Use this glossary to become familiar with Automate Schedule terminology.

Note: Skybot Scheduler has been renamed to Automate Schedule and is now part of the Automate suite of products. The existing Skybot Scheduler features and functionality are the same; only the product name has changed.

TermDefinition

agent

The service or daemon that runs on your agent systems and connects to Automate Schedule on your enterprise server.

agent environment

A defined set of job attributes that can be shared across multiple jobs. Agent environments contain attributes to run your jobs, including which user to run the job as, password, working directories, and environment variables.

agent event monitor

Agent event monitor is an alert to let you know when something has happened on one of your agents. You can monitor for events such as changes to a file or directory, when a process starts or ends, or your own user-defined events.

agent system

The Windows, UNIX, and Linux servers in your enterprise that run the Automate Schedule agent.

agent time

The time on the system running the agent software.

Automate Schedule variable

Automate Schedule variables can be used to store values that will be inserted into runtime environment variables for jobs.

calendar

Calendars define weekly work days and non-working days, define specific non-working dates such as holidays, and allow users to specify a fiscal calendar.

command set

A command set is a group of commands that can be used by many different jobs.

date list

Date Lists allow you to select the exact dates to run a job.

DTS

DTS is the former name of SSIS (pre SQL Server 2005). DTS is still use in technical periodicals and by db professionals.

enterprise server

The server where Automate Schedule is installed.

ETL

Extract, Transform & Load: A database/data warehousing term that refers to the general process of extracting data from a variety of data sources, transforming that data to fit some storage model or business rules and loading that data into SQL Server. These types of operations are supported for SQL Server via SSIS/DTS technologies.

file transfer system

File transfer systems let you define remote systems in one spot, then quickly point to the remote system when creating FTP jobs.

job monitor

A job monitor lets you know if a job runs long, ends early, or started late.

job step

A single, sequentially-constrained unit of execution in a specific SQL server job.

notification list

A notification list lets you create groups of users or email addresses to send notifications to.

object

An object (previously known as scheduling object) in Automate Schedule is shared by multiple jobs on any connected agent systems. Their purpose is to make job scheduling easier. Types of objects include agent environments, agent event monitors, calendars, command sets, date lists, file transfer systems, notification lists, return codes, remote servers, Automate Schedule variables, SNMP trap monitors, SQL server definitions, and web server definitions.

outlying job

An outlying job is any job occurring outside of the expected forecast. They are displayed by default in the Schedule Activity Monitor (SAM). Outlying jobs include held jobs, missed jobs, jobs in a retry wait status, jobs with monitor events, and jobs that are running, starting, or ending at an abnormal time. From SAM, users may run, hold, or edit outlying jobs, or choose "check off" to remove the job from the gantt chart.

return code

When commands are executed on remote systems, each command ends with a numeric return code. This code determines if a job completed successfully or not.

server initiated time

The time that Automate Schedule assigned the job to run.

server submitted time

The time that Automate Schedule submits the job to a job queue. In most cases, the Server Initiated Time and Server Submitted Time will be close to the same time.

server time

The time on the enterprise server where the Automate Schedule software is installed.

SNMP trap monitor

Automate Schedule can monitor for SNMP traps coming from other applications.

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Last Modified On: March 21, 2017