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So, How Long Have You Been in That Job Queue?

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It sounded simple at first. Several people at one of my client’s remote sites were complaining to the support center that their jobs were taking longer to complete—sometimes hours longer—than they ever did before. This was a busy system, with 30,000 jobs submitted every day. When I began to look into the problem, I had trouble zeroing in on just those problem jobs. The job names and user IDs weren’t unique enough to easily distinguish them from jobs submitted at other sites. To make things more difficult, the only performance data available only covered a single week, precluding any chance for a comparison with performance data from “normal times.”

This article describes the process I went through to identify the reason why some jobs were running longer than they should. The article will also introduce you to the utility I used, GENPFRLOG, to make the analysis easier. I’ll also describe how I converted the old RPG III-based utility into a browser-based utility that uses Java servlets.

I wrote the GENPFRLOG utility to scan the history log and build a database that I could analyze more easily than the raw history log. It’s also useful when performance data isn’t available and facilitates analysis by putting data into one place, in contrast to the previous method of storing performance and history log data. I soon realized that there was a lot of data to plow through, but another benefit to this technique was that I could build an index over the file to optimize my research.

Well, This Isn’t Working...

In this kind of situation, the first thing I typically do is gather background information. In this case, I spoke with those users who originally reported a problem. Primarily, the users were concerned about their entered status orders report, which they frequently submitted to batch throughout the day. There didn’t seem to be a pattern. Mostly, the jobs behaved as expected, but at odd intervals, the jobs would take longer than normal to complete. Sometimes these delays would occur in the wee hours of the morning, or sometimes in the middle of the day.

Next, I spoke with some of the IT employees who were familiar with the application. They told me there was a sequence of jobs that were scheduled to run at regular intervals, and there were also jobs that were submitted on request. Some of the jobs were


specific to a remote site, but some processed data for all the sites. They all worked together and could impact the data for the report in question.

To complicate matters, another server would periodically submit jobs remotely to the system, sometimes up to a thousand jobs at once. My ears perked up when I heard that, and I made a mental note to follow up on that issue.

Since I had performance data from the performance monitor available for the past week, I first tried to use the performance tools reports. These reports didn’t tell me anything I could use. In fact, it seemed that the job usually ran in just a few minutes. I needed another way to look into the problem. At this point, I still wasn’t even sure I had identified the correct instance of the job that was a problem. There certainly didn’t seem to be a correlation between job runtimes and what the users at the remote site were experiencing.

I decided to use my GENPFRLOG utility. Composed of a command, a CL program, and an RPG program, GENPFRLOG uses entries in the system history log, much like a utility described by Gene Gaunt in his article “SYSOP: Using the System Log” (in the March 1999 isuue of MC). I took a different approach, however; I found that by using the job start message (CPF1124) along with the job completion message (CPF1164), I could determine the entire life history of the job, from submission to initiation to completion.

My utility reads through QHST* files for the given date and time range. Records for the job start messages are written to a table called PERFLOGP. When the program finds a job completion message, it retrieves the record from the job start and updates the remaining fields.

After I ran the utility, I used SQL to analyze the data collected. I sorted the table by total duration, from job submission to completion, in descending order. After a couple of passes, I filtered out jobs that weren’t relevant and saw some of the jobs that had been identified earlier. The interesting thing about these jobs was that the total runtimes weren’t really that long, but the time between job submissions and job initiation was often significant. It looked like these jobs spent a lot of time in the job queue. But why?

Using SQL again (how did I ever get along without it?), I generated a list of jobs that went through the same subsystem as the jobs in question and were submitted during the same time period or a little before. Interestingly enough, I didn’t see the jobs submitted by the remote server, as I expected. I did see some other jobs, though: query jobs.

I ran the GENPFRLOG utility again, going back as far as I could so that I could compare that earlier history log data to the current week’s data. I’ve found that history log data is often kept for a month or more, compared to a typical week or so for performance data. I set the selection criteria to select the same jobs identified earlier and found dramatically different times for the duration spent in the job queue. Something had changed to make these jobs wait longer before beginning to execution.

It looked like the query jobs were implicated, but they ran through a different job queue. I was able to put a rough time line together and find that at certain times, up to three query jobs were running concurrently while the jobs in question were in the job queue. A quick look at the subsystem description confirmed my suspicions: The maximum activity level was set to three.

When I spoke with the people in production, they confirmed that the query jobs listed were indeed important. But the entered status orders job was more important. The production folks and I decided to try creating a new job queue and adding another job queue entry to the subsystem description. Overall resource utilization wasn’t too bad; it appeared that the system could handle additional work. We changed the job submission to use the new job queue, bumped up the activity level, and sat back and watched.


Aha!

No News Is Good News

After a week had passed, the support center hadn’t received any calls regarding these jobs. This was a nice change. To confirm our success, I again ran my utility and reviewed the total time spent in the job queue compared to data from before our change. The data confirmed what the silent telephones were telling us. The average time from submission to completion dropped from 29 minutes and 34 seconds to 2 minutes and 33 seconds, with only a few seconds in the job queue. We looked at the performance data to confirm that we hadn’t put too much of a load on the system. We also reviewed times in job queues for other jobs to ensure that we hadn’t caused other jobs to wait longer to begin executing. It looked like the project was complete.

You might think that I could have just looked at the job queues to see if jobs were waiting. I did, but there were usually so many jobs going through the queues, and so quickly, that it was difficult to keep track of it all. Plus, it wasn’t easy to tell in advance just when the jobs would be coming through, so it was a little like being a policeman sitting in front of a bank and hoping that a bank robber would come by.

The Same, But Different

When I contacted the editors of Midrange Computing about this article, they told me “We would really like this to be a PC GUI interface.” I thought, why not? I’d been playing with Java a bit but didn’t really have a good project to work with, which for me is usually the most effective way to learn something new.

I developed a series of HTML documents and Java servlets to organize the different utility functions, as well as some new functionality, into a browser-based interface. This series also integrated my legacy utility, since I didn’t want to recreate that part of the utility. I took the opportunity to augment my utility to make my analysis easier, providing the additional ability to view all resulting data, run a canned query, set a filter, set sort order, enter SQL on the fly, and clear data.

There was a steep learning curve. The little bit of Java experience I had was all on a Windows 95 platform, primarily with console applications. I had to learn how to set up and use the AS/400 Toolbox for Java, Qshell on the AS/400, servlets with the WebSphere application server, plus adapt the examples I saw to work with servlets. Most AS/400 Java programming examples that I’ve been able to find are for console applications and applets. But I stuck with it and learned some Java along the way.

Now, I have an AS/400 command interface I can use, along with interactive SQL. I also have a browser interface that has performance benefits from running as a noninteractive job, and which will let me easily run SQL statements on systems where the SQL/400 feature wasn’t purchased. In Figure 1, you can see what the data table looks like.

A key technique to reusing the existing legacy utility is the CommandCall class from the Toolbox. I found it easier to use commands than to call a program, but in an environment where many calls are made, this may not be an appropriate strategy. An example is shown here:

AS400 sys = new AS400(“localhost”,userid,password);
CommandCall myCommand = new CommandCall(sys);
myCommand.run(cmd.toString());

You can use the techniques and utility I’ve described in this article to investigate and find hard data for cases in which time spent in job queues is a problem. For complete instructions on installing and using the utility, refer to the readme.txt file in the zip file
you’ll download from MC at www. midrangecomputing.com/mc. The utility and techniques described here are also useful if performance data isn’t available, but history logs are. The history log data is well suited to frequency distribution and trend analysis. In


addition, try some of the techniques described here to put a new face on some of your own utilities, enhancing their usability and functionality at the same time.

REFERENCES AND RELATED MATERIALS

• AS/400e Work Management Version 4 (SC41-5306-03, CD-ROM SK3T-0118-04)

• Beginning Java. Ivor Horton. Chicago, Illinois: Wrox Press, 1997

• Instant Java Servlets. Phil Hanna. Berkeley, California: Osborne/McGraw-Hill, 2000

• Joe Pluta’s Install Java 1.1/400 Web page: www.zappie.net/Java/Javatorium/installi.htm

• “SYSOP: Using the System Log,” Gene Gaunt, MC, March 1999

Figure 1: You can use a browser to view your performance data table.


So__How_Long_Have_You_Been_in_That_Job_Queue-04-00.png 447x334

It sounded simple at first. Several people at one of my client’s remote sites were complaining to the support center that their jobs were taking longer to complete—sometimes hours longer—than they ever did before. This was a busy system, with 30,000 jobs submitted every day. When I began to look into the problem, I had trouble zeroing in on just those problem jobs. The job names and user IDs weren’t unique enough to easily distinguish them from jobs submitted at other sites. To make things more difficult, the only performance data available only covered a single week, precluding any chance for a comparison with performance data from “normal times.”

This article describes the process I went through to identify the reason why some jobs were running longer than they should. The article will also introduce you to the utility I used, GENPFRLOG, to make the analysis easier. I’ll also describe how I converted the old RPG III-based utility into a browser-based utility that uses Java servlets.

I wrote the GENPFRLOG utility to scan the history log and build a database that I could analyze more easily than the raw history log. It’s also useful when performance data isn’t available and facilitates analysis by putting data into one place, in contrast to the previous method of storing performance and history log data. I soon realized that there was a lot of data to plow through, but another benefit to this technique was that I could build an index over the file to optimize my research.

Well, This Isn’t Working...

In this kind of situation, the first thing I typically do is gather background information. In this case, I spoke with those users who originally reported a problem. Primarily, the users were concerned about their entered status orders report, which they frequently submitted to batch throughout the day. There didn’t seem to be a pattern. Mostly, the jobs behaved as expected, but at odd intervals, the jobs would take longer than normal to complete. Sometimes these delays would occur in the wee hours of the morning, or sometimes in the middle of the day.

Next, I spoke with some of the IT employees who were familiar with the application. They told me there was a sequence of jobs that were scheduled to run at regular intervals, and there were also jobs that were submitted on request. Some of the jobs were


specific to a remote site, but some processed data for all the sites. They all worked together and could impact the data for the report in question.

To complicate matters, another server would periodically submit jobs remotely to the system, sometimes up to a thousand jobs at once. My ears perked up when I heard that, and I made a mental note to follow up on that issue.

Since I had performance data from the performance monitor available for the past week, I first tried to use the performance tools reports. These reports didn’t tell me anything I could use. In fact, it seemed that the job usually ran in just a few minutes. I needed another way to look into the problem. At this point, I still wasn’t even sure I had identified the correct instance of the job that was a problem. There certainly didn’t seem to be a correlation between job runtimes and what the users at the remote site were experiencing.

I decided to use my GENPFRLOG utility. Composed of a command, a CL program, and an RPG program, GENPFRLOG uses entries in the system history log, much like a utility described by Gene Gaunt in his article “SYSOP: Using the System Log” (in the March 1999 isuue of MC). I took a different approach, however; I found that by using the job start message (CPF1124) along with the job completion message (CPF1164), I could determine the entire life history of the job, from submission to initiation to completion.

My utility reads through QHST* files for the given date and time range. Records for the job start messages are written to a table called PERFLOGP. When the program finds a job completion message, it retrieves the record from the job start and updates the remaining fields.

After I ran the utility, I used SQL to analyze the data collected. I sorted the table by total duration, from job submission to completion, in descending order. After a couple of passes, I filtered out jobs that weren’t relevant and saw some of the jobs that had been identified earlier. The interesting thing about these jobs was that the total runtimes weren’t really that long, but the time between job submissions and job initiation was often significant. It looked like these jobs spent a lot of time in the job queue. But why?

Using SQL again (how did I ever get along without it?), I generated a list of jobs that went through the same subsystem as the jobs in question and were submitted during the same time period or a little before. Interestingly enough, I didn’t see the jobs submitted by the remote server, as I expected. I did see some other jobs, though: query jobs.

I ran the GENPFRLOG utility again, going back as far as I could so that I could compare that earlier history log data to the current week’s data. I’ve found that history log data is often kept for a month or more, compared to a typical week or so for performance data. I set the selection criteria to select the same jobs identified earlier and found dramatically different times for the duration spent in the job queue. Something had changed to make these jobs wait longer before beginning to execution.

It looked like the query jobs were implicated, but they ran through a different job queue. I was able to put a rough time line together and find that at certain times, up to three query jobs were running concurrently while the jobs in question were in the job queue. A quick look at the subsystem description confirmed my suspicions: The maximum activity level was set to three.

When I spoke with the people in production, they confirmed that the query jobs listed were indeed important. But the entered status orders job was more important. The production folks and I decided to try creating a new job queue and adding another job queue entry to the subsystem description. Overall resource utilization wasn’t too bad; it appeared that the system could handle additional work. We changed the job submission to use the new job queue, bumped up the activity level, and sat back and watched.


Aha!

No News Is Good News

After a week had passed, the support center hadn’t received any calls regarding these jobs. This was a nice change. To confirm our success, I again ran my utility and reviewed the total time spent in the job queue compared to data from before our change. The data confirmed what the silent telephones were telling us. The average time from submission to completion dropped from 29 minutes and 34 seconds to 2 minutes and 33 seconds, with only a few seconds in the job queue. We looked at the performance data to confirm that we hadn’t put too much of a load on the system. We also reviewed times in job queues for other jobs to ensure that we hadn’t caused other jobs to wait longer to begin executing. It looked like the project was complete.

You might think that I could have just looked at the job queues to see if jobs were waiting. I did, but there were usually so many jobs going through the queues, and so quickly, that it was difficult to keep track of it all. Plus, it wasn’t easy to tell in advance just when the jobs would be coming through, so it was a little like being a policeman sitting in front of a bank and hoping that a bank robber would come by.

The Same, But Different

When I contacted the editors of Midrange Computing about this article, they told me “We would really like this to be a PC GUI interface.” I thought, why not? I’d been playing with Java a bit but didn’t really have a good project to work with, which for me is usually the most effective way to learn something new.

I developed a series of HTML documents and Java servlets to organize the different utility functions, as well as some new functionality, into a browser-based interface. This series also integrated my legacy utility, since I didn’t want to recreate that part of the utility. I took the opportunity to augment my utility to make my analysis easier, providing the additional ability to view all resulting data, run a canned query, set a filter, set sort order, enter SQL on the fly, and clear data.

There was a steep learning curve. The little bit of Java experience I had was all on a Windows 95 platform, primarily with console applications. I had to learn how to set up and use the AS/400 Toolbox for Java, Qshell on the AS/400, servlets with the WebSphere application server, plus adapt the examples I saw to work with servlets. Most AS/400 Java programming examples that I’ve been able to find are for console applications and applets. But I stuck with it and learned some Java along the way.

Now, I have an AS/400 command interface I can use, along with interactive SQL. I also have a browser interface that has performance benefits from running as a noninteractive job, and which will let me easily run SQL statements on systems where the SQL/400 feature wasn’t purchased. In Figure 1, you can see what the data table looks like.

A key technique to reusing the existing legacy utility is the CommandCall class from the Toolbox. I found it easier to use commands than to call a program, but in an environment where many calls are made, this may not be an appropriate strategy. An example is shown here:

AS400 sys = new AS400(“localhost”,userid,password);
CommandCall myCommand = new CommandCall(sys);
myCommand.run(cmd.toString());

You can use the techniques and utility I’ve described in this article to investigate and find hard data for cases in which time spent in job queues is a problem. For complete instructions on installing and using the utility, refer to the readme.txt file in the zip file
you’ll download from MC at www. midrangecomputing.com/mc. The utility and techniques described here are also useful if performance data isn’t available, but history logs are. The history log data is well suited to frequency distribution and trend analysis. In


addition, try some of the techniques described here to put a new face on some of your own utilities, enhancing their usability and functionality at the same time.

REFERENCES AND RELATED MATERIALS

• AS/400e Work Management Version 4 (SC41-5306-03, CD-ROM SK3T-0118-04)

• Beginning Java. Ivor Horton. Chicago, Illinois: Wrox Press, 1997

• Instant Java Servlets. Phil Hanna. Berkeley, California: Osborne/McGraw-Hill, 2000

• Joe Pluta’s Install Java 1.1/400 Web page: www.zappie.net/Java/Javatorium/installi.htm

• “SYSOP: Using the System Log,” Gene Gaunt, MC, March 1999

Figure 1: You can use a browser to view your performance data table.


So__How_Long_Have_You_Been_in_That_Job_Queue-04-00.png 447x334

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  • How to Manage Documents the Easy Way

    SB_HelpSystems_WC_GenericWhat happens when your company depends on an outdated document management strategy?
    Everything is harder.
    You don’t need to stick with status quo anymore.
    Watch the webinar to learn how to put effective document management into practice and:

    • Capture documents faster, instead of wasting everyone’s time
    • Manage documents easily, so you can always find them
    • Distribute documents automatically, and move on to the next task

     

  • Lessons Learned from the AS/400 Breach

    SB_PowerTech_WC_GenericGet actionable info to avoid becoming the next cyberattack victim.
    In “Data breach digest—Scenarios from the field,” Verizon documented an AS/400 security breach. Whether you call it AS/400, iSeries, or IBM i, you now have proof that the system has been breached.
    Watch IBM i security expert Robin Tatam give an insightful discussion of the issues surrounding this specific scenario.
    Robin will also draw on his extensive cybersecurity experience to discuss policies, processes, and configuration details that you can implement to help reduce the risk of your system being the next victim of an attack.

  • Overwhelmed by Operating Systems?

    SB_HelpSystems_WC_GenericIn this 30-minute recorded webinar, our experts demonstrate how you can:

    • Manage multiple platforms from a central location
    • View monitoring results in a single pane of glass on your desktop or mobile device
    • Take advantage of best practice, plug-and-play monitoring templates
    • Create rules to automate daily checks across your entire infrastructure
    • Receive notification if something is wrong or about to go wrong

    This presentation includes a live demo of Network Server Suite.

     

  • Real-Time Disk Monitoring with Robot Monitor

    SB_HelpSystems_WC_GenericYou need to know when IBM i disk space starts to disappear and where it has gone before system performance and productivity start to suffer. Our experts will show you how Robot Monitor can help you pinpoint exactly when your auxiliary storage starts to disappear and why, so you can start taking a proactive approach to disk monitoring and analysis. You’ll also get insight into:

    • The main sources of disk consumption
    • How to monitor temporary storage and QTEMP objects in real time
    • How to monitor objects and libraries in real time and near-real time
    • How to track long-term disk trends

     

     

  • Stop Re-keying Data Between IBM I and Other Applications

    SB_HelpSystems_WC_GenericMany business still depend on RPG for their daily business processes and report generation.Wouldn’t it be nice if you could stop re-keying data between IBM i and other applications? Or if you could stop replicating data and start processing orders faster? Or what if you could automatically extract data from existing reports instead of re-keying? It’s all possible. Watch this webinar to learn about:

    • The data dilemma
    • 3 ways to stop re-keying data
    • Data automation in practice

    Plus, see how HelpSystems data automation software will help you stop re-keying data.

     

  • The Top Five RPG Open Access Myths....BUSTED!

    SB_Profound_WC_GenericWhen it comes to IBM Rational Open Access: RPG Edition, there are still many misconceptions - especially where application modernization is concerned!

    In this Webinar, we'll address some of the biggest myths about RPG Open Access, including:

    • Modernizing with RPG OA requires significant changes to the source code
    • The RPG language is outdated and impractical for modernizing applications
    • Modernizing with RPG OA is the equivalent to "screen scraping"

     

  • Time to Remove the Paper from Your Desk and Become More Efficient

    SB_HelpSystems_WC_GenericToo much paper is wasted. Attempts to locate documents in endless filing cabinets.And distributing documents is expensive and takes up far too much time.
    These are just three common reasons why it might be time for your company to implement a paperless document management system.
    Watch the webinar to learn more and discover how easy it can be to:

    • Capture
    • Manage
    • And distribute documents digitally

     

  • IBM i: It’s Not Just AS/400

    SB_HelpSystems_WC_Generic

    IBM’s Steve Will talks AS/400, POWER9, cognitive systems, and everything in between

    Are there still companies that use AS400? Of course!

    IBM i was built on the same foundation.
    Watch this recorded webinar with IBM i Chief Architect Steve Will and IBM Power Champion Tom Huntington to gain a unique perspective on the direction of this platform, including:

    • IBM i development strategies in progress at IBM
    • Ways that Watson will shake hands with IBM i
    • Key takeaways from the AS/400 days

     

  • Ask the RDi Experts

    SB_HelpSystems_WC_GenericWatch this recording where Jim Buck, Susan Gantner, and Charlie Guarino answered your questions, including:

    • What are the “hidden gems” in RDi that can make me more productive?
    • What makes RDi Debug better than the STRDBG green screen debugger?
    • How can RDi help me find out if I’ve tested all lines of a program?
    • What’s the best way to transition from PDM to RDi?
    • How do I convince my long-term developers to use RDi?

    This is a unique, online opportunity to hear how you can get more out of RDi.

     

  • Node.js on IBM i Webinar Series Pt. 2: Setting Up Your Development Tools

    Profound Logic Software, Inc.Have you been wondering about Node.js? Our free Node.js Webinar Series takes you from total beginner to creating a fully-functional IBM i Node.js business application. In Part 2, Brian May teaches you the different tooling options available for writing code, debugging, and using Git for version control. Attend this webinar to learn:

    • Different tools to develop Node.js applications on IBM i
    • Debugging Node.js
    • The basics of Git and tools to help those new to it
    • Using NodeRun.com as a pre-built development environment

     

     

  • Inside the Integrated File System (IFS)

    SB_HelpSystems_WC_GenericDuring this webinar, you’ll learn basic tips, helpful tools, and integrated file system commands—including WRKLNK—for managing your IFS directories and Access Client Solutions (ACS). We’ll answer your most pressing IFS questions, including:

    • What is stored inside my IFS directories?
    • How do I monitor the IFS?
    • How do I replicate the IFS or back it up?
    • How do I secure the IFS?

    Understanding what the integrated file system is and how to work with it must be a critical part of your systems management plans for IBM i.

     

  • Expert Tips for IBM i Security: Beyond the Basics

    SB PowerTech WC GenericIn this session, IBM i security expert Robin Tatam provides a quick recap of IBM i security basics and guides you through some advanced cybersecurity techniques that can help you take data protection to the next level. Robin will cover:

    • Reducing the risk posed by special authorities
    • Establishing object-level security
    • Overseeing user actions and data access

    Don't miss this chance to take your knowledge of IBM i security beyond the basics.

     

     

  • 5 IBM i Security Quick Wins

    SB PowerTech WC GenericIn today’s threat landscape, upper management is laser-focused on cybersecurity. You need to make progress in securing your systems—and make it fast.
    There’s no shortage of actions you could take, but what tactics will actually deliver the results you need? And how can you find a security strategy that fits your budget and time constraints?
    Join top IBM i security expert Robin Tatam as he outlines the five fastest and most impactful changes you can make to strengthen IBM i security this year.
    Your system didn’t become unsecure overnight and you won’t be able to turn it around overnight either. But quick wins are possible with IBM i security, and Robin Tatam will show you how to achieve them.

  • How to Meet the Newest Encryption Requirements on IBM i

    SB PowerTech WC GenericA growing number of compliance mandates require sensitive data to be encrypted. But what kind of encryption solution will satisfy an auditor and how can you implement encryption on IBM i? Watch this on-demand webinar to find out how to meet today’s most common encryption requirements on IBM i. You’ll also learn:

    • Why disk encryption isn’t enough
    • What sets strong encryption apart from other solutions
    • Important considerations before implementing encryption

     

     

  • Security Bulletin: Malware Infection Discovered on IBM i Server!

    SB PowerTech WC GenericMalicious programs can bring entire businesses to their knees—and IBM i shops are not immune. It’s critical to grasp the true impact malware can have on IBM i and the network that connects to it. Attend this webinar to gain a thorough understanding of the relationships between:

    • Viruses, native objects, and the integrated file system (IFS)
    • Power Systems and Windows-based viruses and malware
    • PC-based anti-virus scanning versus native IBM i scanning

    There are a number of ways you can minimize your exposure to viruses. IBM i security expert Sandi Moore explains the facts, including how to ensure you're fully protected and compliant with regulations such as PCI.

     

     

  • Fight Cyber Threats with IBM i Encryption

    SB PowerTech WC GenericCyber attacks often target mission-critical servers, and those attack strategies are constantly changing. To stay on top of these threats, your cybersecurity strategies must evolve, too. In this session, IBM i security expert Robin Tatam provides a quick recap of IBM i security basics and guides you through some advanced cybersecurity techniques that can help you take data protection to the next level. Robin will cover:

    • Reducing the risk posed by special authorities
    • Establishing object-level security
    • Overseeing user actions and data access

     

     

     

  • 10 Practical IBM i Security Tips for Surviving Covid-19 and Working From Home

    SB PowerTech WC GenericNow that many organizations have moved to a work from home model, security concerns have risen.

    During this session Carol Woodbury will discuss the issues that the world is currently seeing such as increased malware attacks and then provide practical actions you can take to both monitor and protect your IBM i during this challenging time.

     

  • How to Transfer IBM i Data to Microsoft Excel

    SB_HelpSystems_WC_Generic3 easy ways to get IBM i data into Excel every time
    There’s an easy, more reliable way to import your IBM i data to Excel? It’s called Sequel. During this webinar, our data access experts demonstrate how you can simplify the process of getting data from multiple sources—including Db2 for i—into Excel. Watch to learn how to:

    • Download your IBM i data to Excel in a single step
    • Deliver data to business users in Excel via email or a scheduled job
    • Access IBM i data directly using the Excel add-in in Sequel

    Make 2020 the year you finally see your data clearly, quickly, and securely. Start by giving business users the ability to access crucial business data from IBM i the way they want it—in Microsoft Excel.

     

     

  • HA Alternatives: MIMIX Is Not Your Only Option on IBM i

    SB_HelpSystems_WC_GenericIn this recorded webinar, our experts introduce you to the new HA transition technology available with our Robot HA software. You’ll learn how to:

    • Transition your rules from MIMIX (if you’re happy with them)
    • Simplify your day-to-day activities around high availability
    • Gain back time in your work week
    • Make your CEO happy about reducing IT costs

    Don’t stick with a legacy high availability solution that makes you uncomfortable when transitioning to something better can be simple, safe, and cost-effective.

     

     

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  • Backup and Recovery on IBM i: Your Strategy for the Unexpected

    SB HelpSystems SC 5413Robot automates the routine tasks of iSeries backup and recovery, saving you time and money and making the process safer and more reliable. Automate your backups with the Robot Backup and Recovery Solution. Key features include:
    - Simplified backup procedures
    - Easy data encryption
    - Save media management
    - Guided restoration
    - Seamless product integration
    Make sure your data survives when catastrophe hits. Try the Robot Backup and Recovery Solution FREE for 30 days.

  • Manage IBM i Messages by Exception with Robot

    SB HelpSystems SC 5413Managing messages on your IBM i can be more than a full-time job if you have to do it manually. How can you be sure you won’t miss important system events?
    Automate your message center with the Robot Message Management Solution. Key features include:
    - Automated message management
    - Tailored notifications and automatic escalation
    - System-wide control of your IBM i partitions
    - Two-way system notifications from your mobile device
    - Seamless product integration
    Try the Robot Message Management Solution FREE for 30 days.

  • Easiest Way to Save Money? Stop Printing IBM i Reports

    SB HelpSystems SC 5413Robot automates report bursting, distribution, bundling, and archiving, and offers secure, selective online report viewing.
    Manage your reports with the Robot Report Management Solution. Key features include:

    - Automated report distribution
    - View online without delay
    - Browser interface to make notes
    - Custom retention capabilities
    - Seamless product integration
    Rerun another report? Never again. Try the Robot Report Management Solution FREE for 30 days.

  • Hassle-Free IBM i Operations around the Clock

    SB HelpSystems SC 5413For over 30 years, Robot has been a leader in systems management for IBM i.
    Manage your job schedule with the Robot Job Scheduling Solution. Key features include:
    - Automated batch, interactive, and cross-platform scheduling
    - Event-driven dependency processing
    - Centralized monitoring and reporting
    - Audit log and ready-to-use reports
    - Seamless product integration
    Scale your software, not your staff. Try the Robot Job Scheduling Solution FREE for 30 days.

  • ACO MONITOR Manages your IBM i 24/7 and Notifies You When Your IBM i Needs Assistance!

    SB DDL Systems 5429More than a paging system - ACO MONITOR is a complete systems management solution for your Power Systems running IBM i. ACO MONITOR manages your Power System 24/7, uses advanced technology (like two-way messaging) to notify on-duty support personnel, and responds to complex problems before they reach critical status.

    ACO MONITOR is proven technology and is capable of processing thousands of mission-critical events daily. The software is pre-configured, easy to install, scalable, and greatly improves data center efficiency.