diff --git a/content/en/blog/_posts/2017-08-00-Kubernetes-Meets-High-Performance.md b/content/en/blog/_posts/2017-08-00-Kubernetes-Meets-High-Performance.md
index a8bbac6f73f12..6f2bb392ab57e 100644
--- a/content/en/blog/_posts/2017-08-00-Kubernetes-Meets-High-Performance.md
+++ b/content/en/blog/_posts/2017-08-00-Kubernetes-Meets-High-Performance.md
@@ -16,12 +16,10 @@ In Kubernetes, the base unit of scheduling is a Pod: one or more Docker containe
 
 Traditional HPC applications often exhibit different characteristics:
 
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-In financial or engineering simulations, a job may be comprised of tens of thousands of short-running tasks, demanding low-latency and high-throughput scheduling to complete a simulation in an acceptable amount of time.
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-A computational fluid dynamics (CFD) problem may execute in parallel across many hundred or even thousands of nodes using a message passing library to synchronize state. This requires specialized scheduling and job management features to allocate and launch such jobs and then to checkpoint, suspend/resume or backfill them.
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-Other HPC workloads may require specialized resources like GPUs or require access to limited software licenses. Organizations may enforce policies around what types of resources can be used by whom to ensure projects are adequately resourced and deadlines are met.
+- In financial or engineering simulations, a job may be comprised of tens of thousands of short-running tasks, demanding low-latency and high-throughput scheduling to complete a simulation in an acceptable amount of time.
+- A computational fluid dynamics (CFD) problem may execute in parallel across many hundred or even thousands of nodes using a message passing library to synchronize state. This requires specialized scheduling and job management features to allocate and launch such jobs and then to checkpoint, suspend/resume or backfill them.
+- Other HPC workloads may require specialized resources like GPUs or require access to limited software licenses. Organizations may enforce policies around what types of resources can be used by whom to ensure projects are adequately resourced and deadlines are met.
+
 HPC workload schedulers have evolved to support exactly these kinds of workloads. Examples include [Univa Grid Engine](http://www.univa.com/products/), [IBM Spectrum LSF](https://www-03.ibm.com/systems/spectrum-computing/products/lsf/) and Altair’s [PBS Professional](http://www.pbsworks.com/PBSProduct.aspx?n=PBS-Professional&c=Overview-and-Capabilities). Sites managing HPC workloads have come to rely on capabilities like array jobs, configurable pre-emption, user, group or project based quotas and a variety of other features.  
 
 ## Blurring the lines between containers and HPC