic delayed retrial may subsist then this would subsist the best approach.

     

    From http://theholyjava.wordpress.com/2010/09/13/implementing-retrial-with-a-mdb-or-an-mq-batch-job-was-7-mq-6/


    Review: RSA ClearTrust 5.5 secure federated identity management system | killexams.com actual questions and Pass4sure dumps

    Secure (SSO) lone sign-on to multiple websites is the ultimate draw for emerging Web services. Security managers want to leverage architecture to redeem costs and multiply user productivity. That means extending digital identities across applications that reside on multiple platforms and domains inside and outside the enterprise. RSA Security's ClearTrust 5.5 is designed to deliver SSO through federated identity, user management champion and dynamic transactional authorization for multipartner Web services.

    ClearTrust 5.5 provides SAML-based identity and authentication via a Federated Identity Management (FIM) module. Its API allows developers to bundle authentication and authorization requests from legacy and fresh applications. The release likewise features user management enhancements and automated workflow to empower account creation, group assignment, profile updates and password resets. It includes transactional Smart Rules, which enable dynamic spy up in databases and LDAP directories to champion authorization decisions.

    While ClearTrust's federated identity is a no-brainer for developing real-time SSO authorization for Web services, security managers will subsist distracted by having to toggle across the application's three interfaces.

    Simple SSOClearTrust 5.5's FIM module provides access to multiple Web sites with a lone logon -- import a Web service user can authenticate once and benefit from a distributed SSO to other Web sites that believe a trusted relationship. FIM enables SAML 1.1-compliant identity management by generating and processing SAML assertions, which provide XML-based authentication and authorization.

    FIM makes it easy to manage SAML Asserting and Relying Parties. The Asserting Party is the one who requests access to a resource on a Relying Party's site. The Relying Party accepts SAML assertions, which are statements that declare that the identity of a user has been authenticated. dependence relations, established by defining the Asserting Party and Relying Party, enable one identity to subsist mapped to multiple identities on other sites to eliminate the constant toggling of names and passwords. ClearTrust maintains a local store of relationship data (user names and aliases).

    We configured an associated Relying Party for their Web service, a remote user identity and the authentication methods allowed, and mapped their local identity to a different remote identity to fully test the SSO federated identity capabilities.

    We set the Asserting Party issuer and source identity, Asserting Party policy and trusted Relying Parties. The issuer and source identity -- the equivalent of a user ID for a Web service consumer -- is a 40-character randomly generated string that's similar to a shared key in a site-to-site security relationship. ClearTrust binds this identity string to a SOAP transport service URL, which acts as a broker for requests to a Web service. They used the FIM interface to configure length assertion lifetime policy, which defines how long the session is allowed, and custom authentication and Relying Party verification methods, such as digital certificate or basic authentication.

    We authenticated to the Web service hosted on their system via the local client domain. An encrypted cookie identified us as a trusted authenticated party, and their request was directed via an SSL-secured connection to the remote Web service domain associated with their Relying Party. The SAML assertion essentially mapped their local identity to the remote identity. The remote Web service, which was configured to parade the entire SAML assertion upon successful authentication and authorization, accepted their assertion, and the comprehensive parade verified the receipt and accuracy in processing the SAML assertion.

    Along with the benchmark SAML fields, ClearTrust allows for the enumeration of additional attributes, which can subsist used to pass information to other Web services. For example, they were able to pass metadata in the shape of name/value pairs for an affinity program to the remote domain. It accepted their identity and authentication assertions, but relied on remote site authorization to control what they were able to access.

    Streamlining Web Services SecurityRSA includes its ClearTrust API in version 5.5 as a "One Call" Web service for enhanced integration and to extend its achieve to enterprise applications. For example, developers can bundle authentication and authorization requests from legacy and fresh applications such as Microsoft's .NET into a lone Web service API call. ClearTrust can respond to the Web services calls with a lone response that answers the packaged requests. This reduces the number of conversations between systems and improves performance considerably. For example, providing the API as a standards-based Web service allows enterprises to integrate Microsoft's BizTalk and Sun Microsystems' J2EE to exercise the same authentication and authorization scheme.

    ClearTrust employs a Web Services Description Language interface, which uses an XML-based language to report various Web services calls, their related functions and how to access them.

    We installed their Web archive file, which is used for deploying Web applications, on a BEA WebLogic server to test the ClearTrust API, and made several test calls to the ClearTrust Web service API requesting authentication and authorization. Their simple Web service client sent the packaged request seeking authorization to three URLs (/secure, /test and /accounts). The ClearTrust Web service API bundled its answer, and following policy, returned three "allow" responses.

    ClearTrust compares the user ID, authentication surreptitious and URL requested with the local ClearTrust security policy to issue allowance decisions. They removed their user's entitlements to the three URLs to test ClearTrust's ability to negate access, and resent their packaged request. The Web service API responded by bundling three "deny" responses.

    Transactional AuthorizationsClearTrust has extended its benchmark Smart Rules in 5.5 to enable a dynamic lookup of authorization decision data stored in databases, LDAP directories, Web services and XML files.

    We created an XML file with a user ID for dynamically checking a value, and a file with a territory called "credit card approval" and an assigned value of 0,1 to toggle between. They set the rule to negate access if the value for the user was 0, and allow access to a resource if the value was 1. The ACL resource was defined as their Web server directory containing a collection of analyst reports that were for paying subscribers only. Their transactional rule performed a credit card validation lookup, and issued file access pending the impregnate acceptance.

    The transactional smart rule denied us when they tried to access the directory with the value set to 0, and with the value set to 1 allowed their access to observe pages within the protected directory. ClearTrust's pairing of dynamic data and traffic logic for driving security decisions is an notable functionality. In the case where a user's access to downloadable software is based on available credit, ClearTrust could check the user's credit to dynamically negate or empower access.

    Empowered UsersClearTrust 5.5 has eased the sting of managing discontinue users with its Advanced User Management (AUM) module. With AUM's built-in workflow, security managers can preapprove a train of actions for authorized users, including account creation, group assignment, profile update and password reset requests.

    We completed the username, password, e-mail address, full title and zip code to empower account creation. Three questions were selected from a pull-down menu to empower future unassisted password resets. Questions are configurable, but they applied the RSA templates for "favorite teacher," "first pet's name" and "name of your elementary school." A receipt was issued, and they were notified by e-mail when the account was approved.

    The AUM module provides a list of approval tasks, and they clicked to endorse the account. An e-mail message was issued to their discontinue user that the account activation had been approved. They tested the password reset by entering their user title in the text territory and providing their three previously validated responses to the psychographic questions. Their verified responses allowed us to supersede their forgotten password.

    A worthy MarriageRSA ClearTrust 5.5 has introduced useful features that champion the emerging Web services SAML 1.1 standard. Its self-service eases user administration. Dynamic transaction rules marry traffic logic to security authorization decisions, with the ability to query both internal and external partner Web services for dynamic decision support. These features, when combined with the ability to expose the API as Web service, create a centralized security architecture with quick-witted and distributed capabilities.

    While accessing three administrative interface links from a browser-based dashboard served their purposes, combining the consoles into a lone interface would get ClearTrust a more efficient appliance for security managers. But given the robust and intuitive feature set in ClearTrust 5.5, they can't complain.

    Snapshot

    RSA ClearTrust 5.5RSA SecurityPrice: Starts at $26/user

    PURPOSE: ClearTrust 5.5 provides access and federated identity management for Web services.

    REQUIREMENTS: Requires Microsoft Windows 2000/2003, Red Hat Linux Enterprise or SuSE Linux, Sun Solaris 8/9, IBM AIX or HP-UX; Oracle, Microsoft SQL Server 2000, Sybase, Microsoft lively Directory or Sun One Directory Server; Sun One Webserver, Microsoft IIS 5.0/6.0 or Apache; BEA WebLogic 8.1, IBM WebSphere or Tomcat.

    KEY FEATURES:- Provides SAML 1.1-based Web service authentication.- Comprehensive API Web service integration.- Dynamic transaction authorization based on traffic logic.

    PROS:- Federated identity maps user IDs across Web services and sites.- Automated user account management and workflow.

    CONS:- Three part administrative GUI's.

    VERDICT: RSA ClearTrust 5.5 delivers key components that target the exigency for federated identity with champion for emerging Web service standards. User self-service eases the administrative burden for authorizing Web services authentication. RSA offers a robust feature set and practical solution.

    George Wrenn, CISSP, is a technical editor for Information Security, a graduate fellow at the Massachusetts Institute of Technology and a director of security at a fiscal services firm.



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