With AWS Batch, users package the code for batch jobs, specify dependencies, and submit batch jobs using the AWS Management Console, CLIs, or SDKs. AWS Batch allows users to specify execution parameters and job dependencies, and facilitates integration with a broad range of popular batch computing workflow engines and languages (e.g., Pegasus WMS, Luigi, Nextflow, Metaflow, Apache Airflow, and AWS Step Functions).
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ignio AIOps
Score 8.1 out of 10
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ignio AIOps, from Digitate in Santa Clara, is a solution designed to improve business agility by creating a unified view of the IT estate, connecting business functions to applications and infrastructure. This is combined with behavior profile of systems and applications that is continuously learnt using this blueprint. ignio aims to improve the transparency of complex Enterprise IT landscapes.
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Pricing
AWS Batch
ignio AIOps
Editions & Modules
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No answers on this topic
Offerings
Pricing Offerings
AWS Batch
ignio AIOps
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
AWS Batch
ignio AIOps
Considered Both Products
AWS Batch
Verified User
Anonymous
Chose AWS Batch
Overall AWS Batch, I found easy compare to other softwares which i have tried, It is easy to setup the multiple jobs and on demand we can push our new jobs and same will be monitored by the monitoring dashboards provided by AWS batch, easy to schedule the new job using AWS batch.
Start with reviewing all your jobs, consolidating the timeline, and making a plan on what all jobs need to be prioritized. These can be optimized based on cost and performance. With a continuously changing workload, AWS Batch helps to build and automate the jobs across various resources. It also helps to manage the performance and workload.
-Autonomous alert and incident management related to infrastructure, NW, and applications. -Excellent fit to handle CPU, memory, and disk space alert management - proactive and predictive. -Several automation features (self-healing) - CPU/Memory modifications; disk extensions; patch management -Provisioning of user access and infrastructure servers, etc.
There is a lot more the desktop tool can do. For example, we need to apply an upgrade to get the tool to talk to our infrastructure while employees are working from home. The tool was initially installed with the assumption that the desktops would be in UserLand. Instead after COVID-19 the desktop/laptops have been used for over a year on people's home networks. As of right now, we have to sync when the devices are connected to VPN. Moving forward with the upgrade, we will be getting this data over TLS when they are connected to the untrusted networks.
The concept of ignio AlOps requires OCM efforts within most operational teams. This isn't necessarily the fault of the tool itself, but when implementing ignio, or any AIOps tool, the team will get a lot of pushback as an outside team is centralizing the operational improvements. The tool should have a centralized intake process that will allow the collection, ranking, and management of automation opportunities. ignio AlOps should then simulate the proposed efficiencies from implementing something within the backlog. Right now a lot of local teams are having a hard time getting on the same page as the enterprise teams, and a common methodology for prioritizing (even if overly simplistic) would go a long way to enterprise planning.
These tools are very new and things get added to them all the time. There should be a way for the product's stakeholders and process owners to understand the additional value ignio AlOps is gaining over time.
Key advantages include cost-effectiveness through dynamic resource provisioning and the use of spot instances. It auto-scales to meet workload demands, allowing easy job submission via the AWS Management Console or SDKs. It integrates seamlessly with other services like S3 and CloudWatch. It features automatic retries for failed jobs. It allows for a custom computing environment tailored to specific needs
ignio AIOps version upgrades were a heavy lift. Having to learn a new language versus an industry standard language took time. More consideration on overall internal long-term support needs to be determined.
We have built a healthy relationship with the vendor support team throughout the implementation phase, all incidents raised were resolved within the SLA without a fail
I am happy with the way team has implemented and shared the product for our organization. However, would like to see it get extended to the other line of business too.