ActiveBatch from Advanced Systems Concepts in New Jersey is IT workload automation software.
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HashiCorp Terraform
Score 8.6 out of 10
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Terraform from HashiCorp is a cloud infrastructure automation tool that enables users to create, change, and improve production infrastructure, and it allows infrastructure to be expressed as code. It codifies APIs into declarative configuration files that can be shared amongst team members, treated as code, edited, reviewed, and versioned. It is available Open Source, and via Cloud and Self-Hosted editions.
Any large business or organisation that wants to manage their workload effectively and with the least amount of room for error might choose the ActiveBatch Automation tool. Being a consultant I feel that It aids in task automation and has the flexibility to change in response to varying company requirements. It helps to save huge time by doing all the repetitive tasks on daily basis. During the patching activity the schedulers can be stopped. It also help by alerting us if any system/job is down so that SLA can be saved. Overall ActiveBatch Automation stands as a dependable cornerstone for ensuring the seamless operation of our tasks.
Anything that needs to be repeated en masse. Terraform is great at taking a template and have it be repeated across your estate. You can dynamically change the assets they're generating depending on certain variables. Which means though templated assets will all be similar, they're allowed to have unique properties about them. For example flattening JSON into tabular data and ensuring the flattening code is unique to the file's schema.
Businesses can use ActiveBatch to plan tasks based on parameters like frequency, dependencies, and the time of day. By automating typical actions like backups and data transfers, businesses can make sure that crucial operations go off without a hitch.
Multiple systems and apps can be used in complicated workflows that ActiveBatch can automate. For instance, it can automate a workflow for processing orders from beginning to end, from the customer order through inventory control and delivery through the processing of invoices and payments.
Files can be sent between many platforms and systems safely with ActiveBatch. Transfers to cloud-based storage systems like Amazon S3 and Microsoft Azure are also included in this. SFTP and FTP transfers are also included.
The language itself is a bit unusual and this makes it hard for new users to get onboarded into the codebase. While it's improving with later releases, basic concepts like "map an array of options into a set of configurations" or "apply this logic if a variable is specified" are possible but unnecessarily cumbersome.
The 'Terraform Plan' operation could be substantially more sophisticated. There are many situations where a Terraform file could never work but successfully passes the 'plan' phase only to fail during the 'apply' phase.
Environment migrations could be smoother. Renaming/refactoring files is a challenge because of the need to use 'Terraform mv' commands, etc.
We can easily add new plans/jobs in our batch schedules. Also, coordination with reporting and QA jobs is simple to do. Building schedules, restarting jobs, triggering dependencies is easy to understand. The system is very stable and allows us to easily see overall processing times.
I love Terraform and I think it has done some great things for people that are working to automate their provisioning processes and also for those that are in the process of moving to the cloud or managing cloud resources. There are some quirks to HCL that take a little bit of getting used to and give picking up Terraform a little bit of a learning curve, thus the rating
Terraform's performance is quite amazing when it comes to deployment of resources in AWS. Of course, the deployment times depend on various parameters like the number of resources to deploy and different regions to deploy. Terraform cannot control that. The only minor drawback probably shows up when a terraform job is terminated mid way. Then in many cases, time-consuming manual cleanup is required.
I have yet to have an opportunity to reach out directly to HashiCorp for support on Terraform. However, I have spent a great deal of time considering their documentation as I use the tool. This opinion is based solely on that. I find the Terraform documentation to have great breadth but lacking in depth in many areas. I appreciate that all of the tool's resources have an entry in the docs but often the examples are lacking. Often, the examples provided are very basic and prompt additional exploration. Also, the links in the documentation often link back to the same page where one might expect to be linked to a different source with additional information.
The workload automation solution is based on the specific needs of an organization, as well as the features, capabilities, and costs of various solutions. A thorough evaluation process and consideration of these factors can help ensure the selection of a solution that aligns with overall business objectives and meets the specific needs of the organization.
Terraform is the solid leader in the space. It allows you to do more then just provisioning within a pre-existing servers. It is more extensible and has more providers available than it competitors. It is also open source and more adopted by the community then some of the other solutions that are available in the market place.
I have not run numbers to determine hard impact, but a quick estimate is that at least one job is running for a average of about 6 hours per day - that 6 hours, if done by hand, would equate to about 30 - 40 hours per day (and in some cases, could not be duplicated manually, as the job repeats faster than a person could accomplish one cycle.)
we are able to deploy our infrastructure in a couple of ours in an automated and repeatable way, before this could take weeks if the work was done manually and was a lot of error prone.
having the state file, you can see a diff of what things have changed manually out side of Terraform which is a huge plus
if state file gets corrupted, it is very hard to debug or restore it without an impact or spending hours ..
writing big scale code can be very challenging and hard to be efficient so it's usable by the whole team
