Agents
Learn about the different types of agents and how to set up your own agent.
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Learn about the different types of agents and how to set up your own agent.
Last updated
Was this helpful?
There are two types of agents:
Hosted agents. These are included in your DataBug plan and are operated by us on your behalf.
Private agents. You host these by running our Docker image on your own on-premise or Cloud infrastructure.
Your plan will include a limited number of hosted agent hours per month. As hosted agents carry out the steps described in your Problem Definition, that time will be eaten up on a per-second basis. We do this to ensure that all our customers have fair access to our agent pool.
With private agents, you can use them as much as you like without any quotas since they're running on the infrastructure you're already paying for yourself.
Hosted agents can only connect to Internet-accessible data sources. This includes Cloud data providers such as AWS or Azure, plus any on-premise data source that you've made available to our .
An agent also runs in a place. A place might be somewhere that's operated by us or one that you own.
We have a presence in data centres around the world. When running a query, you may decide that the optimum place to run a particular query is in the EU data centre.
Here, you'd specify a place of eu
and we'd allocate the Problem Definition to an agent running in that data centre.
The available DataBug places are:
uk
- the United Kingdom
us
- the United States
eu
- the European Union
When you host your own agent, you will be able to define your own custom places.
Each place name is made up of two parts:
Your customer identifier which is assigned by us (e.g. A5QRY
)
A name that you specify.
For example, private place names might include:
A5QRY-LosAngeles
A5QRY-London
A5QRY-Factory
You can then specify where the steps in your Problem Definition are carried out. This would allow you to query one database that's only available within the LA office, and another that's only available in the London office, for example. You could then bring these two datasets together for analysis.
One private place can have multiple agents running. Where that's the case, whichever agent isn't busy will pick up the work. If all agents are busy, their work will stay queued for them.
To deploy your own agent, see .