3 Key Benefits to Container-Based Background Job Processing

Whether deploying applications or providing microservices, being able to get tasks done in the background without user intervention is key to operating efficiently for IT and development teams. One effective way to facilitate background job processing is with the help of containers.

Container-based background job processing comes with a whole host of benefits. Here are some of the key benefits of using container-based background job processing that IT and development teams can leverage.

Enhanced Security

With ever-increasing data breaches and ransomware threats, keeping applications secure during deployment is vital. Managing the deployment of applications often calls for working with several development teams distributed across different locations. Having more people work on these teams can create a higher risk of exposure and data breaches due to errors or vulnerabilities from mistakes by the staff.

The great news is that containers offer enhanced security. That’s because more effort has been put in place to safeguard containers. For instance, container systems and container management systems, such as Docker and Kubernetes, require container image signing to ensure your team is deploying containers from trusted resources.

Moreover, container scanning solutions also help enhance security by quickly identifying vulnerabilities that may exist in your containers, including the containers that were signed. This helps reduce security risks, including deploying unsafe containers.

Versatile Background Job Capabilities

Being able to provide on-time delivery to clients is essential for enhancing the customer’s experience. With the help of container-based background job processing, IT and development teams can manage a variety of background tasks.

For instance, tasks such as email delivery, automated scaling, calculating bandwidths or automating push notifications can be handled by containers. That’s because containers can fragment applications into smaller components while enabling communication among developer teams. This also helps facilitate speedy software development and testing. Moreover, using a container-based workload platform from development tool expert services, such as Iron IO, helps enterprises free up staff from handling background job processing so they can focus on more vital tasks, such as testing and developing their software applications.

Flexible Deployment

Thanks to the container’s shareability, enterprises can leverage flexible deployment options, including the shared, on-premise, dedicated or hybrid deployment options offered by a reliable container-based workload hosted platform, such as Iron IO’s Worker. That means enterprise leaders can choose a deployment option that’s customized to their needs.

For instance, development teams working in enterprises that often deal with classified or highly sensitive data or personal information, such as banks, hospitals or federal agencies, often have to follow several compliance regulations. Having the ability to use on-premise deployment solutions can help support background tasks in a secure manner.

At the same time, enterprises that must support staying in compliance with enterprise and federal rules while facilitating a distributed team may find a hybrid deployment approach more feasible. This deployment option is ideal for handling secure background job processing for tasks, such as scheduling and authentication, while letting development teams run their containers on-premise.

Final Thoughts

From flexible deployment options to versatile background task processing capabilities, containers offer much for development teams to leverage. While containers provide several benefits, it’s important to also use reputable platforms and professional teams that have the experience and expertise in managing and implementing containers to support container-based background jobs.  By leveraging containers and the platforms that support them, enterprises can better serve their clients for an enhanced customer experience.

Iron.io at The Machine Learning Conference

 

 

Attending MLconf in San Francisco on November 10th? If so, come say hello!

We’ve been seeing more and more customers hiring machine learning talent in order to tackle operational efficiencies and hone in on their forecasting. Iron’s platform is helping in almost all phases of the process, from ETL operations helping with the build phase to building models through distributed, hybrid and on-prem, IronWorker deployments.  We’ve never thought of ourselves as a machine learning as a service (MLaaS) company, but we’re apparently getting a lot of traction in the industry which is music to our ears!

The speakers this year are incredible and we’re looking forward to the entire event. From Xavier Amatriain’s background with ML driven medicine to Franziska Bell’s work on uncertainty estimations at Uber, we’re pretty awestruck at the lineup.

The event is being held at the Nikko Hotel in San Francisco on the 10th of November, and you can find more details here:  https://mlconf.com/events/san-francisco-ca-2/

We’ll be following up with a great recap, so stay tuned.  We hope to see you there!

Massive Content, Validation & Serverless: Cloud Expo 2016 Recap

Cloud Expo Banner

The Cloud Expo was held June 7-9, 2016 in New York City, and Iron.io sent a team to present our vision for the future, collaborate with other attendees and answer questions. Below is a summary of three technical sessions representative of the Containers track at the conference:

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Introducing Lambda support on Iron.io

AWSonDocker_revised

Serverless computing has become a compelling model for companies to add business value without their development teams having to worry about provisioning, managing and scaling infrastructure. The concept is that developers write code that performs business logic based on  some specific input data, and the platform handles the details of:

  • Where to run it: Use some machine with available capacity in its pool
  • When to run it: Either event-driven or scheduled
  • How to run it: Decouple your developers from your runtime. You do not have to be concerned about whether your program is running on bare metal, in a VM or in some sort of container

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